"keyword","repo_name","file_path","file_extension","file_size","line_count","content","language" "Biophysics","tritemio/pycorrelate","setup.py",".py","1272","45","#!/usr/bin/env python # -*- coding: utf-8 -*- """"""The setup script."""""" from setuptools import setup, find_packages import versioneer with open('README.rst') as readme_file: readme = readme_file.read() with open('HISTORY.rst') as history_file: history = history_file.read() requirements = [ 'numpy', 'numba', ] setup( name='pycorrelate', version=versioneer.get_version(), cmdclass=versioneer.get_cmdclass(), description=""Fast and accurate timestamps correlation in python."", long_description=readme + '\n\n' + history, author=""Antonino Ingargiola"", author_email='tritemio@gmail.com', url='https://github.com/tritemio/pycorrelate', packages=find_packages(include=['pycorrelate']), include_package_data=True, install_requires=requirements, license=""GNU General Public License v3"", zip_safe=False, keywords='pycorrelate', classifiers=[ 'Development Status :: 2 - Pre-Alpha', 'Intended Audience :: Developers', 'License :: OSI Approved :: GNU General Public License v3 (GPLv3)', 'Natural Language :: English', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', ], ) ","Python" "Biophysics","tritemio/pycorrelate","versioneer.py",".py","68611","1823"," # Version: 0.18 """"""The Versioneer - like a rocketeer, but for versions. The Versioneer ============== * like a rocketeer, but for versions! * https://github.com/warner/python-versioneer * Brian Warner * License: Public Domain * Compatible With: python2.6, 2.7, 3.2, 3.3, 3.4, 3.5, 3.6, and pypy * [![Latest Version] (https://pypip.in/version/versioneer/badge.svg?style=flat) ](https://pypi.python.org/pypi/versioneer/) * [![Build Status] (https://travis-ci.org/warner/python-versioneer.png?branch=master) ](https://travis-ci.org/warner/python-versioneer) This is a tool for managing a recorded version number in distutils-based python projects. The goal is to remove the tedious and error-prone ""update the embedded version string"" step from your release process. Making a new release should be as easy as recording a new tag in your version-control system, and maybe making new tarballs. ## Quick Install * `pip install versioneer` to somewhere to your $PATH * add a `[versioneer]` section to your setup.cfg (see below) * run `versioneer install` in your source tree, commit the results ## Version Identifiers Source trees come from a variety of places: * a version-control system checkout (mostly used by developers) * a nightly tarball, produced by build automation * a snapshot tarball, produced by a web-based VCS browser, like github's ""tarball from tag"" feature * a release tarball, produced by ""setup.py sdist"", distributed through PyPI Within each source tree, the version identifier (either a string or a number, this tool is format-agnostic) can come from a variety of places: * ask the VCS tool itself, e.g. ""git describe"" (for checkouts), which knows about recent ""tags"" and an absolute revision-id * the name of the directory into which the tarball was unpacked * an expanded VCS keyword ($Id$, etc) * a `_version.py` created by some earlier build step For released software, the version identifier is closely related to a VCS tag. Some projects use tag names that include more than just the version string (e.g. ""myproject-1.2"" instead of just ""1.2""), in which case the tool needs to strip the tag prefix to extract the version identifier. For unreleased software (between tags), the version identifier should provide enough information to help developers recreate the same tree, while also giving them an idea of roughly how old the tree is (after version 1.2, before version 1.3). Many VCS systems can report a description that captures this, for example `git describe --tags --dirty --always` reports things like ""0.7-1-g574ab98-dirty"" to indicate that the checkout is one revision past the 0.7 tag, has a unique revision id of ""574ab98"", and is ""dirty"" (it has uncommitted changes. The version identifier is used for multiple purposes: * to allow the module to self-identify its version: `myproject.__version__` * to choose a name and prefix for a 'setup.py sdist' tarball ## Theory of Operation Versioneer works by adding a special `_version.py` file into your source tree, where your `__init__.py` can import it. This `_version.py` knows how to dynamically ask the VCS tool for version information at import time. `_version.py` also contains `$Revision$` markers, and the installation process marks `_version.py` to have this marker rewritten with a tag name during the `git archive` command. As a result, generated tarballs will contain enough information to get the proper version. To allow `setup.py` to compute a version too, a `versioneer.py` is added to the top level of your source tree, next to `setup.py` and the `setup.cfg` that configures it. This overrides several distutils/setuptools commands to compute the version when invoked, and changes `setup.py build` and `setup.py sdist` to replace `_version.py` with a small static file that contains just the generated version data. ## Installation See [INSTALL.md](./INSTALL.md) for detailed installation instructions. ## Version-String Flavors Code which uses Versioneer can learn about its version string at runtime by importing `_version` from your main `__init__.py` file and running the `get_versions()` function. From the ""outside"" (e.g. in `setup.py`), you can import the top-level `versioneer.py` and run `get_versions()`. Both functions return a dictionary with different flavors of version information: * `['version']`: A condensed version string, rendered using the selected style. This is the most commonly used value for the project's version string. The default ""pep440"" style yields strings like `0.11`, `0.11+2.g1076c97`, or `0.11+2.g1076c97.dirty`. See the ""Styles"" section below for alternative styles. * `['full-revisionid']`: detailed revision identifier. For Git, this is the full SHA1 commit id, e.g. ""1076c978a8d3cfc70f408fe5974aa6c092c949ac"". * `['date']`: Date and time of the latest `HEAD` commit. For Git, it is the commit date in ISO 8601 format. This will be None if the date is not available. * `['dirty']`: a boolean, True if the tree has uncommitted changes. Note that this is only accurate if run in a VCS checkout, otherwise it is likely to be False or None * `['error']`: if the version string could not be computed, this will be set to a string describing the problem, otherwise it will be None. It may be useful to throw an exception in setup.py if this is set, to avoid e.g. creating tarballs with a version string of ""unknown"". Some variants are more useful than others. Including `full-revisionid` in a bug report should allow developers to reconstruct the exact code being tested (or indicate the presence of local changes that should be shared with the developers). `version` is suitable for display in an ""about"" box or a CLI `--version` output: it can be easily compared against release notes and lists of bugs fixed in various releases. The installer adds the following text to your `__init__.py` to place a basic version in `YOURPROJECT.__version__`: from ._version import get_versions __version__ = get_versions()['version'] del get_versions ## Styles The setup.cfg `style=` configuration controls how the VCS information is rendered into a version string. The default style, ""pep440"", produces a PEP440-compliant string, equal to the un-prefixed tag name for actual releases, and containing an additional ""local version"" section with more detail for in-between builds. For Git, this is TAG[+DISTANCE.gHEX[.dirty]] , using information from `git describe --tags --dirty --always`. For example ""0.11+2.g1076c97.dirty"" indicates that the tree is like the ""1076c97"" commit but has uncommitted changes ("".dirty""), and that this commit is two revisions (""+2"") beyond the ""0.11"" tag. For released software (exactly equal to a known tag), the identifier will only contain the stripped tag, e.g. ""0.11"". Other styles are available. See [details.md](details.md) in the Versioneer source tree for descriptions. ## Debugging Versioneer tries to avoid fatal errors: if something goes wrong, it will tend to return a version of ""0+unknown"". To investigate the problem, run `setup.py version`, which will run the version-lookup code in a verbose mode, and will display the full contents of `get_versions()` (including the `error` string, which may help identify what went wrong). ## Known Limitations Some situations are known to cause problems for Versioneer. This details the most significant ones. More can be found on Github [issues page](https://github.com/warner/python-versioneer/issues). ### Subprojects Versioneer has limited support for source trees in which `setup.py` is not in the root directory (e.g. `setup.py` and `.git/` are *not* siblings). The are two common reasons why `setup.py` might not be in the root: * Source trees which contain multiple subprojects, such as [Buildbot](https://github.com/buildbot/buildbot), which contains both ""master"" and ""slave"" subprojects, each with their own `setup.py`, `setup.cfg`, and `tox.ini`. Projects like these produce multiple PyPI distributions (and upload multiple independently-installable tarballs). * Source trees whose main purpose is to contain a C library, but which also provide bindings to Python (and perhaps other langauges) in subdirectories. Versioneer will look for `.git` in parent directories, and most operations should get the right version string. However `pip` and `setuptools` have bugs and implementation details which frequently cause `pip install .` from a subproject directory to fail to find a correct version string (so it usually defaults to `0+unknown`). `pip install --editable .` should work correctly. `setup.py install` might work too. Pip-8.1.1 is known to have this problem, but hopefully it will get fixed in some later version. [Bug #38](https://github.com/warner/python-versioneer/issues/38) is tracking this issue. The discussion in [PR #61](https://github.com/warner/python-versioneer/pull/61) describes the issue from the Versioneer side in more detail. [pip PR#3176](https://github.com/pypa/pip/pull/3176) and [pip PR#3615](https://github.com/pypa/pip/pull/3615) contain work to improve pip to let Versioneer work correctly. Versioneer-0.16 and earlier only looked for a `.git` directory next to the `setup.cfg`, so subprojects were completely unsupported with those releases. ### Editable installs with setuptools <= 18.5 `setup.py develop` and `pip install --editable .` allow you to install a project into a virtualenv once, then continue editing the source code (and test) without re-installing after every change. ""Entry-point scripts"" (`setup(entry_points={""console_scripts"": ..})`) are a convenient way to specify executable scripts that should be installed along with the python package. These both work as expected when using modern setuptools. When using setuptools-18.5 or earlier, however, certain operations will cause `pkg_resources.DistributionNotFound` errors when running the entrypoint script, which must be resolved by re-installing the package. This happens when the install happens with one version, then the egg_info data is regenerated while a different version is checked out. Many setup.py commands cause egg_info to be rebuilt (including `sdist`, `wheel`, and installing into a different virtualenv), so this can be surprising. [Bug #83](https://github.com/warner/python-versioneer/issues/83) describes this one, but upgrading to a newer version of setuptools should probably resolve it. ### Unicode version strings While Versioneer works (and is continually tested) with both Python 2 and Python 3, it is not entirely consistent with bytes-vs-unicode distinctions. Newer releases probably generate unicode version strings on py2. It's not clear that this is wrong, but it may be surprising for applications when then write these strings to a network connection or include them in bytes-oriented APIs like cryptographic checksums. [Bug #71](https://github.com/warner/python-versioneer/issues/71) investigates this question. ## Updating Versioneer To upgrade your project to a new release of Versioneer, do the following: * install the new Versioneer (`pip install -U versioneer` or equivalent) * edit `setup.cfg`, if necessary, to include any new configuration settings indicated by the release notes. See [UPGRADING](./UPGRADING.md) for details. * re-run `versioneer install` in your source tree, to replace `SRC/_version.py` * commit any changed files ## Future Directions This tool is designed to make it easily extended to other version-control systems: all VCS-specific components are in separate directories like src/git/ . The top-level `versioneer.py` script is assembled from these components by running make-versioneer.py . In the future, make-versioneer.py will take a VCS name as an argument, and will construct a version of `versioneer.py` that is specific to the given VCS. It might also take the configuration arguments that are currently provided manually during installation by editing setup.py . Alternatively, it might go the other direction and include code from all supported VCS systems, reducing the number of intermediate scripts. ## License To make Versioneer easier to embed, all its code is dedicated to the public domain. The `_version.py` that it creates is also in the public domain. Specifically, both are released under the Creative Commons ""Public Domain Dedication"" license (CC0-1.0), as described in https://creativecommons.org/publicdomain/zero/1.0/ . """""" from __future__ import print_function try: import configparser except ImportError: import ConfigParser as configparser import errno import json import os import re import subprocess import sys class VersioneerConfig: """"""Container for Versioneer configuration parameters."""""" def get_root(): """"""Get the project root directory. We require that all commands are run from the project root, i.e. the directory that contains setup.py, setup.cfg, and versioneer.py . """""" root = os.path.realpath(os.path.abspath(os.getcwd())) setup_py = os.path.join(root, ""setup.py"") versioneer_py = os.path.join(root, ""versioneer.py"") if not (os.path.exists(setup_py) or os.path.exists(versioneer_py)): # allow 'python path/to/setup.py COMMAND' root = os.path.dirname(os.path.realpath(os.path.abspath(sys.argv[0]))) setup_py = os.path.join(root, ""setup.py"") versioneer_py = os.path.join(root, ""versioneer.py"") if not (os.path.exists(setup_py) or os.path.exists(versioneer_py)): err = (""Versioneer was unable to run the project root directory. "" ""Versioneer requires setup.py to be executed from "" ""its immediate directory (like 'python setup.py COMMAND'), "" ""or in a way that lets it use sys.argv[0] to find the root "" ""(like 'python path/to/setup.py COMMAND')."") raise VersioneerBadRootError(err) try: # Certain runtime workflows (setup.py install/develop in a setuptools # tree) execute all dependencies in a single python process, so # ""versioneer"" may be imported multiple times, and python's shared # module-import table will cache the first one. So we can't use # os.path.dirname(__file__), as that will find whichever # versioneer.py was first imported, even in later projects. me = os.path.realpath(os.path.abspath(__file__)) me_dir = os.path.normcase(os.path.splitext(me)[0]) vsr_dir = os.path.normcase(os.path.splitext(versioneer_py)[0]) if me_dir != vsr_dir: print(""Warning: build in %s is using versioneer.py from %s"" % (os.path.dirname(me), versioneer_py)) except NameError: pass return root def get_config_from_root(root): """"""Read the project setup.cfg file to determine Versioneer config."""""" # This might raise EnvironmentError (if setup.cfg is missing), or # configparser.NoSectionError (if it lacks a [versioneer] section), or # configparser.NoOptionError (if it lacks ""VCS=""). See the docstring at # the top of versioneer.py for instructions on writing your setup.cfg . setup_cfg = os.path.join(root, ""setup.cfg"") parser = configparser.SafeConfigParser() with open(setup_cfg, ""r"") as f: parser.readfp(f) VCS = parser.get(""versioneer"", ""VCS"") # mandatory def get(parser, name): if parser.has_option(""versioneer"", name): return parser.get(""versioneer"", name) return None cfg = VersioneerConfig() cfg.VCS = VCS cfg.style = get(parser, ""style"") or """" cfg.versionfile_source = get(parser, ""versionfile_source"") cfg.versionfile_build = get(parser, ""versionfile_build"") cfg.tag_prefix = get(parser, ""tag_prefix"") if cfg.tag_prefix in (""''"", '""""'): cfg.tag_prefix = """" cfg.parentdir_prefix = get(parser, ""parentdir_prefix"") cfg.verbose = get(parser, ""verbose"") return cfg class NotThisMethod(Exception): """"""Exception raised if a method is not valid for the current scenario."""""" # these dictionaries contain VCS-specific tools LONG_VERSION_PY = {} HANDLERS = {} def register_vcs_handler(vcs, method): # decorator """"""Decorator to mark a method as the handler for a particular VCS."""""" def decorate(f): """"""Store f in HANDLERS[vcs][method]."""""" if vcs not in HANDLERS: HANDLERS[vcs] = {} HANDLERS[vcs][method] = f return f return decorate def run_command(commands, args, cwd=None, verbose=False, hide_stderr=False, env=None): """"""Call the given command(s)."""""" assert isinstance(commands, list) p = None for c in commands: try: dispcmd = str([c] + args) # remember shell=False, so use git.cmd on windows, not just git p = subprocess.Popen([c] + args, cwd=cwd, env=env, stdout=subprocess.PIPE, stderr=(subprocess.PIPE if hide_stderr else None)) break except EnvironmentError: e = sys.exc_info()[1] if e.errno == errno.ENOENT: continue if verbose: print(""unable to run %s"" % dispcmd) print(e) return None, None else: if verbose: print(""unable to find command, tried %s"" % (commands,)) return None, None stdout = p.communicate()[0].strip() if sys.version_info[0] >= 3: stdout = stdout.decode() if p.returncode != 0: if verbose: print(""unable to run %s (error)"" % dispcmd) print(""stdout was %s"" % stdout) return None, p.returncode return stdout, p.returncode LONG_VERSION_PY['git'] = ''' # This file helps to compute a version number in source trees obtained from # git-archive tarball (such as those provided by githubs download-from-tag # feature). Distribution tarballs (built by setup.py sdist) and build # directories (produced by setup.py build) will contain a much shorter file # that just contains the computed version number. # This file is released into the public domain. Generated by # versioneer-0.18 (https://github.com/warner/python-versioneer) """"""Git implementation of _version.py."""""" import errno import os import re import subprocess import sys def get_keywords(): """"""Get the keywords needed to look up the version information."""""" # these strings will be replaced by git during git-archive. # setup.py/versioneer.py will grep for the variable names, so they must # each be defined on a line of their own. _version.py will just call # get_keywords(). git_refnames = ""%(DOLLAR)sFormat:%%d%(DOLLAR)s"" git_full = ""%(DOLLAR)sFormat:%%H%(DOLLAR)s"" git_date = ""%(DOLLAR)sFormat:%%ci%(DOLLAR)s"" keywords = {""refnames"": git_refnames, ""full"": git_full, ""date"": git_date} return keywords class VersioneerConfig: """"""Container for Versioneer configuration parameters."""""" def get_config(): """"""Create, populate and return the VersioneerConfig() object."""""" # these strings are filled in when 'setup.py versioneer' creates # _version.py cfg = VersioneerConfig() cfg.VCS = ""git"" cfg.style = ""%(STYLE)s"" cfg.tag_prefix = ""%(TAG_PREFIX)s"" cfg.parentdir_prefix = ""%(PARENTDIR_PREFIX)s"" cfg.versionfile_source = ""%(VERSIONFILE_SOURCE)s"" cfg.verbose = False return cfg class NotThisMethod(Exception): """"""Exception raised if a method is not valid for the current scenario."""""" LONG_VERSION_PY = {} HANDLERS = {} def register_vcs_handler(vcs, method): # decorator """"""Decorator to mark a method as the handler for a particular VCS."""""" def decorate(f): """"""Store f in HANDLERS[vcs][method]."""""" if vcs not in HANDLERS: HANDLERS[vcs] = {} HANDLERS[vcs][method] = f return f return decorate def run_command(commands, args, cwd=None, verbose=False, hide_stderr=False, env=None): """"""Call the given command(s)."""""" assert isinstance(commands, list) p = None for c in commands: try: dispcmd = str([c] + args) # remember shell=False, so use git.cmd on windows, not just git p = subprocess.Popen([c] + args, cwd=cwd, env=env, stdout=subprocess.PIPE, stderr=(subprocess.PIPE if hide_stderr else None)) break except EnvironmentError: e = sys.exc_info()[1] if e.errno == errno.ENOENT: continue if verbose: print(""unable to run %%s"" %% dispcmd) print(e) return None, None else: if verbose: print(""unable to find command, tried %%s"" %% (commands,)) return None, None stdout = p.communicate()[0].strip() if sys.version_info[0] >= 3: stdout = stdout.decode() if p.returncode != 0: if verbose: print(""unable to run %%s (error)"" %% dispcmd) print(""stdout was %%s"" %% stdout) return None, p.returncode return stdout, p.returncode def versions_from_parentdir(parentdir_prefix, root, verbose): """"""Try to determine the version from the parent directory name. Source tarballs conventionally unpack into a directory that includes both the project name and a version string. We will also support searching up two directory levels for an appropriately named parent directory """""" rootdirs = [] for i in range(3): dirname = os.path.basename(root) if dirname.startswith(parentdir_prefix): return {""version"": dirname[len(parentdir_prefix):], ""full-revisionid"": None, ""dirty"": False, ""error"": None, ""date"": None} else: rootdirs.append(root) root = os.path.dirname(root) # up a level if verbose: print(""Tried directories %%s but none started with prefix %%s"" %% (str(rootdirs), parentdir_prefix)) raise NotThisMethod(""rootdir doesn't start with parentdir_prefix"") @register_vcs_handler(""git"", ""get_keywords"") def git_get_keywords(versionfile_abs): """"""Extract version information from the given file."""""" # the code embedded in _version.py can just fetch the value of these # keywords. When used from setup.py, we don't want to import _version.py, # so we do it with a regexp instead. This function is not used from # _version.py. keywords = {} try: f = open(versionfile_abs, ""r"") for line in f.readlines(): if line.strip().startswith(""git_refnames =""): mo = re.search(r'=\s*""(.*)""', line) if mo: keywords[""refnames""] = mo.group(1) if line.strip().startswith(""git_full =""): mo = re.search(r'=\s*""(.*)""', line) if mo: keywords[""full""] = mo.group(1) if line.strip().startswith(""git_date =""): mo = re.search(r'=\s*""(.*)""', line) if mo: keywords[""date""] = mo.group(1) f.close() except EnvironmentError: pass return keywords @register_vcs_handler(""git"", ""keywords"") def git_versions_from_keywords(keywords, tag_prefix, verbose): """"""Get version information from git keywords."""""" if not keywords: raise NotThisMethod(""no keywords at all, weird"") date = keywords.get(""date"") if date is not None: # git-2.2.0 added ""%%cI"", which expands to an ISO-8601 -compliant # datestamp. However we prefer ""%%ci"" (which expands to an ""ISO-8601 # -like"" string, which we must then edit to make compliant), because # it's been around since git-1.5.3, and it's too difficult to # discover which version we're using, or to work around using an # older one. date = date.strip().replace("" "", ""T"", 1).replace("" "", """", 1) refnames = keywords[""refnames""].strip() if refnames.startswith(""$Format""): if verbose: print(""keywords are unexpanded, not using"") raise NotThisMethod(""unexpanded keywords, not a git-archive tarball"") refs = set([r.strip() for r in refnames.strip(""()"").split("","")]) # starting in git-1.8.3, tags are listed as ""tag: foo-1.0"" instead of # just ""foo-1.0"". If we see a ""tag: "" prefix, prefer those. TAG = ""tag: "" tags = set([r[len(TAG):] for r in refs if r.startswith(TAG)]) if not tags: # Either we're using git < 1.8.3, or there really are no tags. We use # a heuristic: assume all version tags have a digit. The old git %%d # expansion behaves like git log --decorate=short and strips out the # refs/heads/ and refs/tags/ prefixes that would let us distinguish # between branches and tags. By ignoring refnames without digits, we # filter out many common branch names like ""release"" and # ""stabilization"", as well as ""HEAD"" and ""master"". tags = set([r for r in refs if re.search(r'\d', r)]) if verbose: print(""discarding '%%s', no digits"" %% "","".join(refs - tags)) if verbose: print(""likely tags: %%s"" %% "","".join(sorted(tags))) for ref in sorted(tags): # sorting will prefer e.g. ""2.0"" over ""2.0rc1"" if ref.startswith(tag_prefix): r = ref[len(tag_prefix):] if verbose: print(""picking %%s"" %% r) return {""version"": r, ""full-revisionid"": keywords[""full""].strip(), ""dirty"": False, ""error"": None, ""date"": date} # no suitable tags, so version is ""0+unknown"", but full hex is still there if verbose: print(""no suitable tags, using unknown + full revision id"") return {""version"": ""0+unknown"", ""full-revisionid"": keywords[""full""].strip(), ""dirty"": False, ""error"": ""no suitable tags"", ""date"": None} @register_vcs_handler(""git"", ""pieces_from_vcs"") def git_pieces_from_vcs(tag_prefix, root, verbose, run_command=run_command): """"""Get version from 'git describe' in the root of the source tree. This only gets called if the git-archive 'subst' keywords were *not* expanded, and _version.py hasn't already been rewritten with a short version string, meaning we're inside a checked out source tree. """""" GITS = [""git""] if sys.platform == ""win32"": GITS = [""git.cmd"", ""git.exe""] out, rc = run_command(GITS, [""rev-parse"", ""--git-dir""], cwd=root, hide_stderr=True) if rc != 0: if verbose: print(""Directory %%s not under git control"" %% root) raise NotThisMethod(""'git rev-parse --git-dir' returned error"") # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] # if there isn't one, this yields HEX[-dirty] (no NUM) describe_out, rc = run_command(GITS, [""describe"", ""--tags"", ""--dirty"", ""--always"", ""--long"", ""--match"", ""%%s*"" %% tag_prefix], cwd=root) # --long was added in git-1.5.5 if describe_out is None: raise NotThisMethod(""'git describe' failed"") describe_out = describe_out.strip() full_out, rc = run_command(GITS, [""rev-parse"", ""HEAD""], cwd=root) if full_out is None: raise NotThisMethod(""'git rev-parse' failed"") full_out = full_out.strip() pieces = {} pieces[""long""] = full_out pieces[""short""] = full_out[:7] # maybe improved later pieces[""error""] = None # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] # TAG might have hyphens. git_describe = describe_out # look for -dirty suffix dirty = git_describe.endswith(""-dirty"") pieces[""dirty""] = dirty if dirty: git_describe = git_describe[:git_describe.rindex(""-dirty"")] # now we have TAG-NUM-gHEX or HEX if ""-"" in git_describe: # TAG-NUM-gHEX mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe) if not mo: # unparseable. Maybe git-describe is misbehaving? pieces[""error""] = (""unable to parse git-describe output: '%%s'"" %% describe_out) return pieces # tag full_tag = mo.group(1) if not full_tag.startswith(tag_prefix): if verbose: fmt = ""tag '%%s' doesn't start with prefix '%%s'"" print(fmt %% (full_tag, tag_prefix)) pieces[""error""] = (""tag '%%s' doesn't start with prefix '%%s'"" %% (full_tag, tag_prefix)) return pieces pieces[""closest-tag""] = full_tag[len(tag_prefix):] # distance: number of commits since tag pieces[""distance""] = int(mo.group(2)) # commit: short hex revision ID pieces[""short""] = mo.group(3) else: # HEX: no tags pieces[""closest-tag""] = None count_out, rc = run_command(GITS, [""rev-list"", ""HEAD"", ""--count""], cwd=root) pieces[""distance""] = int(count_out) # total number of commits # commit date: see ISO-8601 comment in git_versions_from_keywords() date = run_command(GITS, [""show"", ""-s"", ""--format=%%ci"", ""HEAD""], cwd=root)[0].strip() pieces[""date""] = date.strip().replace("" "", ""T"", 1).replace("" "", """", 1) return pieces def plus_or_dot(pieces): """"""Return a + if we don't already have one, else return a ."""""" if ""+"" in pieces.get(""closest-tag"", """"): return ""."" return ""+"" def render_pep440(pieces): """"""Build up version string, with post-release ""local version identifier"". Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty Exceptions: 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] if pieces[""distance""] or pieces[""dirty""]: rendered += plus_or_dot(pieces) rendered += ""%%d.g%%s"" %% (pieces[""distance""], pieces[""short""]) if pieces[""dirty""]: rendered += "".dirty"" else: # exception #1 rendered = ""0+untagged.%%d.g%%s"" %% (pieces[""distance""], pieces[""short""]) if pieces[""dirty""]: rendered += "".dirty"" return rendered def render_pep440_pre(pieces): """"""TAG[.post.devDISTANCE] -- No -dirty. Exceptions: 1: no tags. 0.post.devDISTANCE """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] if pieces[""distance""]: rendered += "".post.dev%%d"" %% pieces[""distance""] else: # exception #1 rendered = ""0.post.dev%%d"" %% pieces[""distance""] return rendered def render_pep440_post(pieces): """"""TAG[.postDISTANCE[.dev0]+gHEX] . The "".dev0"" means dirty. Note that .dev0 sorts backwards (a dirty tree will appear ""older"" than the corresponding clean one), but you shouldn't be releasing software with -dirty anyways. Exceptions: 1: no tags. 0.postDISTANCE[.dev0] """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] if pieces[""distance""] or pieces[""dirty""]: rendered += "".post%%d"" %% pieces[""distance""] if pieces[""dirty""]: rendered += "".dev0"" rendered += plus_or_dot(pieces) rendered += ""g%%s"" %% pieces[""short""] else: # exception #1 rendered = ""0.post%%d"" %% pieces[""distance""] if pieces[""dirty""]: rendered += "".dev0"" rendered += ""+g%%s"" %% pieces[""short""] return rendered def render_pep440_old(pieces): """"""TAG[.postDISTANCE[.dev0]] . The "".dev0"" means dirty. Eexceptions: 1: no tags. 0.postDISTANCE[.dev0] """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] if pieces[""distance""] or pieces[""dirty""]: rendered += "".post%%d"" %% pieces[""distance""] if pieces[""dirty""]: rendered += "".dev0"" else: # exception #1 rendered = ""0.post%%d"" %% pieces[""distance""] if pieces[""dirty""]: rendered += "".dev0"" return rendered def render_git_describe(pieces): """"""TAG[-DISTANCE-gHEX][-dirty]. Like 'git describe --tags --dirty --always'. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] if pieces[""distance""]: rendered += ""-%%d-g%%s"" %% (pieces[""distance""], pieces[""short""]) else: # exception #1 rendered = pieces[""short""] if pieces[""dirty""]: rendered += ""-dirty"" return rendered def render_git_describe_long(pieces): """"""TAG-DISTANCE-gHEX[-dirty]. Like 'git describe --tags --dirty --always -long'. The distance/hash is unconditional. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] rendered += ""-%%d-g%%s"" %% (pieces[""distance""], pieces[""short""]) else: # exception #1 rendered = pieces[""short""] if pieces[""dirty""]: rendered += ""-dirty"" return rendered def render(pieces, style): """"""Render the given version pieces into the requested style."""""" if pieces[""error""]: return {""version"": ""unknown"", ""full-revisionid"": pieces.get(""long""), ""dirty"": None, ""error"": pieces[""error""], ""date"": None} if not style or style == ""default"": style = ""pep440"" # the default if style == ""pep440"": rendered = render_pep440(pieces) elif style == ""pep440-pre"": rendered = render_pep440_pre(pieces) elif style == ""pep440-post"": rendered = render_pep440_post(pieces) elif style == ""pep440-old"": rendered = render_pep440_old(pieces) elif style == ""git-describe"": rendered = render_git_describe(pieces) elif style == ""git-describe-long"": rendered = render_git_describe_long(pieces) else: raise ValueError(""unknown style '%%s'"" %% style) return {""version"": rendered, ""full-revisionid"": pieces[""long""], ""dirty"": pieces[""dirty""], ""error"": None, ""date"": pieces.get(""date"")} def get_versions(): """"""Get version information or return default if unable to do so."""""" # I am in _version.py, which lives at ROOT/VERSIONFILE_SOURCE. If we have # __file__, we can work backwards from there to the root. Some # py2exe/bbfreeze/non-CPython implementations don't do __file__, in which # case we can only use expanded keywords. cfg = get_config() verbose = cfg.verbose try: return git_versions_from_keywords(get_keywords(), cfg.tag_prefix, verbose) except NotThisMethod: pass try: root = os.path.realpath(__file__) # versionfile_source is the relative path from the top of the source # tree (where the .git directory might live) to this file. Invert # this to find the root from __file__. for i in cfg.versionfile_source.split('/'): root = os.path.dirname(root) except NameError: return {""version"": ""0+unknown"", ""full-revisionid"": None, ""dirty"": None, ""error"": ""unable to find root of source tree"", ""date"": None} try: pieces = git_pieces_from_vcs(cfg.tag_prefix, root, verbose) return render(pieces, cfg.style) except NotThisMethod: pass try: if cfg.parentdir_prefix: return versions_from_parentdir(cfg.parentdir_prefix, root, verbose) except NotThisMethod: pass return {""version"": ""0+unknown"", ""full-revisionid"": None, ""dirty"": None, ""error"": ""unable to compute version"", ""date"": None} ''' @register_vcs_handler(""git"", ""get_keywords"") def git_get_keywords(versionfile_abs): """"""Extract version information from the given file."""""" # the code embedded in _version.py can just fetch the value of these # keywords. When used from setup.py, we don't want to import _version.py, # so we do it with a regexp instead. This function is not used from # _version.py. keywords = {} try: f = open(versionfile_abs, ""r"") for line in f.readlines(): if line.strip().startswith(""git_refnames =""): mo = re.search(r'=\s*""(.*)""', line) if mo: keywords[""refnames""] = mo.group(1) if line.strip().startswith(""git_full =""): mo = re.search(r'=\s*""(.*)""', line) if mo: keywords[""full""] = mo.group(1) if line.strip().startswith(""git_date =""): mo = re.search(r'=\s*""(.*)""', line) if mo: keywords[""date""] = mo.group(1) f.close() except EnvironmentError: pass return keywords @register_vcs_handler(""git"", ""keywords"") def git_versions_from_keywords(keywords, tag_prefix, verbose): """"""Get version information from git keywords."""""" if not keywords: raise NotThisMethod(""no keywords at all, weird"") date = keywords.get(""date"") if date is not None: # git-2.2.0 added ""%cI"", which expands to an ISO-8601 -compliant # datestamp. However we prefer ""%ci"" (which expands to an ""ISO-8601 # -like"" string, which we must then edit to make compliant), because # it's been around since git-1.5.3, and it's too difficult to # discover which version we're using, or to work around using an # older one. date = date.strip().replace("" "", ""T"", 1).replace("" "", """", 1) refnames = keywords[""refnames""].strip() if refnames.startswith(""$Format""): if verbose: print(""keywords are unexpanded, not using"") raise NotThisMethod(""unexpanded keywords, not a git-archive tarball"") refs = set([r.strip() for r in refnames.strip(""()"").split("","")]) # starting in git-1.8.3, tags are listed as ""tag: foo-1.0"" instead of # just ""foo-1.0"". If we see a ""tag: "" prefix, prefer those. TAG = ""tag: "" tags = set([r[len(TAG):] for r in refs if r.startswith(TAG)]) if not tags: # Either we're using git < 1.8.3, or there really are no tags. We use # a heuristic: assume all version tags have a digit. The old git %d # expansion behaves like git log --decorate=short and strips out the # refs/heads/ and refs/tags/ prefixes that would let us distinguish # between branches and tags. By ignoring refnames without digits, we # filter out many common branch names like ""release"" and # ""stabilization"", as well as ""HEAD"" and ""master"". tags = set([r for r in refs if re.search(r'\d', r)]) if verbose: print(""discarding '%s', no digits"" % "","".join(refs - tags)) if verbose: print(""likely tags: %s"" % "","".join(sorted(tags))) for ref in sorted(tags): # sorting will prefer e.g. ""2.0"" over ""2.0rc1"" if ref.startswith(tag_prefix): r = ref[len(tag_prefix):] if verbose: print(""picking %s"" % r) return {""version"": r, ""full-revisionid"": keywords[""full""].strip(), ""dirty"": False, ""error"": None, ""date"": date} # no suitable tags, so version is ""0+unknown"", but full hex is still there if verbose: print(""no suitable tags, using unknown + full revision id"") return {""version"": ""0+unknown"", ""full-revisionid"": keywords[""full""].strip(), ""dirty"": False, ""error"": ""no suitable tags"", ""date"": None} @register_vcs_handler(""git"", ""pieces_from_vcs"") def git_pieces_from_vcs(tag_prefix, root, verbose, run_command=run_command): """"""Get version from 'git describe' in the root of the source tree. This only gets called if the git-archive 'subst' keywords were *not* expanded, and _version.py hasn't already been rewritten with a short version string, meaning we're inside a checked out source tree. """""" GITS = [""git""] if sys.platform == ""win32"": GITS = [""git.cmd"", ""git.exe""] out, rc = run_command(GITS, [""rev-parse"", ""--git-dir""], cwd=root, hide_stderr=True) if rc != 0: if verbose: print(""Directory %s not under git control"" % root) raise NotThisMethod(""'git rev-parse --git-dir' returned error"") # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] # if there isn't one, this yields HEX[-dirty] (no NUM) describe_out, rc = run_command(GITS, [""describe"", ""--tags"", ""--dirty"", ""--always"", ""--long"", ""--match"", ""%s*"" % tag_prefix], cwd=root) # --long was added in git-1.5.5 if describe_out is None: raise NotThisMethod(""'git describe' failed"") describe_out = describe_out.strip() full_out, rc = run_command(GITS, [""rev-parse"", ""HEAD""], cwd=root) if full_out is None: raise NotThisMethod(""'git rev-parse' failed"") full_out = full_out.strip() pieces = {} pieces[""long""] = full_out pieces[""short""] = full_out[:7] # maybe improved later pieces[""error""] = None # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] # TAG might have hyphens. git_describe = describe_out # look for -dirty suffix dirty = git_describe.endswith(""-dirty"") pieces[""dirty""] = dirty if dirty: git_describe = git_describe[:git_describe.rindex(""-dirty"")] # now we have TAG-NUM-gHEX or HEX if ""-"" in git_describe: # TAG-NUM-gHEX mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe) if not mo: # unparseable. Maybe git-describe is misbehaving? pieces[""error""] = (""unable to parse git-describe output: '%s'"" % describe_out) return pieces # tag full_tag = mo.group(1) if not full_tag.startswith(tag_prefix): if verbose: fmt = ""tag '%s' doesn't start with prefix '%s'"" print(fmt % (full_tag, tag_prefix)) pieces[""error""] = (""tag '%s' doesn't start with prefix '%s'"" % (full_tag, tag_prefix)) return pieces pieces[""closest-tag""] = full_tag[len(tag_prefix):] # distance: number of commits since tag pieces[""distance""] = int(mo.group(2)) # commit: short hex revision ID pieces[""short""] = mo.group(3) else: # HEX: no tags pieces[""closest-tag""] = None count_out, rc = run_command(GITS, [""rev-list"", ""HEAD"", ""--count""], cwd=root) pieces[""distance""] = int(count_out) # total number of commits # commit date: see ISO-8601 comment in git_versions_from_keywords() date = run_command(GITS, [""show"", ""-s"", ""--format=%ci"", ""HEAD""], cwd=root)[0].strip() pieces[""date""] = date.strip().replace("" "", ""T"", 1).replace("" "", """", 1) return pieces def do_vcs_install(manifest_in, versionfile_source, ipy): """"""Git-specific installation logic for Versioneer. For Git, this means creating/changing .gitattributes to mark _version.py for export-subst keyword substitution. """""" GITS = [""git""] if sys.platform == ""win32"": GITS = [""git.cmd"", ""git.exe""] files = [manifest_in, versionfile_source] if ipy: files.append(ipy) try: me = __file__ if me.endswith("".pyc"") or me.endswith("".pyo""): me = os.path.splitext(me)[0] + "".py"" versioneer_file = os.path.relpath(me) except NameError: versioneer_file = ""versioneer.py"" files.append(versioneer_file) present = False try: f = open("".gitattributes"", ""r"") for line in f.readlines(): if line.strip().startswith(versionfile_source): if ""export-subst"" in line.strip().split()[1:]: present = True f.close() except EnvironmentError: pass if not present: f = open("".gitattributes"", ""a+"") f.write(""%s export-subst\n"" % versionfile_source) f.close() files.append("".gitattributes"") run_command(GITS, [""add"", ""--""] + files) def versions_from_parentdir(parentdir_prefix, root, verbose): """"""Try to determine the version from the parent directory name. Source tarballs conventionally unpack into a directory that includes both the project name and a version string. We will also support searching up two directory levels for an appropriately named parent directory """""" rootdirs = [] for i in range(3): dirname = os.path.basename(root) if dirname.startswith(parentdir_prefix): return {""version"": dirname[len(parentdir_prefix):], ""full-revisionid"": None, ""dirty"": False, ""error"": None, ""date"": None} else: rootdirs.append(root) root = os.path.dirname(root) # up a level if verbose: print(""Tried directories %s but none started with prefix %s"" % (str(rootdirs), parentdir_prefix)) raise NotThisMethod(""rootdir doesn't start with parentdir_prefix"") SHORT_VERSION_PY = """""" # This file was generated by 'versioneer.py' (0.18) from # revision-control system data, or from the parent directory name of an # unpacked source archive. Distribution tarballs contain a pre-generated copy # of this file. import json version_json = ''' %s ''' # END VERSION_JSON def get_versions(): return json.loads(version_json) """""" def versions_from_file(filename): """"""Try to determine the version from _version.py if present."""""" try: with open(filename) as f: contents = f.read() except EnvironmentError: raise NotThisMethod(""unable to read _version.py"") mo = re.search(r""version_json = '''\n(.*)''' # END VERSION_JSON"", contents, re.M | re.S) if not mo: mo = re.search(r""version_json = '''\r\n(.*)''' # END VERSION_JSON"", contents, re.M | re.S) if not mo: raise NotThisMethod(""no version_json in _version.py"") return json.loads(mo.group(1)) def write_to_version_file(filename, versions): """"""Write the given version number to the given _version.py file."""""" os.unlink(filename) contents = json.dumps(versions, sort_keys=True, indent=1, separators=("","", "": "")) with open(filename, ""w"") as f: f.write(SHORT_VERSION_PY % contents) print(""set %s to '%s'"" % (filename, versions[""version""])) def plus_or_dot(pieces): """"""Return a + if we don't already have one, else return a ."""""" if ""+"" in pieces.get(""closest-tag"", """"): return ""."" return ""+"" def render_pep440(pieces): """"""Build up version string, with post-release ""local version identifier"". Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty Exceptions: 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] if pieces[""distance""] or pieces[""dirty""]: rendered += plus_or_dot(pieces) rendered += ""%d.g%s"" % (pieces[""distance""], pieces[""short""]) if pieces[""dirty""]: rendered += "".dirty"" else: # exception #1 rendered = ""0+untagged.%d.g%s"" % (pieces[""distance""], pieces[""short""]) if pieces[""dirty""]: rendered += "".dirty"" return rendered def render_pep440_pre(pieces): """"""TAG[.post.devDISTANCE] -- No -dirty. Exceptions: 1: no tags. 0.post.devDISTANCE """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] if pieces[""distance""]: rendered += "".post.dev%d"" % pieces[""distance""] else: # exception #1 rendered = ""0.post.dev%d"" % pieces[""distance""] return rendered def render_pep440_post(pieces): """"""TAG[.postDISTANCE[.dev0]+gHEX] . The "".dev0"" means dirty. Note that .dev0 sorts backwards (a dirty tree will appear ""older"" than the corresponding clean one), but you shouldn't be releasing software with -dirty anyways. Exceptions: 1: no tags. 0.postDISTANCE[.dev0] """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] if pieces[""distance""] or pieces[""dirty""]: rendered += "".post%d"" % pieces[""distance""] if pieces[""dirty""]: rendered += "".dev0"" rendered += plus_or_dot(pieces) rendered += ""g%s"" % pieces[""short""] else: # exception #1 rendered = ""0.post%d"" % pieces[""distance""] if pieces[""dirty""]: rendered += "".dev0"" rendered += ""+g%s"" % pieces[""short""] return rendered def render_pep440_old(pieces): """"""TAG[.postDISTANCE[.dev0]] . The "".dev0"" means dirty. Eexceptions: 1: no tags. 0.postDISTANCE[.dev0] """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] if pieces[""distance""] or pieces[""dirty""]: rendered += "".post%d"" % pieces[""distance""] if pieces[""dirty""]: rendered += "".dev0"" else: # exception #1 rendered = ""0.post%d"" % pieces[""distance""] if pieces[""dirty""]: rendered += "".dev0"" return rendered def render_git_describe(pieces): """"""TAG[-DISTANCE-gHEX][-dirty]. Like 'git describe --tags --dirty --always'. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] if pieces[""distance""]: rendered += ""-%d-g%s"" % (pieces[""distance""], pieces[""short""]) else: # exception #1 rendered = pieces[""short""] if pieces[""dirty""]: rendered += ""-dirty"" return rendered def render_git_describe_long(pieces): """"""TAG-DISTANCE-gHEX[-dirty]. Like 'git describe --tags --dirty --always -long'. The distance/hash is unconditional. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] rendered += ""-%d-g%s"" % (pieces[""distance""], pieces[""short""]) else: # exception #1 rendered = pieces[""short""] if pieces[""dirty""]: rendered += ""-dirty"" return rendered def render(pieces, style): """"""Render the given version pieces into the requested style."""""" if pieces[""error""]: return {""version"": ""unknown"", ""full-revisionid"": pieces.get(""long""), ""dirty"": None, ""error"": pieces[""error""], ""date"": None} if not style or style == ""default"": style = ""pep440"" # the default if style == ""pep440"": rendered = render_pep440(pieces) elif style == ""pep440-pre"": rendered = render_pep440_pre(pieces) elif style == ""pep440-post"": rendered = render_pep440_post(pieces) elif style == ""pep440-old"": rendered = render_pep440_old(pieces) elif style == ""git-describe"": rendered = render_git_describe(pieces) elif style == ""git-describe-long"": rendered = render_git_describe_long(pieces) else: raise ValueError(""unknown style '%s'"" % style) return {""version"": rendered, ""full-revisionid"": pieces[""long""], ""dirty"": pieces[""dirty""], ""error"": None, ""date"": pieces.get(""date"")} class VersioneerBadRootError(Exception): """"""The project root directory is unknown or missing key files."""""" def get_versions(verbose=False): """"""Get the project version from whatever source is available. Returns dict with two keys: 'version' and 'full'. """""" if ""versioneer"" in sys.modules: # see the discussion in cmdclass.py:get_cmdclass() del sys.modules[""versioneer""] root = get_root() cfg = get_config_from_root(root) assert cfg.VCS is not None, ""please set [versioneer]VCS= in setup.cfg"" handlers = HANDLERS.get(cfg.VCS) assert handlers, ""unrecognized VCS '%s'"" % cfg.VCS verbose = verbose or cfg.verbose assert cfg.versionfile_source is not None, \ ""please set versioneer.versionfile_source"" assert cfg.tag_prefix is not None, ""please set versioneer.tag_prefix"" versionfile_abs = os.path.join(root, cfg.versionfile_source) # extract version from first of: _version.py, VCS command (e.g. 'git # describe'), parentdir. This is meant to work for developers using a # source checkout, for users of a tarball created by 'setup.py sdist', # and for users of a tarball/zipball created by 'git archive' or github's # download-from-tag feature or the equivalent in other VCSes. get_keywords_f = handlers.get(""get_keywords"") from_keywords_f = handlers.get(""keywords"") if get_keywords_f and from_keywords_f: try: keywords = get_keywords_f(versionfile_abs) ver = from_keywords_f(keywords, cfg.tag_prefix, verbose) if verbose: print(""got version from expanded keyword %s"" % ver) return ver except NotThisMethod: pass try: ver = versions_from_file(versionfile_abs) if verbose: print(""got version from file %s %s"" % (versionfile_abs, ver)) return ver except NotThisMethod: pass from_vcs_f = handlers.get(""pieces_from_vcs"") if from_vcs_f: try: pieces = from_vcs_f(cfg.tag_prefix, root, verbose) ver = render(pieces, cfg.style) if verbose: print(""got version from VCS %s"" % ver) return ver except NotThisMethod: pass try: if cfg.parentdir_prefix: ver = versions_from_parentdir(cfg.parentdir_prefix, root, verbose) if verbose: print(""got version from parentdir %s"" % ver) return ver except NotThisMethod: pass if verbose: print(""unable to compute version"") return {""version"": ""0+unknown"", ""full-revisionid"": None, ""dirty"": None, ""error"": ""unable to compute version"", ""date"": None} def get_version(): """"""Get the short version string for this project."""""" return get_versions()[""version""] def get_cmdclass(): """"""Get the custom setuptools/distutils subclasses used by Versioneer."""""" if ""versioneer"" in sys.modules: del sys.modules[""versioneer""] # this fixes the ""python setup.py develop"" case (also 'install' and # 'easy_install .'), in which subdependencies of the main project are # built (using setup.py bdist_egg) in the same python process. Assume # a main project A and a dependency B, which use different versions # of Versioneer. A's setup.py imports A's Versioneer, leaving it in # sys.modules by the time B's setup.py is executed, causing B to run # with the wrong versioneer. Setuptools wraps the sub-dep builds in a # sandbox that restores sys.modules to it's pre-build state, so the # parent is protected against the child's ""import versioneer"". By # removing ourselves from sys.modules here, before the child build # happens, we protect the child from the parent's versioneer too. # Also see https://github.com/warner/python-versioneer/issues/52 cmds = {} # we add ""version"" to both distutils and setuptools from distutils.core import Command class cmd_version(Command): description = ""report generated version string"" user_options = [] boolean_options = [] def initialize_options(self): pass def finalize_options(self): pass def run(self): vers = get_versions(verbose=True) print(""Version: %s"" % vers[""version""]) print("" full-revisionid: %s"" % vers.get(""full-revisionid"")) print("" dirty: %s"" % vers.get(""dirty"")) print("" date: %s"" % vers.get(""date"")) if vers[""error""]: print("" error: %s"" % vers[""error""]) cmds[""version""] = cmd_version # we override ""build_py"" in both distutils and setuptools # # most invocation pathways end up running build_py: # distutils/build -> build_py # distutils/install -> distutils/build ->.. # setuptools/bdist_wheel -> distutils/install ->.. # setuptools/bdist_egg -> distutils/install_lib -> build_py # setuptools/install -> bdist_egg ->.. # setuptools/develop -> ? # pip install: # copies source tree to a tempdir before running egg_info/etc # if .git isn't copied too, 'git describe' will fail # then does setup.py bdist_wheel, or sometimes setup.py install # setup.py egg_info -> ? # we override different ""build_py"" commands for both environments if ""setuptools"" in sys.modules: from setuptools.command.build_py import build_py as _build_py else: from distutils.command.build_py import build_py as _build_py class cmd_build_py(_build_py): def run(self): root = get_root() cfg = get_config_from_root(root) versions = get_versions() _build_py.run(self) # now locate _version.py in the new build/ directory and replace # it with an updated value if cfg.versionfile_build: target_versionfile = os.path.join(self.build_lib, cfg.versionfile_build) print(""UPDATING %s"" % target_versionfile) write_to_version_file(target_versionfile, versions) cmds[""build_py""] = cmd_build_py if ""cx_Freeze"" in sys.modules: # cx_freeze enabled? from cx_Freeze.dist import build_exe as _build_exe # nczeczulin reports that py2exe won't like the pep440-style string # as FILEVERSION, but it can be used for PRODUCTVERSION, e.g. # setup(console=[{ # ""version"": versioneer.get_version().split(""+"", 1)[0], # FILEVERSION # ""product_version"": versioneer.get_version(), # ... class cmd_build_exe(_build_exe): def run(self): root = get_root() cfg = get_config_from_root(root) versions = get_versions() target_versionfile = cfg.versionfile_source print(""UPDATING %s"" % target_versionfile) write_to_version_file(target_versionfile, versions) _build_exe.run(self) os.unlink(target_versionfile) with open(cfg.versionfile_source, ""w"") as f: LONG = LONG_VERSION_PY[cfg.VCS] f.write(LONG % {""DOLLAR"": ""$"", ""STYLE"": cfg.style, ""TAG_PREFIX"": cfg.tag_prefix, ""PARENTDIR_PREFIX"": cfg.parentdir_prefix, ""VERSIONFILE_SOURCE"": cfg.versionfile_source, }) cmds[""build_exe""] = cmd_build_exe del cmds[""build_py""] if 'py2exe' in sys.modules: # py2exe enabled? try: from py2exe.distutils_buildexe import py2exe as _py2exe # py3 except ImportError: from py2exe.build_exe import py2exe as _py2exe # py2 class cmd_py2exe(_py2exe): def run(self): root = get_root() cfg = get_config_from_root(root) versions = get_versions() target_versionfile = cfg.versionfile_source print(""UPDATING %s"" % target_versionfile) write_to_version_file(target_versionfile, versions) _py2exe.run(self) os.unlink(target_versionfile) with open(cfg.versionfile_source, ""w"") as f: LONG = LONG_VERSION_PY[cfg.VCS] f.write(LONG % {""DOLLAR"": ""$"", ""STYLE"": cfg.style, ""TAG_PREFIX"": cfg.tag_prefix, ""PARENTDIR_PREFIX"": cfg.parentdir_prefix, ""VERSIONFILE_SOURCE"": cfg.versionfile_source, }) cmds[""py2exe""] = cmd_py2exe # we override different ""sdist"" commands for both environments if ""setuptools"" in sys.modules: from setuptools.command.sdist import sdist as _sdist else: from distutils.command.sdist import sdist as _sdist class cmd_sdist(_sdist): def run(self): versions = get_versions() self._versioneer_generated_versions = versions # unless we update this, the command will keep using the old # version self.distribution.metadata.version = versions[""version""] return _sdist.run(self) def make_release_tree(self, base_dir, files): root = get_root() cfg = get_config_from_root(root) _sdist.make_release_tree(self, base_dir, files) # now locate _version.py in the new base_dir directory # (remembering that it may be a hardlink) and replace it with an # updated value target_versionfile = os.path.join(base_dir, cfg.versionfile_source) print(""UPDATING %s"" % target_versionfile) write_to_version_file(target_versionfile, self._versioneer_generated_versions) cmds[""sdist""] = cmd_sdist return cmds CONFIG_ERROR = """""" setup.cfg is missing the necessary Versioneer configuration. You need a section like: [versioneer] VCS = git style = pep440 versionfile_source = src/myproject/_version.py versionfile_build = myproject/_version.py tag_prefix = parentdir_prefix = myproject- You will also need to edit your setup.py to use the results: import versioneer setup(version=versioneer.get_version(), cmdclass=versioneer.get_cmdclass(), ...) Please read the docstring in ./versioneer.py for configuration instructions, edit setup.cfg, and re-run the installer or 'python versioneer.py setup'. """""" SAMPLE_CONFIG = """""" # See the docstring in versioneer.py for instructions. Note that you must # re-run 'versioneer.py setup' after changing this section, and commit the # resulting files. [versioneer] #VCS = git #style = pep440 #versionfile_source = #versionfile_build = #tag_prefix = #parentdir_prefix = """""" INIT_PY_SNIPPET = """""" from ._version import get_versions __version__ = get_versions()['version'] del get_versions """""" def do_setup(): """"""Main VCS-independent setup function for installing Versioneer."""""" root = get_root() try: cfg = get_config_from_root(root) except (EnvironmentError, configparser.NoSectionError, configparser.NoOptionError) as e: if isinstance(e, (EnvironmentError, configparser.NoSectionError)): print(""Adding sample versioneer config to setup.cfg"", file=sys.stderr) with open(os.path.join(root, ""setup.cfg""), ""a"") as f: f.write(SAMPLE_CONFIG) print(CONFIG_ERROR, file=sys.stderr) return 1 print("" creating %s"" % cfg.versionfile_source) with open(cfg.versionfile_source, ""w"") as f: LONG = LONG_VERSION_PY[cfg.VCS] f.write(LONG % {""DOLLAR"": ""$"", ""STYLE"": cfg.style, ""TAG_PREFIX"": cfg.tag_prefix, ""PARENTDIR_PREFIX"": cfg.parentdir_prefix, ""VERSIONFILE_SOURCE"": cfg.versionfile_source, }) ipy = os.path.join(os.path.dirname(cfg.versionfile_source), ""__init__.py"") if os.path.exists(ipy): try: with open(ipy, ""r"") as f: old = f.read() except EnvironmentError: old = """" if INIT_PY_SNIPPET not in old: print("" appending to %s"" % ipy) with open(ipy, ""a"") as f: f.write(INIT_PY_SNIPPET) else: print("" %s unmodified"" % ipy) else: print("" %s doesn't exist, ok"" % ipy) ipy = None # Make sure both the top-level ""versioneer.py"" and versionfile_source # (PKG/_version.py, used by runtime code) are in MANIFEST.in, so # they'll be copied into source distributions. Pip won't be able to # install the package without this. manifest_in = os.path.join(root, ""MANIFEST.in"") simple_includes = set() try: with open(manifest_in, ""r"") as f: for line in f: if line.startswith(""include ""): for include in line.split()[1:]: simple_includes.add(include) except EnvironmentError: pass # That doesn't cover everything MANIFEST.in can do # (http://docs.python.org/2/distutils/sourcedist.html#commands), so # it might give some false negatives. Appending redundant 'include' # lines is safe, though. if ""versioneer.py"" not in simple_includes: print("" appending 'versioneer.py' to MANIFEST.in"") with open(manifest_in, ""a"") as f: f.write(""include versioneer.py\n"") else: print("" 'versioneer.py' already in MANIFEST.in"") if cfg.versionfile_source not in simple_includes: print("" appending versionfile_source ('%s') to MANIFEST.in"" % cfg.versionfile_source) with open(manifest_in, ""a"") as f: f.write(""include %s\n"" % cfg.versionfile_source) else: print("" versionfile_source already in MANIFEST.in"") # Make VCS-specific changes. For git, this means creating/changing # .gitattributes to mark _version.py for export-subst keyword # substitution. do_vcs_install(manifest_in, cfg.versionfile_source, ipy) return 0 def scan_setup_py(): """"""Validate the contents of setup.py against Versioneer's expectations."""""" found = set() setters = False errors = 0 with open(""setup.py"", ""r"") as f: for line in f.readlines(): if ""import versioneer"" in line: found.add(""import"") if ""versioneer.get_cmdclass()"" in line: found.add(""cmdclass"") if ""versioneer.get_version()"" in line: found.add(""get_version"") if ""versioneer.VCS"" in line: setters = True if ""versioneer.versionfile_source"" in line: setters = True if len(found) != 3: print("""") print(""Your setup.py appears to be missing some important items"") print(""(but I might be wrong). Please make sure it has something"") print(""roughly like the following:"") print("""") print("" import versioneer"") print("" setup( version=versioneer.get_version(),"") print("" cmdclass=versioneer.get_cmdclass(), ...)"") print("""") errors += 1 if setters: print(""You should remove lines like 'versioneer.VCS = ' and"") print(""'versioneer.versionfile_source = ' . This configuration"") print(""now lives in setup.cfg, and should be removed from setup.py"") print("""") errors += 1 return errors if __name__ == ""__main__"": cmd = sys.argv[1] if cmd == ""setup"": errors = do_setup() errors += scan_setup_py() if errors: sys.exit(1) ","Python" "Biophysics","tritemio/pycorrelate","travis_pypi_setup.py",".py","4079","128","#!/usr/bin/env python # -*- coding: utf-8 -*- """"""Update encrypted deploy password in Travis config file."""""" from __future__ import print_function import base64 import json import os from getpass import getpass import yaml from cryptography.hazmat.primitives.serialization import load_pem_public_key from cryptography.hazmat.backends import default_backend from cryptography.hazmat.primitives.asymmetric.padding import PKCS1v15 try: from urllib import urlopen except ImportError: from urllib.request import urlopen GITHUB_REPO = 'tritemio/pycorrelate' TRAVIS_CONFIG_FILE = os.path.join( os.path.dirname(os.path.abspath(__file__)), '.travis.yml') def load_key(pubkey): """"""Load public RSA key. Work around keys with incorrect header/footer format. Read more about RSA encryption with cryptography: https://cryptography.io/latest/hazmat/primitives/asymmetric/rsa/ """""" try: return load_pem_public_key(pubkey.encode(), default_backend()) except ValueError: # workaround for https://github.com/travis-ci/travis-api/issues/196 pubkey = pubkey.replace('BEGIN RSA', 'BEGIN').replace('END RSA', 'END') return load_pem_public_key(pubkey.encode(), default_backend()) def encrypt(pubkey, password): """"""Encrypt password using given RSA public key and encode it with base64. The encrypted password can only be decrypted by someone with the private key (in this case, only Travis). """""" key = load_key(pubkey) encrypted_password = key.encrypt(password, PKCS1v15()) return base64.b64encode(encrypted_password) def fetch_public_key(repo): """"""Download RSA public key Travis will use for this repo. Travis API docs: http://docs.travis-ci.com/api/#repository-keys """""" keyurl = 'https://api.travis-ci.org/repos/{0}/key'.format(repo) data = json.loads(urlopen(keyurl).read().decode()) if 'key' not in data: errmsg = ""Could not find public key for repo: {}.\n"".format(repo) errmsg += ""Have you already added your GitHub repo to Travis?"" raise ValueError(errmsg) return data['key'] def prepend_line(filepath, line): """"""Rewrite a file adding a line to its beginning."""""" with open(filepath) as f: lines = f.readlines() lines.insert(0, line) with open(filepath, 'w') as f: f.writelines(lines) def load_yaml_config(filepath): """"""Load yaml config file at the given path."""""" with open(filepath) as f: return yaml.load(f) def save_yaml_config(filepath, config): """"""Save yaml config file at the given path."""""" with open(filepath, 'w') as f: yaml.dump(config, f, default_flow_style=False) def update_travis_deploy_password(encrypted_password): """"""Put `encrypted_password` into the deploy section of .travis.yml."""""" config = load_yaml_config(TRAVIS_CONFIG_FILE) config['deploy']['password'] = dict(secure=encrypted_password) save_yaml_config(TRAVIS_CONFIG_FILE, config) line = ('# This file was autogenerated and will overwrite' ' each time you run travis_pypi_setup.py\n') prepend_line(TRAVIS_CONFIG_FILE, line) def main(args): """"""Add a PyPI password to .travis.yml so that Travis can deploy to PyPI. Fetch the Travis public key for the repo, and encrypt the PyPI password with it before adding, so that only Travis can decrypt and use the PyPI password. """""" public_key = fetch_public_key(args.repo) password = args.password or getpass('PyPI password: ') update_travis_deploy_password(encrypt(public_key, password.encode())) print(""Wrote encrypted password to .travis.yml -- you're ready to deploy"") if '__main__' == __name__: import argparse parser = argparse.ArgumentParser(description=__doc__) parser.add_argument('--repo', default=GITHUB_REPO, help='GitHub repo (default: %s)' % GITHUB_REPO) parser.add_argument('--password', help='PyPI password (will prompt if not provided)') args = parser.parse_args() main(args) ","Python" "Biophysics","tritemio/pycorrelate","pycorrelate/__init__.py",".py","261","11","from .pycorrelate import pcorrelate, ucorrelate, make_loglags, pnormalize from . import utils __author__ = """"""Antonino Ingargiola"""""" __email__ = 'tritemio@gmail.com' from ._version import get_versions __version__ = get_versions()['version'] del get_versions ","Python" "Biophysics","tritemio/pycorrelate","pycorrelate/pycorrelate.py",".py","7243","199",""""""" Functions to compute linear correlation on discrete signals (uniformly sampled in time) **or** on point-processes (e.g. timestamps of events). """""" import numpy as np import numba @numba.jit(nopython=True) def pnormalize(G, t, u, bins): r""""""Normalize point-process cross-correlation function. This normalization is usually employed for fluorescence correlation spectroscopy (FCS) analysis. The normalization is performed according to `(Laurence 2006) `__. Basically, the input argument `G` is multiplied by: .. math:: \frac{T-\tau}{n(\{i \ni t_i \le T - \tau\})n(\{j \ni u_j \ge \tau\})} where `n({})` is the operator counting the elements in a set, *t* and *u* are the input arrays of the correlation, *τ* is the time lag and *T* is the measurement duration. Arguments: G (array): raw cross-correlation to be normalized. t (array): first input array of ""points"" used to compute `G`. u (array): second input array of ""points"" used to compute `G`. bins (array): array of bins used to compute `G`. Needs to have the same units as input arguments `t` and `u`. Returns: Array of normalized values for the cross-correlation function, same size as the input argument `G`. """""" duration = max((t.max(), u.max())) - min((t.min(), u.min())) Gn = G.copy() for i, tau in enumerate(bins[1:]): Gn[i] *= ((duration - tau) / (float((t >= tau).sum()) * float((u <= (u.max() - tau)).sum()))) return Gn @numba.jit(nopython=True) def pcorrelate(t, u, bins, normalize=False): """"""Compute correlation of two arrays of discrete events (Point-process). The input arrays need to be values of a point process, such as photon arrival times or positions. The correlation is efficiently computed on an arbitrary array of lag-bins. As an example, bins can be uniformly spaced in log-space and span several orders of magnitudes. (you can use :func:`make_loglags` to creat log-spaced bins). This function implements the algorithm described in `(Laurence 2006) `__. Arguments: t (array): first array of ""points"" to correlate. The array needs to be monothonically increasing. u (array): second array of ""points"" to correlate. The array needs to be monothonically increasing. bins (array): bin edges for lags where correlation is computed. normalize (bool): if True, normalize the correlation function as typically done in FCS using :func:`pnormalize`. If False, return the unnormalized correlation function. Returns: Array containing the correlation of `t` and `u`. The size is `len(bins) - 1`. See also: :func:`make_loglags` to genetate log-spaced lag bins. """""" nbins = len(bins) - 1 # Array of counts (histogram) counts = np.zeros(nbins, dtype=np.int64) # For each bins, imin is the index of first `u` >= of each left bin edge imin = np.zeros(nbins, dtype=np.int64) # For each bins, imax is the index of first `u` >= of each right bin edge imax = np.zeros(nbins, dtype=np.int64) # For each ti, perform binning of (u - ti) and accumulate counts in Y for ti in t: for k, (tau_min, tau_max) in enumerate(zip(bins[:-1], bins[1:])): #print ('\nbin %d' % k) if k == 0: j = imin[k] # We start by finding the index of the first `u` element # which is >= of the first bin edge `tau_min` while j < len(u): if u[j] - ti >= tau_min: break j += 1 imin[k] = j if imax[k] > j: j = imax[k] while j < len(u): if u[j] - ti >= tau_max: break j += 1 imax[k] = j # Now j is the index of the first `u` element >= of # the next bin left edge counts += imax - imin G = counts / np.diff(bins) if normalize: G = pnormalize(G, t, u, bins) return G @numba.jit def ucorrelate(t, u, maxlag=None): """"""Compute correlation of two signals defined at uniformly-spaced points. The correlation is defined only for positive lags (including zero). The input arrays represent signals defined at uniformily-spaced points. This function is equivalent to :func:`numpy.correlate`, but can efficiently compute correlations on a limited number of lags. Note that binning point-processes with uniform bins, provides signals that can be passed as argument to this function. Arguments: tx (array): first signal to be correlated ux (array): second signal to be correlated maxlag (int): number of lags where correlation is computed. If None, computes all the lags where signals overlap `min(tx.size, tu.size) - 1`. Returns: Array contained the correlation at different lags. The size of this array is equal to the input argument `maxlag` (if defined) or to `min(tx.size, tu.size) - 1`. Example: Correlation of two signals `t` and `u`:: >>> t = np.array([1, 2, 0, 0]) >>> u = np.array([0, 1, 1]) >>> pycorrelate.ucorrelate(t, u) array([2, 3, 0]) The same result can be obtained with numpy swapping `t` and `u` and restricting the results only to positive lags:: >>> np.correlate(u, t, mode='full')[t.size - 1:] array([2, 3, 0]) """""" if maxlag is None: maxlag = u.size maxlag = int(min(u.size, maxlag)) C = np.zeros(maxlag, dtype=np.int64) for lag in range(C.size): tmax = min(u.size - lag, t.size) umax = min(u.size, t.size + lag) C[lag] = (t[:tmax] * u[lag:umax]).sum() return C def make_loglags(exp_min, exp_max, points_per_base, base=10): """"""Make a log-spaced array useful as lag bins for cross-correlation. This function conveniently creates an arrays on lag-bins to be used with :func:`pcorrelate`. Arguments: exp_min (int): exponent of the minimum value exp_max (int): exponent of the maximum value points_per_base (int): number of points per base (i.e. in a decade when `base = 10`) base (int): base of the exponent. Default 10. Returns: Array of log-spaced values with specified range and spacing. Example: Compute log10-spaced bins with 2 bins per decade, starting from 10⁻¹ and stopping at 10³:: >>> make_loglags(-1, 3, 2) array([ 1.00000000e-01, 3.16227766e-01, 1.00000000e+00, 3.16227766e+00, 1.00000000e+01, 3.16227766e+01, 1.00000000e+02, 3.16227766e+02, 1.00000000e+03]) See also: :func:`pcorrelate` """""" num_points = points_per_base * (exp_max - exp_min) + 1 bins = np.logspace(exp_min, exp_max, num_points, base=base) return bins ","Python" "Biophysics","tritemio/pycorrelate","pycorrelate/utils.py",".py","1242","46",""""""" Various utilities. """""" import sys from pathlib import Path from urllib.request import urlopen, urlretrieve from urllib.error import HTTPError, URLError def download_file(url, save_dir='./'): """"""Download a file from `url` saving it to disk. The file name is taken from `url` and left unchanged. The destination dir can be set using `save_dir` (Default: the current dir). """""" # Check if local path already exist fname = url.split('/')[-1] print('URL: %s' % url) print('File: %s\n ' % fname) path = Path(save_dir, fname) if path.exists(): print('File already on disk: %s \nDelete it to re-download.' % path) return # Check if the URL is valid try: urlopen(url) except URLError as e: print('Wrong URL or no connection.\n\nError:\n%s\n' % e) except HTTPError: print('URL not found: ' + url) return # Donwload the file def _report(blocknr, blocksize, size): current = blocknr * blocksize / 2**20 sys.stdout.write( ""\rDownloaded {0:4.1f} / {1:4.1f} MB"" .format(current, size / 2**20)) Path(save_dir).mkdir(parents=True, exist_ok=True) urlretrieve(url, str(path), _report) ","Python" "Biophysics","tritemio/pycorrelate","pycorrelate/_version.py",".py","18460","521"," # This file helps to compute a version number in source trees obtained from # git-archive tarball (such as those provided by githubs download-from-tag # feature). Distribution tarballs (built by setup.py sdist) and build # directories (produced by setup.py build) will contain a much shorter file # that just contains the computed version number. # This file is released into the public domain. Generated by # versioneer-0.18 (https://github.com/warner/python-versioneer) """"""Git implementation of _version.py."""""" import errno import os import re import subprocess import sys def get_keywords(): """"""Get the keywords needed to look up the version information."""""" # these strings will be replaced by git during git-archive. # setup.py/versioneer.py will grep for the variable names, so they must # each be defined on a line of their own. _version.py will just call # get_keywords(). git_refnames = ""$Format:%d$"" git_full = ""$Format:%H$"" git_date = ""$Format:%ci$"" keywords = {""refnames"": git_refnames, ""full"": git_full, ""date"": git_date} return keywords class VersioneerConfig: """"""Container for Versioneer configuration parameters."""""" def get_config(): """"""Create, populate and return the VersioneerConfig() object."""""" # these strings are filled in when 'setup.py versioneer' creates # _version.py cfg = VersioneerConfig() cfg.VCS = ""git"" cfg.style = ""pep440"" cfg.tag_prefix = """" cfg.parentdir_prefix = ""pycorrelate-"" cfg.versionfile_source = ""pycorrelate/_version.py"" cfg.verbose = False return cfg class NotThisMethod(Exception): """"""Exception raised if a method is not valid for the current scenario."""""" LONG_VERSION_PY = {} HANDLERS = {} def register_vcs_handler(vcs, method): # decorator """"""Decorator to mark a method as the handler for a particular VCS."""""" def decorate(f): """"""Store f in HANDLERS[vcs][method]."""""" if vcs not in HANDLERS: HANDLERS[vcs] = {} HANDLERS[vcs][method] = f return f return decorate def run_command(commands, args, cwd=None, verbose=False, hide_stderr=False, env=None): """"""Call the given command(s)."""""" assert isinstance(commands, list) p = None for c in commands: try: dispcmd = str([c] + args) # remember shell=False, so use git.cmd on windows, not just git p = subprocess.Popen([c] + args, cwd=cwd, env=env, stdout=subprocess.PIPE, stderr=(subprocess.PIPE if hide_stderr else None)) break except EnvironmentError: e = sys.exc_info()[1] if e.errno == errno.ENOENT: continue if verbose: print(""unable to run %s"" % dispcmd) print(e) return None, None else: if verbose: print(""unable to find command, tried %s"" % (commands,)) return None, None stdout = p.communicate()[0].strip() if sys.version_info[0] >= 3: stdout = stdout.decode() if p.returncode != 0: if verbose: print(""unable to run %s (error)"" % dispcmd) print(""stdout was %s"" % stdout) return None, p.returncode return stdout, p.returncode def versions_from_parentdir(parentdir_prefix, root, verbose): """"""Try to determine the version from the parent directory name. Source tarballs conventionally unpack into a directory that includes both the project name and a version string. We will also support searching up two directory levels for an appropriately named parent directory """""" rootdirs = [] for i in range(3): dirname = os.path.basename(root) if dirname.startswith(parentdir_prefix): return {""version"": dirname[len(parentdir_prefix):], ""full-revisionid"": None, ""dirty"": False, ""error"": None, ""date"": None} else: rootdirs.append(root) root = os.path.dirname(root) # up a level if verbose: print(""Tried directories %s but none started with prefix %s"" % (str(rootdirs), parentdir_prefix)) raise NotThisMethod(""rootdir doesn't start with parentdir_prefix"") @register_vcs_handler(""git"", ""get_keywords"") def git_get_keywords(versionfile_abs): """"""Extract version information from the given file."""""" # the code embedded in _version.py can just fetch the value of these # keywords. When used from setup.py, we don't want to import _version.py, # so we do it with a regexp instead. This function is not used from # _version.py. keywords = {} try: f = open(versionfile_abs, ""r"") for line in f.readlines(): if line.strip().startswith(""git_refnames =""): mo = re.search(r'=\s*""(.*)""', line) if mo: keywords[""refnames""] = mo.group(1) if line.strip().startswith(""git_full =""): mo = re.search(r'=\s*""(.*)""', line) if mo: keywords[""full""] = mo.group(1) if line.strip().startswith(""git_date =""): mo = re.search(r'=\s*""(.*)""', line) if mo: keywords[""date""] = mo.group(1) f.close() except EnvironmentError: pass return keywords @register_vcs_handler(""git"", ""keywords"") def git_versions_from_keywords(keywords, tag_prefix, verbose): """"""Get version information from git keywords."""""" if not keywords: raise NotThisMethod(""no keywords at all, weird"") date = keywords.get(""date"") if date is not None: # git-2.2.0 added ""%cI"", which expands to an ISO-8601 -compliant # datestamp. However we prefer ""%ci"" (which expands to an ""ISO-8601 # -like"" string, which we must then edit to make compliant), because # it's been around since git-1.5.3, and it's too difficult to # discover which version we're using, or to work around using an # older one. date = date.strip().replace("" "", ""T"", 1).replace("" "", """", 1) refnames = keywords[""refnames""].strip() if refnames.startswith(""$Format""): if verbose: print(""keywords are unexpanded, not using"") raise NotThisMethod(""unexpanded keywords, not a git-archive tarball"") refs = set([r.strip() for r in refnames.strip(""()"").split("","")]) # starting in git-1.8.3, tags are listed as ""tag: foo-1.0"" instead of # just ""foo-1.0"". If we see a ""tag: "" prefix, prefer those. TAG = ""tag: "" tags = set([r[len(TAG):] for r in refs if r.startswith(TAG)]) if not tags: # Either we're using git < 1.8.3, or there really are no tags. We use # a heuristic: assume all version tags have a digit. The old git %d # expansion behaves like git log --decorate=short and strips out the # refs/heads/ and refs/tags/ prefixes that would let us distinguish # between branches and tags. By ignoring refnames without digits, we # filter out many common branch names like ""release"" and # ""stabilization"", as well as ""HEAD"" and ""master"". tags = set([r for r in refs if re.search(r'\d', r)]) if verbose: print(""discarding '%s', no digits"" % "","".join(refs - tags)) if verbose: print(""likely tags: %s"" % "","".join(sorted(tags))) for ref in sorted(tags): # sorting will prefer e.g. ""2.0"" over ""2.0rc1"" if ref.startswith(tag_prefix): r = ref[len(tag_prefix):] if verbose: print(""picking %s"" % r) return {""version"": r, ""full-revisionid"": keywords[""full""].strip(), ""dirty"": False, ""error"": None, ""date"": date} # no suitable tags, so version is ""0+unknown"", but full hex is still there if verbose: print(""no suitable tags, using unknown + full revision id"") return {""version"": ""0+unknown"", ""full-revisionid"": keywords[""full""].strip(), ""dirty"": False, ""error"": ""no suitable tags"", ""date"": None} @register_vcs_handler(""git"", ""pieces_from_vcs"") def git_pieces_from_vcs(tag_prefix, root, verbose, run_command=run_command): """"""Get version from 'git describe' in the root of the source tree. This only gets called if the git-archive 'subst' keywords were *not* expanded, and _version.py hasn't already been rewritten with a short version string, meaning we're inside a checked out source tree. """""" GITS = [""git""] if sys.platform == ""win32"": GITS = [""git.cmd"", ""git.exe""] out, rc = run_command(GITS, [""rev-parse"", ""--git-dir""], cwd=root, hide_stderr=True) if rc != 0: if verbose: print(""Directory %s not under git control"" % root) raise NotThisMethod(""'git rev-parse --git-dir' returned error"") # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] # if there isn't one, this yields HEX[-dirty] (no NUM) describe_out, rc = run_command(GITS, [""describe"", ""--tags"", ""--dirty"", ""--always"", ""--long"", ""--match"", ""%s*"" % tag_prefix], cwd=root) # --long was added in git-1.5.5 if describe_out is None: raise NotThisMethod(""'git describe' failed"") describe_out = describe_out.strip() full_out, rc = run_command(GITS, [""rev-parse"", ""HEAD""], cwd=root) if full_out is None: raise NotThisMethod(""'git rev-parse' failed"") full_out = full_out.strip() pieces = {} pieces[""long""] = full_out pieces[""short""] = full_out[:7] # maybe improved later pieces[""error""] = None # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] # TAG might have hyphens. git_describe = describe_out # look for -dirty suffix dirty = git_describe.endswith(""-dirty"") pieces[""dirty""] = dirty if dirty: git_describe = git_describe[:git_describe.rindex(""-dirty"")] # now we have TAG-NUM-gHEX or HEX if ""-"" in git_describe: # TAG-NUM-gHEX mo = re.search(r'^(.+)-(\d+)-g([0-9a-f]+)$', git_describe) if not mo: # unparseable. Maybe git-describe is misbehaving? pieces[""error""] = (""unable to parse git-describe output: '%s'"" % describe_out) return pieces # tag full_tag = mo.group(1) if not full_tag.startswith(tag_prefix): if verbose: fmt = ""tag '%s' doesn't start with prefix '%s'"" print(fmt % (full_tag, tag_prefix)) pieces[""error""] = (""tag '%s' doesn't start with prefix '%s'"" % (full_tag, tag_prefix)) return pieces pieces[""closest-tag""] = full_tag[len(tag_prefix):] # distance: number of commits since tag pieces[""distance""] = int(mo.group(2)) # commit: short hex revision ID pieces[""short""] = mo.group(3) else: # HEX: no tags pieces[""closest-tag""] = None count_out, rc = run_command(GITS, [""rev-list"", ""HEAD"", ""--count""], cwd=root) pieces[""distance""] = int(count_out) # total number of commits # commit date: see ISO-8601 comment in git_versions_from_keywords() date = run_command(GITS, [""show"", ""-s"", ""--format=%ci"", ""HEAD""], cwd=root)[0].strip() pieces[""date""] = date.strip().replace("" "", ""T"", 1).replace("" "", """", 1) return pieces def plus_or_dot(pieces): """"""Return a + if we don't already have one, else return a ."""""" if ""+"" in pieces.get(""closest-tag"", """"): return ""."" return ""+"" def render_pep440(pieces): """"""Build up version string, with post-release ""local version identifier"". Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty Exceptions: 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] if pieces[""distance""] or pieces[""dirty""]: rendered += plus_or_dot(pieces) rendered += ""%d.g%s"" % (pieces[""distance""], pieces[""short""]) if pieces[""dirty""]: rendered += "".dirty"" else: # exception #1 rendered = ""0+untagged.%d.g%s"" % (pieces[""distance""], pieces[""short""]) if pieces[""dirty""]: rendered += "".dirty"" return rendered def render_pep440_pre(pieces): """"""TAG[.post.devDISTANCE] -- No -dirty. Exceptions: 1: no tags. 0.post.devDISTANCE """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] if pieces[""distance""]: rendered += "".post.dev%d"" % pieces[""distance""] else: # exception #1 rendered = ""0.post.dev%d"" % pieces[""distance""] return rendered def render_pep440_post(pieces): """"""TAG[.postDISTANCE[.dev0]+gHEX] . The "".dev0"" means dirty. Note that .dev0 sorts backwards (a dirty tree will appear ""older"" than the corresponding clean one), but you shouldn't be releasing software with -dirty anyways. Exceptions: 1: no tags. 0.postDISTANCE[.dev0] """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] if pieces[""distance""] or pieces[""dirty""]: rendered += "".post%d"" % pieces[""distance""] if pieces[""dirty""]: rendered += "".dev0"" rendered += plus_or_dot(pieces) rendered += ""g%s"" % pieces[""short""] else: # exception #1 rendered = ""0.post%d"" % pieces[""distance""] if pieces[""dirty""]: rendered += "".dev0"" rendered += ""+g%s"" % pieces[""short""] return rendered def render_pep440_old(pieces): """"""TAG[.postDISTANCE[.dev0]] . The "".dev0"" means dirty. Eexceptions: 1: no tags. 0.postDISTANCE[.dev0] """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] if pieces[""distance""] or pieces[""dirty""]: rendered += "".post%d"" % pieces[""distance""] if pieces[""dirty""]: rendered += "".dev0"" else: # exception #1 rendered = ""0.post%d"" % pieces[""distance""] if pieces[""dirty""]: rendered += "".dev0"" return rendered def render_git_describe(pieces): """"""TAG[-DISTANCE-gHEX][-dirty]. Like 'git describe --tags --dirty --always'. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] if pieces[""distance""]: rendered += ""-%d-g%s"" % (pieces[""distance""], pieces[""short""]) else: # exception #1 rendered = pieces[""short""] if pieces[""dirty""]: rendered += ""-dirty"" return rendered def render_git_describe_long(pieces): """"""TAG-DISTANCE-gHEX[-dirty]. Like 'git describe --tags --dirty --always -long'. The distance/hash is unconditional. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """""" if pieces[""closest-tag""]: rendered = pieces[""closest-tag""] rendered += ""-%d-g%s"" % (pieces[""distance""], pieces[""short""]) else: # exception #1 rendered = pieces[""short""] if pieces[""dirty""]: rendered += ""-dirty"" return rendered def render(pieces, style): """"""Render the given version pieces into the requested style."""""" if pieces[""error""]: return {""version"": ""unknown"", ""full-revisionid"": pieces.get(""long""), ""dirty"": None, ""error"": pieces[""error""], ""date"": None} if not style or style == ""default"": style = ""pep440"" # the default if style == ""pep440"": rendered = render_pep440(pieces) elif style == ""pep440-pre"": rendered = render_pep440_pre(pieces) elif style == ""pep440-post"": rendered = render_pep440_post(pieces) elif style == ""pep440-old"": rendered = render_pep440_old(pieces) elif style == ""git-describe"": rendered = render_git_describe(pieces) elif style == ""git-describe-long"": rendered = render_git_describe_long(pieces) else: raise ValueError(""unknown style '%s'"" % style) return {""version"": rendered, ""full-revisionid"": pieces[""long""], ""dirty"": pieces[""dirty""], ""error"": None, ""date"": pieces.get(""date"")} def get_versions(): """"""Get version information or return default if unable to do so."""""" # I am in _version.py, which lives at ROOT/VERSIONFILE_SOURCE. If we have # __file__, we can work backwards from there to the root. Some # py2exe/bbfreeze/non-CPython implementations don't do __file__, in which # case we can only use expanded keywords. cfg = get_config() verbose = cfg.verbose try: return git_versions_from_keywords(get_keywords(), cfg.tag_prefix, verbose) except NotThisMethod: pass try: root = os.path.realpath(__file__) # versionfile_source is the relative path from the top of the source # tree (where the .git directory might live) to this file. Invert # this to find the root from __file__. for i in cfg.versionfile_source.split('/'): root = os.path.dirname(root) except NameError: return {""version"": ""0+unknown"", ""full-revisionid"": None, ""dirty"": None, ""error"": ""unable to find root of source tree"", ""date"": None} try: pieces = git_pieces_from_vcs(cfg.tag_prefix, root, verbose) return render(pieces, cfg.style) except NotThisMethod: pass try: if cfg.parentdir_prefix: return versions_from_parentdir(cfg.parentdir_prefix, root, verbose) except NotThisMethod: pass return {""version"": ""0+unknown"", ""full-revisionid"": None, ""dirty"": None, ""error"": ""unable to compute version"", ""date"": None} ","Python" "Biophysics","tritemio/pycorrelate","docs/conf.py",".py","9197","303","#!/usr/bin/env python # -*- coding: utf-8 -*- # # pycorrelate documentation build configuration file, created by # sphinx-quickstart on Tue Jul 9 22:26:36 2013. # # This file is execfile()d with the current directory set to its # containing dir. # # Note that not all possible configuration values are present in this # autogenerated file. # # All configuration values have a default; values that are commented out # serve to show the default. import sys import os import time on_rtd = os.environ.get('READTHEDOCS', None) == 'True' # If extensions (or modules to document with autodoc) are in another # directory, add these directories to sys.path here. If the directory is # relative to the documentation root, use os.path.abspath to make it # absolute, like shown here. #sys.path.insert(0, os.path.abspath('.')) # Get the project root dir, which is the parent dir of this cwd = os.getcwd() project_root = os.path.dirname(cwd) # Insert the project root dir as the first element in the PYTHONPATH. # This lets us ensure that the source package is imported, and that its # version is used. sys.path.insert(0, project_root) import pycorrelate # -- General configuration --------------------------------------------- # If your documentation needs a minimal Sphinx version, state it here. #needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom ones. extensions = [ 'nbsphinx', 'sphinx.ext.autodoc', 'sphinx.ext.viewcode', 'sphinx.ext.intersphinx', 'sphinx.ext.coverage', 'sphinx.ext.mathjax', 'sphinx.ext.napoleon', 'IPython.sphinxext.ipython_console_highlighting', 'sphinx.ext.intersphinx', ] nbsphinx_allow_errors = False nbsphinx_execute = 'always' # 'never' nbsphinx_timeout = 60 intersphinx_mapping = { 'numpy': ('http://docs.scipy.org/doc/numpy/', None), } # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # The suffix of source filenames. source_suffix = '.rst' # The encoding of source files. #source_encoding = 'utf-8-sig' # The master toctree document. master_doc = 'index' # General information about the project. project = 'Pycorrelate' copyright = ('2017-{}, The Regents of the University of California, ' 'Antonino Ingargiola and contributors' .format(time.strftime(""%Y""))) # The version info for the project you're documenting, acts as replacement # for |version| and |release|, also used in various other places throughout # the built documents. # # The short X.Y version. version = pycorrelate.__version__ # The full version, including alpha/beta/rc tags. release = pycorrelate.__version__ # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. #language = None # There are two options for replacing |today|: either, you set today to # some non-false value, then it is used: #today = '' # Else, today_fmt is used as the format for a strftime call. #today_fmt = '%B %d, %Y' # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. exclude_patterns = ['_build', '**.ipynb_checkpoints'] # The reST default role (used for this markup: `text`) to use for all # documents. #default_role = None # If true, '()' will be appended to :func: etc. cross-reference text. #add_function_parentheses = True # If true, the current module name will be prepended to all description # unit titles (such as .. function::). #add_module_names = True # If true, sectionauthor and moduleauthor directives will be shown in the # output. They are ignored by default. #show_authors = False # The name of the Pygments (syntax highlighting) style to use. pygments_style = 'sphinx' # A list of ignored prefixes for module index sorting. #modindex_common_prefix = [] # If true, keep warnings as ""system message"" paragraphs in the built # documents. #keep_warnings = False # -- Options for HTML output ------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. if not on_rtd: import sphinx_rtd_theme html_theme = 'sphinx_rtd_theme' html_theme_path = [sphinx_rtd_theme.get_html_theme_path()] # Theme options are theme-specific and customize the look and feel of a # theme further. For a list of options available for each theme, see the # documentation. #html_theme_options = {} # Add any paths that contain custom themes here, relative to this directory. #html_theme_path = [] # The name for this set of Sphinx documents. If None, it defaults to # "" v documentation"". #html_title = None # A shorter title for the navigation bar. Default is the same as # html_title. #html_short_title = None # The name of an image file (relative to this directory) to place at the # top of the sidebar. #html_logo = None # The name of an image file (within the static path) to use as favicon # of the docs. This file should be a Windows icon file (.ico) being # 16x16 or 32x32 pixels large. #html_favicon = None # Add any paths that contain custom static files (such as style sheets) # here, relative to this directory. They are copied after the builtin # static files, so a file named ""default.css"" will overwrite the builtin # ""default.css"". html_static_path = ['_static'] # If not '', a 'Last updated on:' timestamp is inserted at every page # bottom, using the given strftime format. #html_last_updated_fmt = '%b %d, %Y' # If true, SmartyPants will be used to convert quotes and dashes to # typographically correct entities. #html_use_smartypants = True # Custom sidebar templates, maps document names to template names. #html_sidebars = {} # Additional templates that should be rendered to pages, maps page names # to template names. #html_additional_pages = {} # If false, no module index is generated. #html_domain_indices = True # If false, no index is generated. #html_use_index = True # If true, the index is split into individual pages for each letter. #html_split_index = False # If true, links to the reST sources are added to the pages. #html_show_sourcelink = True # If true, ""Created using Sphinx"" is shown in the HTML footer. # Default is True. #html_show_sphinx = True # If true, ""(C) Copyright ..."" is shown in the HTML footer. # Default is True. #html_show_copyright = True # If true, an OpenSearch description file will be output, and all pages # will contain a tag referring to it. The value of this option # must be the base URL from which the finished HTML is served. #html_use_opensearch = '' # This is the file name suffix for HTML files (e.g. "".xhtml""). #html_file_suffix = None # Output file base name for HTML help builder. htmlhelp_basename = 'pycorrelatedoc' # -- Options for LaTeX output ------------------------------------------ latex_elements = { # The paper size ('letterpaper' or 'a4paper'). #'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). #'pointsize': '10pt', # Additional stuff for the LaTeX preamble. #'preamble': '', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, author, documentclass # [howto/manual]). latex_documents = [ ('index', 'pycorrelate.tex', u'Pycorrelate Documentation', u'Antonino Ingargiola', 'manual'), ] # The name of an image file (relative to this directory) to place at # the top of the title page. #latex_logo = None # For ""manual"" documents, if this is true, then toplevel headings # are parts, not chapters. #latex_use_parts = False # If true, show page references after internal links. #latex_show_pagerefs = False # If true, show URL addresses after external links. #latex_show_urls = False # Documents to append as an appendix to all manuals. #latex_appendices = [] # If false, no module index is generated. #latex_domain_indices = True # -- Options for manual page output ------------------------------------ # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ ('index', 'pycorrelate', u'Pycorrelate Documentation', [u'Antonino Ingargiola'], 1) ] # If true, show URL addresses after external links. #man_show_urls = False # -- Options for Texinfo output ---------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ ('index', 'pycorrelate', 'Pycorrelate Documentation', 'Antonino Ingargiola', 'pycorrelate', 'One line description of project.', 'Miscellaneous'), ] # Documents to append as an appendix to all manuals. #texinfo_appendices = [] # If false, no module index is generated. #texinfo_domain_indices = True # How to display URL addresses: 'footnote', 'no', or 'inline'. #texinfo_show_urls = 'footnote' # If true, do not generate a @detailmenu in the ""Top"" node's menu. #texinfo_no_detailmenu = False ","Python" "Biophysics","tritemio/pycorrelate","docs/notebooks/pycorrelate-examples.ipynb",".ipynb","13985","587","{ ""cells"": [ { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""# Pycorrelate examples\n"", ""\n"", ""This notebook shows howto use `pycorrelate` as well as comparisons with other \n"", ""implementations."" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""import numpy as np\n"", ""import h5py"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""# Tweak here matplotlib style\n"", ""import matplotlib.pyplot as plt\n"", ""import matplotlib as mpl\n"", ""mpl.rcParams['font.sans-serif'].insert(0, 'Arial')\n"", ""mpl.rcParams['font.size'] = 14\n"", ""%config InlineBackend.figure_format = 'retina'\n"", ""%matplotlib inline"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""import pycorrelate as pyc"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""## Load Data"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""We start by downloading some timestamps data:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""url = 'http://files.figshare.com/2182601/0023uLRpitc_NTP_20dT_0.5GndCl.hdf5'\n"", ""pyc.utils.download_file(url, save_dir='data')"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""fname = './data/' + url.split('/')[-1]\n"", ""h5 = h5py.File(fname)\n"", ""unit = 12.5e-9"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""num_ph = int(3e6)\n"", ""detectors = h5['photon_data']['detectors'][:num_ph]\n"", ""timestamps = h5['photon_data']['timestamps'][:num_ph]\n"", ""t = timestamps[detectors == 0]\n"", ""u = timestamps[detectors == 1]"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""t.shape, u.shape, t[0], u[0]"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""t.max()*unit, u.max()*unit"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""Timestamps need to be monotonic, let's test it:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""assert (np.diff(t) > 0).all()\n"", ""assert (np.diff(u) > 0).all()"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""## Log-scale bins (base 10)\n"", ""\n"", ""Here we compute the cross-correlation on log10-spaced bins.\n"", ""\n"", ""First we compute the array of lag bins using the function [make_loglags](http://pycorrelate.readthedocs.io/en/latest/api.html#pycorrelate.pycorrelate.make_loglags):"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""# compute lags in sec. then convert to timestamp units\n"", ""bins = pyc.make_loglags(-7, 0, 10) / unit"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""Then, we compute the cross-correlation using the function \n"", ""[pcorrelate](http://pycorrelate.readthedocs.io/en/latest/api.html#pycorrelate.pycorrelate.pcorrelate):"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""G = pyc.pcorrelate(t, u, bins)"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""fig, ax = plt.subplots(figsize=(10, 6))\n"", ""plt.plot(bins*unit, np.hstack((G[:1], G)), drawstyle='steps-pre')\n"", ""plt.xlabel('Time (s)')\n"", ""#for x in bins[1:]: plt.axvline(x*unit, lw=0.2) # to mark bins\n"", ""plt.grid(True); plt.grid(True, which='minor', lw=0.3)\n"", ""plt.xscale('log')\n"", ""plt.xlim(30e-9, 2)"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""## Log-scale bins (base 2)\n"", ""\n"", ""Here we compute the same cross-correlation on log2-spaced bins.\n"", ""\n"", ""First we compute the array of lag bins using the function [make_loglags](http://pycorrelate.readthedocs.io/en/latest/api.html#pycorrelate.pycorrelate.make_loglags):"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""# compute lags directly in timestamp units\n"", ""bins = pyc.make_loglags(-1, 28, 1, base=2).astype('int')"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""Then, we compute the cross-correlation using the function \n"", ""[pcorrelate](http://pycorrelate.readthedocs.io/en/latest/api.html#pycorrelate.pycorrelate.pcorrelate):"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""G = pyc.pcorrelate(t, u, bins)"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""fig, ax = plt.subplots(figsize=(10, 6))\n"", ""plt.plot(bins*unit, np.hstack((G[:1], G)), drawstyle='steps-pre')\n"", ""plt.xlabel('Time (s)')\n"", ""#for x in bins[1:]: plt.axvline(x*unit, lw=0.2) # to mark bins\n"", ""plt.grid(True); plt.grid(True, which='minor', lw=0.3)\n"", ""plt.xscale('log')\n"", ""plt.xlim(30e-9, 2)"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""## Multi-tau bins\n"", ""\n"", ""Finally, we compute the cross-correlation on arbitrarly-spaced bins.\n"", ""Similar to the multi-tau bins, here we use constant bin size for \n"", ""a number of bins (`n_group`), then we double the bin size and we keep it constant\n"", ""for another `n_group` and so on:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""n_group = 4\n"", ""bin_widths = []\n"", ""for i in range(26):\n"", "" bin_widths += [2**i]*n_group\n"", ""np.array(bin_widths)\n"", ""bins = np.hstack(([0], np.cumsum(bin_widths)))"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""Then, we compute the cross-correlation using the function \n"", ""[pcorrelate](http://pycorrelate.readthedocs.io/en/latest/api.html#pycorrelate.pycorrelate.pcorrelate):"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""G = pyc.pcorrelate(t, u, bins)"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""fig, ax = plt.subplots(figsize=(10, 6))\n"", ""plt.plot(bins*unit, np.hstack((G[:1], G)), drawstyle='steps-pre')\n"", ""plt.xlabel('Time (s)')\n"", ""#for x in bins[1:]: plt.axvline(x*unit, lw=0.2) # to mark bins\n"", ""plt.grid(True); plt.grid(True, which='minor', lw=0.3)\n"", ""plt.xscale('log')\n"", ""plt.xlim(30e-9, 2)"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""## Test: comparison with np.histogram\n"", ""\n"", ""For testing alternative (slower) implementations we use smaller input arrays:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""tt = t[:5000]\n"", ""uu = u[:5000]"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""The algoritm implemented in `pycorrelate.pcorrelate` can be re-written in a very \n"", ""simple way using `numpy.histogram`:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""# compute lags in sec. then convert to timestamp units\n"", ""bins = pyc.make_loglags(-7, 0, 10) / unit"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""Y = np.zeros(bins.size - 1, dtype=np.int64)\n"", ""for ti in tt:\n"", "" Yc, _ = np.histogram(uu - ti, bins=bins)\n"", "" Y += Yc\n"", ""G = Y / np.diff(bins)"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""assert (G == pyc.pcorrelate(tt, uu, bins)).all()"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""Test passed! Here we demonstrated that the logic of the algorithm\n"", ""is implemented as described in the paper (and in the few lines of code above)."" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""## Tests: comparison with np.correlate\n"", ""\n"", ""The comparison with `np.correlate` is a little tricky.\n"", ""First we need to bin our input to create timetraces that can be correlated\n"", ""by linear convolution. For testing purposes, let's choice\n"", ""some timetrace bins:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""binwidth = 50e-6\n"", ""bins_tt = np.arange(0, tt.max()*unit, binwidth) / unit\n"", ""bins_uu = np.arange(0, uu.max()*unit, binwidth) / unit"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""bins_tt.max()*unit, bins_tt.size"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""bins_uu.max()*unit, bins_uu.size"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""tx, _ = np.histogram(tt, bins=bins_tt)\n"", ""ux, _ = np.histogram(uu, bins=bins_uu)\n"", ""\n"", ""plt.figure(figsize=(10, 6))\n"", ""plt.plot(bins_tt[1:]*unit, tx)\n"", ""plt.plot(bins_uu[1:]*unit, ux)\n"", ""plt.xlabel('Time (s)')"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""The plots above are the two curves we are going to feed to\n"", ""`np.correlate`:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""C = np.correlate(ux, tx, mode='full')"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""We need to trim the result to obtain a proper alignment with\n"", ""the 0-time lag:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""Gn = C[tx.size-1:] # trim to positive time lags"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""Now, we can check that both `numpy.correlate` and `pycorrelate.ucorrelate`\n"", ""give the same result:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""Gu = pyc.ucorrelate(tx, ux)\n"", ""assert (Gu == Gn).all()"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""Now, let's compute the correlation also with `pycorrelate.pcorrelate`:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""maxlag_sec = 3.9\n"", ""lagbins = (np.arange(0, maxlag_sec, binwidth) / unit).astype('int64')"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""Gp = pyc.pcorrelate(tt, uu, lagbins) * int(binwidth / unit)"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""Let's plot a comparison:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""fig, ax = plt.subplots(figsize=(10, 6))\n"", ""Gn_t = np.arange(1, Gn.size+1) * binwidth * 1e3\n"", ""Gu_t = np.arange(1, Gu.size+1) * binwidth * 1e3\n"", ""Gp_t = lagbins[1:] * unit * 1e3\n"", ""plt.plot(Gn_t, Gn, alpha=1, lw=2, label='numpy.correlate') \n"", ""plt.plot(Gu_t, Gu, alpha=0.6, lw=2, label='pycorrelate.ucorrelate')\n"", ""plt.plot(Gp_t, Gp, alpha=0.7, lw=2, label='pycorrelate.pcorrelate')\n"", ""plt.xlabel('Time (ms)', fontsize='large')\n"", ""plt.grid(True)\n"", ""plt.xlim(30e-3, 500)\n"", ""plt.xscale('log')\n"", ""plt.title('pycorrelate.correlate vs numpy.correlate', fontsize='x-large')\n"", ""plt.legend(loc='best', fontsize='x-large');"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""## Conclusion\n"", ""\n"", ""- `numpy.correlate` and `pycorrelate.ucorrelate` give identical results,\n"", "" with the latter being much faster. Note that the inputs are swapped between the \n"", "" two functions.\n"", "" \n"", ""- `pycorrelate.ucorrelate` and `pycorrelate.pcorrelate` agree when using \n"", "" uniform time-lag bins."" ] } ], ""metadata"": { ""kernelspec"": { ""display_name"": ""Python 3"", ""language"": ""python"", ""name"": ""python3"" }, ""language_info"": { ""codemirror_mode"": { ""name"": ""ipython"", ""version"": 3 }, ""file_extension"": "".py"", ""mimetype"": ""text/x-python"", ""name"": ""python"", ""nbconvert_exporter"": ""python"", ""pygments_lexer"": ""ipython3"", ""version"": ""3.6.0"" }, ""toc"": { ""colors"": { ""hover_highlight"": ""#DAA520"", ""running_highlight"": ""#FF0000"", ""selected_highlight"": ""#FFD700"" }, ""moveMenuLeft"": true, ""nav_menu"": { ""height"": ""264px"", ""width"": ""252px"" }, ""navigate_menu"": true, ""number_sections"": false, ""sideBar"": true, ""threshold"": 4, ""toc_cell"": false, ""toc_position"": { ""height"": ""673px"", ""left"": ""0px"", ""right"": ""1139.11px"", ""top"": ""107px"", ""width"": ""212px"" }, ""toc_section_display"": ""block"", ""toc_window_display"": true, ""widenNotebook"": false } }, ""nbformat"": 4, ""nbformat_minor"": 1 } ","Unknown" "Biophysics","tritemio/pycorrelate","docs/notebooks/Simple FCS example.ipynb",".ipynb","10593","398","{ ""cells"": [ { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""# Simple FCS example\n"", ""\n"", ""This notebook shows howto compute and fit an FCS curve\n"", ""using `pycorrelate`.\n"", ""\n"", ""## Initial imports"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""import numpy as np\n"", ""import h5py"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""# Tweak here matplotlib style\n"", ""%matplotlib inline\n"", ""%config InlineBackend.figure_format = 'retina'\n"", ""import matplotlib.pyplot as plt\n"", ""import matplotlib as mpl\n"", ""mpl.rcParams['font.sans-serif'].insert(0, 'Arial')\n"", ""mpl.rcParams['font.size'] = 14"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""import pycorrelate as pyc\n"", ""pyc.__version__"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""import lmfit\n"", ""lmfit.__version__"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""## Load Data\n"", ""\n"", ""We start downloading a sample dataset of a smFRET \""measurement\"" with a \n"", ""single CW excitation laser and two detectors donor (D) and acceptor (A)\n"", ""(the data is actually a simulation performed with [PyBroMo](http://tritemio.github.io/PyBroMo/))."" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""url = 'http://files.figshare.com/4917046/smFRET_44f3da_P_20_s0_20_s20_D_6.0e11_6.0e11_E_75_30_EmTot_200k_200k_BgD1500_BgA800_t_max_600s.hdf5'\n"", ""pyc.utils.download_file(url, save_dir='data')"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""fname = './data/' + url.split('/')[-1]\n"", ""h5 = h5py.File(fname)\n"", ""unit = h5['photon_data']['timestamps_specs']['timestamps_unit'][()]\n"", ""unit"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""We can check that there are only two detectors:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""np.unique(h5['photon_data']['detectors'][:])"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""Then we load the timestamps in two arrays `t` and `u`:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""detectors = h5['photon_data']['detectors'][:]\n"", ""timestamps = h5['photon_data']['timestamps'][:]\n"", ""t = timestamps[detectors == 0]\n"", ""u = timestamps[detectors == 1]"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""t.shape, u.shape, t[0], u[0]"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""t.max()*unit, u.max()*unit"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""Timestamps need to be monotonic, let's check:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""assert (np.diff(t) >= 0).all()\n"", ""assert (np.diff(u) >= 0).all()"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""## Compute CCF\n"", ""\n"", ""To avoid afterpulsing, we can compute the cross-correlation function (CCF) between D and A channels.\n"", ""\n"", ""We first create the array of time-lag bins using [make_loglags()](http://pycorrelate.readthedocs.io/en/latest/api.html#pycorrelate.pycorrelate.make_loglags):"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""# compute lags in sec. then convert to timestamp units\n"", ""bins_per_dec = 20\n"", ""bins = pyc.make_loglags(-6, 1, bins_per_dec)[bins_per_dec // 2:] / unit\n"", ""print('Number of time-lag bins:', bins.size)"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""Then, we compute the cross-correlation with\n"", ""[pcorrelate](http://pycorrelate.readthedocs.io/en/latest/api.html#pycorrelate.pycorrelate.pcorrelate):"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""Gn = pyc.pcorrelate(t, u, bins, normalize=True)"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""Plotting the CCF function `Gn` we observe the typical diffusion shape:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""fig, ax = plt.subplots(figsize=(10, 6))\n"", ""plt.semilogx(bins[1:]*unit, Gn, drawstyle='steps-pre')\n"", ""plt.xlabel('Time (s)')\n"", ""plt.grid(True); plt.grid(True, which='minor', lw=0.3);"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""## Fit FCS model\n"", ""\n"", ""The next step is fitting the computed CCF with a model. For freely-diffusing species under confocal excitation \n"", ""(and no photo-physics) the simplest model is the 2D model (i.e. the PSF z dimension is neglected):\n"", ""\n"", ""$$\n"", ""G(\\tau) = 1 + A_0 \\, \\left(1 + \\frac{\\tau}{\\tau_D} \\right)^{-1}\n"", ""$$\n"", ""\n"", ""The full 3D model is just slightly more complicated:\n"", ""\n"", ""$$\n"", ""G(\\tau) = 1 + A_0 \\, \\left(1 + \\frac{\\tau}{\\tau_D} \\right)^{-1} \\; \n"", ""\\left[ 1 + \\left(\\frac{r}{z}\\right)^2\\frac{\\tau}{\\tau_D} \\right]^{-1/2}\n"", ""$$\n"", ""\n"", ""There is a link between $A_0$ and concentration. Neglecting background, \n"", ""$A_0 = 1/N$ where $N$ is the mean number of molecules in the excitation volume.\n"", ""The background makes $A_0 < 1/N$.\n"", ""For full expression see \n"", ""[Orrit 2002](http://doi.org/10.1002%2F1438-5171%28200211%293%3A5%2F6%3C255%3A%3AAID-SIMO255%3E3.0.CO%3B2-8).\n"", ""\n"", ""Here, for the sake of the example, we will just fit the simple 2D model.\n"", ""\n"", ""Let's start defining the model functions and the array of time-lags `tau`:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""def diffusion_2d(timelag, tau_diff, A0):\n"", "" return 1 + A0 * 1/(1 + timelag/tau_diff)\n"", ""\n"", ""def diffusion_3d(timelag, tau_diff, A0, waist_z_ratio=0.1):\n"", "" return (1 + A0 * 1/(1 + timelag/tau_diff) * \n"", "" 1/np.sqrt(1 + waist_z_ratio**2 * timelag/tau_diff))"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""tau = 0.5 * (bins[1:] + bins[:-1]) * unit"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""Now, we build a \""fitting model\"" with [lmfit](https://lmfit.github.io/lmfit-py/) \n"", ""and use it to fit the CCF curve `Gn`:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""model = lmfit.Model(diffusion_2d)\n"", ""params = model.make_params(A0=1, tau_diff=1e-3)\n"", ""params['A0'].set(min=0.01, value=1)\n"", ""params['tau_diff'].set(min=1e-6, value=1e-3)\n"", ""#params['waist_z_ratio'].set(value=1/6, vary=False) # 3D model only\n"", ""\n"", ""weights = np.ones_like(Gn) \n"", ""#weights = np.log(np.sqrt(G*np.diff(bins))) # and example of using weights\n"", ""fitres = model.fit(Gn, timelag=tau, params=params, method='least_squares',\n"", "" weights=weights)\n"", ""print('\\nList of fitted parameters for %s: \\n' % model.name)\n"", ""fitres.params.pretty_print(colwidth=10, columns=['value', 'min', 'max'])"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""Finally, we plot fit results and residuals:"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""fig, ax = plt.subplots(2, 1, figsize=(10, 8), sharex=True,\n"", "" gridspec_kw={'height_ratios': [3, 1]})\n"", ""plt.subplots_adjust(hspace=0)\n"", ""ax[0].semilogx(tau, Gn)\n"", ""for a in ax:\n"", "" a.grid(True); a.grid(True, which='minor', lw=0.3)\n"", ""ax[0].plot(tau, fitres.best_fit)\n"", ""ax[1].plot(tau, fitres.residual*weights, 'k')\n"", ""ym = np.abs(fitres.residual*weights).max()\n"", ""ax[1].set_ylim(-ym, ym)\n"", ""ax[1].set_xlim(bins[0]*unit, bins[-1]*unit);\n"", ""tau_diff_us = fitres.values['tau_diff'] * 1e6\n"", ""msg = ((r'$G(0)-1$ = {A0:.2f}'+'\\n'+r'$\\tau_D$ = {tau_diff_us:.0f} μs')\n"", "" .format(A0=fitres.values['A0'], tau_diff_us=tau_diff_us))\n"", ""ax[0].text(.75, .9, msg, \n"", "" va='top', ha='left', transform=ax[0].transAxes, fontsize=18);\n"", ""ax[0].set_ylabel('G(τ)')\n"", ""ax[1].set_ylabel('residuals')\n"", ""ax[0].set_title('Donor-Acceptor CCF')\n"", ""ax[1].set_xlabel('Time Lag, τ (s)');"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""The flatness of the residual indicates a good fit. If you followed so far,\n"", ""you should be able to extent this example to use more complex models \n"", ""when needed."" ] } ], ""metadata"": { ""kernelspec"": { ""display_name"": ""Python 3"", ""language"": ""python"", ""name"": ""python3"" }, ""language_info"": { ""codemirror_mode"": { ""name"": ""ipython"", ""version"": 3 }, ""file_extension"": "".py"", ""mimetype"": ""text/x-python"", ""name"": ""python"", ""nbconvert_exporter"": ""python"", ""pygments_lexer"": ""ipython3"", ""version"": ""3.6.2"" }, ""toc"": { ""colors"": { ""hover_highlight"": ""#DAA520"", ""running_highlight"": ""#FF0000"", ""selected_highlight"": ""#FFD700"" }, ""moveMenuLeft"": true, ""nav_menu"": { ""height"": ""264px"", ""width"": ""252px"" }, ""navigate_menu"": true, ""number_sections"": false, ""sideBar"": true, ""threshold"": 4, ""toc_cell"": false, ""toc_position"": { ""height"": ""673px"", ""left"": ""0px"", ""right"": ""1139.11px"", ""top"": ""107px"", ""width"": ""212px"" }, ""toc_section_display"": ""block"", ""toc_window_display"": true, ""widenNotebook"": false } }, ""nbformat"": 4, ""nbformat_minor"": 1 } ","Unknown" "Biophysics","tritemio/pycorrelate","tests/test_pycorrelate.py",".py","3168","101","#!/usr/bin/env python # -*- coding: utf-8 -*- """"""Tests for `pycorrelate` package."""""" import pytest import h5py import numpy as np import pycorrelate as pyc DATA_URL = 'http://files.figshare.com/4917046/smFRET_44f3da_P_20_s0_20_s20_D_6.0e11_6.0e11_E_75_30_EmTot_200k_200k_BgD1500_BgA800_t_max_600s.hdf5' def load_dataset(): pyc.utils.download_file(DATA_URL, save_dir='data') fname = './data/' + DATA_URL.split('/')[-1] h5 = h5py.File(fname) num_ph = int(10e3) timestamps = h5['photon_data']['timestamps'][:num_ph] detectors = h5['photon_data']['detectors'][:num_ph] unit = h5['photon_data']['timestamps_specs']['timestamps_unit'][()] t = timestamps[detectors == 0] u = timestamps[detectors == 1] return t, u, unit @pytest.fixture() def data(): t, u, unit = load_dataset() return t, u, unit def test_pcorrelate(data): """"""Test pcorrelate algorithm using np.histogram."""""" t, u, unit = data n = 10000 # ~ 3s of data t, u = t[:n], u[:n] bins = pyc.make_loglags(-6, 0, 20, base=10) / unit nbins = len(bins) - 1 G = pyc.pcorrelate(t, u, bins) Y = np.zeros(nbins, dtype=np.int64) for ti in t: Yc, _ = np.histogram(u - ti, bins=bins) Y += Yc Gn = Y / np.diff(bins) # The last bin in np.histogram includes the right edge while pcorrelate # does not. This creates a potential discrepancy for the last bin. assert np.allclose(G, Gn) assert np.allclose(G[:-1], Gn[:-1]) # However the value in the last bin when using np.histogram needs to be # >= than pcorrelate value. assert (Gn[-1] >= G[-1]).all() def test_pcorrelate_normalization(data): """"""Test pcorrelate algorithm using np.histogram."""""" t, u, unit = data bins = pyc.make_loglags(-6, 0, 20, base=10) / unit Gn = pyc.pcorrelate(t, u, bins, normalize=True) G = pyc.pcorrelate(t, u, bins, normalize=False) Gn2 = pyc.pnormalize(G, t, u, bins) assert (Gn == Gn2).all() def test_ucorrelate(data): """"""Test ucorrelate against np.correlate."""""" t, u, unit = data binwidth = 50e-6 bins_tt = np.arange(0, t.max() * unit, binwidth) / unit bins_uu = np.arange(0, u.max() * unit, binwidth) / unit tx, _ = np.histogram(t, bins=bins_tt) ux, _ = np.histogram(u, bins=bins_uu) C = np.correlate(ux, tx, mode='full') Gn = C[tx.size - 1:] # trim to positive time lags Gu = pyc.ucorrelate(tx, ux) assert (Gu == Gn).all() Gu2 = pyc.ucorrelate(tx, ux, maxlag=1000) assert (Gu2 == Gn[:1000]).all() def test_pcorrelate_vs_ucorrelate(data): t, u, unit = data binwidth = 50e-6 bins_tt = np.arange(0, t.max() * unit, binwidth) / unit bins_uu = np.arange(0, u.max() * unit, binwidth) / unit tx, _ = np.histogram(t, bins=bins_tt) ux, _ = np.histogram(u, bins=bins_uu) Gu = pyc.ucorrelate(tx, ux) maxlag_sec = 1.2 # seconds lagbins = (np.arange(0, maxlag_sec, binwidth) / unit).astype('int64') Gp = pyc.pcorrelate(t, u, lagbins) * int(binwidth / unit) n = 6000 err = np.abs(Gp[:n] - Gu[:n]) / (0.5 * (Gp[:n] + Gu[:n])) assert err.max() < 0.23 assert err.mean() < 0.05 ","Python" "Biophysics","tritemio/pycorrelate","tests/nbrun.py",".py","9764","223","# Copyright (c) 2015-2017 Antonino Ingargiola # License: MIT """""" nbrun - Run an Jupyter/IPython notebook, optionally passing arguments. USAGE ----- Copy this file in the folder containing the master notebook used to execute the other notebooks. Then use `run_notebook()` to execute notebooks. """""" import time from pathlib import Path from IPython.display import display, FileLink import nbformat from nbconvert.preprocessors import ExecutePreprocessor from nbconvert import HTMLExporter __version__ = '0.2' def dict_to_code(mapping): """"""Convert input dict `mapping` to a string containing python code. Each key is the name of a variable and each value is the variable content. Each variable assignment is separated by a newline. Keys must be strings, and cannot start with a number (i.e. must be valid python identifiers). Values must be objects with a string representation (the result of repr(obj)) which is valid python code for re-creating the object. For examples, numbers, strings or list/tuple/dict of numbers and strings are allowed. Returns: A string containing the python code. """""" lines = (""{} = {}"".format(key, repr(value)) for key, value in mapping.items()) return '\n'.join(lines) def run_notebook(notebook_path, nb_kwargs=None, suffix='-out', out_path_ipynb=None, out_path_html=None, kernel_name=None, working_dir='./', timeout=3600, execute_kwargs=None, save_ipynb=True, save_html=False, insert_pos=1, hide_input=False, display_links=True, return_nb=False, add_timestamp=True): """"""Runs a notebook and saves the output in a new notebook. Executes a notebook, optionally passing ""arguments"" similarly to passing arguments to a function. Notebook arguments are passed in a dictionary (`nb_kwargs`) which is converted into a string containing python assignments. This string is inserted in the template notebook as a code cell. The code assigns variables which can be used to control the execution. When ""calling"" a notebook, you need to know which arguments (variables) to pass. Unlike normal python functions, no check is performed on the input arguments. For sanity, we recommended describing the variables that can be assigned using a markdown cell at the beginning of the template notebook. Arguments: notebook_path (pathlib.Path or string): input notebook filename. This is the notebook to be executed (i.e. template notebook). nb_kwargs (dict or None): If not None, this dict is converted to a string of python assignments using the dict keys as variables names and the dict values as variables content. This string is inserted as code-cell in the notebook to be executed. suffix (string): suffix to append to the file name of the executed notebook. Argument ignored if `out_notebook_path` is not None. out_path_ipynb (pathlib.Path, string or None): file name for the output ipynb notebook. If None, the ouput ipynb notebook has the same name as the input notebook plus a suffix, specified by the `suffix` argument. If not None, `suffix` is ignored. If argument `save_ipynb` is False this argument is ignored. out_path_html (pathlib.Path, string or None): file name for the output HTML notebook. If None, the ouput HTML notebook has the same name as the input notebook plus a suffix, specified by the `suffix` argument. If not None, `suffix` is ignored. If argument `save_html` is False this argument is ignored. kernel_name (string or None): name of the kernel used to execute the notebook. Use the default kernel if None. working_dir (string or Path): the folder the kernel is started into. timeout (int): max execution time (seconds) for each cell before the execution is aborted. execute_kwargs (dict): additional arguments passed to `ExecutePreprocessor`. save_ipynb (bool): if True, save the output notebook in ipynb format. Default True. save_html (bool): if True, save the output notebook in HTML format. Default False. insert_pos (int): position of insertion of the code-cell containing the input arguments. Default is 1 (i.e. second cell). With this default, the first cell of the input notebook can define default argument values (used when the notebook is executed with no arguments or through the Notebook App). hide_input (bool): whether to create a notebook with input cells hidden (useful to remind user that the auto-generated output is not meant to have the code edited. display_links (bool): if True, display/print ""link"" of template and output notebooks. Links are only rendered in a notebook. In a text terminal, links are displayed as full file names. return_nb (bool): if True, returns the notebook object. If False returns None. Default False. add_timestamp (bool): if True, add a timestamp cell to the executed notebook containing time of execution, duration and the name of the template notebook. """""" timestamp = (""**Executed:** %s
**Duration:** %d seconds.
"" ""**Autogenerated from:** [%s](%s)\n\n---"") if nb_kwargs is None: nb_kwargs = {} else: header = '# Cell inserted during automated execution.' code = dict_to_code(nb_kwargs) code_cell = '\n'.join((header, code)) notebook_path = Path(notebook_path) if not notebook_path.is_file(): raise FileNotFoundError(""Path '%s' not found."" % notebook_path) def check_out_path(notebook_path, out_path, ext, save): if out_path is None: out_path = Path(notebook_path.parent, notebook_path.stem + suffix + ext) out_path = Path(out_path) if save and not out_path.parent.exists(): msg = ""Folder of the output %s file was not found:\n - %s\n."" raise FileNotFoundError(msg % (ext, out_path_ipynb.parent)) return out_path out_path_ipynb = check_out_path(notebook_path, out_path_ipynb, ext='.ipynb', save=save_ipynb) out_path_html = check_out_path(notebook_path, out_path_html, ext='.html', save=save_html) if display_links: display(FileLink(str(notebook_path))) if execute_kwargs is None: execute_kwargs = {} execute_kwargs.update(timeout=timeout) if kernel_name is not None: execute_kwargs.update(kernel_name=kernel_name) ep = ExecutePreprocessor(**execute_kwargs) nb = nbformat.read(str(notebook_path), as_version=4) if hide_input: nb[""metadata""].update({""hide_input"": True}) if len(nb_kwargs) > 0: nb['cells'].insert(insert_pos, nbformat.v4.new_code_cell(code_cell)) start_time = time.time() try: # Execute the notebook ep.preprocess(nb, {'metadata': {'path': working_dir}}) except: # Execution failed, print a message then raise. msg = ('Error executing the notebook ""%s"".\n' 'Notebook arguments: %s\n\n' 'See notebook ""%s"" for the traceback.' % (notebook_path, str(nb_kwargs), out_path_ipynb)) print(msg) timestamp += '\n\nError occurred during execution. See below.' raise finally: if add_timestamp: duration = time.time() - start_time timestamp = timestamp % (time.ctime(start_time), duration, notebook_path, out_path_ipynb) timestamp_cell = nbformat.v4.new_markdown_cell(timestamp) nb['cells'].insert(0, timestamp_cell) # Save the executed notebook to disk if save_ipynb: nbformat.write(nb, str(out_path_ipynb)) if display_links: display(FileLink(str(out_path_ipynb))) if save_html: html_exporter = HTMLExporter() body, resources = html_exporter.from_notebook_node(nb) with open(str(out_path_html), 'w') as f: f.write(body) if return_nb: return nb if __name__ == '__main__': import argparse descr = """"""\ Execute all notebooks in a folder saving the result in the ""out"" subfolder. """""" parser = argparse.ArgumentParser(description=descr, epilog='\n') parser.add_argument('folder', help='Source folder with files to be processed.') msg = ('Name of kernel executing the notebook.\n' 'Use `jupyter kernelspec list` for a list of kernels.') parser.add_argument('--kernel', metavar='KERNEL_NAME', default=None, help=msg) args = parser.parse_args() folder = Path(args.folder) assert folder.is_dir(), 'Folder ""%s"" not found.' % folder out_path = Path(folder, 'out/') if not out_path.is_dir(): out_path.mkdir(parents=True) # py2 compat print('Executing notebooks in ""%s"" ... ' % folder) pathlist = list(folder.glob('*.ipynb')) for nbpath in pathlist: if not (nbpath.stem.endswith('-out') or nbpath.stem.startswith('_')): print() out_path_ipynb = Path(out_path, nbpath.name) run_notebook(nbpath, out_path_ipynb=out_path_ipynb, kernel_name=args.kernel) ","Python" "Biophysics","tritemio/pycorrelate","tests/__init__.py",".py","66","4","# -*- coding: utf-8 -*- """"""Unit test package for pycorrelate."""""" ","Python" "Biophysics","tritemio/pycorrelate","tests/Unit tests-debug.ipynb",".ipynb","2947","126","{ ""cells"": [ { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""# Debug unit test errors\n"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""import test_pycorrelate as tp"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""import pycorrelate as pyc\n"", ""import numpy as np\n"", ""import matplotlib.pyplot as plt\n"", ""%matplotlib inline"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""data = tp.load_dataset()"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""t, u, unit = data"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""tp.test_pcorrelate(data)"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""# binwidth = 50e-6\n"", ""# bins_tt = np.arange(0, t.max() * unit, binwidth) / unit\n"", ""# bins_uu = np.arange(0, u.max() * unit, binwidth) / unit\n"", ""# tx, _ = np.histogram(t, bins=bins_tt)\n"", ""# ux, _ = np.histogram(u, bins=bins_uu)\n"", ""# Gu = pyc.ucorrelate(tx, ux)\n"", ""# maxlag_sec = 1.2 # seconds\n"", ""# lagbins = (np.arange(0, maxlag_sec, binwidth) / unit).astype('int64')\n"", ""# Gp = pyc.pcorrelate(t, u, lagbins) * int(binwidth / unit)\n"", ""# n = 6000\n"", ""# err = np.abs(Gp[:n] - Gu[:n]) / (0.5 * (Gp[:n] + Gu[:n]))"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [ ""# fig, ax = plt.subplots(figsize=(10, 6))\n"", ""# Gu_t = np.arange(1, Gu.size+1) * binwidth * 1e3\n"", ""# Gp_t = lagbins[1:] * unit * 1e3 + 0.5*binwidth\n"", ""# plt.plot(Gu_t, Gu, alpha=0.6, lw=2, label='pycorrelate.ucorrelate')\n"", ""# plt.plot(Gp_t, Gp, alpha=0.7, lw=2, label='pycorrelate.pcorrelate')\n"", ""# plt.xlabel('Time (ms)', fontsize='large')\n"", ""# plt.grid(True)\n"", ""# #plt.xlim(30e-3, 500)\n"", ""# plt.xscale('log')\n"", ""# plt.title('pycorrelate.correlate vs numpy.correlate', fontsize='x-large')\n"", ""# plt.legend(loc='best', fontsize='x-large');"" ] }, { ""cell_type"": ""code"", ""execution_count"": null, ""metadata"": {}, ""outputs"": [], ""source"": [] } ], ""metadata"": { ""kernelspec"": { ""display_name"": ""Python 3.6 (pycorrelate-dev)"", ""language"": ""python"", ""name"": ""pycorrelate-dev"" }, ""language_info"": { ""codemirror_mode"": { ""name"": ""ipython"", ""version"": 3 }, ""file_extension"": "".py"", ""mimetype"": ""text/x-python"", ""name"": ""python"", ""nbconvert_exporter"": ""python"", ""pygments_lexer"": ""ipython3"", ""version"": ""3.6.2"" } }, ""nbformat"": 4, ""nbformat_minor"": 1 } ","Unknown" "Biophysics","rhomu/celadro","src/reduce.h",".h","1979","68","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef REDUCE_H_ #define REDUCE_H_ #include ""cuda.h"" // ============================================================================= // Warp reduce, from: // https://devblogs.nvidia.com/parallelforall/faster-parallel-reductions-kepler/ template __inline__ __device__ void warpReduceSum(T& val) { for (int offset = WarpSize/2; offset > 0; offset /= 2) val += __shfl_down(val, offset); } template __inline__ __device__ void warpReduceSum(vec &val) { for (int offset = WarpSize/2; offset > 0; offset /= 2) for(int i=0; i __inline__ __device__ void blockReduceSum(T& val) { static __shared__ T shared[WarpSize]; int lane = threadIdx.x % WarpSize; int wid = threadIdx.x / WarpSize; warpReduceSum(val); // Each warp performs partial reduction if (lane==0) shared[wid]=val; // Write reduced value to shared memory __syncthreads(); // Wait for all partial reductions // read from shared memory only if that warp existed if(threadIdx.x < blockDim.x / warpSize) val = shared[lane]; else val = 0; if (wid==0) warpReduceSum(val); // Final reduce within first warp } #endif//REDUCE_H_ ","Unknown" "Biophysics","rhomu/celadro","src/stencil.hpp",".hpp","1609","55","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef STENCIL_HPP_ #define STENCIL_HPP_ /** Indices of a given point and its direct neighbourhood * * A stencil is a list of 9 (in two dimensions) grid indices of a point and its * neighbourhood. The convention is the following: if s is a given stencil, then * s[0][0] is the grid coordinate of the central point, s[1][0] the coordinate * of the point to its right, s[-1][0] the point to its left, etc. * */ struct stencil { struct shifted_array { unsigned data[3]; CUDA_host_device unsigned& operator[](int i) { return data[i+1]; } CUDA_host_device const unsigned& operator[](int i) const { return data[i+1]; } }; shifted_array data[3]; CUDA_host_device shifted_array& operator[](int i) { return data[i+1]; } CUDA_host_device const shifted_array& operator[](int i) const { return data[i+1]; } }; #endif//STENCIL_HPP_ ","Unknown" "Biophysics","rhomu/celadro","src/random.cpp",".cpp","1518","64","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #include ""header.hpp"" #include ""model.hpp"" using namespace std; double Model::random_real(double min, double max) { return uniform_real_distribution<>(min, max)(gen); } double Model::random_normal(double sigma) { return normal_distribution<>(0., sigma)(gen); } unsigned Model::random_geometric(double p) { return geometric_distribution<>(p)(gen); } unsigned Model::random_unsigned() { return gen(); } void Model::InitializeRandomNumbers() { if(not set_seed) { // 'Truly random' device to generate seed std::random_device rd; seed = rd(); } gen.seed(seed); } unsigned Model::random_poisson(double lambda) { return poisson_distribution<>(lambda)(gen); } int Model::random_exponential(double lambda) { return exponential_distribution<>(lambda)(gen); } ","C++" "Biophysics","rhomu/celadro","src/cuda.h",".h","1348","52","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ /** There are two different compiler flags associated with CUDA: * * _CUDA is defined when compiling device source code (using NVCC) * _CUDA_ENABLED is defined project-wise when cuda is enabled, i.e. also for * host source code. **/ #ifndef CUDA_HPP_ #define CUDA_HPP_ // CUDA support is disabled for now #undef _CUDA #ifdef _CUDA #define _CUDA_ENABLED #ifdef _OPENMP #error ""Cuda can not be used along with OpenMP"" #endif #define WarpSize 32 #define ThreadsPerBlock 1024 #define CUDA_host_device __host__ __device__ // #ifdef _CUDA #else #define CUDA_host_device #endif #endif//CUDA_HPP_ ","Unknown" "Biophysics","rhomu/celadro","src/derivatives.hpp",".hpp","2050","66","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef DERIVATIVES_HPP_ #define DERIVATIVES_HPP_ #include ""stencil.hpp"" // ============================================================================= // Derivatives /** Symmetric finite difference derivative along the x direction */ inline double derivX(const field& f, const stencil& s) { return .5*( f[s[+1][0]] - f[s[-1][0]] ); } /** Symmetric finite difference derivative along the y direction */ inline double derivY(const field& f, const stencil& s) { return .5*( f[s[0][+1]] - f[s[0][-1]] ); } /** Five-point finite difference laplacian */ inline double laplacian(const field& f, const stencil& s) { return f[s[+1][0]] + f[s[0][+1]] + f[s[-1][0]] + f[s[0][-1]] - 4.*f[s[0][0]]; } /** Symmetric finite difference derivative along the x direction (arrays) */ CUDA_host_device inline double derivX(double *f, const stencil& s) { return .5*( f[s[+1][0]] - f[s[-1][0]] ); } /** Symmetric finite difference derivative along the y direction (arrays) */ CUDA_host_device inline double derivY(double *f, const stencil& s) { return .5*( f[s[0][+1]] - f[s[0][-1]] ); } /** Five-point finite difference laplacian (arrays) */ CUDA_host_device inline double laplacian(double *f, const stencil& s) { return f[s[+1][0]] + f[s[0][+1]] + f[s[-1][0]] + f[s[0][-1]] - 4.*f[s[0][0]]; } #endif//DERIVATIVES_HPP_ ","Unknown" "Biophysics","rhomu/celadro","src/vec_cuda.h",".h","5901","271","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef VEC_HPP_ #define VEC_HPP_ #include #include /** Simple euclidean vector * * The all-time most famous class among C++ students! This is simply an array * with euclidean operations built on top. * */ template struct vec { /** Individual components */ T data[D]; __host__ __device__ vec() = default; __host__ __device__ vec(const vec& v) = default; __host__ __device__ vec& operator=(const vec& v) = default; __host__ __device__ vec& operator=(const T& t) { for(size_t i = 0; i friend vec operator+(const U&, const vec&); template friend vec operator+(const vec&, const U&); template friend vec operator-(const U&, const vec&); template friend vec operator-(const vec&, const U&); template friend vec operator*(const U&, const vec&); template friend vec operator*(const vec&, const U&); template friend vec operator/(const vec&, const U&); template friend std::ostream& operator<<(std::ostream&, const vec&); template explicit operator vec() const { vec ret; for(size_t i = 0; i vec operator+(const vec& v, const T& t) { vec ret; for(size_t i = 0; i vec operator+(const T& t, const vec& v) { vec ret; for(size_t i = 0; i vec operator-(const vec& v, const T& t) { vec ret; for(size_t i = 0; i vec operator-(const T& t, const vec& v) { vec ret; for(size_t i = 0; i vec operator*(const vec& v, const T& t) { vec ret; for(size_t i = 0; i vec operator*(const T& t, const vec& v) { vec ret; for(size_t i = 0; i vec operator/(const vec& v, const T& t) { vec ret; for(size_t i = 0; i std::ostream& operator<<(std::ostream& stream, const vec& v) { stream << '['; if(D>0) { stream << v[0]; for(size_t i = 1; i * * Applies modulo component-wise. * */ template __host__ __device__ vec operator%(const vec& a, const vec& b) { auto ret = a; for(size_t i = 0; i. */ #include ""header.hpp"" #include ""serialization.hpp"" using namespace std; /** The number of spaces in indendation */ static const unsigned padding = 2; oarchive::oarchive(std::ostream& stream_, string id, unsigned version) : stream(stream_) { if(!stream.good()) throw bad_stream(); // write initial brace open_group(); // add description and version add(""id"", id); add(""version"", version); // open the data group add_key(""data""); open_group(); } oarchive::~oarchive() { // close the 'data' group close_group(); // write final brace if(stream.good()) stream << endl << '}'; } void oarchive::indent(unsigned n) { level += n; } void oarchive::unindent(unsigned n) { level -= n; } void oarchive::open_group(const std::string& obrace) { // open brace stream << obrace; // indent one level indent(); // next element is first first = true; } void oarchive::close_group(const string& cbrace) { // unindent unindent(); // new line stream << endl << string(padding*level, ' '); // close brace stream << cbrace; // not the first in the list first = false; } void oarchive::add_key(const string& key) { new_line(); stream << ""\"""" << key << ""\"" : ""; } void oarchive::new_line() { // add comma if(!first) stream << ','; else first = false; // new line stream << endl; // indent stream << string(padding*level, ' '); } template<> void oarchive::add_element(const char* const& t) { std::stringstream ss; ss << ""\"""" << t << ""\""""; stream << ss.str(); } template<> void oarchive::add_element(const std::string& t) { add_element(t.c_str()); } ","C++" "Biophysics","rhomu/celadro","src/options.cpp",".cpp","12733","333","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #include ""header.hpp"" #include ""model.hpp"" using namespace std; void Model::ParseProgramOptions(int ac, char **av) { // =========================================================================== // Declaration // options allowed only in the command line opt::options_description generic(""Generic options""); generic.add_options() (""help,h"", ""produce help message"") (""verbose,v"", opt::value(&verbose)->implicit_value(2), ""verbosity level (0=none, 1=little, 2=normal, 3=debug)"") (""input,i"", opt::value(&inputname), ""input file"") (""force-delete,f"", opt::bool_switch(&force_delete), ""force deletion of existing output file"") #ifdef _OPENMP (""threads,t"", opt::value(&nthreads)->default_value(0)->implicit_value(1), ""number of threads (0=no multithreading, 1=OpenMP default, "" "">1=your favorite number)"") #endif (""compress,c"", opt::bool_switch(&compress), ""compress individual files using zip"") (""compress-full"", opt::bool_switch(&compress_full), ""compress full output using zip (might be slow)"") (""no-write"", opt::bool_switch(&no_write), ""disable file output (for testing purposes)""); // options allowed both in the command line and config file opt::options_description config(""Program options""); config.add_options() (""output,o"", opt::value(&runname), ""output name (if compression is on, then .zip is added automatically)"") (""seed"", opt::value(&seed), ""set seed for random number generation (random if unset)"") (""no-warning"", opt::bool_switch(&no_warning), ""disable model specific runtime warnings"") (""stop-at-warning"", opt::bool_switch(&stop_at_warning), ""runtime warnings interrupt the algorithm"") (""check"", opt::bool_switch(&runtime_check), ""perform runtime checks"") (""stat"", opt::bool_switch(&runtime_stats), ""print runtime stats"") (""nstart"", opt::value(&nstart)->default_value(0u), ""time at which to start the output"") (""bc"", opt::value(&BC)->default_value(0u), ""boundary conditions flag (0=pbc, 1=box, 2=channel, 3=ellipse)""); // model specific options opt::options_description simulation(""Simulation options""); simulation.add_options() (""LX"", opt::value(&Size[0]), ""# of nodes in the x direction"") (""LY"", opt::value(&Size[1]), ""# of nodes in the y direction"") (""nsteps"", opt::value(&nsteps), ""iterate this many steps in total"") (""nsubsteps"", opt::value(&nsubsteps)->default_value(1u), ""subdivision of a single time step "" ""(effective time step is 1/nsubsteps)"") (""ninfo"", opt::value(&ninfo), ""save frame every so many steps"") (""nphases"", opt::value(&nphases), ""Number of phases"") (""gamma"", opt::value(&gam), ""Elastic constant of each phase (array)"") (""mu"", opt::value(&mu), ""Energy penalty for area of each phase (array)"") (""lambda"", opt::value(&lambda), ""Interface thickness parameter"") (""kappa"", opt::value(&kappa), ""Interaction strength"") (""npc"", opt::value(&npc)->default_value(1u), ""Number of predictor-corrector steps"") (""margin"", opt::value(&margin)->default_value(0u), ""Margin for the definition of restricted domains (if 0: update full box)"") //(""friction"", opt::value(&f), // ""Cell-cell friction parameter"") //(""friction-walls"", opt::value(&f_walls), // ""Cell-wall friction parameter"") (""xi"", opt::value(&xi), ""Substrate friction parameter"") (""K-pol"", opt::value(&Kpol), ""elastic constant for the polarisation"") (""K-nem"", opt::value(&Knem), ""elastic constant for the nematic"") //(""C-pol"", opt::value(&Cpol), // ""Strength of LdG potential for the polarisation"") (""J-pol"", opt::value(&Jpol), ""Nematic flow alignment strength"") (""J-nem"", opt::value(&Jnem), ""Nematic flow alignment strength"") (""W-nem"", opt::value(&Wnem), ""Strength of vorticity torque"") (""D-nem"", opt::value(&Dnem), ""Nematic noise strength"") (""D-pol"", opt::value(&Dpol), ""Polarisation noise strength"") (""S-nem"", opt::value(&Snem), ""Order of the nematic tensors"") (""S-pol"", opt::value(&Spol), ""Norm of the polarisation vector"") (""alpha"", opt::value(&alpha), ""Strength of propulsion"") (""zetaQ"", opt::value(&zetaQ), ""Activity from internal nematic tensor"") (""zetaS"", opt::value(&zetaS), ""Activity from shape"") (""omega"", opt::value(&omega), ""Adhesion parameter"") (""wall-thickness"", opt::value(&wall_thickness), ""Wall thickness (typical decay length)"") (""wall-kappa"", opt::value(&wall_kappa)->default_value(kappa), ""Wall repulsion"") (""wall-omega"", opt::value(&wall_omega)->default_value(0.), ""Wall adhesion"") (""R"", opt::value(&R), ""Preferred radius (defines area Pi*R*R)"") (""align-polarization-to"", opt::value(&align_polarization_to), ""Align polarization to velocity (=0) or pressure force (=1)"") (""align-nematic-to"", opt::value(&align_nematic_to), ""Align nematic tensor to velocity (=0), pressure force (=1), or shape (=2)""); // init config options opt::options_description init(""Initial configuration options""); init.add_options() (""config"", opt::value(&init_config), ""Initial configuration"") (""relax-time"", opt::value(&relax_time)->default_value(0u), ""Relaxation time steps at initialization."") (""noise"", opt::value(&noise), ""Noise level for initial nematic angle, in (0,1)."") (""cross-ratio"", opt::value(&cross_ratio), ""Ratio of the size of the cross compared to the domain size (for BC=4)"") (""wound-ratio"", opt::value(&wound_ratio), ""Ratio of the size of the wound open space compared to the domain size (for BC=5)"") (""tumor-ratio"", opt::value(&tumor_ratio), ""Ratio of the size of the tumor compared to the domain size (for BC=6)"") (""birth-boundaries"", opt::value>(&birth_bdries)->multitoken(), ""Boundaries in which the cells are created "" ""when the initial configuration 'random' is choosed. "" ""Format: {min x, max, x, min y, max y}"") (""relax-nsubsteps"", opt::value(&relax_nsubsteps)->default_value(0u), ""Value of nsubsteps to use at initial relaxation (0 means use nsubsteps).""); // =========================================================================== // Parsing // command line options opt::options_description cmdline_options; cmdline_options.add(generic).add(config).add(simulation).add(init); // config file options opt::options_description config_file_options; config_file_options.add(config).add(simulation).add(init); // first unnamed argument is the input file opt::positional_options_description p; p.add(""input"", 1); // reintialize vm in case we run this function twice vm = opt::variables_map(); // parse first the cmd line opt::store( opt::command_line_parser(ac, av) .options(cmdline_options) .positional(p) .run(), vm); opt::notify(vm); // print help msg and exit if(vm.count(""help"")) { cout << config_file_options << endl; exit(0); } // parse input file (values are not erased, such that cmd line args // are 'stronger') if(inputname.empty()) throw error_msg(""please provide an input file / type -h for help.""); else { std::fstream file(inputname.c_str(), std::fstream::in); // try to read one char out of file to check that it exists file.get(); if(!file.good()) { throw error_msg(""can not open runcard file '"", inputname, ""' or file is empty.""); } // rewind file file.clear(); file.seekg(0); // parse options opt::store(opt::parse_config_file(file, config_file_options), vm); opt::notify(vm); } // =========================================================================== // Fixing some secondary values // fix compression mode: if we compress the full archive we do not compress // individual files. if(compress_full) compress=false; // Set default value for runname (depends on compression) if(vm.count(""output"")==0) { if(compress_full) runname = ""output""; else runname = ""./""; } // init random numbers? set_seed = vm.count(""seed""); // compute the correct padding pad = inline_str(nsteps).length(); // compute effective time step time_step = 1./nsubsteps; // set nstart to the next correct frame (round above) if(nstart%ninfo) nstart = (1u+nstart/ninfo)*ninfo; } /** Print variables from variables_map * * from: https://gist.github.com/gesquive/8673796 */ void print_vm(const opt::variables_map& vm, unsigned padding) { for (opt::variables_map::const_iterator it = vm.begin(); it != vm.end(); ++it) { // pass if defaulted or empty if (vm[it->first].defaulted() || it->second.defaulted()) continue; if (((boost::any)it->second.value()).empty()) continue; std::cout << std::left << std::setw(floor(padding/2)) << it->first; /*if (((boost::any)it->second.value()).empty()) { std::cout << ""(empty)""; } if (vm[it->first].defaulted() || it->second.defaulted()) { std::cout << ""(default)""; }*/ std::cout << std::right << std::setw(ceil(padding/2)); bool is_char; try { boost::any_cast(it->second.value()); is_char = true; } catch (const boost::bad_any_cast &) { is_char = false; } bool is_str; try { boost::any_cast(it->second.value()); is_str = true; } catch (const boost::bad_any_cast &) { is_str = false; } if (((boost::any)it->second.value()).type() == typeid(int)) { std::cout << vm[it->first].as() << std::endl; } else if (((boost::any)it->second.value()).type() == typeid(unsigned)) { std::cout << vm[it->first].as() << std::endl; } else if (((boost::any)it->second.value()).type() == typeid(size_t)) { std::cout << vm[it->first].as() << std::endl; } else if (((boost::any)it->second.value()).type() == typeid(bool)) { std::cout << (vm[it->first].as() ? ""true"" : ""false"") << std::endl; } else if (((boost::any)it->second.value()).type() == typeid(double)) { std::cout << vm[it->first].as() << std::endl; } else if (((boost::any)it->second.value()).type() == typeid(vector)) { std::cout << vec2str(vm[it->first].as>()) << std::endl; } else if (((boost::any)it->second.value()).type() == typeid(vector)) { std::cout << vec2str(vm[it->first].as>()) << std::endl; } else if (is_char) { std::cout << vm[it->first].as() << std::endl; } else if (is_str) { std::string temp = vm[it->first].as(); if (temp.size()) { std::cout << temp << std::endl; } else { std::cout << ""true"" << std::endl; } } else { // Assumes that the only remainder is vector try { auto vect = vm[it->first].as >(); uint i = 0; for (auto oit=vect.begin(); oit != vect.end(); oit++, ++i) { std::cout << ""\r> "" << it->first << ""["" << i << ""]="" << (*oit) << std::endl; } } catch (const boost::bad_any_cast &) { std::cout << ""UnknownType("" << ((boost::any)it->second.value()).type().name() << "")"" << std::endl; } } } } void Model::PrintProgramOptions() { // print the simulation parameters print_vm(vm, width); } ","C++" "Biophysics","rhomu/celadro","src/tools.hpp",".hpp","4273","169","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef TOOLS_HPP_ #define TOOLS_HPP_ #include #include #include #include #include /** Modulo function that works correctly with negative values */ template inline T modu(const T& num, const T& div) { if(num < 0) return div + num%div; else return num%div; } /** Modulo function that works correctly with negative values */ inline double modu(double num, double div) { if(num < 0) return div + std::fmod(num, div); else return std::fmod(num, div); } /** Unsigned difference * * This function can be used with unsigned types with no fear of loosing the * sign. * */ template inline T diff(const T& a, const T& b) { return a>b ? a-b : b-a; } /** Check that two doubles are equal * * This somewhat complicated expression avoids false negative from finite * precision of the floating point arithmetic. Precision threshold can be * set using the error_factor parameter. * */ inline bool check_equal(double a, double b, double error_factor=1.) { return a==b || std::abs(a-b)::epsilon()* error_factor; } /** Wrap point around periodic boundaries * * This function is useful when dealing with periodic boundary conditions, * simply returns the minimum of x%L and L-x%L * */ template inline T wrap(const T& x, const U& L) { return std::min(modu(x, L), L-modu(x, L)); } /** Specialization for double */ inline double wrap(double x, double L) { const auto y = modu(x, L); if(std::abs(y) inline void set_if_smaller(T& dst, const U& src) { if(src inline void set_if_bigger(T& dst, const U& src) { if(src>dst) dst = src; } namespace detail { /** Convert to strig and catenate arguments */ template void inline_str_add_args(std::ostream& stream, Head&& head) { stream << std::forward(head); } /** Convert to strig and catenate arguments */ template void inline_str_add_args(std::ostream& stream, Head&& head, Tail&&... tail) { stream << std::forward(head); inline_str_add_args(stream, std::forward(tail)...); } } // namespace detail /** Convert any number of arguments to string and catenate * * It does pretty much what is advertised. Look at the code if you want to learn * some pretty neat modern C++. * */ template std::string inline_str(Args&&... args) { std::stringstream s; detail::inline_str_add_args(s, std::forward(args)...); return s.str(); } /** Convert iterable to string of the form {a,b,c,...} */ template std::string vec2str(const T& iterable) { std::stringstream s; s << '{'; for(auto it = begin(iterable);;) { s << *it; if(++it==end(iterable)) break; s << ','; } s << '}'; return s.str(); } /** Split string * * My most famous contribution to stack overflow. * */ inline std::vector split(const std::string& s, char sep=' ') { std::vector words; for(size_t p=0, q=0; p!=s.npos; p=q) words.push_back(s.substr(p+(p!=0), (q=s.find(sep, p+1))-p-(p!=0))); return words; } #endif//TOOLS_HPP_ ","Unknown" "Biophysics","rhomu/celadro","src/run.cpp",".cpp","12111","428","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #include ""header.hpp"" #include ""model.hpp"" #include ""derivatives.hpp"" #include ""tools.hpp"" using namespace std; void Model::Pre() { // we make the system relax (without activity) if(relax_time>0) { double save_alpha = 0; swap(alpha, save_alpha); double save_zetaS = 0; swap(zetaS, save_zetaS); double save_zetaQ = 0; swap(zetaQ, save_zetaQ); double save_Dnem = 0; swap(Dnem, save_Dnem); double save_Dpol = 0; swap(Dpol, save_Dpol); double save_Jnem = 0; swap(Jnem, save_Jnem); double save_Jpol = 0; swap(Jpol, save_Jpol); double save_Kpol = 0; swap(Kpol, save_Kpol); double save_Knem = 0; swap(Knem, save_Knem); double save_Wnem = 0; swap(Wnem, save_Wnem); if(relax_nsubsteps) swap(nsubsteps, relax_nsubsteps); for(unsigned i=0; i.2) throw warning_msg(""area is not conserved.""); for(unsigned n=0; n1/2). double a = 0.; // compute area of points outside the cell (<1/2) for(const auto v : phi[n]) if(v<.5) a += v*v; // check that it is less than 5% if(a/area[n]>.90) throw warning_msg(""your cells are leaking!""); // check that the phase fields stay between 0 and 1 for(const auto& p : phi[n]) if(p<-0.5 or p>1.5) throw warning_msg(""phase-field is not in [0,1]!""); } } void Model::UpdateSumsAtNode(unsigned n, unsigned q) { const auto k = GetIndexFromPatch(n, q); const auto p = phi[n][q]; sum[k] += p; square[k] += p*p; thirdp[k] += p*p*p; fourthp[k] += p*p*p*p; sumA[k] += p*p*area[n]; sumS00[k] += p*S00[n]; sumS01[k] += p*S01[n]; sumQ00[k] += p*Q00[n]; sumQ01[k] += p*Q01[n]; P0[k] += p*polarization[n][0]; P1[k] += p*polarization[n][1]; U0[k] += p*velocity[n][0]; U1[k] += p*velocity[n][1]; } void Model::UpdatePotAtNode(unsigned n, unsigned q) { const auto k = GetIndexFromPatch(n, q); const auto& s = neighbors[k]; const auto& sq = neighbors_patch[q]; const auto p = phi[n][q]; const auto a = area[n]; const auto ll = laplacian(phi[n], sq); const auto ls = laplacian(sum, s); const double internal = ( // CH term + gam*(8*p*(1-p)*(1-2*p)/lambda - 2*lambda*ll) // area conservation term - 4*mu/a0*(1-a/a0)*p ); const double interactions = ( // repulsion term + 2*kappa/lambda*p*(square[k]-p*p) // adhesion term - 2*omega*lambda*(ls-ll) // repulsion with walls + 2*wall_kappa/lambda*p*walls[k]*walls[k] // adhesion with walls - 2*wall_omega*lambda*walls_laplace[k] ); // delta F / delta phi_i V[n][q] = internal + interactions; // pressure pressure[k] += p*interactions; } void Model::UpdateForcesAtNode(unsigned n, unsigned q) { const auto k = GetIndexFromPatch(n, q); const auto& s = neighbors[k]; const auto& sq = neighbors_patch[q]; const auto p = phi[n][q]; const auto dx = derivX(phi[n], sq); const auto dy = derivY(phi[n], sq); const auto dxs = derivX(sum, s); const auto dys = derivY(sum, s); stress_xx[k] = - pressure[k] - zetaS*sumS00[k] - zetaQ*sumQ00[k]; stress_yy[k] = - pressure[k] + zetaS*sumS00[k] + zetaQ*sumQ00[k]; stress_xy[k] = - zetaS*sumS01[k] - zetaQ*sumQ01[k]; Fpressure[n] += { pressure[k]*dx, pressure[k]*dy }; Fshape[n] += { zetaS*sumS00[k]*dx + zetaS*sumS01[k]*dy, zetaS*sumS01[k]*dx - zetaS*sumS00[k]*dy }; Fnem[n] += { zetaQ*sumQ00[k]*dx + zetaQ*sumQ01[k]*dy, zetaQ*sumQ01[k]*dx - zetaQ*sumQ00[k]*dy }; // store derivatives phi_dx[n][q] = dx; phi_dy[n][q] = dy; // nematic torques tau[n] += p*(Q00[n]*sumQ01[k] - Q01[n]*sumQ00[k]); vorticity[n] += dx*U1[k] - dy*U0[k]; // polarisation torques (not super nice) const double ovlap = -(dx*(dxs-dx)+dy*(dys-dy)); const vec P = {P0[k]-phi[n][k]*polarization[n][0], P1[k]-phi[n][k]*polarization[n][1]}; delta_theta_pol[n] += ovlap*atan2(P[0]*polarization[n][1]-P[1]*polarization[n][0], P[0]*polarization[n][0]+P[1]*polarization[n][1]); } void Model::UpdatePhaseFieldAtNode(unsigned n, unsigned q, bool store) { const auto k = GetIndexFromPatch(n, q); // compute dphi dphi[n][q] = // free energy - V[n][q] // advection term - velocity[n][0]*phi_dx[n][q] - velocity[n][1]*phi_dy[n][q]; ; // store values if(store) { dphi_old[n][q] = dphi[n][q]; phi_old[n][q] = phi[n][q]; } // predictor-corrector { double p = phi_old[n][q] + time_step*.5*(dphi[n][q] + dphi_old[n][q]); // update for next call phi[n][q] = p; com_x[n] += com_x_table[GetXPosition(k)]*p; com_y[n] += com_y_table[GetYPosition(k)]*p; area[n] += p*p; } // reinit values: we do reinit values here for the simple reason that it is // faster than having a supplementary loop afterwards. There is a race // condition in principle here but since we are setting evth back to 0 it // should be fine. Note that this should be done before the patches are updated ReinitSumsAtNode(k); } void Model::UpdateNematic(unsigned n, bool store) { // euler-marijuana update if(store) theta_nem_old[n] = theta_nem[n] + sqrt_time_step*Dnem*random_normal(); double F00 = 0, F01 = 0; switch(align_nematic_to) { case 0: { const auto ff = velocity[n]; F00 = ff[0]*ff[0] - ff[1]*ff[1]; F01 = 2*ff[0]*ff[1]; break; } case 1: { const auto ff = Fpressure[n]; F00 = ff[0]*ff[0] - ff[1]*ff[1]; F01 = 2*ff[0]*ff[1]; break; } case 2: F00 = S00[n]; F01 = S01[n]; break; } const auto strength = pow(F01*F01 + F00*F00, 0.25); theta_nem[n] = theta_nem_old[n] + time_step*( + Knem*tau[n] - Jnem*strength*atan2(F00*Q01[n]-F01*Q00[n], F00*Q00[n]+F01*Q01[n])) + Wnem*vorticity[n]; Q00[n] = Snem*cos(2*theta_nem[n]); Q01[n] = Snem*sin(2*theta_nem[n]); } void Model::UpdatePolarization(unsigned n, bool store) { // euler-marijuana update if(store) theta_pol_old[n] = theta_pol[n] + sqrt_time_step*Dpol*random_normal(); vec ff = {0, 0}; switch(align_polarization_to) { case 0: ff = velocity[n]; break; case 1: ff = Fpressure[n]; break; } theta_pol[n] = theta_pol_old[n] - time_step*( + Kpol*delta_theta_pol[n] + Jpol*ff.abs()*atan2(ff[0]*polarization[n][1]-ff[1]*polarization[n][0], ff*polarization[n])); polarization[n] = { Spol*cos(theta_pol[n]), Spol*sin(theta_pol[n]) }; } void Model::ComputeCoM(unsigned n) { // the strategy to deal with the periodic boundary conditions is to compute // all the integrals in Fourier space and come back at the end. This way the // periodicity of the domain is automatically taken into account. const auto mx = arg(com_x[n]/static_cast(N)) + Pi; const auto my = arg(com_y[n]/static_cast(N)) + Pi; com[n] = { mx/2./Pi*Size[0], my/2./Pi*Size[1] }; } void Model::UpdatePatch(unsigned n) { // obtain the new location of the patch min and max const coord com_grd { unsigned(round(com[n][0])), unsigned(round(com[n][1])) }; const coord new_min = ( com_grd + Size - patch_margin ) % Size; const coord new_max = ( com_grd + patch_margin - coord {1u, 1u} ) % Size; coord displacement = ( Size + new_min - patch_min[n] ) % Size; // I guess there is somehthing better than this... if(displacement[0]==Size[0]-1u) displacement[0] = patch_size[0]-1u; if(displacement[1]==Size[1]-1u) displacement[1] = patch_size[1]-1u; // update offset and patch location offset[n] = ( offset[n] + patch_size - displacement ) % patch_size; patch_min[n] = new_min; patch_max[n] = new_max; } void Model::UpdateStructureTensorAtNode(unsigned n, unsigned q) { const auto dx = phi_dx[n][q]; const auto dy = phi_dy[n][q]; S00[n] += -0.5*(dx*dx-dy*dy); S01[n] += -dx*dy; } void Model::ReinitSumsAtNode(unsigned k) { sum[k] = 0; square[k] = 0; thirdp[k] = 0; fourthp[k] = 0; sumA[k] = 0; sumS00[k] = 0; sumS01[k] = 0; sumQ00[k] = 0; sumQ01[k] = 0; pressure[k] = 0; U0[k] = 0; U1[k] = 0; } void Model::Update(bool store, unsigned nstart) { // Compute all global sums for(unsigned n=nstart; n. */ #include ""header.hpp"" #include ""model.hpp"" using namespace std; void Model::Initialize() { N = Size[0]*Size[1]; sqrt_time_step = sqrt(time_step); // rectifies margin in case it is bigger than domain // and compensate for the boundary layer patch_margin = { min(margin, Size[0]/2 - 1 + (Size[0]%2)), min(margin, Size[1]/2 - 1 + (Size[1]%2)) }; // total size including bdry layer patch_size = 2u*patch_margin + 1u; patch_N = patch_size[0]*patch_size[1]; // initialize memory for global fields walls.resize(N, 0.); walls_dx.resize(N, 0.); walls_dy.resize(N, 0.); walls_laplace.resize(N, 0.); sum.resize(N, 0.); pressure.resize(N, 0.); stress_xx.resize(N, 0.); stress_xy.resize(N, 0.); stress_yy.resize(N, 0.); sumA.resize(N, 0.); sumS00.resize(N, 0.); sumS01.resize(N, 0.); sumQ00.resize(N, 0.); sumQ01.resize(N, 0.); square.resize(N, 0.); thirdp.resize(N, 0.); fourthp.resize(N, 0.); P0.resize(N, 0.); P1.resize(N, 0.); U0.resize(N, 0.); U1.resize(N, 0.); // allocate memory for individual cells SetCellNumber(nphases); // --------------------------------------------------------------------------- if(zetaQ!=0.) sign_zetaQ = zetaQ>0. ? 1 : -1; if(zetaS!=0.) sign_zetaS = zetaS>0. ? 1 : -1; // compute tables for(unsigned i=0; i(patch_N, 0.)); phi_dx.resize(nphases, vector(patch_N, 0.)); phi_dy.resize(nphases, vector(patch_N, 0.)); phi_old.resize(nphases, vector(patch_N, 0.)); V.resize(nphases, vector(patch_N, 0.)); dphi.resize(nphases, vector(patch_N, 0.)); dphi_old.resize(nphases, vector(patch_N, 0.)); // allocate memory for cell properties area.resize(nphases, 0.); patch_min.resize(nphases, {0, 0}); patch_max.resize(nphases, Size); com.resize(nphases, {0., 0.}); com_prev.resize(nphases, {0., 0.}); polarization.resize(nphases, {0., 0.}); velocity.resize(nphases, {0., 0.}); Fpressure.resize(nphases, {0., 0.}); Fshape.resize(nphases, {0., 0.}); Fnem.resize(nphases, {0., 0.}); Fpol.resize(nphases, {0., 0.}); com_x.resize(nphases, 0.); com_y.resize(nphases, 0.); S00.resize(nphases, 0.); S01.resize(nphases, 0.); Q00.resize(nphases, 0.); Q01.resize(nphases, 0.); offset.resize(nphases, {0u, 0u}); theta_pol.resize(nphases, 0.); theta_pol_old.resize(nphases, 0.); delta_theta_pol.resize(nphases, 0.); theta_nem.resize(nphases, 0.); theta_nem_old.resize(nphases, 0.); vorticity.resize(nphases, 0.); tau.resize(nphases, 0.); } void Model::InitializeNeighbors() { neighbors.resize(N); neighbors_patch.resize(patch_N); // define the neighbours, accounting for the periodic boundaries for(unsigned k=0; k. */ #ifdef _OPENMP #include ""threads.hpp"" /** number of threads */ unsigned nthreads; /** Init multi-threading * * Somewhow omp_get_num_threads() is not working properly with gcc... so we * need to use this trick to get the standard number of threads. Or I am too * dumb to use omp... * */ void SetThreads() { // if nthreads is 1 we use the default number of threads from OpenMP if(nthreads == 1) { // count the number of OpenMP threads unsigned count = 0; PRAGMA_OMP(omp parallel) { PRAGMA_OMP(omp atomic) ++count; } nthreads = count; } } #endif ","C++" "Biophysics","rhomu/celadro","src/vec.hpp",".hpp","6722","299","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef VEC_HPP_ #define VEC_HPP_ #include #include #include /** Simple euclidean vector * * The all-time most famous class among C++ students! This is simply an array * with euclidean operations built on top. * */ template struct vec { /** Individual components */ std::array data; vec() = default; vec(const vec& v) = default; vec& operator=(const vec& v) = default; vec& operator+=(const vec& v) { for(size_t i = 0; i(const vec& v) const { for(size_t i=0; i=v.data[i]) return false; return true; } /** Component-wise comparison operator */ bool operator>=(const vec& v) const { for(size_t i=0; iv.data[i]) return false; return true; } /** Square */ T sq() const { return (*this)*(*this); } /** Absolute value */ T abs() const { return sqrt(sq()); } /** Return unit vector */ vec unit_vector() const { return *this/abs(); } template friend vec operator+(const U&, const vec&); template friend vec operator+(const vec&, const U&); template friend vec operator-(const U&, const vec&); template friend vec operator-(const vec&, const U&); template friend vec operator*(const U&, const vec&); template friend vec operator*(const vec&, const U&); template friend vec operator/(const vec&, const U&); template friend std::ostream& operator<<(std::ostream&, const vec&); template explicit operator vec() const { vec ret; for(size_t i = 0; i::iterator begin() { return data.begin(); } typename std::array::iterator end() { return data.end(); } typename std::array::const_iterator begin() const { return data.begin(); } typename std::array::const_iterator end() const { return data.end(); } size_t size() const { return D; } }; // ============================================================================= // External functions implementation template vec operator+(const vec& v, const T& t) { vec ret; for(size_t i = 0; i vec operator+(const T& t, const vec& v) { vec ret; for(size_t i = 0; i vec operator-(const vec& v, const T& t) { vec ret; for(size_t i = 0; i vec operator-(const T& t, const vec& v) { vec ret; for(size_t i = 0; i vec operator*(const vec& v, const T& t) { vec ret; for(size_t i = 0; i vec operator*(const T& t, const vec& v) { vec ret; for(size_t i = 0; i vec operator/(const vec& v, const T& t) { vec ret; for(size_t i = 0; i std::ostream& operator<<(std::ostream& stream, const vec& v) { stream << '['; if(D>0) { stream << v[0]; for(size_t i = 1; i * * Applies modulo component-wise. * */ template vec operator%(const vec& a, const vec& b) { auto ret = a; for(size_t i = 0; i inline vec wrap(vec v, const vec& L) { for(size_t i=0; i. */ #include ""header.hpp"" #include ""model.hpp"" #ifdef DEBUG #include #endif using namespace std; /** pure eyecandy */ string title = R""( ______ __ __ / ____/__ / /___ _____/ /________ / / / _ \/ / __ `/ __ / ___/ __ \ / /___/ __/ / /_/ / /_/ / / / /_/ / \____/\___/_/\__,_/\__,_/_/ \____/ ----------------------------------- Celadro: Cells as active droplets (c) 2016-17, Romain Mueller )""; // ============================================================================= void Model::Algorithm() { // number of steps between two writes const unsigned streak_length = nsubsteps*ninfo; for(unsigned t=0; t=nstart) { const auto start = chrono::steady_clock::now(); try { WriteFrame(t); } catch(...) { cerr << ""error"" << endl; throw; } write_duration += chrono::steady_clock::now() - start; } // some verbose if(verbose>1) cout << '\n'; if(verbose) cout << ""timesteps t = "" << setw(pad) << setfill(' ') << right << t << "" to "" << setw(pad) << setfill(' ') << right << t+ninfo << endl; if(verbose>1) cout << string(width, '-') << endl; // do the computation for(unsigned s=0; s1) RuntimeStats(); if(runtime_check) RuntimeChecks(); } catch(const error_msg& e) { throw; } catch(const warning_msg& e) { if(stop_at_warning) throw; else if(verbose and !no_warning) cerr << ""warning: "" << e.what() << ""\n""; } } // finally write final frame if(!no_write and nsteps>=nstart) WriteFrame(nsteps); } void Model::Setup(int argc, char **argv) { // ======================================== // Setup if(argc<2) throw error_msg(""no argument provided. Type -h for help.""); // parse program options ParseProgramOptions(argc, argv); // check that we have a run name if(runname.empty()) throw error_msg(""please specify a file path for this run.""); // print simulation parameters if(verbose) { cout << ""Run parameters"" << endl; cout << string(width, '=') << endl; PrintProgramOptions(); } // ======================================== // Initialization if(verbose) cout << endl << ""Initialization"" << endl << string(width, '=') << endl; // warning and flags // no output if(no_write and verbose) cout << ""warning: output is not enabled."" << endl; // ---------------------------------------- // model init if(verbose) cout << ""model initialization ..."" << flush; try { InitializeRandomNumbers(); Initialize(); InitializeNeighbors(); } catch(...) { if(verbose) cout << "" error"" << endl; throw; } if(verbose) cout << "" done"" << endl; // ---------------------------------------- // parameters init if(verbose) cout << ""system initialisation ..."" << flush; try { Configure(); ConfigureWalls(BC); } catch(...) { if(verbose) cout << "" error"" << endl; throw; } if(verbose) cout << "" done"" << endl; // ---------------------------------------- // multi-threading #ifdef _OPENMP if(nthreads) { if(verbose) cout << ""multi-threading ... "" << flush; SetThreads(); if(verbose) cout << nthreads << "" active threads"" << endl; } #endif // ---------------------------------------- // cuda, see random numbers section as well #ifdef _CUDA_ENABLED if(verbose) cout << ""setting up CUDA devices ..."" << endl; QueryDeviceProperties(); InitializeCuda(); if(verbose) cout << ""... allocate device memory ...""; AllocDeviceMemory(); if(verbose) cout << "" done"" << endl; if(verbose) cout << ""... random numbers initialization ..."" << flush; InitializeCUDARandomNumbers(); if(verbose) cout << "" done"" << endl; if(verbose) cout << ""... copy data to device ...""; PutToDevice(); if(verbose) cout << "" done"" << endl; #endif // ---------------------------------------- // write params to file if(!no_write) { if(verbose) cout << ""create output directory "" << "" ...""; try { CreateOutputDir(); } catch(...) { if(verbose) cout << "" error"" << endl; throw; } if(verbose) cout << "" done"" << endl; if(verbose and compress_full) cout << ""create output file "" << runname << "".zip ...""; if(verbose and not compress_full) cout << ""write parameters ...""; try { WriteParams(); } catch(...) { if(verbose) cout << "" error"" << endl; throw; } if(verbose) cout << "" done"" << endl; } } void Model::Run() { // preparation if(verbose) cout << ""preparation ... "" << flush; Pre(); if(verbose) cout << "" done"" << endl; if(verbose) cout << endl << ""Run"" << endl << string(width, '=') << ""\n\n""; // print some stats PreRunStats(); // record starting time const auto start = chrono::steady_clock::now(); // run the thing Algorithm(); // record end time const auto duration = chrono::steady_clock::now() - start; if(verbose) cout << ""post-processing ... "" << flush; Post(); if(verbose) cout << ""done"" << endl; if(verbose) { cout << endl << ""Statistics"" << endl << string(width, '=') << endl; cout << ""Total run time : "" << chrono::duration_cast(duration).count() /1000. << "" s"" << endl; cout << ""Total time spent writing output : "" << chrono::duration_cast(write_duration).count() /1000. << "" s"" << endl; } } void Model::Cleanup() { #ifdef _CUDA_ENABLED FreeDeviceMemory(); #endif } /** Program entry */ int main(int argc, char **argv) { // if in debug mode, catch all arithmetic exceptions #ifdef DEBUG feenableexcept(FE_INVALID | FE_OVERFLOW); #endif // print that beautiful title cout << title << endl; // do the job try { Model model; model.Setup(argc, argv); model.Run(); model.Cleanup(); } // custom small messages catch(const error_msg& e) { cerr << argv[0] << "": error: "" << e.what() << endl; return 1; } // bad alloc (possibly from memory()) catch(const bad_alloc& ba) { cerr << argv[0] << "": error initializing memory: "" << ba.what() << endl; return 1; } // all the rest (mainly from boost) catch(const exception& e) { cerr << argv[0] << "": "" << e.what() << endl; return 1; } return 0; } ","C++" "Biophysics","rhomu/celadro","src/model.hpp",".hpp","19129","673","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef MODEL_HPP_ #define MODEL_HPP_ #include #include #include ""vec.hpp"" #include ""stencil.hpp"" #include ""serialization.hpp"" /** Type used to represent values on the grid */ using field = std::vector; /** Grid coordinate */ using coord = vec; /** Model class * * This class contains the whole program and is mainly used to be able to * scatter the implementation to different files without having to declare * every single variable extern. The architecture has not been really thought * through and one should not create two of these objects. * */ struct Model { /** Simulation variables * @{ */ /** List of neighbours * * The list of neighbours is used for computing the derivatives and is pre- * computed during initialization. The neighbours_patch variable has the same * role but for a region of the size of the cell patches (all patches have the * same size). These variables are computed in Initialize() and do not change * at runtime. * */ std::vector neighbors, neighbors_patch; /** Phase fields and derivatives */ std::vector phi, phi_dx, phi_dy; /** Predicted phi in a PC^n step */ std::vector phi_old; /** Phi difference */ std::vector dphi; /** Predicted phi difference in a P(C)^n step */ std::vector dphi_old; /** V = delta F / delta phi */ std::vector V; /** Sum of phi at each node */ field sum; /** Sum_i S_i phi_i */ field sumS00, sumS01; /** Sum_i Q_i phi_i */ field sumQ00, sumQ01; /** Sum_i Area_i phi_i */ field sumA; /** Sum of square, third, and fourth powers of phi at each node */ field square, thirdp, fourthp; /** Phase-field for the walls and their derivatives */ field walls, walls_dx, walls_dy, walls_laplace; /** Total polarization of the tissue */ field P0, P1; /** Total velocity of the tissue */ field U0, U1; /** Area associated with a phase field */ std::vector area; /** Forces */ std::vector> Fpol, Fnem, Fshape, Fpressure; /** Velocity */ std::vector> velocity; /** Structure tensor */ std::vector S00, S01; /** Q-tensor */ std::vector Q00, Q01; /** Polarisation */ std::vector> polarization; /** Direction of the polarisation */ std::vector theta_pol, theta_pol_old; /** Direction of the nematics */ std::vector theta_nem, theta_nem_old; /** Polarisation total torque */ std::vector delta_theta_pol; /** Stress tensor */ field stress_xx, stress_xy , stress_yy, pressure; /** Elastic torque for the nematic */ std::vector tau; /** Vorticity around each cell */ std::vector vorticity; /** Alignement options (see options.cpp) */ int align_nematic_to = 0, align_polarization_to = 1; /** @} */ /** Domain managment * @{ */ /** Min of the boundaries of the patches and center of mass */ std::vector patch_min; /** Max of the boundaries of the patches and center of mass */ std::vector patch_max; /** Size of the patch (set by margin) */ coord patch_size, patch_margin; /** Total number of nodes in a patch */ unsigned patch_N; /** Memory offset for each patch */ std::vector offset; /** Center-of-mass */ std::vector> com, com_prev; /** Counter to compute com in Fourier space */ std::vector> com_x, com_y; /** Precomputed tables for sin and cos (as complex numbers) used in the * computation of the com. * */ std::vector> com_x_table, com_y_table; /** @} */ /** Program options * @{ */ /** verbosity level * * 0: no output * 1: some output * 2: extended output (default) * 3: debug * */ unsigned verbose = 2; /** compress output? (we use zip) */ bool compress, compress_full; /** name of the run */ std::string runname; /** Output dir (or tmp dir before moving files to the archive) */ std::string output_dir; /** write any output? */ bool no_write = false; /** skip runtime warnings? */ bool no_warning = false; /** are the runtime warnings fatal? (i.e. they do stop the simulation) */ bool stop_at_warning = false; /** shall we perform runtime checks ? */ bool runtime_check = false; /** shall we print some runtime stats ? */ bool runtime_stats = false; /** padding for onscreen output */ unsigned pad; /** name of the inpute file */ std::string inputname = """"; /** Delete output? */ bool force_delete; /** The random number seed */ unsigned long seed; // picked using a fair die /** Flag if seed was set in the arguments, see options.hpp */ bool set_seed; /** Number of predictor-corrector steps */ unsigned npc = 1; /** Relaxation time at initialization */ unsigned relax_time = 0; /** Value of nsubstep to use for initialization */ unsigned relax_nsubsteps = 0; /** Total time spent writing output */ std::chrono::duration write_duration; /** @} */ /** Simulation parameters * @{ */ /** size of the system */ vec Size; /** total number of nodes */ unsigned N; /** Total number of time steps */ unsigned nsteps; /** Time interval between data outputs */ unsigned ninfo = 10; /** Time at which to start the output */ unsigned nstart = 0; /** number of subdivisions for a time step */ unsigned nsubsteps = 10; /** effective time step */ double time_step, sqrt_time_step; /** Number of phases */ unsigned nphases; /** angle in degrees (input variable only) */ double angle_deg; /** Margin for the definition of patches */ unsigned margin = 25; /** Boudaries for cell generation * * These are the boundaries (min and max x and y components) of the domain in * which the cells are created when the initial config 'random' is choosen. * */ std::vector birth_bdries; /** @} */ /** Cell properties * @{ */ /** Elasticity */ double gam = 0.1; /** Energy penalty for area */ double mu = 3; /** Interface thickness */ double lambda = 3; /** Interaction stength */ double kappa = 0.2; /** Adhesion */ double omega = 0; /** Activity from shape */ double zetaS = 0, sign_zetaS = 0; /** Activity from internal Q tensor */ double zetaQ = 0, sign_zetaQ = 0; /** Propulsion strength */ double alpha = 0; /** Substrate friction parameter */ double xi = 1; /** Prefered radii (area = pi*R*R) and radius growth */ double R = 8; /** Base area: a0 = Pi*R*R */ double a0; /** Repuslion by the wall */ double wall_kappa = 0.5; /** Adhesion on the wall */ double wall_omega = 0; /** Elasitc parameters */ double Knem = 0, Kpol = 0; /** Strength of polarity / nematic tensor */ double Spol = 0, Snem = 0; /** Flow alignment strenght */ double Jpol = 0, Jnem = 0; /** Vorticity coupling */ double Wnem = 0; /** Noise strength */ double Dpol = 0, Dnem = 0; /** @} */ /** Multi-threading parameters * @{ */ #ifdef _OPENMP /** number of threads */ unsigned nthreads; #endif /** @} */ // =========================================================================== // Options. Implemented in options.cpp /** the variables map used to collect options */ opt::variables_map vm; /** Set parameters from input */ void ParseProgramOptions(int ac, char **av); /** Output all program options */ void PrintProgramOptions(); // ========================================================================= // Program managment. Implemented in main.cpp /** The main loop */ void Algorithm(); /** Setup computation */ void Setup(int, char**); /** Do the computation */ void Run(); /** Clean after you */ void Cleanup(); // =========================================================================== // Configuration. Implemented in configure.cpp /** Initial configuration parameters * @{ */ /** Initial configuration name */ std::string init_config; /** Boundary conditions flag */ unsigned BC = 0; /** Noise level for the nematic tensor initial configuration */ double noise = 1; /** Wall thickness */ double wall_thickness = 1.; /** Ratio of the cross vs size of the domain (BC=4) */ double cross_ratio = .25; /** Ratio of the wound vs size of the domain (BC=5) */ double wound_ratio = .50; /** Ratio of the tumor vs size of the domain (BC=6) */ double tumor_ratio = .80; /** @} */ /** Add cell with number n at a certain position */ void AddCell(unsigned n, const coord& center); /** Subfunction for AddCell() */ void AddCellAtNode(unsigned n, unsigned q, const coord& center); /** Set initial condition for the fields */ void Configure(); /** Set initial configuration for the walls */ void ConfigureWalls(int BC); // ========================================================================== // Writing to file. Implemented in write.cpp /** Write current state of the system */ void WriteFrame(unsigned); /** Write run parameters */ void WriteParams(); /** Remove old files */ void ClearOutput(); /** Create output directory */ void CreateOutputDir(); // ========================================================================== // Initialization. Implemented in init.cpp /** Initialize memory for field */ void Initialize(); /** Allocate memory for individual cells */ void SetCellNumber(unsigned new_nphases); /** Initialize neighbors list (stencils) */ void InitializeNeighbors(); /** Swap two cells in the internal arrays */ void SwapCells(unsigned n, unsigned m); // =========================================================================== // Random numbers generation. Implemented in random.cpp /** Pseudo random generator */ std::mt19937 gen; //ranlux24 gen; /** Return random real, uniform distribution */ double random_real(double min=0., double max=1.); /** Return random real, gaussian distributed */ double random_normal(double sigma=1.); /** Return geometric dist numbers, prob is p */ unsigned random_geometric(double p); /** Return poisson distributed unsigned integers */ unsigned random_poisson(double lambda); /** Return exp distributed unsigned integers */ int random_exponential(double lambda); /** Return random unsigned uniformly distributed */ unsigned random_unsigned(); /** Initialize random numbers * * If CUDA is enabled, alos intialize CUDA random numbers * */ void InitializeRandomNumbers(); // ========================================================================== // Support for cuda. Implemented in cuda.cu #ifdef _CUDA_ENABLED /** Device(s) propeties * @{ */ /** Obtain (and print) device(s) properties * * Also checks that the device properties are compatible with the values given * in src/cuda.h. * */ void QueryDeviceProperties(); /** @} */ /** Pointer to device global memory * * These pointers reflects the program data strcuture and represents the cor- * responding data on the device global memory. All names should be identical * to their host counterparts apart from the d_ prefix. * * @{ */ double *d_phi, *d_phi_old, *d_V, *d_potential, *d_potential_old, *d_sum, *d_square, *d_Q00, *d_Q01, *d_walls, *d_walls_laplace, *d_walls_dx, *d_walls_dy, *d_sum_cnt, *d_square_cnt, *d_Q00_cnt, *d_Q01_cnt, *d_area, *d_area_cnt, *d_c, *d_S00, *d_S01, *d_S_order, *d_S_angle, *d_theta, *d_alpha, *d_gam, *d_mu; vec *d_vel, *d_force_p, *d_force_c, *d_force_f, *d_com, *d_com_prev; stencil *d_neighbors, *d_neighbors_patch; coord *d_patch_min, *d_patch_max, *d_offset; cuDoubleComplex *d_com_x, *d_com_y, *d_com_x_table, *d_com_y_table; /** @} */ /** Random number generation * @{ */ /** Random states on the device */ curandState *d_rand_states; /** Initialization function */ void InitializeCuda(); /** Initialization function for random numbers */ void InitializeCUDARandomNumbers(); /** @} */ /** CUDA device memory managment * @{ */ /** In which direction do we copy data? */ enum class CopyMemory { HostToDevice, DeviceToHost }; /** Allocate or free memory? */ enum class ManageMemory { Allocate, Free }; /** Implementation for AllocDeviceMemory() and FreeDeviceMemory() */ void _manage_device_memory(ManageMemory); /** Implementation for PutToDevice() and GetFromDevice() */ void _copy_device_memory(CopyMemory); /** Copy data to the device global memory * * This function is called at the begining of the program just before the main * loop but after the system has been initialized. * */ void PutToDevice(); /** Copy data from the device global memory * * This function is called every time the results need to be dumped on the disk. * */ void GetFromDevice(); /** Allocate memory for all device arrays */ void AllocDeviceMemory(); /** Allocate memory for all device arrays */ void FreeDeviceMemory(); /** @} */ /** Runtime properties * @{ */ int n_total, n_blocks, n_threads; /** @} */ #endif // =========================================================================== // Run. Implemented in run.cpp /** Time step * * This is the time-stepping function and performs the main computation. * */ void Step(); /** Prepare before run */ void Pre(); /** Prints some stats before running */ void PreRunStats(); /** Prints some stats in between ninfo steps */ void RuntimeStats(); /** Performs punctual check at runtime */ void RuntimeChecks(); /** Post run function */ void Post(); /** Subfunction for update */ void UpdatePotAtNode(unsigned, unsigned); /** Subfunction for update */ void UpdatePhaseFieldAtNode(unsigned, unsigned, bool); /** Subfunction for update */ void UpdateForcesAtNode(unsigned, unsigned); /** Subfunction for update */ void UpdateStructureTensorAtNode(unsigned, unsigned); /** Subfunction for update */ void UpdateSumsAtNode(unsigned, unsigned); /** Subfunction for update */ void ReinitSumsAtNode(unsigned); /** Compute center of mass of a given phase field */ void ComputeCoM(unsigned); /** Update polarisation of a given field */ void UpdatePolarization(unsigned, bool); /** Update nematic tensor of a given field */ void UpdateNematic(unsigned, bool); /** Compute shape parameters * * This function effectively computes the second moment of area, which ca n be used to * fit the shape of a cell to an ellipse. * */ void ComputeShape(unsigned); /** Update the moving patch following each cell */ void UpdatePatch(unsigned); /** Update fields * * The boolean argument is used to differentiate between the predictor step * (true) and subsequent corrector steps. * */ void Update(bool, unsigned=0); // =========================================================================== // Serialization /** Serialization of parameters (in and out) */ template void SerializeParameters(Archive& ar) { ar & auto_name(gam) & auto_name(mu) & auto_name(lambda) & auto_name(nphases) & auto_name(init_config) & auto_name(kappa) & auto_name(xi) & auto_name(R) & auto_name(alpha) & auto_name(zetaS) & auto_name(zetaQ) & auto_name(omega) & auto_name(wall_thickness) & auto_name(wall_kappa) & auto_name(wall_omega) & auto_name(walls) & auto_name(patch_margin) & auto_name(relax_time) & auto_name(relax_nsubsteps) & auto_name(npc) & auto_name(seed) & auto_name(Knem) & auto_name(Kpol) & auto_name(Snem) & auto_name(Spol) & auto_name(Jnem) & auto_name(Jpol) & auto_name(Wnem) & auto_name(Dpol) & auto_name(Dnem) & auto_name(margin) & auto_name(patch_size) & auto_name(align_nematic_to) & auto_name(align_polarization_to); } /** Serialization of parameters (in and out) */ template void SerializeFrame(Archive& ar) { ar & auto_name(nphases) & auto_name(phi) & auto_name(offset) & auto_name(com) & auto_name(area) & auto_name(S00) & auto_name(S01) & auto_name(Q00) & auto_name(Q01) & auto_name(stress_xx) & auto_name(stress_xy) & auto_name(stress_yy) & auto_name(velocity) & auto_name(Fpol) & auto_name(Fnem) & auto_name(Fshape) & auto_name(Fpressure) & auto_name(theta_pol) & auto_name(theta_nem) & auto_name(patch_min) & auto_name(patch_max); } // =========================================================================== // Tools /** Gives domain coordinate corresponding to a domain index */ coord GetPosition(unsigned k) const { return { GetXPosition(k), GetYPosition(k) }; } /** Gives domain x-coordinate corresponding to a domain index */ unsigned GetXPosition(unsigned k) const { return k/Size[1]; } /** Gives domain y-coordinate corresponding to a domain index */ unsigned GetYPosition(unsigned k) const { return k%Size[1]; } /** Get domain index from domain coordinates */ unsigned GetIndex(const coord& p) const { return p[1] + Size[1]*p[0]; } /** Get patch index from domain coordinates */ unsigned GetPatchIndex(unsigned n, coord p) const { // get difference to the patch min p = (p + Size - patch_min[n])%Size; // correct for offset p = (p + patch_size - offset[n])%patch_size; // remap linearly return p[1] + patch_size[1]*p[0]; } /** Get patch index from domain index */ unsigned GetPatchIndex(unsigned n, unsigned k) const { return GetPatchIndex(n, GetPosition(k)); } /** Get domain index from patch index */ unsigned GetIndexFromPatch(unsigned n, unsigned q) const { // position on the patch const coord qpos = { q/patch_size[1], q%patch_size[1] }; // position on the domain const coord dpos = ( (qpos + offset[n])%patch_size + patch_min[n] )%Size; // return domain index return GetIndex(dpos); } }; #endif//MODEL_HPP_ ","Unknown" "Biophysics","rhomu/celadro","src/files.hpp",".hpp","537","25"," #ifndef FILES_HPP_ #define FILES_HPP_ /** Create directory * * All subdirectories are created as necessary. * */ void create_directory(const std::string& dir); /** Remove file or directory * * This is equivalent to 'rm -rf fname' * */ void remove_file(const std::string& fname); /** Compress file iname to oname.zip using zip * * The file is moved to the archive, i.e. iname does not exsit after this * function has returned. * */ void compress_file(const std::string& iname, const std::string& oname); #endif//FILES_HPP_ ","Unknown" "Biophysics","rhomu/celadro","src/configure.cpp",".cpp","15383","470","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #include ""header.hpp"" #include ""model.hpp"" #include ""derivatives.hpp"" using namespace std; void Model::AddCellAtNode(unsigned n, unsigned q, const coord& center) { const auto k = GetIndexFromPatch(n, q); const unsigned xk = GetXPosition(k); const unsigned yk = GetYPosition(k); // we create smaller cells that will then relax // this improves greatly the stability at the first steps const auto radius = max(R/2., 4.); // round shape (do not wrap if no PBC) if( (BC==0 and pow(wrap(diff(yk, center[1]), Size[1]), 2) + pow(wrap(diff(xk, center[0]), Size[0]), 2)<=ceil(radius*radius)) or (BC>=1 and pow(diff(yk, center[1]), 2) + pow(diff(xk, center[0]), 2)<=ceil(radius*radius)) ) { phi[n][q] = 1.; phi_old[n][q] = 1.; area[n] += 1.; square[k] += 1.; thirdp[k] += 1.; fourthp[k] += 1.; sum[k] += 1.; sumQ00[k] += Q00[n]; sumQ01[k] += Q01[n]; } else { phi[n][q] = 0.; phi_old[n][q] = 0.; } } void Model::AddCell(unsigned n, const coord& center) { // update patch coordinates patch_min[n] = (center+Size-patch_margin)%Size; patch_max[n] = (center+patch_margin-1u)%Size; // init polarisation and nematic theta_pol[n] = noise*Pi*(1-2*random_real()); polarization[n] = { Spol*cos(theta_pol[n]), Spol*sin(theta_pol[n]) }; theta_nem[n] = noise*Pi*(1-2*random_real()); Q00[n] = Snem*cos(2*theta_nem[n]); Q01[n] = Snem*sin(2*theta_nem[n]); // create the cells at the centers we just computed for(unsigned q=0; q(center); } void Model::Configure() { // number of nodes in the birth area unsigned Nbirth = (birth_bdries[1]-birth_bdries[0])* (birth_bdries[3]-birth_bdries[2]); // target radius for spacing between cells unsigned radius = sqrt(double(Nbirth/nphases)/Pi); // =========================================================================== // adding cells at random while trying to keep their center non overlapping if(init_config==""random"" and BC==0) { // list of all centers vector centers; for(unsigned n=0; n(birth_bdries[0] +random_real()*(birth_bdries[1]-birth_bdries[0])), static_cast(birth_bdries[2] +random_real()*(birth_bdries[3]-birth_bdries[2])) }; bool is_overlapping = false; for(const auto& c : centers) { if(pow(wrap(diff(center[0], c[0]), Size[0]), 2) + pow(wrap(diff(center[1], c[1]), Size[1]), 2) < 0.9*radius*radius) { is_overlapping = true; break; } } if(!is_overlapping) { centers.emplace_back(center); break; } } // add cell AddCell(n, centers.back()); } } // =========================================================================== // same but with walls: we need to be careful not to create cells on the wall else if(init_config==""random"" and BC>=1) { // list of all centers vector centers; for(unsigned n=0; n(birth_bdries[0] +random_real()*(birth_bdries[1]-birth_bdries[0])), static_cast(birth_bdries[2] +random_real()*(birth_bdries[3]-birth_bdries[2])) }; // detect walls // ... box only if(BC==1) if(center[0]<0.9*R or Size[0]-center[0]<0.9*R) continue; // ... box and channel if(BC==1 or BC==2) if(center[1]<0.9*R or Size[1]-center[1]<0.9*R) continue; // ... ellipse if(BC==3) { // compute distance from the elliptic wall // ... angle of the current point (from center of the patch) const auto theta = atan2(Size[1]/2.-center[1], Size[0]/2.-center[0]); // ... small helper function to compute radius auto rad = [](auto x, auto y) { return sqrt(x*x + y*y); }; // ... distance is the difference between wall and current point const auto d = rad(Size[0]/2.*cos(theta), Size[1]/2.*sin(theta)) -rad(Size[0]/2.-center[0], Size[1]/2.-center[1]); if(d<0.9*R) continue; } // ... cross if(BC==4) { if(fabs(center[0]-Size[0]/2.)+0.9*R>cross_ratio*.5*Size[0] and fabs(center[1] - Size[1]/2.)+0.9*R>cross_ratio*.5*Size[1]) continue; } // ... wound if(BC==5) { // wall boundary condition if(center[0]<0.9*R or Size[0]-center[0]<0.9*R) continue; if(center[1]<0.9*R or Size[1]-center[1]<0.9*R) continue; double xl = Size[0]*.5*(1.-wound_ratio); double xr = Size[0]*.5*(1.+wound_ratio); if(xl-center[0]<0.9*R and center[0]-xr<0.9*R) continue; } // ... two phase ellipse if(BC==6) { // compute distance from the elliptic wall // ... angle of the current point (from center of the patch) const auto theta = atan2(Size[1]/2.-center[1], Size[0]/2.-center[0]); // ... small helper function to compute radius auto rad = [](auto x, auto y) { return sqrt(x*x + y*y); }; // ... distance is the difference between wall and current point const auto d = rad(Size[0]/2.*cos(theta)*tumor_ratio, Size[1]/2.*sin(theta)*tumor_ratio) -rad(Size[0]/2.-center[0], Size[1]/2.-center[1]); if(fabs(d)<0.9*R) continue; } // ... wound on one side if(BC==7) { // wall boundary condition if(center[0]<0.9*R or Size[0]-center[0]<0.9*R) continue; if(center[1]<0.9*R or Size[1]-center[1]<0.9*R) continue; double xl = Size[0]*(1.-wound_ratio); if(xl-center[0]<0.9*R) continue; } // overlapp between cells bool is_overlapping = false; for(const auto& c : centers) { if(pow(wrap(diff(center[0], c[0]), Size[0]), 2) + pow(wrap(diff(center[1], c[1]), Size[1]), 2) < 0.9*radius*radius) { is_overlapping = true; break; } } if(!is_overlapping) { centers.emplace_back(center); break; } } // add cell AddCell(n, centers.back()); } } // =========================================================================== // cluster of close cells in the center else if(init_config==""cluster"") { const double theta = 2*Pi/nphases; for(unsigned n=0; n= xb and y >= yb) d = sqrt(pow(x-xb,2.)+pow(y-yb,2.)); else if(x >= xb) d = x-xb; else if(y >= yb) d = y-yb; if(x < xb and y < yb) walls[k] = 1.; else walls[k] = exp(-d/wall_thickness); if(x >= xb and y < yb) walls[k] += exp(-y/wall_thickness); if(x < xb and y >= yb) walls[k] += exp(-x/wall_thickness); } if(x >= Size[0]/2 && y < Size[1]/2){ // right bottom corner const double xb = Size[0]*b2; const double yb = Size[1]*b1; double d = 0.; if(x < xb and y >= yb) d = sqrt(pow(x-xb,2.)+pow(y-yb,2.)); else if(x < xb) d = xb-x; else if(y >= yb) d = y-yb; if(x >= xb && y < yb) walls[k] = 1.; else walls[k] = exp(-d/wall_thickness); if(x < xb and y < yb) walls[k] += exp(-y/wall_thickness); if(x >= xb and y >= yb) walls[k] += exp(-(Size[0]-1-x)/wall_thickness); } if(x < Size[0]/2 && y >= Size[1]/2){// left top corner const double xb = Size[0]*b1; const double yb = Size[1]*b2; double d = 0.; if(x >= xb and y < yb) d = sqrt(pow(x-xb,2.)+pow(y-yb,2.)); else if(x >= xb) d = x-xb; else if(y < yb) d = yb-y; if(x < xb && y >= yb) walls[k] = 1.; else walls[k] = exp(-d/wall_thickness); if(x >= xb and y >= yb) walls[k] += exp(-(Size[1]-1-y)/wall_thickness); if(x < xb and y < yb) walls[k] += exp(-x/wall_thickness); } if(x >= Size[0]/2 && y >= Size[1]/2){ // right top corner const double xb = Size[0]*b2; const double yb = Size[1]*b2; double d = 0.; if(x < xb and y < yb) d = sqrt(pow(x-xb,2.)+pow(y-yb,2.)); else if(x < xb) d = xb-x; else if(y < yb) d = yb-y; if(x >= xb && y >= yb) walls[k] = 1.; else walls[k] = exp(-d/wall_thickness); if(x >= xb and y < yb) walls[k] += exp(-(Size[0]-1-x)/wall_thickness); if(x < xb and y >= yb) walls[k] += exp(-(Size[1]-1-y)/wall_thickness); } } break; // wound case 5: for(unsigned k=0; k= xr) walls[k] += exp(-(x - xr)/wall_thickness); if(xl < x and x < xr) walls[k] = 1.; } break; // two phase ellipse case 6: for(unsigned k=0; k. */ #include ""header.hpp"" #include ""model.hpp"" #include ""files.hpp"" using namespace std; void Model::WriteFrame(unsigned t) { // construct output name const string oname = inline_str(output_dir, ""frame"", t, "".json""); // write { stringstream buffer; { oarchive ar(buffer, ""frame"", 1); // serialize SerializeFrame(ar); if(ar.bad_value()) throw error_msg(""nan found while writing file.""); } // dump to file std::ofstream ofs(oname.c_str(), ios::out); ofs << buffer.rdbuf(); } // compress if(compress) compress_file(oname, oname); if(compress_full) compress_file(oname, runname); } void Model::WriteParams() { // a name that makes sense const string oname = inline_str(output_dir, ""parameters.json""); // write { stringstream buffer; { // serialize oarchive ar(buffer, ""parameters"", 1); // ...program parameters... ar & auto_name(Size) & auto_name(BC) & auto_name(nsteps) & auto_name(nsubsteps) & auto_name(ninfo) & auto_name(nstart); // ...and model parameters SerializeParameters(ar); if(ar.bad_value()) throw error_msg(""nan found while writing file.""); } // dump to file std::ofstream ofs(oname.c_str(), ios::out); ofs << buffer.rdbuf(); } // compress if(compress) compress_file(oname, oname); if(compress_full) compress_file(oname, runname); } void Model::ClearOutput() { if(compress_full) { // file name of the output file const string fname = runname + "".zip""; { // try open it ifstream infile(fname); // does not exist we are fine if(not infile.good()) return; } if(not force_delete) { // ask char answ = 0; cout << "" remove output file '"" << fname << ""'? ""; cin >> answ; if(answ != 'y' and answ != 'Y') throw error_msg(""output file '"", fname, ""' already exist, please provide a different name.""); } // delete remove_file(fname); } else { // extension of single files string ext = compress ? "".json.zip"" : "".json""; // check that parameters.json does not exist in the output dir and if it // does ask for deletion (this is not completely fool proof, but ok...) { ifstream infile(output_dir + ""parameters"" + ext); if(not infile.good()) return; } if(not force_delete) { // ask char answ = 0; cout << "" remove output files in directory '"" << output_dir << ""'? ""; cin >> answ; if(answ != 'y' and answ != 'Y') throw error_msg(""output files already exist in directory '"", output_dir, ""'.""); } // delete all output files remove_file(output_dir); } } void Model::CreateOutputDir() { // if full compression is on: we need to create a random tmp directory if(compress_full) { // use hash of runname string plus salt hash hash_fn; unsigned dir_name = hash_fn(inline_str(runname, random_unsigned())); output_dir = inline_str(""/tmp/"", dir_name, ""/""); } // if full compression is off: just dump files where they belong else // note that runname can not be empty from options.cpp output_dir = runname + ( runname.back()=='/' ? """" : ""/"" ); // clear output if needed ClearOutput(); // create output dir if needed create_directory(output_dir); } ","C++" "Biophysics","rhomu/celadro","src/error_msg.hpp",".hpp","2192","76","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef ERROR_MSG_HPP_ #define ERROR_MSG_HPP_ /** Error messages made easy * * This class makes it easy to construct simple error messages. Usage: * * error_msg(A, B, C, ...) * * automatically converts arguments A, B, C, ... to string and catenate. The resulting message can be obtained with what(). */ template class inline_msg : std::exception { /** The stream to store the msg */ std::string msg; /** Convert to strig and catenate arguments */ template void add_args(std::ostream& stream, Head&& head) { stream << std::forward(head); } /** Convert to strig and catenate arguments */ template void add_args(std::ostream& stream, Head&& head, Tail&&... tail) { stream << std::forward(head); add_args(stream, std::forward(tail)...); } public: /** Convert to strig and catenate arguments */ template inline_msg(Args&&... args) { std::stringstream s; add_args(s, std::forward(args)...); msg = s.str(); } inline_msg(inline_msg& e) = default; inline_msg(inline_msg&& e) = default; /** Returns msg */ const char* what() const throw () { return msg.c_str(); } }; /** Dummy exception (doing nothing) */ class dummy_exception {}; /** Error message */ using error_msg = inline_msg; /** Warning message */ using warning_msg = inline_msg; #endif//ERROR_MSG_HPP_ ","Unknown" "Biophysics","rhomu/celadro","src/files.cpp",".cpp","1440","40","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #include ""header.hpp"" #include ""files.hpp"" using namespace std; void create_directory(const string& dir) { const int ret = system(inline_str(""mkdir -p "", dir).c_str()); if(ret) throw error_msg(""can not create output directory, mkdir returned "", ret, "".""); } void remove_file(const string& fname) { const int ret = system(inline_str(""rm -rf "", fname).c_str()); if(ret) throw error_msg(""rm returned non-zero value "", ret, "".""); } void compress_file(const string& iname, const string& oname) { const int ret = system(inline_str(""zip -jm "", oname, "".zip "", iname, "" > /dev/null 2>&1"").c_str()); if(ret!=0) throw error_msg(""zip non-zero return value "", ret, "".""); } ","C++" "Biophysics","rhomu/celadro","src/header.hpp",".hpp","1845","71","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef HEADER_HPP_ #define HEADER_HPP_ // defines project-wide header list to be precompiled // this allows us to reduce the compile time considerably #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include ""cuda.h"" #ifdef _CUDA_ENABLED #include #include #include #ifdef _CUDA #include ""vec_cuda.h"" #else #include ""vec.hpp"" #endif #endif #include ""error_msg.hpp"" #include ""threads.hpp"" #include ""tools.hpp"" // boost program_options #include namespace opt = boost::program_options; // ============================================================================= // Constants /** display width (change it directly here) */ constexpr unsigned width = 70; /** An infmaous constant */ constexpr double Pi = 3.14159265358979323846; #endif//HEADER_HPP_ ","Unknown" "Biophysics","rhomu/celadro","src/stencil_cuda.h",".h","1571","53","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef STENCIL_HPP_ #define STENCIL_HPP_ #include /** Indices of a given point and its direct neighbourhood * * A stencil is a list of 9 (in two dimensions) grid indices of a point and its * neighbourhood. The convention is the following: if s is a given stencil, then * s[0][0] is the grid coordinate of the central point, s[1][0] the coordinate * of the point to its right, s[-1][0] the point to its left, etc. * */ struct stencil { struct shifted_array { std::array data; unsigned& operator[](int i) { return data[i+1]; } const unsigned& operator[](int i) const { return data[i+1]; } }; std::array data; shifted_array& operator[](int i) { return data[i+1]; } const shifted_array& operator[](int i) const { return data[i+1]; } }; #endif//STENCIL_HPP_ ","Unknown" "Biophysics","rhomu/celadro","src/threads.hpp",".hpp","906","30","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ #ifndef THREADS_HPP_ #define THREADS_HPP_ #ifdef _OPENMP #define PRAGMA_OMP(x) _Pragma(#x) #else #define PRAGMA_OMP(cmd) {} #endif void SetThreads(); #endif//THREADS_HPP_ ","Unknown" "Biophysics","rhomu/celadro","src/serialization.hpp",".hpp","12789","432","/* * This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see . */ /** Small json serialization library. * * Minimal json library for arbitrary types. It goes together with the python * file archive.py that allows to import automatically the data dumped using * this library. * * Usage is similar to boost::serialization, but the API is minimal. The * implementation is also inspired from this library. The main choice is to * avoid RTI and use templates. This is more efficient, but comes with a lot * of difficulties because template functions can not be virtual in C++. Hence * we have to resort to dirty template tricks (and admit it you like dirty * tricks). This is a very good opportunity to write code that is: (i) overly * complicated and (ii) unmaintainable by any standard. * * Remark: We can not deduce names automatically because these are * implementation defined (even through ). This would mean that an * output file produced on a computer might not be usable on another, which * is uncool. * * TODO: * * Declare string types * * InputArchive * * Be careful, part of this code is serious C++. * * Romain Mueller, name dot surname at gmail dot com */ #ifndef SERIALIZATION_HPP_ #define SERIALIZATION_HPP_ // ============================================================================= // Tools /** Bad stream exception * * In rare cases the stream might smell funny before the archive destructor is * called. We throw an exception instead of creating a seg fault. * */ struct bad_stream : public std::exception { const char * what () const throw () { return ""can not use stream""; } }; /** Pairs a variable with its display name * * We need to provide names in json! We do this using std::pair. The name of a * variable can be anything but if you want the same name as in the code you * can use this macro. * */ #define auto_name(obj) std::pair {obj, #obj} // ============================================================================= // Type traits (using SFINAE) namespace detail { /** Check if type is iterable * * We use SFINAE to check at compile time if a type is iterable, i.e. if it * implements begin, end, !=, operator++ and dereferencement for iterators. * */ template auto is_iterable_impl(int) -> decltype ( // begin/end and operator != std::begin(std::declval()) != std::end(std::declval()), // operator ++ on begin iterator ++std::declval()))&>(), // operator* on begin iterator *std::begin(std::declval()), // value type std::declval(), std::true_type {} ); template std::false_type is_iterable_impl(...); /** Check if type has a serialize() function * * We use SFINAE to detect at compile time if a certain type implements a * serialize function. * */ template auto is_serializable_impl(int) -> decltype( std::declval().serialize(std::declval()), std::true_type {} ); template std::false_type is_serializable_impl(...); /** Wrapper to serialization * * This objects allows us to differentiate objects that implement a * serialize() function or not, as well as objects that are iterable. * */ template struct wrapper; } /** is_iterable::value is true if T is iterable, false otherwise */ template using is_iterable = decltype(detail::is_iterable_impl(0)); /** is_serializable::value is true if T declares serializable, false * otherwise */ template using is_serializable = decltype(detail::is_serializable_impl(0)); /** is_true_iterable: iterable and NOT string */ template struct is_true_iterable { const static bool value = is_iterable::value && !std::is_same::value; }; // ============================================================================= // Traits for fundamental types /** Type traits to differentiate iterable types */ template struct type_name_impl {}; /** Small type traits class * * We use this small struct to generate strings corresponding to types at * compile time, e.g. double -> ""double"", in a somewhat platform independent * way. If you get error involving this class this probably means that you need * to register a new type: add the corresponding REGISTER_TYPE_NAME or * REGISTER_TYPE_NAME_OTHER instruction in serialization.cpp or below your * class definition. * */ template struct type_name : type_name_impl::value> {}; /** Iterable types are all called 'array(...)' * * Iterable types must have T::value_type, as in the standard containers, to * declare what type they are storing. Remember that in C++ the types are * homogeneous within a container. * */ template struct type_name_impl { static std::string name() { return ""array(""+type_name::name()+"")""; } }; /** Register type X to have name Y */ #define REGISTER_TYPE_NAME_OTHER(X, Y) \ template<> struct type_name_impl \ { static std::string name() { return Y; } }; /** Register type X to have name ""X"" */ #define REGISTER_TYPE_NAME(X) REGISTER_TYPE_NAME_OTHER(X, #X) // We register the names of the different fundamental types REGISTER_TYPE_NAME(bool) REGISTER_TYPE_NAME(int) REGISTER_TYPE_NAME(unsigned) REGISTER_TYPE_NAME(short) REGISTER_TYPE_NAME(unsigned short) REGISTER_TYPE_NAME(long) REGISTER_TYPE_NAME(unsigned long) REGISTER_TYPE_NAME(long long) REGISTER_TYPE_NAME(unsigned long long) REGISTER_TYPE_NAME(float) REGISTER_TYPE_NAME(double) REGISTER_TYPE_NAME(long double) REGISTER_TYPE_NAME_OTHER(std::string, ""string"") REGISTER_TYPE_NAME_OTHER(char, ""string"") REGISTER_TYPE_NAME_OTHER(wchar_t, ""string"") REGISTER_TYPE_NAME_OTHER(char16_t, ""string"") REGISTER_TYPE_NAME_OTHER(char32_t, ""string"") REGISTER_TYPE_NAME_OTHER(const char*, ""string"") REGISTER_TYPE_NAME_OTHER(const unsigned char*, ""string"") REGISTER_TYPE_NAME_OTHER(const wchar_t*, ""string"") REGISTER_TYPE_NAME_OTHER(const char16_t*, ""string"") REGISTER_TYPE_NAME_OTHER(const char32_t*, ""string"") // ============================================================================= // Traits to obtain shape of iterables /** Type traits to differentiate iterable types */ template struct get_shape_impl {}; template std::vector get_shape(const T& iterable) { auto ret = get_shape_impl::value>::shape(iterable); std::reverse(ret.begin(), ret.end()); return ret; } template struct get_shape_impl { static std::vector shape(const T& iterable) { return {}; } }; template struct get_shape_impl { static std::vector shape(const T& iterable) { using U = typename std::decay::type; auto ret = get_shape_impl< U, is_true_iterable::value >::shape(*std::begin(iterable)); ret.push_back(iterable.size()); return ret; } }; // ============================================================================= // The archive types /** Output json archive */ class oarchive : public std::ostream { /** The output stream */ std::ostream& stream; /** Indentation level (we aren't monsters) */ unsigned level = 0; /** Add indentation level */ void indent(unsigned=1); /** Remove indentation level */ void unindent(unsigned=1); /** Used to avoid having commas everywhere */ bool first = true; /** Open new group { ... } */ void open_group(const std::string& = ""{""); /** Close current group */ void close_group(const std::string& = ""}""); /** Create a new line, taking care of the commas and indentation */ void new_line(); /** Write key ( ""key"" : element ) */ void add_key(const std::string&); /** Write element ( ""key"" : element ), while putting quotes for strings */ template void add_element(const T&); /** Write key/element pair */ template void add(const std::string& key, const T& element) { add_key(key); add_element(element); } /** Write iterable element -> [ ... ] */ template void add_iterable(const T&); /** Bad value flag (nans) */ bool f_bad_value = false; public: /** Contructor * * Arguments are the output stream, the id, and version number. * */ oarchive(std::ostream&, std::string, unsigned=0); /** Write final characters to stream and destruct */ ~oarchive(); /** The archive output operator */ template oarchive& operator&(const std::pair&); template friend struct detail::wrapper; template void serialize(const T&); /** Return true if a nan was found while writting */ bool bad_value() const { return f_bad_value; } }; /** For non-string types: put into stream using stringstream directly */ template void oarchive::add_element(const T& value) { // detect nans if(value!=value) f_bad_value = true; // write std::stringstream ss; ss << value; stream << ss.str(); } /** Template specialization for const char*: add enclsoing braces */ template<> void oarchive::add_element(const char* const&); /** Template specialization for strings: add enclosing braces */ template<> void oarchive::add_element(const std::string&); template void oarchive::add_iterable(const T& value) { stream << ""[ ""; bool f = true; for(const auto& i : value) { // commas if(f) f=false; else stream << "", ""; // add elements serialize(i); } stream << "" ]""; } /** Input archive * * Not implemented. */ struct iarchive { /** The archive input operator */ template iarchive& operator&(const std::pair&) { return *this; } }; // ============================================================================= // Template specializations for traits namespace detail { /** If object has a serialize function */ template struct wrapper { wrapper(Archive& ar, const T& obj) { ar.open_group(); // this cast is fine because we are only writting const_cast(obj).serialize(ar); ar.close_group(); } }; /** If the object has no serialize function (non-iterable) */ template struct wrapper { wrapper(Archive& ar, const T& obj) { ar.add_element(obj); } }; /** If the object has no serialize function (iterable) */ template struct wrapper { wrapper(Archive& ar, const T& obj) { ar.add_iterable(obj); } }; } // ============================================================================= // Here is where things happen /** Most of the magic is happening here * * This function is merely a shortcut for calling the wrapper. * */ template void oarchive::serialize(const T& t) { detail::wrapper < oarchive, T, is_serializable::value, is_true_iterable::value > (*this, t); } template oarchive& oarchive::operator&(const std::pair& t) { // open a new group with variable name add_key(t.second); open_group(); // write the type add_key(""type""); add_element(type_name::name()); // in the case it is iterable, print shape /*if(is_true_iterable::value) { add_key(""shape""); serialize(get_shape(t.first)); }*/ // write value add_key(""value""); // serialize the object serialize(t.first); // close the group close_group(); // bye return *this; } #endif//SERIALIZATION_HPP_ ","Unknown" "Biophysics","rhomu/celadro","plot/archive.py",".py","2109","61","# This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see . import numpy as np import archive_base class archive(archive_base.archive): """"""Simply reshape 2d fields after importing"""""" def __init__(self, path): super(archive, self).__init__(path) self.parameters[""walls""] = np.reshape(self.parameters[""walls""], self.Size) self.__dict__.update(self.parameters) def read_frame(self, frame): frame = super(archive, self).read_frame(frame) # array sizes lx, ly = self.Size px, py = self.patch_size phi = [] for i in range(len(frame.phi)): p = np.reshape(frame.phi[i], (px, py)) # compensate for offset p = np.roll(p, frame.offset[i][0], axis=0) p = np.roll(p, frame.offset[i][1], axis=1) # extend to full size p = np.concatenate((p, np.zeros((px, ly - py))), axis=1) p = np.concatenate((p, np.zeros((lx - px, ly))), axis=0) # put in right postition p = np.roll(p, frame.patch_min[i][0], axis=0) p = np.roll(p, frame.patch_min[i][1], axis=1) # save phi.append(p) frame.phi = phi if hasattr(frame, ""stress_xx""): frame.stress_xx.shape = (lx, ly) frame.stress_xy.shape = (lx, ly) frame.stress_yy.shape = (lx, ly) return frame def loadarchive(path): return archive(path) ","Python" "Biophysics","rhomu/celadro","plot/__init__.py",".py","772","19","# This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see . from plot import * from animation import * from archive import * ","Python" "Biophysics","rhomu/celadro","plot/animation.py",".py","1876","64","# This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see . import numpy as np import matplotlib.pyplot as plt import matplotlib.animation as ani ###################################################################### # animation def animate(oa, fn, rng=[], inter=200, show=True): """""" Show a frame-by-frame animation. Args: oa -- the output archive fn -- the plot function (argument: frame, plot engine) rng -- range of the frames to be ploted interval -- time between frames (ms) """""" # set range if len(rng) == 0: rng = [1, oa._nframes + 1] # create the figure fig = plt.figure() # the local animation function def animate_fn(i): # we want a fresh figure everytime fig.clf() # load the frame frame = oa.read_frame(i) # call the global function fn(frame, fig) anim = ani.FuncAnimation( fig, animate_fn, frames=np.arange(rng[0], rng[1]), interval=inter, blit=False ) if show: return plt.show() else: return anim def save(an, fname, fps, tt=""ffmpeg"", bitrate=-1): writer = ani.writers[tt](fps=fps, bitrate=bitrate) an.save(fname, writer=writer) ","Python" "Biophysics","rhomu/celadro","plot/plot.py",".py","24550","806","# This file is part of CELADRO, Copyright (C) 2016-19, Romain Mueller # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see . import numpy as np import matplotlib.pyplot as plt from math import sqrt, pi, atan2, cos, sin from matplotlib.colors import LinearSegmentedColormap from scipy import ndimage from itertools import product def _update_dict(d, k, v): """""" Update dictionary with k:v pair if k is not in d. Args: d: The dictionary to update. k, v: The key/value pair. """""" if k not in d: d[k] = v def _get_field(phases, vals, size=1, mode=""wrap""): """""" Compute the coarse grained field from a collection of phase-fields and associated values: ret[i] = sum_j phases[j]*values[i, j]. Args: phases: List of phase-fields. vals: List of lists of size (None, len(phases)) of values to be associated with each phase-field. size: Coarse-graining size. mode: How to treat the boundaries, see scipy.ndimage.filters.uniform_filter. Returns: A list of fields, each corresponding to the individual values. """""" ret = [] for vlist in vals: assert len(vlist) == len(phases) field = np.zeros(phases[0].shape) for n in range(len(phases)): field += vlist[n] * phases[n] field = ndimage.filters.uniform_filter(field, size=size, mode=mode) ret.append(field) return ret def get_velocity_field(phases, vel, size=1, mode=""wrap""): """""" Compute coarse-grained nematic field. Args: phases: List of phase fields. vel: List of 2d velocities associated with each phase field. size: Coarse-graining size. mode: How to treat the boundaries, see scipy.ndimage.filters.uniform_filter. """""" v0 = [v[0] for v in vel] v1 = [v[1] for v in vel] return _get_field(phases, [v0, v1], size, mode) def get_nematic_field(phases, qxx, qxy, size=1, mode=""wrap""): """""" Compute coarse-grained nematic field. Args: phases: List of phase fields. qxx, qxy: Components of the nematic field of the individual phase fields. size: Coarse-graining size. mode: How to treat the boundaries, see scipy.ndimage.filters.uniform_filter. """""" return _get_field(phases, [qxx, qxy], size, mode) def get_vorticity_field(ux, uy, pbc=True): """""" Compute vorticity field from velocity field Args: ux, uy: the individual components of the velocity field. pbc: How to treat boundaries, set to true if using pbc. Returns: Vorticity field. """""" if pbc: dxuy = np.gradient(np.pad(uy, 2, mode=""wrap""), axis=0)[2:-2, 2:-2] dyux = np.gradient(np.pad(ux, 2, mode=""wrap""), axis=1)[2:-2, 2:-2] else: dxuy = np.gradient(uy, axis=0) dyux = np.gradient(ux, axis=1) return dxuy - dyux def get_gradient_field(ux, uy, pbc=True): """""" Compute gradient field from velocity field Args: ux, uy: the individual components of the velocity field. pbc: How to treat boundaries, set to true if using pbc. Returns: Gradient field. """""" if pbc: dxux = np.gradient(np.pad(ux, 2, mode=""wrap""), axis=0)[2:-2, 2:-2] dyuy = np.gradient(np.pad(uy, 2, mode=""wrap""), axis=1)[2:-2, 2:-2] else: dxux = np.gradient(ux, axis=0) dyuy = np.gradient(uy, axis=1) return dxux + dyuy def get_corr(u): """""" Compute the cross-correlation (as a function of distance) of a real two- dimensional scalar field. Arguments: u: The scalar field. Returns: The cross-correlation of u as an array. """""" # get 2d correlations c = np.fft.rfft2(u) c = np.fft.irfft2(np.multiply(c, np.conj(c))) # go to polar coords s = int(sqrt(c.size) / 2) r = np.zeros(s) n = np.zeros(s) k = 0 for (i, j), v in np.ndenumerate(c): k = int(sqrt(i ** 2 + j ** 2)) if k >= s: continue r[k] += v n[k] += 1 r = np.divide(r, n) r /= r[0] return r def get_corr2(ux, uy): """""" Compute the correlation (as a function of distance) of two real two- dimensional scalar fields. Arguments: ux, uy: The scalar fields. Returns: The correlation of ux and uy as an array. """""" # get 2d correlations cx = np.fft.rfft2(ux) cx = np.fft.irfft2(np.multiply(cx, np.conj(cx))) cy = np.fft.rfft2(uy) cy = np.fft.irfft2(np.multiply(cy, np.conj(cy))) c = cx + cy # go to polar coords s = int(sqrt(c.size) / 2) r = np.zeros(s) n = np.zeros(s) k = 0 for (i, j), v in np.ndenumerate(c): k = int(sqrt(i ** 2 + j ** 2)) if k >= s: continue r[k] += v n[k] += 1 r = np.divide(r, n) r /= r[0] return r def charge_array(Q00, Q01): """""" Compute the charge array associated with a Q-tensor field. The defects then show up as small regions of non-zero charge (typically 2x2). Args: Q00, Q01: The components of the nematic field. Returns: Field of the same shape as Q00 and Q01. """""" # compute angle def wang(a, b): """"""Infamous chinese function"""""" ang = atan2(abs(a[0] * b[1] - a[1] * b[0]), a[0] * b[0] + a[1] * b[1]) if ang > pi / 2.0: b = [-i for i in b] m = a[0] * b[1] - a[1] * b[0] return -np.sign(m) * atan2(abs(m), a[0] * b[0] + a[1] * b[1]) # get shape and init charge array (LX, LY) = Q00.shape w = np.zeros((LX, LY)) # we use the director field instead of Q S = np.vectorize(sqrt)(Q00 ** 2 + Q01 ** 2) nx = np.vectorize(sqrt)((1 + Q00 / S) / 2) ny = np.sign(Q01) * np.vectorize(sqrt)((1 - Q00 / S) / 2) # This mysterious part was stolen from Amin's code. for i in range(LX): for j in range(LY): ax1 = [nx[(i + 1) % LX, j], ny[(i + 1) % LX, j]] ax2 = [nx[(i - 1 + LX) % LX, j], ny[(i - 1 + LX) % LX, j]] ax3 = [nx[i, (j - 1 + LY) % LY], ny[i, (j - 1 + LY) % LY]] ax4 = [nx[i, (j + 1) % LY], ny[i, (j + 1) % LY]] ax5 = [ nx[(i + 1) % LX, (j - 1 + LY) % LY], ny[(i + 1) % LX, (j - 1 + LY) % LY], ] ax6 = [ nx[(i - 1 + LX) % LX, (j - 1 + LY) % LY], ny[(i - 1 + LX) % LX, (j - 1 + LY) % LY], ] ax7 = [nx[(i + 1) % LX, (j + 1) % LY], ny[(i + 1) % LX, (j + 1) % LY]] ax8 = [ nx[(i - 1 + LX) % LX, (j + 1) % LY], ny[(i - 1 + LX) % LX, (j + 1) % LY], ] w[i, j] = wang(ax1, ax5) w[i, j] += wang(ax5, ax3) w[i, j] += wang(ax3, ax6) w[i, j] += wang(ax6, ax2) w[i, j] += wang(ax2, ax8) w[i, j] += wang(ax8, ax4) w[i, j] += wang(ax4, ax7) w[i, j] += wang(ax7, ax1) w[i, j] /= 2.0 * pi return w def get_defects(w, Qxx, Qxy): """""" Returns list of defects from charge array. Args: w: Charge array. Returns: List of the form [ [ (x, y), charge] ]. """""" # defects show up as 2x2 regions in the charge array w and must be # collapsed to a single point by taking the average position of # neighbouring points with the same charge (by breath first search). # bfs recursive function def collapse(i, j, s, x=0, y=0, n=0): if s * w[i, j] > 0.4: x += i + 1.5 y += j + 1.5 n += 1 w[i, j] = 0 collapse((i + 1) % LX, j, s, x, y, n) collapse((i - 1 + LX) % LX, j, s, x, y, n) collapse(i, (j + 1) % LY, s, x, y, n) collapse(i, (j - 1 + LY) % LY, s, x, y, n) return x / n, y / n (LX, LY) = w.shape d = [] for i in range(LX): for j in range(LY): if abs(w[i, j]) > 0.4: # charge sign s = np.sign(w[i, j]) # bfs x, y = collapse(i, j, s) # compute angle, see doi:10.1039/c6sm01146b num = 0 den = 0 for (dx, dy) in [(0, 0), (0, 1), (1, 1), (1, 0)]: # coordinates of nodes around the defect kk = (int(x) + LX + dx) % LX ll = (int(y) + LY + dy) % LY # derivative at these points dxQxx = 0.5 * (Qxx[(kk + 1) % LX, ll] - Qxx[(kk - 1 + LX) % LX, ll]) dxQxy = 0.5 * (Qxy[(kk + 1) % LX, ll] - Qxy[(kk - 1 + LX) % LX, ll]) dyQxx = 0.5 * (Qxx[kk, (ll + 1) % LY] - Qxx[kk, (ll - 1 + LY) % LY]) dyQxy = 0.5 * (Qxy[kk, (ll + 1) % LY] - Qxy[kk, (ll - 1 + LY) % LY]) # accumulate numerator and denominator num += s * dxQxy - dyQxx den += dxQxx + s * dyQxy psi = s / (2.0 - s) * atan2(num, den) # add defect to list d.append({""pos"": np.array([x, y]), ""charge"": 0.5 * s, ""angle"": psi}) return d def defects(Q00, Q01, engine=plt, arrow_len=0): """""" Plot defects of the nematic field Q. Args: Q00, Q01: Components of the nematic field. engine: Plotting engine or axis. arrow_len: If non-zero plot speed of defects as well. """""" w = charge_array(Q00, Q01) defects = get_defects(w, Q00, Q01) for d in defects: if d[""charge""] == 0.5: engine.plot(d[""pos""][0], d[""pos""][1], ""go"") # plot direction of pos defects if not arrow_len == 0: engine.arrow( d[""pos""][0], d[""pos""][1], -arrow_len * cos(d[""angle""]), -arrow_len * sin(d[""angle""]), color=""r"", head_width=3, head_length=3, ) else: engine.plot(d[""pos""][0], d[""pos""][1], ""b^"") def cell(frame, i, engine=plt, **kwargs): """""" Plot a single phase field as a contour. Args: frame: Frame to plot, from archive module. i: Index of the cell to plot. engine: Plotting engine or axis. color: Color to use for the contour. **kwargs: Keyword arguments passed to contour(). """""" p = frame.phi[i] _update_dict(kwargs, ""colors"", ""k"") _update_dict(kwargs, ""levels"", [0.5]) engine.contour( np.arange(0, frame.parameters[""Size""][0]), np.arange(0, frame.parameters[""Size""][1]), p.T, **kwargs ) def cells(frame, engine=plt, colors=""k""): """""" Plot all cells as contours. Args: frame: Frame to plot, from archive module. engine: Plotting engine or axis. colors: Colors to use for the contour. Can also be a list of colors, one for each cell. """""" if not isinstance(colors, list): colors = len(frame.phi) * [colors] for i in range(len(frame.phi)): cell(frame, i, engine, colors=colors[i]) def interfaces(frame, engine=plt): """""" Plot the overlap between cells as heatmap using beautiful shades of gray for an absolutely photorealistic effect that will impress all your friends. Args: frame: Frame to plot, from archive module. engine: Plotting engine or axis. """""" totphi = np.zeros(frame.parameters[""Size""]) for i in range(len(frame.phi)): totphi += frame.phi[i] * frame.parameters[""walls""] for j in range(i + 1, len(frame.phi)): totphi += frame.phi[i] * frame.phi[j] cmap = LinearSegmentedColormap.from_list(""mycmap"", [""grey"", ""white""]) engine.imshow(totphi.T, interpolation=""lanczos"", cmap=cmap, origin=""lower"") def interfaces2(frame, engine=plt): """""" Plot the overlap between cells as heatmap in a different but also beatiful way. Args: frame: Frame to plot, from archive module. engine: Plotting engine or axis. """""" totphi = [np.zeros(frame.parameters[""Size""]), np.zeros(frame.parameters[""Size""])] for i in range(len(frame.phi)): k = 0 if i < 64 else 1 totphi[k] += frame.phi[i] * frame.parameters[""walls""] for j in range(i + 1, len(frame.phi)): totphi[k] += frame.phi[i] * frame.phi[j] cmap0 = LinearSegmentedColormap.from_list(""mycmap"", [""grey"", ""white""]) cmap1 = LinearSegmentedColormap.from_list(""mycmap"", [""blue"", ""white""]) engine.imshow(totphi[0].T, interpolation=""lanczos"", cmap=cmap0, origin=""lower"") engine.imshow(totphi[1].T, interpolation=""lanczos"", cmap=cmap1, origin=""lower"") def solidarea(frame, engine=plt): """""" Plot all phase fields with solid colours corresponding to individual areas. Args: frame: Frame to plot, from archive module. engine: Plotting engine or axis. """""" for i in range(len(frame.phi)): color = str(min(1, frame.area[i] / (pi * frame.parameters[""R""] ** 2))) engine.contourf( np.arange(0, frame.parameters[""Size""][0]), np.arange(0, frame.parameters[""Size""][1]), frame.phi[i].T, levels=[0.5, 10.0], colors=color, ) def com(frame, engine=plt): """""" Plot the center-of-mass of each cell as a red dot. Not really photorealistic. Args: frame: Frame to plot, from archive module. engine: Plotting engine or axis. """""" for c in frame.com: engine.plot(c[0], c[1], ""ro"") def shape(frame, engine=plt, **kwargs): """""" Print shape tensor of each cell as the director of a nematic tensor. Args: frame: Frame to plot, from archive module. engine: Plotting engine or axis. **kwargs: Keyword arguments passed to the arrow function. """""" _update_dict(kwargs, ""color"", ""k"") for i in range(frame.nphases): Q00 = frame.S00[i] Q01 = frame.S01[i] S = sqrt(Q00 ** 2 + Q01 ** 2) w = atan2(Q01, Q00) / 2 nx = cos(w) ny = sin(w) c = frame.com[i] a = S engine.arrow(c[0], c[1], a * nx, a * ny, **kwargs) engine.arrow(c[0], c[1], -a * nx, -a * ny, **kwargs) def director(Qxx, Qxy, avg=1, scale=False, engine=plt, **kwargs): """""" Plot director field associated with a given nematic field. Args: Qxx, Qxy: Components of the nematic field. avg: Coarse-graining size. scale: Scale factor that controls the size of the director. engine: Plotting engine or axis. **kwargs: Keyword arguments passed to the plot function. """""" # obtain S, nx, and ny S = np.vectorize(sqrt)(Qxy ** 2 + Qxx ** 2) nx = np.vectorize(sqrt)((1 + Qxx / S) / 2) ny = np.sign(Qxy) * np.vectorize(sqrt)((1 - Qxx / S) / 2) # coarse grain S = ndimage.generic_filter(S, np.mean, size=avg) nx = ndimage.generic_filter(nx, np.mean, size=avg) ny = ndimage.generic_filter(ny, np.mean, size=avg) (LX, LY) = S.shape # construct nematic lines x = [] y = [] for i, j in product(np.arange(LX, step=avg), np.arange(LY, step=avg)): f = avg * (S[i, j] if scale else 1.0) x.append(i + 0.5 - f * nx[i, j] / 2.0) x.append(i + 0.5 + f * nx[i, j] / 2.0) x.append(None) y.append(j + 0.5 - f * ny[i, j] / 2.0) y.append(j + 0.5 + f * ny[i, j] / 2.0) y.append(None) _update_dict(kwargs, ""linestyle"", ""-"") _update_dict(kwargs, ""linewidth"", 1) engine.plot(x, y, **kwargs) def nematic_field( frame, size=1, avg=1, show_def=False, arrow_len=0, engine=plt, **kwargs ): """""" Plot nematic field associated with the internal degree of freedom Args: frame: Frame to plot, from archive module. size: Coarse-graining size. avg: Average size (reduces the number of points plotted) show_def: If true, show defects. arrow_len: If non-zero, prints defect speed. engine: Plotting engine or axis. **kwargs: Keyword arguments passed to the director function. """""" # get field mode = ""wrap"" if frame.parameters[""BC""] == 0 else ""constant"" (Qxx, Qxy) = get_nematic_field( frame.phi, frame.Q00, frame.Q01, size=size, mode=mode ) Qxx *= 1.0 - frame.parameters[""walls""] Qxy *= 1.0 - frame.parameters[""walls""] # plot director(Qxx, Qxy, avg=avg, engine=engine, **kwargs) # defects if show_def: defects(Qxx, Qxy, engine=engine, arrow_len=arrow_len) def shape_field( frame, size=1, avg=1, show_def=False, arrow_len=0, engine=plt, **kwargs ): """""" Plot nematic field associated with the shape tensor of each cell. Args: frame: Frame to plot, from archive module. size: Coarse-graining size. avg: Average size (reduces the number of points plotted) show_def: If true, show defects. arrow_len: If non-zero, prints defect speed. engine: Plotting engine or axis. **kwargs: Keyword arguments passed to the director function. """""" # get field mode = ""wrap"" if frame.parameters[""BC""] == 0 else ""constant"" (Qxx, Qxy) = get_nematic_field( frame.phi, frame.S00, frame.S01, size=size, mode=mode ) Qxx *= 1.0 - frame.parameters[""walls""] Qxy *= 1.0 - frame.parameters[""walls""] # defects if show_def: defects(Qxx, Qxy, engine=engine, arrow_len=arrow_len) # plot director(Qxx, Qxy, avg=avg, engine=engine, **kwargs) def velocity_field(frame, size=15, engine=plt, magn=True, cbar=True, avg=1): """""" Plot nematic field associated with the shape tensor of each cell. Args: frame: Frame to plot, from archive module. size: Coarse-graining size. engine: Plotting engine or axis. magn: Plot velocity magnitude as a heatmap? cbar: Show color bar? avg: Size of the averaging (drops points) """""" mode = ""wrap"" if frame.parameters[""BC""] == 0 else ""constant"" vx, vy = get_velocity_field(frame.phi, frame.velocity, size, mode=mode) vx *= 1.0 - frame.parameters[""walls""] vy *= 1.0 - frame.parameters[""walls""] if magn: m = np.sqrt(vx ** 2 + vy ** 2) cax = engine.imshow(m.T, interpolation=""lanczos"", cmap=""plasma"", origin=""lower"") if cbar: plt.colorbar(cax) vx = vx.reshape((vx.shape[0] // avg, avg, vx.shape[1] // avg, avg)) vx = np.mean(vx, axis=(1, 3)) vy = vy.reshape((vy.shape[0] // avg, avg, vy.shape[1] // avg, avg)) vy = np.mean(vy, axis=(1, 3)) cax = engine.quiver( np.arange(0, frame.parameters[""Size""][0], step=avg), np.arange(0, frame.parameters[""Size""][1], step=avg), vx.T, vy.T, pivot=""tail"", units=""dots"", scale_units=""dots"", ) def vorticity_field(frame, size=15, engine=plt, cbar=True): """""" Plot nematic field associated with the shape tensor of each cell. Args: frame: Frame to plot, from archive module. size: Coarse-graining size. engine: Plotting engine or axis. cbar: Show color bar? """""" vx, vy = get_velocity_field(frame.phi, frame.velocity, size) w = get_vorticity_field(vx, vy) cax = engine.imshow(w.T, interpolation=""lanczos"", cmap=""viridis"", origin=""lower"") if cbar: plt.colorbar(cax) def _force(frame, i, v, engine=plt, **kwargs): """""" Helper function to plot forces. """""" c = frame.com[i] engine.arrow(c[0], c[1], v[0], v[1], **kwargs) def velocity(frame, engine=plt, color=""r""): """""" Plot total velocity of each cell. Args: frame: Frame to plot, from archive module. engine: Plotting engine or axis. color: Color of the arrow. """""" scale = frame.parameters[""ninfo""] * frame.parameters[""nsubsteps""] for i in range(frame.nphases): _force(frame, i, scale * frame.velocity[i], engine=engine, color=color) def pressure_force(frame, engine=plt, color=""b""): """""" Plot pressure force of each cell. Args: frame: Frame to plot, from archive module. engine: Plotting engine or axis. color: Color of the arrow. """""" scale = frame.parameters[""ninfo""] * frame.parameters[""nsubsteps""] for i in range(frame.nphases): _force(frame, i, scale * frame.Fpressure[i], engine=engine, color=color) def nematic(frame, engine=plt): """""" Print director of each cell as a line at their center. Args: frame: Frame to plot, from archive module. engine: Plotting engine or axis. """""" for i in range(frame.nphases): Q00 = frame.Q00[i] Q01 = frame.Q01[i] S = sqrt(Q00 ** 2 + Q01 ** 2) nx = sqrt((1 + Q00 / S) / 2) ny = np.sign(Q01) * sqrt((1 - Q00 / S) / 2) c = frame.com[i] a = frame.parameters[""R""] / 2.5 * S engine.arrow(c[0], c[1], a * nx, a * ny, color=""k"") engine.arrow(c[0], c[1], -a * nx, -a * ny, color=""k"") def phase(frame, n, engine=plt, cbar=False): """""" Plot single phase as a density plot. Args: frame: Frame to plot, from archive module. n: Index of the cell to plot. engine: Plotting engine or axis. cbar: Display cbar? """""" cax = engine.imshow( frame.phi[n].T, interpolation=""lanczos"", cmap=""Greys"", origin=""lower"" ) if cbar: plt.colorbar(cax) def walls(frame, engine=plt, cbar=False): """""" Plot walls. Args: frame: Frame to plot, from archive module. engine: Plotting engine or axis. cbar: Display cbar? """""" cax = engine.imshow( frame.parameters[""walls""].T, cmap=""Greys"", origin=""lower"", clim=(0.0, 1.0) ) if cbar: plt.colorbar(cax) def patch(frame, n, engine=plt): """"""Plot the restricted patch of a single cell Args: frame: Frame to plot, from archive module. engine: Plotting engine or axis. """""" def plot(m, M): engine.fill( [m[0], M[0], M[0], m[0], m[0], None], [m[1], m[1], M[1], M[1], m[1], None], color=""b"", alpha=0.04, ) LX, LY = frame.parameters[""Size""] m = frame.patch_min[n] M = frame.patch_max[n] if m[0] == M[0]: m[0] += 1e-1 M[0] -= 1e-1 if m[1] == M[1]: m[1] += 1e-1 M[1] -= 1e-1 if m[0] > M[0] and m[1] > M[1]: plot(m, [LX, LY]) plot([0, 0], M) plot([m[0], 0], [LX, M[1]]) plot([0, m[1]], [M[0], LY]) elif m[0] > M[0]: plot(m, [LX, M[1]]) plot([0, m[1]], M) elif m[1] > M[1]: plot(m, [M[0], LY]) plot([m[0], 0], M) else: plot(m, M) def patches(frame, engine=plt): """""" Plot the subdomain patches of each cell. Args: frame: Frame to plot, from archive module. engine: Plotting engine or axis. """""" for n in range(frame.nphases): patch(frame, n, engine) def masks(frame, engine=plt): """""" Plot division/death masks. Args: frame: Frame to plot, from archive module. engine: Plotting engine or axis. """""" m1 = np.array([1 if i else 0 for i in frame.division_mask]) m2 = np.array([1 if i else 0 for i in frame.death_mask]) engine.contour( np.arange(0, frame.parameters[""LX""]), np.arange(0, frame.parameters[""LY""]), m1.reshape(frame.parameters[""Size""]).T, levels=[0.5], colors=[""b""], ) engine.contour( np.arange(0, frame.parameters[""LX""]), np.arange(0, frame.parameters[""LY""]), m2.reshape(frame.parameters[""Size""]).T, levels=[0.5], colors=[""r""], ) ","Python" "Biophysics","rhomu/celadro","plot/archive_base/archive.py",".py","4858","145","# This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see . import os from zipfile import ZipFile import json import numpy as np class archive: """""" Import archive. Automatically import the parameters and allows to extract the individual frame files as well. """""" def __init__(self, path): """"""Reads parameters from archive."""""" # get extension and file name self._path = path self._name, ext = os.path.splitext(path) self._ext = "".json"" # check if we use a compressed archive or a directory if ext == """": self._compress_full = False elif ext == "".zip"": self._compress_full = True else: raise ValueError(""Archive type "" + path + "" not recognized"") # check for single file compression if os.path.isfile(os.path.join(self._path, ""parameters.json.zip"")): self._compress = True self._ext = "".json.zip"" else: self._compress = False # load the parameters as a dictionary dat = self.extract_and_read(""parameters"") self.parameters = { entry: self.get_value(dat[entry][""value""], dat[entry][""type""]) for entry in dat } # add the variables to the object (i luv python) self.__dict__.update(self.parameters) # total number of frames self._nframes = int((self.nsteps - self.nstart) / self.ninfo) def get_value(self, v, t): """"""Convert string to value with correct type handling."""""" if v == ""nan"" or v == ""-nan"": raise ValueError(""Nan found while converting to "" + t) if t == ""double"" or t == ""float"": return float(v) elif t == ""int"" or t == ""unsigned"": return int(v) elif t == ""long"" or t == ""unsigned long"": return int(v) elif t == ""bool"": return bool(v) elif t == ""string"": # quotes are already erased for string types return v elif t[:5] == ""array"": return np.array([self.get_value(i, t[6:-1]) for i in v]) else: raise ValueError(""Unrecognized type "" + t) def extract_and_read(self, fname): """"""Extract json file from archive."""""" # extract if self._compress_full: with ZipFile(self._path, ""r"") as f: data = f.read(fname + self._ext) return json.loads(data.decode(""utf-8"", ""strict""))[""data""] elif self._compress: with ZipFile(os.path.join(self._path, fname + self._ext)) as f: data = f.read(fname + "".json"") return json.loads(data.decode(""utf-8"", ""strict""))[""data""] else: # read content of file output = open(os.path.join(self._path, fname + self._ext)) # load json return json.load(output)[""data""] def read_frame(self, frame): """"""Read state file from archive. Parameters: frame -- the frame number to be read (0,1,2...) """""" if frame > self._nframes: raise ValueError(""Frame does not exist."") # get the json dat = self.extract_and_read(""frame"" + str(self.nstart + frame * self.ninfo)) # convert to dict dat = { entry: self.get_value(dat[entry][""value""], dat[entry][""type""]) for entry in dat } # return a dummy class that holds the data class frame_holder: """""" Dummy frame holder. Automatically define all the variables defined in the corresponding json file. """""" def __init__(self, parameters): self.parameters = parameters # create holder and forward parameters frame = frame_holder(self.parameters) frame.__dict__.update(dat) return frame def __getitem__(self, frame): return self.read_frame(frame) def read_frames(self): """"""Generates all frames successively"""""" for n in range(self._nframes + 1): yield self.read_frame(n) def loadarchive(path): return archive(path) ","Python" "Biophysics","rhomu/celadro","plot/archive_base/__init__.py",".py","783","19","# This file is part of CELADRO, Copyright (C) 2016-17, Romain Mueller # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see . from .archive import archive, loadarchive __all__ = [archive, loadarchive] ","Python" "Biophysics","rhomu/celadro","examples/make_all_movies.sh",".sh","301","14","# # Small script to run all examples and produce movies # CELADRO=../build/celadro THREADS=4 set -e # stop on any error for runcard in $(find */*.dat); do directory=${runcard%/*} $CELADRO $runcard -fco $directory/output -t$THREADS python3 $directory/plot.py $directory/output $directory done ","Shell" "Biophysics","rhomu/celadro","examples/cleanup.sh",".sh","184","10","# # Cleanup all output data and movies. # set -e # stop on any error for runcard in $(find */*.dat); do directory=${runcard%/*} rm -rf $directory/data/ movie_$directory.mp4 done ","Shell" "Biophysics","rhomu/celadro","examples/box/plot.py",".py","1362","64","# # This is a simple example file to show the plotting capabilities of the # program. Uses python2. # # Usage: # # python2 plot-cells.py input [output] # # where # # intput -- the input file or directory # output -- (optional) if present saves the animation as a video to show to # your mom. import sys sys.path.insert(0, ""../plot/"") import plot import archive import animation ################################################## # Init if len(sys.argv) == 1: print(""Please provide an input file."") exit(1) # load archive from file ar = archive.loadarchive(sys.argv[1]) oname = """" if len(sys.argv) == 3: oname = ""movie_"" + sys.argv[2] print(""Output name is"", sys.argv[2]) ################################################## # plot simple animation of phases def myplot(frame, fig): ax = fig.add_subplot(111) plot.cells(frame, ax) plot.solidarea(frame, ax) plot.shape(frame, ax) plot.velocity(frame, ax) plot.pressure_force(frame, ax) ax.axes.set_aspect(""equal"", adjustable=""box"") ax.set_xlim([0, frame.parameters[""Size""][0] - 1]) ax.set_ylim([0, frame.parameters[""Size""][1] - 1]) ax.axis(""off"") if len(oname) == 0: animation.animate(ar, myplot, show=True) exit(0) else: an = animation.animate(ar, myplot, show=False) animation.save(an, oname + "".mp4"", 5) ","Python" "Biophysics","rhomu/celadro","examples/cross/plot.py",".py","1388","65","# # This is a simple example file to show the plotting capabilities of the # program. Uses python2. # # Usage: # # python2 plot-cells.py input [output] # # where # # intput -- the input file or directory # output -- (optional) if present saves the animation as a video to show to # your mom. import sys sys.path.insert(0, ""../plot/"") import plot import archive import animation ################################################## # Init if len(sys.argv) == 1: print(""Please provide an input file."") exit(1) # load archive from file ar = archive.loadarchive(sys.argv[1]) oname = """" if len(sys.argv) == 3: oname = ""movie_"" + sys.argv[2] print(""Output name is"", sys.argv[2]) ################################################## # plot simple animation of phases def myplot(frame, fig): ax = fig.add_subplot(111) plot.cells(frame, ax) plot.solidarea(frame, ax) plot.shape(frame, ax) plot.velocity(frame, ax) plot.pressure_force(frame, ax) plot.walls(frame, ax) ax.axes.set_aspect(""equal"", adjustable=""box"") ax.set_xlim([0, frame.parameters[""Size""][0] - 1]) ax.set_ylim([0, frame.parameters[""Size""][1] - 1]) ax.axis(""off"") if len(oname) == 0: animation.animate(ar, myplot, show=True) exit(0) else: an = animation.animate(ar, myplot, show=False) animation.save(an, oname + "".mp4"", 5) ","Python" "Biophysics","rhomu/celadro","examples/relax/plot.py",".py","1474","68","# # This is a simple example file to show the plotting capabilities of the # program. Uses python2. # # Usage: # # python2 plot-cells.py input [output] # # where # # intput -- the input file or directory # output -- (optional) if present saves the animation as a video to show to # your mom. import sys sys.path.insert(0, ""../plot/"") import plot import archive import animation ################################################## # Init if len(sys.argv) == 1: print(""Please provide an input file."") exit(1) # load archive from file ar = archive.loadarchive(sys.argv[1]) oname = """" if len(sys.argv) == 3: oname = ""movie_"" + sys.argv[2] print(""Output name is"", sys.argv[2]) ################################################## # plot simple animation of phases def myplot(frame, fig): ax1 = fig.add_subplot(121) ax2 = fig.add_subplot(122) plot.cells(frame, ax1) plot.solidarea(frame, ax1) plot.shape(frame, ax1) plot.velocity(frame, ax1) plot.pressure_force(frame, ax1) plot.interfaces(frame, ax2) for ax in [ax1, ax2]: ax.axes.set_aspect(""equal"", adjustable=""box"") ax.set_xlim([0, frame.parameters[""Size""][0] - 1]) ax.set_ylim([0, frame.parameters[""Size""][1] - 1]) ax.axis(""off"") if len(oname) == 0: animation.animate(ar, myplot, show=True) exit(0) else: an = animation.animate(ar, myplot, show=False) animation.save(an, oname + "".mp4"", 5) ","Python" "Biophysics","rhomu/celadro","examples/bend/plot.py",".py","1399","64","# # This is a simple example file to show the plotting capabilities of the # program. Uses python2. # # Usage: # # python2 plot-cells.py input [output] # # where # # intput -- the input file or directory # output -- (optional) if present saves the animation as a video to show to # your mom. import sys sys.path.insert(0, ""../plot/"") import plot import archive import animation ################################################## # Init if len(sys.argv) == 1: print(""Please provide an input file."") exit(1) # load archive from file ar = archive.loadarchive(sys.argv[1]) oname = """" if len(sys.argv) == 3: oname = ""movie_"" + sys.argv[2] print(""Output name is"", sys.argv[2]) ################################################## # plot simple animation of phases def myplot(frame, fig): ax1 = fig.add_subplot(121) ax2 = fig.add_subplot(122) plot.cells(frame, ax1) plot.nematic(frame, ax1) plot.nematic_field(frame, engine=ax2, avg=2, show_def=True) for ax in [ax1, ax2]: ax.axes.set_aspect(""equal"", adjustable=""box"") ax.set_xlim([0, frame.parameters[""Size""][0] - 1]) ax.set_ylim([0, frame.parameters[""Size""][1] - 1]) ax.axis(""off"") if len(oname) == 0: animation.animate(ar, myplot, show=True) else: an = animation.animate(ar, myplot, show=False) animation.save(an, oname + "".mp4"", 5) ","Python" "Biophysics","rhomu/celadro","examples/splay/plot.py",".py","1399","64","# # This is a simple example file to show the plotting capabilities of the # program. Uses python2. # # Usage: # # python2 plot-cells.py input [output] # # where # # intput -- the input file or directory # output -- (optional) if present saves the animation as a video to show to # your mom. import sys sys.path.insert(0, ""../plot/"") import plot import archive import animation ################################################## # Init if len(sys.argv) == 1: print(""Please provide an input file."") exit(1) # load archive from file ar = archive.loadarchive(sys.argv[1]) oname = """" if len(sys.argv) == 3: oname = ""movie_"" + sys.argv[2] print(""Output name is"", sys.argv[2]) ################################################## # plot simple animation of phases def myplot(frame, fig): ax1 = fig.add_subplot(121) ax2 = fig.add_subplot(122) plot.cells(frame, ax1) plot.nematic(frame, ax1) plot.nematic_field(frame, engine=ax2, avg=2, show_def=True) for ax in [ax1, ax2]: ax.axes.set_aspect(""equal"", adjustable=""box"") ax.set_xlim([0, frame.parameters[""Size""][0] - 1]) ax.set_ylim([0, frame.parameters[""Size""][1] - 1]) ax.axis(""off"") if len(oname) == 0: animation.animate(ar, myplot, show=True) else: an = animation.animate(ar, myplot, show=False) animation.save(an, oname + "".mp4"", 5) ","Python" "Biophysics","rhomu/celadro","examples/shape/plot.py",".py","1395","64","# # This is a simple example file to show the plotting capabilities of the # program. Uses python2. # # Usage: # # python2 plot-cells.py input [output] # # where # # intput -- the input file or directory # output -- (optional) if present saves the animation as a video to show to # your mom. import sys sys.path.insert(0, ""../plot/"") import plot import archive import animation ################################################## # Init if len(sys.argv) == 1: print(""Please provide an input file."") exit(1) # load archive from file ar = archive.loadarchive(sys.argv[1]) oname = """" if len(sys.argv) == 3: oname = ""movie_"" + sys.argv[2] print(""Output name is"", sys.argv[2]) ################################################## # plot simple animation of phases def myplot(frame, fig): ax1 = fig.add_subplot(121) ax2 = fig.add_subplot(122) plot.cells(frame, ax1) plot.shape(frame, ax1) plot.velocity_field(frame, avg=5, cbar=False, engine=ax2) for ax in [ax1, ax2]: ax.axes.set_aspect(""equal"", adjustable=""box"") ax.set_xlim([0, frame.parameters[""Size""][0] - 1]) ax.set_ylim([0, frame.parameters[""Size""][1] - 1]) ax.axis(""off"") if len(oname) == 0: animation.animate(ar, myplot, show=True) else: an = animation.animate(ar, myplot, show=False) animation.save(an, oname + "".mp4"", 5) ","Python" "Biophysics","rhomu/celadro","examples/three/plot.py",".py","1439","71","# # This is a simple example file to show the plotting capabilities of the # program. Uses python2. # # Usage: # # python2 plot.py input [output] # # where # # intput -- the input file or directory # output -- (optional) if present saves the animation as a video to show to # your mom. import sys sys.path.insert(0, ""../plot/"") import plot import archive import animation ################################################## # Init if len(sys.argv) == 1: print(""Please provide an input file."") exit(1) # load archive from file ar = archive.loadarchive(sys.argv[1]) oname = """" if len(sys.argv) == 3: oname = ""movie_"" + sys.argv[2] print(""Output name is"", sys.argv[2]) ################################################## # plot simple animation of phases def myplot(frame, fig): ax = fig.add_subplot(111) plot.cells(frame, ax) plot.solidarea(frame, ax) plot.walls(frame, ax) plot.nematic(frame, ax) plot.shape(frame, ax) plot.velocity(frame, ax) plot.pressure_force(frame, ax) plot.patch(frame, 0) ax.axes.set_aspect(""equal"", adjustable=""box"") ax.set_xlim([0, frame.parameters[""Size""][0] - 1]) ax.set_ylim([0, frame.parameters[""Size""][1] - 1]) ax.axis(""off"") if len(oname) == 0: animation.animate(ar, myplot, show=True) exit(0) else: an = animation.animate(ar, myplot, show=False) animation.save(an, oname + "".mp4"", 5) ","Python" "Biophysics","rhomu/celadro","examples/cluster/plot.py",".py","1413","69","# # This is a simple example file to show the plotting capabilities of the # program. Uses python2. # # Usage: # # python2 plot.py input [output] # # where # # intput -- the input file or directory # output -- (optional) if present saves the animation as a video to show to # your mom. import sys sys.path.insert(0, ""../plot/"") import plot import archive import animation ################################################## # Init if len(sys.argv) == 1: print(""Please provide an input file."") exit(1) # load archive from file ar = archive.loadarchive(sys.argv[1]) oname = """" if len(sys.argv) == 3: oname = ""movie_"" + sys.argv[2] print(""Output name is"", sys.argv[2]) ################################################## # plot simple animation of phases def myplot(frame, fig): ax = fig.add_subplot(111) plot.cells(frame, ax) plot.solidarea(frame, ax) plot.walls(frame, ax) plot.nematic(frame, ax) plot.shape(frame, ax) plot.velocity(frame, ax) plot.pressure_force(frame, ax) ax.axes.set_aspect(""equal"", adjustable=""box"") ax.set_xlim([0, frame.parameters[""Size""][0] - 1]) ax.set_ylim([0, frame.parameters[""Size""][1] - 1]) ax.axis(""off"") if len(oname) == 0: animation.animate(ar, myplot, show=True) exit(0) else: an = animation.animate(ar, myplot, show=False) animation.save(an, oname + "".mp4"", 5) ","Python" "Biophysics","rhomu/celadro","scripts/defects-stats.py",".py","2293","100","# # Get defect stats. Uses python2. # # Usage: # # python2 defects-stats.py input defects # # where # # intput -- the input file or directory # defects -- the defects file from defects.py import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np from scipy import ndimage from itertools import product from math import log import sys # import local libs sys.path.insert(0, ""../plot/"") import archive ################################################## # Init if len(sys.argv) < 3: print(""Please provide both input and defects files."") exit(1) # load archive from file ar = archive.loadarchive(sys.argv[1]) # wrapping dist def dist(v1, v2, LX, LY): return min( [ np.linalg.norm(v1 - v2 + [x * LX, y * LY]) for x, y in product([-1, 0, 1], [-1, 0, 1]) ] ) ################################################## # Get stats size = ar.Size[0] * ar.Size[1] defects = np.load(sys.argv[2]) time = np.arange(ar.nstart, ar.nsteps + ar.ninfo, ar.ninfo) dens = np.zeros(ar._nframes + 1) char = np.zeros(ar._nframes + 1) # mean speed of plus and minus defects velp = np.zeros(len(defects)) velm = np.zeros(len(defects)) for i in range(len(defects)): d = defects[i] # print len(d[2]) # compute density of defects and charge density for j in range(d[1], d[1] + len(d[2])): dens[j] += 1.0 / size char[j] += d[0] # speed (only take defects that survive long enough) if len(d[2]) > 5: vel = np.mean( [ dist(d[2][k - 1], d[2][k], ar.Size[0], ar.Size[1]) for k in range(1, len(d[2])) ] ) if d[0] > 0: velp[i] = vel else: velm[i] = vel # mean defect density print(""Mean defect density:"", np.mean(dens)) print(""Mean velcotiy of plus defects:"", np.mean(velp)) print(""Mean velcotiy of minus defects:"", np.mean(velm)) plt.figure() plt.subplot(211) plt.plot(time, char / size, ""r"", label=""charge density"") plt.plot(time, dens, label=""defect density"") plt.plot(time, ndimage.uniform_filter1d(dens, size=50), label=""smoothed defect density"") plt.legend() plt.subplot(212) plt.hist([log(len(d[2])) for d in defects], label=""log(defect lifetime)"") plt.legend() plt.show() ","Python" "Biophysics","rhomu/celadro","scripts/correlations.py",".py","3970","163","# # Computes mean correlations (vorticity^2, velocity^2, Q^2). Uses python2. # # Usage: # # python2 correlations.py input [output] # # where # # intput -- the input file or directory # output -- (optional) if present saves plots instead of showing them import matplotlib.pyplot as plt import sys import numpy as np from math import sqrt # import local libs sys.path.insert(0, ""../plot/"") import plot import archive ################################################## # Init if len(sys.argv) == 1: print(""Please provide an input file."") exit(1) # load archive from file ar = archive.loadarchive(sys.argv[1]) oname = """" if len(sys.argv) == 3: oname = sys.argv[2] print(""Output name is"", sys.argv[2]) ################################################## # compute mean correlations size = int(sqrt(ar.Size[0] * ar.Size[1]) / 2) count = 0 vel_tot = np.zeros(size) vel_err = np.zeros(size) vor_tot = np.zeros(size) vor_err = np.zeros(size) shp_tot = np.zeros(size) shp_err = np.zeros(size) nem_tot = np.zeros(size) nem_err = np.zeros(size) for i in np.arange(int(0.3 * ar._nframes), ar._nframes + 1, step=1): frame = ar.read_frame(i) print(""{}/{}"".format(i, ar._nframes)) # velocity and vorticity vx, vy = plot.get_velocity_field(frame.phi, frame.velocity, size=24) w = plot.get_vorticity_field(vx, vy) corr1 = plot.get_corr2(vx, vy) corr2 = plot.get_corr(w) vel_tot += corr1 vel_err += np.square(corr1) vor_tot += corr2 vor_err += np.square(corr2) # Q Qxx, Qxy = plot.get_nematic_field(frame.phi, frame.Q00, frame.Q01, size=24) corrQ = plot.get_corr2(Qxx, Qxy) # normalization is wrong but cancels nem_tot += corrQ nem_err += np.square(corrQ) # shape Sxx, Sxy = plot.get_nematic_field(frame.phi, frame.S00, frame.S01, size=24) corrS = plot.get_corr2(Sxx, Sxy) # normalization is wrong but cancels shp_tot += corrS shp_err += np.square(corrS) count += 1 for i in range(size): vel_tot[i] /= count vel_err[i] /= count vel_err[i] = sqrt(vel_err[i] - vel_tot[i] ** 2) vor_tot[i] /= count vor_err[i] /= count vor_err[i] = sqrt(vor_err[i] - vor_tot[i] ** 2) nem_tot[i] /= count nem_err[i] /= count nem_err[i] = sqrt(nem_err[i] - nem_tot[i] ** 2) shp_tot[i] /= count shp_err[i] /= count shp_err[i] = sqrt(shp_err[i] - shp_tot[i] ** 2) # # nematic # plt.figure() plt.plot(range(size), nem_tot, ""k"") plt.fill_between(range(size), nem_tot - nem_err, nem_tot + nem_err) if oname == """": plt.show() else: plt.savefig(oname + ""_corr_nem.png"") np.save(oname + ""_nem_tot"", nem_tot) np.save(oname + ""_nem_err"", nem_err) # # shape # plt.figure() plt.plot(range(size), shp_tot, ""k"") plt.fill_between(range(size), shp_tot - shp_err, shp_tot + shp_err) if oname == """": plt.show() else: plt.savefig(oname + ""_corr_shape.png"") np.save(oname + ""_shape_tot"", shp_tot) np.save(oname + ""_shape_err"", shp_err) # # velocity # plt.figure() plt.plot(range(size), vel_tot, ""k"") plt.fill_between(range(size), vel_tot - vel_err, vel_tot + vel_err) if oname == """": plt.show() else: plt.savefig(oname + ""_corr_vel.png"") np.save(oname + ""_vel_tot"", vel_tot) np.save(oname + ""_vel_err"", vel_err) # # vorticity # def zero(x, y): indi = np.where(y[1:] * y[0:-1] < 0.0)[0][0] dx = x[indi + 1] - x[indi] dy = y[indi + 1] - y[indi] z = -y[indi] * (dx / dy) + x[indi] return z # get location of zero of the derivative dvor_tot = np.gradient(vor_tot) xz = zero(range(size), dvor_tot) yz = vor_tot[int(xz)] + (xz - int(xz)) * (vor_tot[int(xz) + 1] - vor_tot[int(xz)]) plt.figure() plt.plot(range(size), vor_tot, ""k"") plt.plot(xz, yz, ""ro"") plt.fill_between(range(size), vor_tot - vor_err, vor_tot + vor_err) if oname == """": plt.show() else: plt.savefig(oname + ""_corr_vor.png"") np.save(oname + ""_vor_tot"", vor_tot) np.save(oname + ""_vor_err"", vor_err) ","Python" "Biophysics","rhomu/celadro","scripts/rmsvel.py",".py","1285","59","# # This is a simple example file to show the plotting capabilities of the # program. Uses python2. # # Usage: # # python2 rmsvel.py input # # where # # intput -- the input file or directory import matplotlib.pyplot as plt import sys import numpy as np from math import sqrt # import local libs sys.path.insert(0, ""../plot/"") import plot import archive ################################################## # Init if len(sys.argv) == 1: print(""Please provide an input file."") exit(1) # load archive from file ar = archive.loadarchive(sys.argv[1]) ################################################## # plot simple animation of phases ar = archive.loadarchive(sys.argv[1]) rms = np.zeros(ar._nframes + 1) tox = np.zeros(ar._nframes + 1) toy = np.zeros(ar._nframes + 1) c = 0 for i in range(0, ar._nframes + 1): frame = ar.read_frame(i) print( ""{}/{}"".format(i, ar._nframes), ) vx, vy = plot.get_velocity_field(frame.phi, frame.velocity, size=24) rms[c] = sqrt(np.mean(vx ** 2 + vy ** 2)) tox[c] = np.mean(vx) toy[c] = np.mean(vy) print(""vx={}, vy={}, rms={}"".format(tox[c], toy[c], rms[c])) c += 1 plt.plot(np.arange(0, len(rms)), rms) plt.plot(np.arange(0, len(rms)), tox) plt.plot(np.arange(0, len(rms)), toy) plt.show() ","Python" "Biophysics","rhomu/celadro","scripts/defects-flowfields.py",".py","4473","166","# # Plot director and flow fields around defects. # # Usage: # # python2 defects-flowfields.py shape/nematic input [output] # # where # # intput -- the input file or directory # output -- (optional) if present saves plots instead of showing them import numpy as np import matplotlib.pyplot as plt import sys sys.path.insert(0, ""../plot/"") import plot import archive from scipy.ndimage import rotate, shift from math import cos, sin ################################################## # Init if len(sys.argv) < 3: print(""Please provide type of nematci and input file to me."") exit(1) qtensor = sys.argv[1] if sys.argv[1] not in [""shape"", ""nematic""]: print(""Please set first argument to be 'shape' or 'nematic'."") exit(1) oname = """" if len(sys.argv) == 4: oname = sys.argv[3] print(""Output name is"", sys.argv[3]) ################################################## # Track defects window_size = 100 charge = 0.5 avg = 4 ar = archive.loadarchive(sys.argv[2]) # https://stackoverflow.com/questions/46657423/rotated-image-coordinates-after-scipy-ndimage-interpolation-rotate def rot(image, xy, angle, crop): # shift, rotate, and shift org_center = (np.array(image.shape[:2][::-1]) - 1) / 2.0 im_rot = shift(image, -xy + org_center, mode=""wrap"") im_rot = rotate(im_rot, np.rad2deg(angle), mode=""wrap"", reshape=False) im_rot = shift(im_rot, -org_center + 2 * [crop / 2], mode=""wrap"") # crop to window size return im_rot[0:crop, 0:crop] c = 0 Q00_tot = np.zeros((window_size, window_size)) Q01_tot = np.zeros((window_size, window_size)) vx_tot = np.zeros((window_size, window_size)) vy_tot = np.zeros((window_size, window_size)) for i in np.arange(ar._nframes + 1, step=1): frame = ar.read_frame(i) print(""{}/{}"".format(i, ar._nframes)) vx, vy = plot.get_velocity_field(frame.phi, frame.velocity, size=24) if qtensor == ""shape"": Q00, Q01 = plot.get_nematic_field(frame.phi, frame.S00, frame.S01, size=24) else: Q00, Q01 = plot.get_nematic_field(frame.phi, frame.Q00, frame.Q01, size=24) defects = plot.get_defects(plot.charge_array(Q00, Q01), Q00, Q01) for d in defects: if d[""charge""] == charge: # rotation angle w = -d[""angle""] p = d[""pos""] # Q tensor Q00 = rot(Q00, p, w, window_size) Q01 = rot(Q01, p, w, window_size) Q00, Q01 = ( cos(2 * w) * Q00 - sin(2 * w) * Q01, sin(2 * w) * Q00 + cos(2 * w) * Q01, ) Q00_tot += Q00 Q01_tot += Q01 # velocity field vx = rot(vx, p, w, window_size) vy = rot(vy, p, w, window_size) vx, vy = cos(w) * vx - sin(w) * vy, sin(w) * vx + cos(w) * vy vx_tot += vx vy_tot += vy c += 1 print(""Averaged over"", c, ""instances"") ################################################################################ # Q tensor Q00_tot /= c Q01_tot /= c plt.figure() plot.director(Q00_tot, Q01_tot, avg=avg) if oname == """": plt.show() else: plt.savefig(oname + ""_director.png"") ################################################################################ # stress (cheating) plt.figure() plot.director(Q00_tot, Q01_tot, avg=avg) cax = plt.imshow(-Q00_tot.T, interpolation=""lanczos"", cmap=""plasma"", origin=""lower"") if oname == """": plt.show() else: plt.savefig(oname + ""_sigmaxx.png"") plt.figure() plot.director(Q00_tot, Q01_tot, avg=avg) cax = plt.imshow(Q01_tot.T, interpolation=""lanczos"", cmap=""plasma"", origin=""lower"") if oname == """": plt.show() else: plt.savefig(oname + ""_sigmaxy.png"") ################################################################################ # velocity vx_tot /= c vy_tot /= c m = np.sqrt(vx_tot ** 2 + vy_tot ** 2) vx_tot = vx_tot.reshape((vx_tot.shape[0] // avg, avg, vx_tot.shape[1] // avg, avg)) vx_tot = np.mean(vx_tot, axis=(1, 3)) vy_tot = vy_tot.reshape((vy_tot.shape[0] // avg, avg, vy_tot.shape[1] // avg, avg)) vy_tot = np.mean(vy_tot, axis=(1, 3)) plt.figure() plt.quiver( avg * np.arange(vx_tot.shape[0]), avg * np.arange(vx_tot.shape[1]), vx_tot.T, vy_tot.T, pivot=""tail"", units=""dots"", scale_units=""dots"", ) cax = plt.imshow(m.T, interpolation=""lanczos"", cmap=""plasma"", origin=""lower"") plt.colorbar(cax) if oname == """": plt.show() else: plt.savefig(oname + ""_flowfield.png"") ","Python" "Biophysics","rhomu/celadro","scripts/single-cells.py",".py","1447","68","# # Computes single cells trajectories and msd. Uses python2. # # Usage: # # python2 single-cells.py input [output] # # where # # intput -- the input file or directory # output -- (optional) if present saves plots instead of showing them import matplotlib.pyplot as plt import sys import numpy as np from itertools import product # import local libs sys.path.insert(0, ""../plot/"") import archive ################################################## # Init if len(sys.argv) == 1: print(""Please provide an input file."") exit(1) # load archive from file ar = archive.loadarchive(sys.argv[1]) oname = """" if len(sys.argv) == 3: oname = sys.argv[2] print(""Output name is"", sys.argv[2]) ################################################## # compute stuff and other things size = ar.nphases traj = [[] for i in range(size)] # for i in np.arange(int(0.3*ar._nframes), ar._nframes+1, step=1): for i in np.arange(0, ar._nframes + 1, step=1): frame = ar.read_frame(i) print(""{}/{}"".format(i, ar._nframes)) for j in range(size): traj[j].append(frame.com[j]) def norm(v1, v2, LX, LY): return min( [ np.linalg.norm(v1 - v2 + [x * LX, y * LY]) for x, y in product([-1, 0, 1], [-1, 0, 1]) ] ) # compute distance dist = [[norm(t[i], t[0], ar.Size[0], ar.Size[1]) for i in range(len(t))] for t in traj] for d in dist: plt.plot(range(len(d)), d) plt.show() ","Python" "Biophysics","rhomu/celadro","scripts/track-defects.py",".py","4329","139","# # Defect tracking script. Uses python2. # # Usage: # # python2 track_defects.py shape/nematic input output # # where # # intput -- the input file or directory # output -- the output file import numpy as np import sys sys.path.insert(0, ""../plot/"") import plot import archive from itertools import product ################################################## # Init if len(sys.argv) < 4: print(""Please provide q-tensor type, input, and output files."") exit(1) qtype = sys.argv[1] if qtype not in [""shape"", ""nematic""]: print(""Q-tensor type should be either 'shape' or 'nematic'."") exit(1) ################################################## # Track defects class defect_tracker: """""" Defect tracker. Honestly this is not good code... if you are reading this I feel for you! """""" def __init__(self, max_dst=5): # all defects in id order self.defects = [] # list of id of active defects by charge self.active = {} # cutoff distance for matching self.max_dst = max_dst # wrapping distance on pbc domain (ugly) def norm(self, v1, v2, LX, LY): return min( [ np.linalg.norm(v1 - v2 + [x * LX, y * LY]) for x, y in product([-1, 0, 1], [-1, 0, 1]) ] ) def add_frame(self, Q00, Q01, t): """"""Add a new frame and detect defects"""""" # get dimension of pbc domain (LX, LY) = Q00.shape # get defects from new frame w = plot.charge_array(Q00, Q01) defects = plot.get_defects(w, Q00, Q01) # new list of active defects active = {} # compare with old ones for new in defects: # distance from all active defects with same charge dist = [ self.norm(new[""pos""], self.defects[i][""pos""][-1], LX, LY) for i in self.active.get(new[""charge""], []) ] if len(dist) != 0: # find minimum and index v, i = min((v, i) for (i, v) in enumerate(dist)) # if min dist is smaller than cutoff then we have found our defect if v < self.max_dst: # add position and angle to stored defect self.defects[self.active[new[""charge""]][i]][""pos""].append( new[""pos""] ) # register it as active for next round active[new[""charge""]] = active.get(new[""charge""], []) + [ self.active[new[""charge""]][i] ] # delete from current list del self.active[new[""charge""]][i] continue # we have found a new defect self.defects.append( {""charge"": new[""charge""], ""birth"": t, ""pos"": [new[""pos""]]} ) # register it as active for next round active[new[""charge""]] = active.get(new[""charge""], []) + [ len(self.defects) - 1 ] # save list of acive defects for next run (all the remaining defects are inactive) self.active = active def plot(self, engine): # get all active defects with a certain charge for chg, dft in self.active.iteritems(): # get all indices of these defects for ind in dft: p = self.defects[ind][""pos""][-1] engine.plot( p[0], p[1], ""b"" if chg == 0.5 else ""g"", marker=r""$ {} $"".format(ind), markersize=15, ) ar = archive.loadarchive(sys.argv[2]) tracker = defect_tracker(max_dst=15) for i in range(0, ar._nframes + 1): frame = ar.read_frame(i) print(""{}/{}"".format(i, ar._nframes)) if qtype == ""shape"": (Q00, Q01) = plot.get_nematic_field(frame.phi, frame.S00, frame.S01, size=24) else: (Q00, Q01) = plot.get_nematic_field(frame.phi, frame.Q00, frame.Q01, size=24) tracker.add_frame(Q00, Q01, i) # convert format to pure np array (ok this is not great) result = np.array( [[i[""charge""], i[""birth""], np.array(i[""pos""])] for i in tracker.defects], dtype=object, ) np.save(sys.argv[3], result) ","Python" "Biophysics","rhomu/celadro","scripts/bend_splay.py",".py","1548","64","# # This is a simple example file to show the plotting capabilities of the # program. Uses python2. # # Usage: # # python2 bend_splay.py input # # where # # intput -- the input file or directory import matplotlib.pyplot as plt import sys import numpy as np from math import sqrt # import local libs sys.path.insert(0, ""../plot/"") import plot import archive ################################################## # Init if len(sys.argv) == 1: print(""Please provide an input file."") exit(1) # load archive from file ar = archive.loadarchive(sys.argv[1]) ################################################## # plot simple animation of phases ll = ar._nframes + 1 ar = archive.loadarchive(sys.argv[1]) bend = np.zeros(ll) splay = np.zeros(ll) c = 0 for i in range(0, ll): frame = ar.read_frame(i) print( ""{}/{}"".format(i, ar._nframes), ) Qxx, Qxy = plot.get_Qtensor(frame.phi, frame.Q00, frame.Q01, size=24) S = np.vectorize(sqrt)(Qxy ** 2 + Qxx ** 2) nx = np.vectorize(sqrt)((1 + Qxx / S) / 2) ny = np.sign(Qxy) * np.vectorize(sqrt)((1 - Qxx / S) / 2) nn = nx * nx + ny * ny bend[c] = 0.5 * np.sum(np.square(nn * plot.get_vorticity_field(nx, ny))) splay[c] = 0.5 * np.sum(np.square(plot.get_gradient_field(nx, ny))) # bend[c] = log(bend[c]) # splay[c] = log(splay[c]) print(""bend={}, splay={}"".format(bend[c], splay[c])) c += 1 plt.plot(ar.ninfo * np.arange(0, c), bend, label=""bend"") plt.plot(ar.ninfo * np.arange(0, c), splay, label=""splay"") plt.legend() plt.show() ","Python" "Biophysics","Eigenstate/psfgen","setup.py",".py","775","37","from setuptools import setup from setuptools.extension import Extension psfgenfiles = [ ""./src/charmm_file.c"", ""./src/charmm_parse_topo_defs.c"", ""./src/extract_alias.c"", ""./src/hash.c"", ""./src/hasharray.c"", ""./src/memarena.c"", ""./src/pdb_file.c"", ""./src/pdb_file_extract.c"", ""./src/psf_file.c"", ""./src/psf_file_extract.c"", ""./src/python_psfgen.c"", ""./src/stringhash.c"", ""./src/topo_defs.c"", ""./src/topo_mol.c"", ""./src/topo_mol_output.c"", ] psfext = Extension( ""_psfgen"", define_macros=[(""PSFGENTCLDLL_EXPORTS"", ""1"")], include_dirs=[""./src""], libraries=[], library_dirs=[], sources=psfgenfiles, ) setup( packages=[""psfgen""], ext_modules=[psfext], include_package_data=True, ) ","Python" "Biophysics","Eigenstate/psfgen","src/python_psfgen.c",".c","41818","1302","#include #include #include #include ""python_psfgen.h"" #include ""psfgen.h"" #include ""hasharray.h"" #include ""pdb_file_extract.h"" #include ""psf_file_extract.h"" #include ""topo_defs.h"" #include ""topo_mol_struct.h"" #include ""topo_mol_output.h"" #include ""charmm_parse_topo_defs.h"" #include ""stringhash.h"" #include ""extract_alias.h"" /* Helper functions */ void python_msg(void *v, const char *msg) { v = (FILE*)v; // print to this file fprintf(v, ""%s\n"", msg); } /* Wrapper function for getting char* from a python string */ static char* as_charptr(PyObject *target) { #if PY_MAJOR_VERSION >=3 return PyUnicode_AsUTF8(target); #else return PyString_AsString(target); #endif } /* Wrapper function for turning char* into a python string */ static PyObject* as_pystring(char *target) { PyObject *result; if (!target) { PyErr_SetString(PyExc_ValueError, ""cannot convert null string""); return NULL; } #if PY_MAJOR_VERSION >= 3 result = PyUnicode_FromString(target); #else result = PyString_FromString(target); #endif if (!result || PyErr_Occurred()) { PyErr_Format(PyExc_ValueError, ""cannot convert char* '%s'"", target); return NULL; } return result; } /* Similar wrapper function for turning int into a python int/long */ static PyObject* as_pyint(int target) { PyObject *result; #if PY_MAJOR_VERSION >= 3 result = PyLong_FromLong((long) target); #else result = PyInt_FromLong((long) target); #endif if (!result || PyErr_Occurred()) { PyErr_Format(PyExc_ValueError, ""cannot convert int %d"", target); return NULL; } return result; } // Converter function for boolean arguments int convert_bool(PyObject *obj, void *boolval) { if (!PyObject_TypeCheck(obj, &PyBool_Type)) { PyErr_SetString(PyExc_TypeError, ""expected a boolean""); return 0; } *((int*)(boolval)) = PyObject_IsTrue(obj); return 1; // success } /* Initialization / destruction functions */ static PyObject* py_init_mol(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""outfd"", NULL}; PyObject *capsule; psfgen_data *data; int outfd = 0; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""|i:__init__"", (char**) kwnames, &outfd)) { return NULL; } data = malloc(sizeof(psfgen_data)); // Initialize topologies data->defs = topo_defs_create(); // Initialize aliases data->aliases = stringhash_create(); data->mol = topo_mol_create(data->defs); // Initialize other stuffs data->id = 0; // Doesn't matter since data is per class instance data->in_use = 0; data->all_caps = 1; /* * Handle output file argument.. Default to stdout * This doesn't need to be closed in del_mol because the file * descriptor is closed in the Python destructor if it is used */ data->outstream = outfd ? fdopen(outfd, ""a"") : stdout; topo_defs_error_handler(data->defs, data->outstream, python_msg); topo_mol_error_handler(data->mol, data->outstream, python_msg); // Encapsulate psf_data object and return it capsule = PyCapsule_New(data, NULL, NULL); if (!capsule || PyErr_Occurred()) return NULL; return capsule; } static PyObject* py_del_mol(PyObject *self, PyObject *stateptr) { psfgen_data *data; // Unpack molecule capsule data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; // Invoke cleanup functions topo_mol_destroy(data->mol); topo_defs_destroy(data->defs); stringhash_destroy(data->aliases); free(data); Py_INCREF(Py_None); return Py_None; } /* Aliases and names and stuff */ static PyObject* py_alias(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""type"", ""name"", ""newname"", ""resname"", NULL}; char *type, *name, *newname, *resname = NULL; PyObject *stateptr; psfgen_data *data; // Parse arguments and put them in the right format if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""Osss|s:alias"", (char**) kwnames, &stateptr, &type, &name, &newname, &resname)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; name = strtoupper(name, data->all_caps); newname = strtoupper(newname, data->all_caps); if (!strcasecmp(type, ""residue"")) { fprintf(data->outstream, ""Aliasing residue %s to %s\n"", name, newname); if(extract_alias_residue_define(data->aliases, name, newname)) { PyErr_SetString(PyExc_ValueError, ""failed on residue alias""); return NULL; } } else if (!strcasecmp(type, ""atom"")) { if (!resname) { PyErr_SetString(PyExc_ValueError, ""resname must be provided when aliasing atoms""); return NULL; } resname = strtoupper(resname, data->all_caps); fprintf(data->outstream, ""Aliasing residue %s atom %s to %s\n"", resname, name, newname); if(extract_alias_atom_define(data->aliases, resname, name, newname)) { PyErr_SetString(PyExc_ValueError, ""failed on atom alias""); return NULL; } } else { PyErr_SetString(PyExc_ValueError, ""alias type must be either 'atom' or 'residue'""); return NULL; } Py_INCREF(Py_None); return Py_None; } static PyObject* py_set_allcaps(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""allcaps"", NULL}; PyObject *stateptr; psfgen_data *data; int allcaps = 1; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""O|O&:set_allcaps"", (char**) kwnames, &stateptr, convert_bool, &allcaps)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; data->all_caps = allcaps ? 1 : 0; Py_INCREF(Py_None); return Py_None; } static PyObject* py_regenerate(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""task"", NULL}; PyObject *stateptr; psfgen_data *data; char *task; int rc; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""Os:regenerate"", (char**) kwnames, &stateptr, &task)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; if (!strcasecmp(task, ""angles"")) { rc = topo_mol_regenerate_angles(data->mol); } else if (!strcasecmp(task, ""dihedrals"")) { rc = topo_mol_regenerate_dihedrals(data->mol); } else if (!strcasecmp(task, ""resids"")) { rc = topo_mol_regenerate_resids(data->mol); } else { PyErr_Format(PyExc_ValueError, ""regenerate must be [angles,resids,dihedrals], got '%s'"", task); return NULL; } if (rc) { PyErr_Format(PyExc_ValueError, ""%s regeneration failed"", task); return NULL; } Py_INCREF(Py_None); return Py_None; } /* IO functions */ static PyObject* py_write_namdbin(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""filename"", ""velocity_filename"", NULL}; char *velfilename = NULL; FILE *velfile = NULL; PyObject *stateptr; psfgen_data *data; char *filename; FILE *pfile; int rc; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""Os|z:write_namdbin"", (char**) kwnames, &stateptr, &filename, &velfilename)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; // Open files for writing, with some error checking pfile = fopen(filename, ""wb""); if (!pfile) { PyErr_Format(PyExc_ValueError, ""Cannot open file '%s' for writing"", filename); return NULL; } if (velfilename) { velfile = fopen(velfilename, ""wb""); if (!velfile) { fclose(pfile); PyErr_Format(PyExc_ValueError, ""Cannot open file '%s' for writing"", velfilename); return NULL; } } // Write the file, clean up, then errocr check rc = topo_mol_write_namdbin(data->mol, pfile, velfile, data->outstream, python_msg); fclose(pfile); if (velfile) fclose(velfile); if (rc) { PyErr_Format(PyExc_ValueError, ""Failed writing namdbin file '%s'"", filename); return NULL; } Py_INCREF(Py_None); return Py_None; } static PyObject* py_write_pdb(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""filename"", NULL}; PyObject *stateptr; psfgen_data *data; char *filename; FILE *fd; int rc; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""Os:write_pdb"", (char**) kwnames, &stateptr, &filename)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; fd = fopen(filename, ""w""); if (!fd) { PyErr_Format(PyExc_OSError, ""cannot open pdb file '%s' for writing"", filename); return NULL; } rc = topo_mol_write_pdb(data->mol, fd, data->outstream, python_msg); fclose(fd); if (rc) { PyErr_Format(PyExc_ValueError, ""cannot write pdb '%s'"", filename); return NULL; } Py_INCREF(Py_None); return Py_None; } static PyObject* py_write_psf(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""filename"", ""type"", NULL}; char *filename, *type; PyObject *stateptr; psfgen_data *data; int rc, charmmfmt; FILE *fd; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""Oss:write_psf"", (char**) kwnames, &stateptr, &filename, &type)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; if (!strcasecmp(type, ""charmm"")) { charmmfmt = 1; } else if (!strcasecmp(type, ""x-plor"")) { charmmfmt = 0; } else { PyErr_Format(PyExc_ValueError, ""psf format '%s' not in [charmm,x-plor]"", type); return NULL; } fd = fopen(filename, ""w""); if (!fd) { PyErr_Format(PyExc_OSError, ""cannot open psf file '%s' for writing"", filename); return NULL; } rc = topo_mol_write_psf(data->mol, fd, charmmfmt, 0, 0, data->outstream, python_msg); fclose(fd); if (rc) { PyErr_Format(PyExc_ValueError, ""cannot write psf '%s'"", filename); return NULL; } Py_INCREF(Py_None); return Py_None; } static PyObject* py_read_psf(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""filename"", ""pdbfile"", ""namdbinfile"", ""velnamdbinfile"", NULL}; FILE *pdb = NULL, *psf = NULL, *namd = NULL, *vel = NULL; char *pdbfile = NULL, *namdfile = NULL, *velfile = NULL; PyObject *stateptr; psfgen_data *data; char *psffile; int rc; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""Os|zzz:read_psf"", (char**) kwnames, &stateptr, &psffile, &pdbfile, &namdfile, &velfile)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; // Open files as psf_file_extract takes file pointers psf = fopen(psffile, ""rb""); if (pdbfile) pdb = fopen(pdbfile, ""rb""); if (namdfile) namd = fopen(namdfile, ""rb""); if (velfile) vel = fopen(velfile, ""rb""); // Error check all files at once, nicer code but less specific error msg if (!psf || (!pdb && pdbfile) || (!namd && namdfile) || (!vel && velfile)) { if (psf) fclose(psf); if (pdb) fclose(pdb); if (namd) fclose(namd); if (vel) fclose(vel); PyErr_Format(PyExc_ValueError, ""Cannot open files for read psf '%s'"", psffile); return NULL; } // Actually do the parsing, and then clean up rc = psf_file_extract(data->mol, psf, pdb, namd, vel, data->outstream, python_msg); fclose(psf); if (pdb) fclose(pdb); if (namd) fclose(namd); if (vel) fclose(vel); if (rc) { PyErr_Format(PyExc_ValueError, ""Failed to parse psf file '%s'"", psffile); return NULL; } Py_INCREF(Py_None); return Py_None; } static PyObject* py_read_coords(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""filename"", ""segid"", NULL}; char *filename, *segid; PyObject *stateptr; psfgen_data *data; FILE *fd; int rc; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""Oss:read_coords"", (char**) kwnames, &stateptr, &filename, &segid)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; fd = fopen(filename, ""r""); if (!fd) { PyErr_Format(PyExc_OSError, ""cannot open coordinate file '%s'"", filename); return NULL; } rc = pdb_file_extract_coordinates(data->mol, fd, NULL, segid, data->aliases, data->all_caps, data->outstream, python_msg); fclose(fd); if (rc) { PyErr_Format(PyExc_ValueError, ""cannot read coordinates '%s' into segment '%s'"", filename, segid); return NULL; } Py_INCREF(Py_None); return Py_None; } /* Segment functions */ static PyObject* py_add_segment(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""segid"", ""pdbfile"", ""first"", ""last"", ""auto_angles"", ""auto_dihedrals"", ""residues"", ""mutate"", NULL}; char *first = NULL, *last = NULL, *filename = NULL; PyObject *mutate = NULL, *residues = NULL; int autoang = 1, autodih = 1; PyObject *stateptr; psfgen_data *data; char *segname; FILE *fd; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""Os|sssO&O&OO:add_segment"", (char**) kwnames, &stateptr, &segname, &filename, &first, &last, convert_bool, &autoang, convert_bool, &autodih, &residues, &mutate)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; // Sanity check segment name segname = strtoupper(segname, data->all_caps); if (strlen(segname) > 7) { PyErr_Format(PyExc_ValueError, ""segment name '%s' more than 7 characters"", segname); return NULL; } if (topo_mol_segment(data->mol, segname)) return NULL; // Set first and last, if present if (first) { if (topo_mol_segment_first(data->mol, first)) { PyErr_Format(PyExc_ValueError, ""Cannot set first patch in segment "" ""'%s' to '%s'"", segname, first); return NULL; } } if (last) { if (topo_mol_segment_last(data->mol, last)) { PyErr_Format(PyExc_ValueError, ""Cannot set last patch in segment "" ""'%s' to '%s'"", segname, last); return NULL; } } // Set auto angles and dihedrals if (topo_mol_segment_auto_angles(data->mol, autoang)) { PyErr_Format(PyExc_ValueError, ""Failed setting angle autogen for "" ""segment %s"", segname); return NULL; } if (topo_mol_segment_auto_dihedrals(data->mol, autodih)) { PyErr_Format(PyExc_ValueError, ""Failed setting dihedral autogen for "" ""segment %s"", segname); return NULL; } // If pdb file, do that before finishing the segment if (filename) { int rc; fd = fopen(filename, ""r""); if (!fd) { PyErr_Format(PyExc_OSError, ""cannot open coordinate file '%s'"", filename); return NULL; } rc = pdb_file_extract_residues(data->mol, fd, data->aliases, data->all_caps, data->outstream, python_msg); fclose(fd); if (rc) { PyErr_Format(PyExc_ValueError, ""cannot read pdb file '%s'"", filename); return NULL; } } // Add residues to end, if desired if (residues && (residues != Py_None)) { char *resid, *resname, *chain; PyObject *residue; int n; if (!PyList_Check(residues)) { PyErr_SetString(PyExc_ValueError, ""residues must be a list!""); return NULL; } for (int i = 0; i < (int)PyList_Size(residues); i++) { residue = PyList_GetItem(residues, i); if (!PyTuple_Check(residue)) { PyErr_SetString(PyExc_ValueError, ""residues must be list of tuple""); return NULL; } n = (int) PyTuple_Size(residue); if ((n != 2) && (n != 3)) { PyErr_SetString(PyExc_ValueError, ""residues must be a list of "" ""2 or 3 tuples""); return NULL; } // Unpack tuple arguments, with chain being optional resid = as_charptr(PyTuple_GetItem(residue, 0)); resname = as_charptr(PyTuple_GetItem(residue, 1)); chain = (n == 3) ? as_charptr(PyTuple_GetItem(residue, 2)) : """"; if (topo_mol_residue(data->mol, resid, resname, chain)) { PyErr_Format(PyExc_ValueError, ""Failed to add residue '%s:%s'"", resname, resid); return NULL; } } } // Do mutations, if provided if (mutate && (mutate != Py_None)) { char *resid, *resname; PyObject *residue; if (!PyList_Check(mutate)) { PyErr_SetString(PyExc_ValueError, ""mutate must be a list!""); return NULL; } for (int i = 0; i < (int)PyList_Size(mutate); i++) { residue = PyList_GetItem(mutate, i); if ( (!PyTuple_Check(residue)) || (int)PyTuple_Size(residue) != 2) { PyErr_SetString(PyExc_ValueError, ""mutate must be a list of "" ""2 or 3-tuples""); return NULL; } // Unpack tuple resid = as_charptr(PyTuple_GetItem(residue, 0)); resname = as_charptr(PyTuple_GetItem(residue, 1)); if (topo_mol_mutate(data->mol, resid, resname)) { PyErr_Format(PyExc_ValueError, ""Failed to mutate residue '%s:%s'"", resname, resid); return NULL; } } } // Check result if (topo_mol_end(data->mol)) { PyErr_Format(PyExc_ValueError, ""failed building segment '%s'"", segname); return NULL; } Py_INCREF(Py_None); return Py_None; } static PyObject* py_query_segment(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""task"", ""segid"", ""resid"", NULL}; char *segid = NULL, *resid = NULL; PyObject *stateptr, *objid; topo_mol_segment_t *seg; PyObject *result = NULL; psfgen_data *data; char *task; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""Os|ss:query_segment"", (char**) kwnames, &stateptr, &task, &segid, &resid)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; // Ensure task argument is valid if (strcasecmp(task, ""first"") && strcasecmp(task, ""last"") \ && strcasecmp(task, ""resids"") && strcasecmp(task, ""residue"") \ && strcasecmp(task, ""segids"")) { PyErr_Format(PyExc_ValueError, ""Unknown segment query '%s'"", task); return NULL; } // Extract segid argument for non-segid requests if ((!segid) && strcasecmp(task, ""segids"")) { PyErr_Format(PyExc_ValueError, ""segid argument must be passed for "" ""segment task '%s'"", task); return NULL; } else if (strcasecmp(task, ""segids"")) { // Identify the segment int segidx = (data->mol ? hasharray_index(data->mol->segment_hash, segid) : HASHARRAY_FAIL); if (segidx == HASHARRAY_FAIL) { PyErr_Format(PyExc_ValueError, ""segid '%s' doesn't exist"", segid); return NULL; } seg = data->mol->segment_array[segidx]; } // Now build the result, depending on what the query is if (!strcasecmp(task, ""segids"")) { result = PyList_New(0); if (data->mol) { for (int i = 0; i < hasharray_count(data->mol->segment_hash); i++) { if (hasharray_index(data->mol->segment_hash, data->mol->segment_array[i]->segid) != HASHARRAY_FAIL) { objid = as_pystring(data->mol->segment_array[i]->segid); if (PyList_Append(result, objid)) return NULL; } } } } else if (!strcasecmp(task, ""first"")) { result = as_pystring(seg->pfirst); // If patch is ""none"", return the Python None object if (!strcasecmp(seg->pfirst, ""none"")) { Py_INCREF(Py_None); result = Py_None; } } else if (!strcasecmp(task, ""last"")) { result = as_pystring(seg->plast); if (!strcasecmp(seg->plast, ""none"")) { Py_INCREF(Py_None); result = Py_None; } } else if (!strcasecmp(task, ""resids"")) { result = PyList_New(0); for (int i = 0; i < hasharray_count(seg->residue_hash); i++) { if (hasharray_index(seg->residue_hash, seg->residue_array[i].resid) != HASHARRAY_FAIL) { objid = as_pystring(seg->residue_array[i].resid); if (PyList_Append(result, objid)) return NULL; } } } else if (!strcasecmp(task, ""residue"")) { int residx; if (!resid) { PyErr_Format(PyExc_ValueError, ""resid argument must be passed "" ""for segment task '%s'"", task); return NULL; } residx = hasharray_index(seg->residue_hash, resid); if (residx == HASHARRAY_FAIL) { PyErr_Format(PyExc_ValueError, ""invalid resid '%s' for segment "" ""'%s'"", resid, segid); return NULL; } result = as_pystring(seg->residue_array[residx].name); } return result; } /* Module topology functions */ static PyObject* py_query_system(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""task"", NULL}; PyObject *stateptr, *result; psfgen_data *data = NULL; topo_defs *defs; char *task; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""Os:query_system"", (char**) kwnames, &stateptr, &task)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; result = PyList_New(0); if (!result) return NULL; defs = data->mol->defs; if (!strcasecmp(task, ""topologies"")) { for (int i = 0; i < hasharray_count(defs->topo_hash); i++) { if (PyList_Append(result, as_pystring(defs->topo_array[i].filename))) { PyErr_SetString(PyExc_ValueError, ""cannot enumerate topologies""); return NULL; } } } else if (!strcasecmp(task, ""patches"") || !strcasecmp(task, ""residues"")) { for (int i = 0; i < hasharray_count(defs->residue_hash); i++) { if ((!strcasecmp(task, ""patches"") && defs->residue_array[i].patch) || (!strcasecmp(task, ""residues"") && !defs->residue_array[i].patch)) { if (PyList_Append(result, as_pystring(defs->residue_array[i].name))) { PyErr_SetString(PyExc_ValueError, ""cannot enumerate residues""); return NULL; } } } } else { PyErr_Format(PyExc_ValueError, ""Task '%s' invalid system query"", task); return NULL; } return result; } static PyObject* py_parse_topology(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""filename"", NULL}; char *filename; PyObject *stateptr; psfgen_data *data = NULL; FILE *fd = NULL; int rc; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""Os:parse_topology"", (char**) kwnames, &stateptr, &filename)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; fd = fopen(filename, ""r""); if (!fd) { PyErr_Format(PyExc_OSError, ""cannot open topology file '%s'"", filename); return NULL; } rc = charmm_parse_topo_defs(data->defs, fd, data->all_caps, data->outstream, python_msg); fclose(fd); if (rc) { PyErr_Format(PyExc_ValueError, ""error parsing topology file '%s'"", filename); return NULL; } topo_defs_add_topofile(data->defs, filename); Py_INCREF(Py_None); return Py_None; } static PyObject* py_get_patches(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""listall"", NULL}; topo_mol_patchres_t *patchres; PyObject *stateptr, *result; topo_mol_patch_t *patch; psfgen_data *data; int listall = 0; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""O|O&:get_patches"", (char**) kwnames, &stateptr, convert_bool, &listall)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; result = PyList_New(0); if (!result) return NULL; for (patch = data->mol->patches; patch; patch = patch->next) { PyObject *patchtuple = NULL; if (patch->deflt && !listall) continue; // Find resids this patch is applied to for (patchres = patch->patchresids; patchres; patchres = patchres->next) { // If invalid patch for this residue, keep going if (!topo_mol_validate_patchres(data->mol, patch->pname, patchres->segid, patchres->resid)) { break; } // Generate a tuple of (patchname, segid, resid) patchtuple = PyTuple_Pack(3, as_pystring(patch->pname), as_pystring(patchres->segid), as_pystring(patchres->resid)); if (!patchtuple || PyList_Append(result, patchtuple)) { PyErr_Format(PyExc_ValueError, ""Patch %s %s:%s failed"", patch->pname, patchres->segid, patchres->resid); return NULL; } } } return result; } static PyObject* py_patch(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""patchname"", ""targets"", NULL}; PyObject *target_seq = NULL, *target = NULL; PyObject *stateptr, *targlist; topo_mol_ident_t *targets; psfgen_data *data; char *patchname; int ntargets; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""OsO:patch"", (char**) kwnames, &stateptr, &patchname, &targlist)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; if (!(target_seq = PySequence_Fast(targlist, ""patch targets must be a list "" ""or tuple!""))) return NULL; ntargets = (int) PySequence_Fast_GET_SIZE(target_seq); // Construct targets // It's a list/tuple of list/tuples targets = malloc(ntargets*sizeof(topo_mol_ident_t)); for (int i = 0; i < ntargets; ++i) { target = PySequence_Fast_GET_ITEM(target_seq, i); if (!(target = PySequence_Fast(PySequence_Fast_GET_ITEM(target_seq, i), ""patch targets must be a list or "" ""tuple of (segid, resid)""))) goto failure; if ((int)PySequence_Fast_GET_SIZE(target) != 2) { PyErr_SetString(PyExc_ValueError, ""patch target must be a list or tuple of "" ""(segid, resid)""); goto failure; } targets[i].segid = as_charptr(PySequence_Fast_GET_ITEM(target, 0)); targets[i].resid = as_charptr(PySequence_Fast_GET_ITEM(target, 1)); targets[i].aname = NULL; if (PyErr_Occurred()) goto failure; Py_XDECREF(target); } // Actually do the work if (topo_mol_patch(data->mol, targets, ntargets, patchname, 0, 0, 0, 0)) { PyErr_Format(PyExc_ValueError, ""Cannot apply patch %s"", patchname); goto failure; } free(targets); Py_XDECREF(target_seq); Py_INCREF(Py_None); return Py_None; failure: Py_XDECREF(target_seq); Py_XDECREF(target); free(targets); return NULL; } static PyObject* py_query_atoms(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""segid"", ""resid"", ""task"", NULL}; PyObject *stateptr, *result, *atomresult; char *segid, *resid, *task; topo_mol_segment_t *seg; topo_mol_atom_t *atoms; int segidx, residx; psfgen_data* data; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""Osss:query_atoms"", (char**) kwnames, &stateptr, &segid, &resid, &task)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; // Get segment index from segid segidx = hasharray_index(data->mol->segment_hash, segid); if (segidx == HASHARRAY_FAIL) { PyErr_Format(PyExc_ValueError, ""Segment '%s' does not exist"", segid); return NULL; } seg = data->mol->segment_array[segidx]; // Get residue index from segid and resid residx = hasharray_index(seg->residue_hash, resid); if (residx == HASHARRAY_FAIL) { PyErr_Format(PyExc_ValueError, ""No resid '%s' in segment '%s'"", resid, segid); return NULL; } // Loop through atoms in residue and add names to list result = PyList_New(0); atoms = seg->residue_array[residx].atoms; while (atoms) { if (!strcasecmp(task, ""name"")) { atomresult = as_pystring(atoms->name); } else if (!strcmp(task, ""coordinates"")) { atomresult = PyTuple_Pack(3, PyFloat_FromDouble(atoms->x), PyFloat_FromDouble(atoms->y), PyFloat_FromDouble(atoms->z)); } else if (!strcmp(task, ""velocities"")) { atomresult = PyTuple_Pack(3, PyFloat_FromDouble(atoms->vx), PyFloat_FromDouble(atoms->vy), PyFloat_FromDouble(atoms->vz)); } else if (!strcmp(task, ""mass"")) { atomresult = PyFloat_FromDouble(atoms->mass); } else if (!strcmp(task, ""charge"")) { atomresult = PyFloat_FromDouble(atoms->charge); } else if (!strcmp(task, ""atomid"")) { atomresult = as_pyint(atoms->atomid); } else { PyErr_Format(PyExc_ValueError, ""invalid atom task '%s'"", task); return NULL; } if (PyList_Append(result, atomresult)) { PyErr_SetString(PyExc_ValueError, ""cannot gather atoms""); return NULL; } atoms = atoms->next; } return result; } static PyObject* py_delete_atoms(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""segid"", ""resid"", ""aname"", NULL}; char *resid = NULL, *aname = NULL; topo_mol_ident_t target; PyObject *stateptr; psfgen_data *data; char *segid; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""Os|zz:delete_atoms"", (char**) kwnames, &stateptr, &segid, &resid, &aname)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; // Build target object target.segid = segid; target.resid = resid; target.aname = aname; if (topo_mol_delete_atom(data->mol, &target)) { PyErr_SetString(PyExc_ValueError, ""failed to delete atoms""); return NULL; } Py_INCREF(Py_None); return Py_None; } static PyObject* py_set_atom_attr(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""attribute"", ""segid"", ""value"", ""resid"", ""aname"", NULL}; char *aname = NULL, *resid = NULL; PyObject *stateptr, *valueobj; topo_mol_ident_t target; char *segid, *attr; psfgen_data *data; int rc = 0; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""OssO|zz:set_atom_attr"", (char**) kwnames, &stateptr, &attr, &segid, &valueobj, &resid, &aname)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; // Build target object with correct case sensitivity target.segid = strtoupper(segid, data->all_caps); target.resid = resid ? strtoupper(resid, data->all_caps) : NULL; target.aname = aname ? strtoupper(aname, data->all_caps) : NULL; // Sanity check for atom arguments. // Makes the next big if/else need much less error checking if (strcasecmp(attr, ""segid"") && strcasecmp(attr, ""resname"") && (!aname || !resid)) { PyErr_SetString(PyExc_ValueError, ""Need resid and atom name for set_atom_attr""); return NULL; } if (!strcasecmp(attr, ""segid"")) { if (resid || aname) { PyErr_SetString(PyExc_ValueError, ""resid/atom name will be ignored for set_segid""); rc = 1; } else rc = topo_mol_set_segid(data->mol, &target, as_charptr(valueobj)); } else if (!strcasecmp(attr, ""resname"")) { if (aname) { PyErr_SetString(PyExc_ValueError, ""atom name ignored for set_resname""); rc = 1; } else rc = topo_mol_set_resname(data->mol, &target, as_charptr(valueobj)); } else if (!strcasecmp(attr, ""name"")) { rc = topo_mol_set_name(data->mol, &target, as_charptr(valueobj)); } else if (!strcasecmp(attr, ""mass"")) { rc = topo_mol_set_mass(data->mol, &target, PyFloat_AsDouble(valueobj)); } else if (!strcasecmp(attr, ""charge"")) { rc = topo_mol_set_charge(data->mol, &target, PyFloat_AsDouble(valueobj)); } else if (!strcasecmp(attr, ""beta"")) { rc = topo_mol_set_bfactor(data->mol, &target, PyFloat_AsDouble(valueobj)); } else if (!strcasecmp(attr, ""vel"")) { // Unpack tuple to x, y, z double x, y, z; if (!PyTuple_Check(valueobj) || PyTuple_Size(valueobj) != 3) { PyErr_SetString(PyExc_ValueError, ""position must be a 3-tuple""); return NULL; } x = PyFloat_AsDouble(PyTuple_GetItem(valueobj, 0)); y = PyFloat_AsDouble(PyTuple_GetItem(valueobj, 1)); z = PyFloat_AsDouble(PyTuple_GetItem(valueobj, 2)); if (PyErr_Occurred()) return NULL; rc = topo_mol_set_vel(data->mol, &target, x, y, z); } else { rc = 1; } if (rc) { PyErr_Format(PyExc_ValueError, ""Cannot set atom attribute '%s'"", attr); return NULL; } Py_INCREF(Py_None); return Py_None; } static PyObject* py_set_coord(PyObject *self, PyObject *args, PyObject *kwargs) { const char *kwnames[] = {""psfstate"", ""segid"", ""resid"", ""aname"", ""position"", NULL}; PyObject *position, *stateptr; char *segid, *aname, *resid; topo_mol_ident_t target; psfgen_data *data; double x, y, z; if (!PyArg_ParseTupleAndKeywords(args, kwargs, ""OsssO:set_coord"", (char**) kwnames, &stateptr, &segid, &resid, &aname, &position)) { return NULL; } data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; // Unpack position tuple to x, y, z if (!PyTuple_Check(position) || PyTuple_Size(position) != 3) { PyErr_SetString(PyExc_ValueError, ""position must be a 3-tuple""); return NULL; } x = PyFloat_AsDouble(PyTuple_GetItem(position, 0)); y = PyFloat_AsDouble(PyTuple_GetItem(position, 1)); z = PyFloat_AsDouble(PyTuple_GetItem(position, 2)); if (PyErr_Occurred()) { return NULL; } // Build target object target.segid = segid; target.resid = resid; target.aname = aname; // Do the work if(topo_mol_set_xyz(data->mol, &target, x, y, z)) { PyErr_SetString(PyExc_ValueError, ""failed to set coordinates""); return NULL; } Py_INCREF(Py_None); return Py_None; } static PyObject* py_guess_coords(PyObject *self, PyObject *stateptr) { psfgen_data* data; // Unpack molecule capsule data = PyCapsule_GetPointer(stateptr, NULL); if (!data || PyErr_Occurred()) return NULL; if (topo_mol_guess_xyz(data->mol)) { PyErr_SetString(PyExc_ValueError, ""failed to guess coordinates""); return NULL; } Py_INCREF(Py_None); return Py_None; } /* Method definitions */ static PyMethodDef methods[] = { {""add_segment"", (PyCFunction)py_add_segment, METH_VARARGS | METH_KEYWORDS}, {""alias"", (PyCFunction)py_alias, METH_VARARGS | METH_KEYWORDS}, {""del_mol"", (PyCFunction)py_del_mol, METH_O}, {""delete_atoms"", (PyCFunction)py_delete_atoms, METH_VARARGS | METH_KEYWORDS}, {""init_mol"", (PyCFunction)py_init_mol, METH_VARARGS | METH_KEYWORDS}, {""get_patches"", (PyCFunction)py_get_patches, METH_VARARGS | METH_KEYWORDS}, {""guess_coords"", (PyCFunction)py_guess_coords, METH_O}, {""parse_topology"", (PyCFunction)py_parse_topology, METH_VARARGS | METH_KEYWORDS}, {""patch"", (PyCFunction)py_patch, METH_VARARGS | METH_KEYWORDS}, {""query_system"", (PyCFunction)py_query_system, METH_VARARGS | METH_KEYWORDS}, {""query_segment"", (PyCFunction)py_query_segment, METH_VARARGS | METH_KEYWORDS}, {""query_atoms"", (PyCFunction)py_query_atoms, METH_VARARGS | METH_KEYWORDS}, {""read_coords"", (PyCFunction)py_read_coords, METH_VARARGS | METH_KEYWORDS}, {""read_psf"", (PyCFunction)py_read_psf, METH_VARARGS | METH_KEYWORDS}, {""regenerate"", (PyCFunction)py_regenerate, METH_VARARGS | METH_KEYWORDS}, {""set_allcaps"", (PyCFunction)py_set_allcaps, METH_VARARGS | METH_KEYWORDS}, {""set_coord"", (PyCFunction)py_set_coord, METH_VARARGS | METH_KEYWORDS}, {""set_atom_attr"", (PyCFunction)py_set_atom_attr, METH_VARARGS | METH_KEYWORDS}, {""write_psf"", (PyCFunction)py_write_psf, METH_VARARGS | METH_KEYWORDS}, {""write_pdb"", (PyCFunction)py_write_pdb, METH_VARARGS | METH_KEYWORDS}, {""write_namdbin"", (PyCFunction)py_write_namdbin, METH_VARARGS | METH_KEYWORDS}, {NULL, NULL, 0, NULL} }; /* Module initialization functions * Python 2 and 3 are totally separate here for clarity */ #if PY_MAJOR_VERSION >= 3 static struct PyModuleDef psfgendef = { PyModuleDef_HEAD_INIT, ""_psfgen"", NULL, -1, methods, }; PyMODINIT_FUNC PyInit__psfgen(void) { PyObject *m = PyModule_Create(&psfgendef); return m; } #else PyMODINIT_FUNC init_psfgen(void) { Py_InitModule(""_psfgen"", methods); } #endif ","C" "Biophysics","Eigenstate/psfgen","src/psf_file.h",".h","682","20"," #ifndef PSF_FILE_H #define PSF_FILE_H #include int psf_start_atoms(FILE *); int psf_start_block(FILE *, const char *blockstr); int psf_get_atom(FILE *f, char *name, char *atype, char *resname, char *segname, char *resid, double *q, double *m); int psf_get_bonds(FILE *f, int fw, int n, int *bonds); int psf_get_angles(FILE *f, int fw, int n, int *angles); int psf_get_dihedrals(FILE *f, int fw, int n, int *dihedrals); int psf_get_impropers(FILE *f, int fw, int n, int *impropers); int psf_get_cmaps(FILE *f, int fw, int n, int *cmaps); int psf_get_exclusions(FILE *f, int fw, int nexcl, int *exclusions, int natom, int *exclusion_indices); #endif ","Unknown" "Biophysics","Eigenstate/psfgen","src/topo_mol.h",".h","2890","88"," #ifndef TOPO_MOL_H #define TOPO_MOL_H #include ""topo_defs.h"" struct topo_mol; typedef struct topo_mol topo_mol; topo_mol * topo_mol_create(topo_defs *defs); void topo_mol_destroy(topo_mol *mol); void topo_mol_error_handler(topo_mol *mol, void *, void (*print_msg)(void *,const char *)); int topo_mol_segment(topo_mol *mol, const char *segid); int topo_mol_segment_first(topo_mol *mol, const char *rname); int topo_mol_segment_last(topo_mol *mol, const char *rname); int topo_mol_segment_auto_angles(topo_mol *mol, int autogen); int topo_mol_segment_auto_dihedrals(topo_mol *mol, int autogen); int topo_mol_residue(topo_mol *mol, const char *resid, const char *rname, const char *chain); int topo_mol_mutate(topo_mol *mol, const char *resid, const char *rname); int topo_mol_end(topo_mol *mol); typedef struct topo_mol_ident_t { const char *segid; const char *resid; const char *aname; } topo_mol_ident_t; int topo_mol_patch(topo_mol *mol, const topo_mol_ident_t *targets, int ntargets, const char *rname, int prepend, int warn_angles, int warn_dihedrals, int deflt); int topo_mol_regenerate_angles(topo_mol *mol); int topo_mol_regenerate_dihedrals(topo_mol *mol); int topo_mol_regenerate_resids(topo_mol *mol); int topo_mol_delete_atom(topo_mol *mol, const topo_mol_ident_t *target); int topo_mol_set_name(topo_mol *mol, const topo_mol_ident_t *target, const char *name); int topo_mol_set_resname(topo_mol *mol, const topo_mol_ident_t *target, const char *rname); int topo_mol_set_segid(topo_mol *mol, const topo_mol_ident_t *target, const char *segid); int topo_mol_multiply_atoms(topo_mol *mol, const topo_mol_ident_t *targets, int ntargets, int ncopies); int topo_mol_set_element(topo_mol *mol, const topo_mol_ident_t *target, const char *element, int replace); int topo_mol_set_chain(topo_mol *mol, const topo_mol_ident_t *target, const char *chain, int replace); int topo_mol_set_xyz(topo_mol *mol, const topo_mol_ident_t *target, double x, double y, double z); int topo_mol_set_vel(topo_mol *mol, const topo_mol_ident_t *target, double vx, double vy, double vz); int topo_mol_set_mass(topo_mol *mol, const topo_mol_ident_t *target, double mass); int topo_mol_set_charge(topo_mol *mol, const topo_mol_ident_t *target, double charge); int topo_mol_set_bfactor(topo_mol *mol, const topo_mol_ident_t *target, double bfactor); int topo_mol_guess_xyz(topo_mol *mol); int topo_mol_add_patch(topo_mol *mol, const char *pname, int deflt); int topo_mol_add_patchres(topo_mol *mol, const topo_mol_ident_t *targets); int topo_mol_validate_patchres(topo_mol *mol, const char *pname, const char *segid, const char *resid); #endif ","Unknown" "Biophysics","Eigenstate/psfgen","src/stringhash.c",".c","1673","72"," #include #include #include ""memarena.h"" #include ""hasharray.h"" #include ""stringhash.h"" struct stringhash { memarena *datarena; char **datarray; hasharray *ha; }; stringhash * stringhash_create(void) { stringhash *h; if ( (h = (stringhash*) malloc(sizeof(stringhash))) ) { if ( ! ( h->datarena = memarena_create() ) ) { free((void*)h); return 0; } if ( ! ( h->ha = hasharray_create((void**)&(h->datarray),sizeof(char*)) ) ) { memarena_destroy(h->datarena); free((void*)h); return 0; } } return h; } void stringhash_destroy(stringhash *h) { if ( ! h ) return; memarena_destroy(h->datarena); hasharray_destroy(h->ha); free((void*)h); } const char* stringhash_insert(stringhash *h, const char *key, const char *data) { int i; char *s; if ( ! h ) return STRINGHASH_FAIL; i = hasharray_insert(h->ha,key); if ( i == HASHARRAY_FAIL ) return STRINGHASH_FAIL; h->datarray[i] = s = memarena_alloc(h->datarena,strlen(data)+1); if ( ! s ) { h->datarray[i] = STRINGHASH_FAIL; /* should always be 0 */ return STRINGHASH_FAIL; } strcpy(s,data); return s; } const char* stringhash_lookup(stringhash *h, const char *key) { int i; if ( ! h ) return STRINGHASH_FAIL; i = hasharray_index(h->ha,key); if ( i == HASHARRAY_FAIL ) return STRINGHASH_FAIL; return h->datarray[i]; } const char* stringhash_delete(stringhash *h, const char *key) { int i; char *s; if ( ! h ) return STRINGHASH_FAIL; i = hasharray_index(h->ha,key); if ( i == HASHARRAY_FAIL ) return STRINGHASH_FAIL; s = h->datarray[i]; h->datarray[i] = STRINGHASH_FAIL; return s; } ","C" "Biophysics","Eigenstate/psfgen","src/pdb_file.c",".c","7375","278"," /*************************************************************************** * DESCRIPTION: * * General routines to read .pdb files. * ***************************************************************************/ #include #include #include #include ""pdb_file.h"" /* read the next record from the specified pdb file, and put the string found in the given string pointer (the caller must provide adequate (81 chars) buffer space); return the type of record found */ int read_pdb_record(FILE *f, char *retStr) { char inbuf[PDB_RECORD_LENGTH+2]; int recType = PDB_UNKNOWN; /* read the next line */ if(inbuf != fgets(inbuf, PDB_RECORD_LENGTH+1, f)) { strcpy(retStr,""""); recType = PDB_EOF; } else { /* remove the newline character, if there is one */ if(inbuf[strlen(inbuf)-1] == '\n') inbuf[strlen(inbuf)-1] = '\0'; /* what was it? */ if (!strncmp(inbuf, ""REMARK"", 6)) { recType = PDB_REMARK; } else if (!strncmp(inbuf, ""CRYST1"", 6)) { recType = PDB_CRYST1; } else if (!strncmp(inbuf, ""ATOM "", 6) || !strncmp(inbuf, ""HETATM"", 6)) { recType = PDB_ATOM; /* the only two END records are ""END "" and ""ENDMDL"" */ } else if (!strcmp(inbuf, ""END"") || /* If not space "" "" filled */ !strncmp(inbuf, ""END "", 4) || /* Allows other stuff */ !strncmp(inbuf, ""ENDMDL"", 6)) { /* NMR records */ recType = PDB_END; } else { recType = PDB_UNKNOWN; } if(recType == PDB_REMARK || recType == PDB_ATOM || recType == PDB_CRYST1) { strcpy(retStr,inbuf); } else { strcpy(retStr,""""); } } /* read the '\r', if there was one */ { int ch = fgetc(f); if (ch != '\r') { ungetc(ch, f); } } return recType; } void get_pdb_cryst1(char *record, float *alpha, float *beta, float *gamma, float *a, float *b, float *c) { char tmp[81]; char ch, *s; int i; for (i=0; i<81; i++) tmp[i] = 0; strncpy(tmp, record, 80); tmp[80] = 0; s = tmp; s = tmp+6 ; ch = tmp[15]; tmp[15] = 0; *a = (float) atof(s); s = tmp+15; *s = ch; ch = tmp[24]; tmp[24] = 0; *b = (float) atof(s); s = tmp+24; *s = ch; ch = tmp[33]; tmp[33] = 0; *c = (float) atof(s); s = tmp+33; *s = ch; ch = tmp[40]; tmp[40] = 0; *alpha = (float) atof(s); s = tmp+40; *s = ch; ch = tmp[47]; tmp[47] = 0; *beta = (float) atof(s); s = tmp+47; *s = ch; ch = tmp[54]; tmp[54] = 0; *gamma = (float) atof(s); } /* Extract the x,y, and z coordinates from the given ATOM record. */ void get_pdb_coordinates(char *record, float *x, float *y, float *z, float *occup, float *beta) { char numstr[9]; /* get X, Y, and Z */ memset(numstr, 0, 9 * sizeof(char)); strncpy(numstr, record + 30, 8); *x = (float) atof(numstr); memset(numstr, 0, 9 * sizeof(char)); strncpy(numstr, record + 38, 8); *y = (float) atof(numstr); memset(numstr, 0, 9 * sizeof(char)); strncpy(numstr, record + 46, 8); *z = (float) atof(numstr); memset(numstr, 0, 9 * sizeof(char)); strncpy(numstr, record + 54, 6); *occup = (float) atof(numstr); memset(numstr, 0, 9 * sizeof(char)); strncpy(numstr, record + 60, 6); *beta = (float) atof(numstr); } /* Break a pdb ATOM record into its fields. The user must provide the necessary space to store the atom name, residue name, and segment name. Character strings will be null-terminated. Returns the atom serial number. */ int get_pdb_fields(char *record, char *name, char *resname, char *chain, char *segname, char *element, char *resid, char *insertion, float *x, float *y, float *z, float *occup, float *beta) { int i,len, num, base; num=0; /* get serial number */ if (record[6] >= 'A' && record[6] <= 'Z') { /* If there are too many atoms, XPLOR uses 99998, 99999, A0000, A0001, */ base = ((int)(record[6] - 'A') + 10) * 100000; sscanf(record + 6, ""%d"", &num); num += base; } else { sscanf(record + 6,""%d"",&num); } /* get atom name */ strncpy(name,record + 12, 4); name[4] = '\0'; while((len = strlen(name)) > 0 && name[len-1] == ' ') name[len-1] = '\0'; while(len > 0 && name[0] == ' ') { for(i=0; i < len; i++) name[i] = name[i+1]; len--; } /* get residue name */ strncpy(resname,record + 17, 4); resname[4] = '\0'; while((len = strlen(resname)) > 0 && resname[len-1] == ' ') resname[len-1] = '\0'; while(len > 0 && resname[0] == ' ') { for(i=0; i < len; i++) resname[i] = resname[i+1]; len--; } chain[0] = record[21]; if ( chain[0] == ' ' ) chain[0] = 0; else chain[1] = 0; /* get residue id number plus insertion code */ strncpy(resid,record + 22, 4); resid[4] = '\0'; while((len = strlen(resid)) > 0 && resid[len-1] == ' ') resid[len-1] = '\0'; if ( record[26] != ' ' ) { resid[len] = record[26]; resid[++len] = '\0'; } while(len > 0 && resid[0] == ' ') { for(i=0; i < len; i++) resid[i] = resid[i+1]; len--; } insertion[0] = record[26]; insertion[1] = 0; /* get x, y, and z coordinates */ get_pdb_coordinates(record, x, y, z, occup, beta); /* get segment name */ if(strlen(record) >= 73) { strncpy(segname, record + 72, 4); segname[4] = '\0'; while((len = strlen(segname)) > 0 && segname[len-1] == ' ') segname[len-1] = '\0'; while(len > 0 && segname[0] == ' ') { for(i=0; i < len; i++) segname[i] = segname[i+1]; len--; } } else { strcpy(segname,""""); } /* get element name */ if(strlen(record) >= 77) { strncpy(element, record + 76, 2); element[2] = '\0'; while((len = strlen(element)) > 0 && element[len-1] == ' ') element[len-1] = '\0'; while(len > 0 && element[0] == ' ') { for(i=0; i < len; i++) element[i] = element[i+1]; len--; } } else { strcpy(element,""""); } return num; } void write_pdb_remark(FILE *outfile, const char *comment) { fprintf(outfile,""REMARK %s\n"",comment); } void write_pdb_end(FILE *outfile) { fprintf(outfile,""END\n""); } void write_pdb_atom(FILE *outfile, int index,char *atomname,char *resname,int resid, char *insertion, float x, float y, float z, float occ, float beta, char *chain, char *segname, char *element) { char name[6], rname[5], sname[5]; char chainc, insertionc; int p; name[0] = ' '; strncpy(name+1, atomname, 4); name[5] = '\0'; if ( strlen(name) == 5 ) { atomname = name + 1; } else { atomname = name; while((p = strlen(name)) < 4) { name[p] = ' '; name[p+1] = '\0'; } } strncpy(rname, resname, 4); rname[4] = '\0'; resname = rname; chainc = ( chain[0] ? chain[0] : ' ' ); resid = resid % 10000; insertionc = ( insertion[0] ? insertion[0] : ' ' ); strncpy(sname, segname, 4); sname[4] = '\0'; segname = sname; if (index < 100000) { fprintf(outfile, ""%s%5d %4s%c%-4s%c%4d%c %8.3f%8.3f%8.3f%6.2f%6.2f %-4s%2s\n"", ""ATOM "", index, atomname, ' ', resname, chainc, resid, insertionc, x, y, z, occ, beta, segname, element); } else { fprintf(outfile, ""%s***** %4s%c%-4s%c%4d%c %8.3f%8.3f%8.3f%6.2f%6.2f %-4s%2s\n"", ""ATOM "", atomname, ' ', resname, chainc, resid, insertionc, x, y, z, occ, beta, segname, element); } } ","C" "Biophysics","Eigenstate/psfgen","src/charmm_parse_topo_defs.c",".c","15124","432"," #include #include #include #include #include ""charmm_file.h"" #include ""topo_defs.h"" #include ""charmm_parse_topo_defs.h"" #if defined(_MSC_VER) #define strcasecmp stricmp #define strncasecmp strnicmp #endif #define TOKLEN 100 #define BUFLEN 200 static char * parse_atom(char *aref, int *res, int *rel) { if ( isdigit(*aref) ) { *res = *aref - '1'; ++aref; } else { *res = 0; } if ( *aref == '-' ) { *rel = -1; ++aref; } else if ( *aref == '+' ) { *rel = 1; ++aref; } else if ( *aref == '#' ) { *rel = 2; ++aref; } else { *rel = 0; } return aref; } static void null_print_msg(void *v, const char *s) { printf(""%s\n"", s); } static void debug_msg(const char *s) { ; } #define PRINT_ERROR(MSG) do {\ sprintf(msgbuf, ""ERROR! "" MSG "" Line %d: %s"", lineno, lbuf);\ print_msg(v,msgbuf);\ } while (0) int charmm_parse_topo_defs(topo_defs *defs, FILE *file, int all_caps, void *v, void (*print_msg)(void *,const char *)) { char *tok[TOKLEN]; char sbuf[BUFLEN]; char lbuf[BUFLEN]; char msgbuf[2*BUFLEN]; int lineno; int ntok; int itok; int first; int skip; int skipall; int stream; char *s1, *s2, *s3, *s4; int i1, i2, i3, i4; int j1, j2, j3, j4; unsigned int utmp; lineno = 0; first = 1; skip = 0; skipall = 0; stream = 0; if ( ! defs ) return -1; if ( ! file ) return -2; if ( print_msg == 0 ) print_msg = null_print_msg; while ( (ntok = charmm_get_tokens(tok,TOKLEN,sbuf,BUFLEN,lbuf,&lineno,file,all_caps)) ) { if ( ! tok[0][0] ) { print_msg(v,tok[1]); continue; } if ( skipall ) { print_msg (v, ""skipping statements at end of file due to end or return statement""); break; } if ( first ) { first = 0; if ( ! strncasecmp(""IOFORMAT"",tok[0],8) ) { first = 1; continue; } else if ( ntok == 2 && sscanf(tok[0],""%u"",&utmp) == 1 && sscanf(tok[1],""%u"",&utmp) == 1 ) { sprintf(msgbuf,""Created by CHARMM version %s %s"",tok[0],tok[1]); print_msg(v,msgbuf); continue; } else if ( ntok == 1 && sscanf(tok[0],""%u"",&utmp) == 1 ) { sprintf(msgbuf,""Created by CHARMM version %s"",tok[0]); print_msg(v,msgbuf); continue; } } if ( ! strncasecmp(""READ"",tok[0],4) && ! strncasecmp(""RTF"",tok[1],4) ) { print_msg (v, ""reading topology from stream file""); skip = 0; first = 1; stream = 1; continue; } else if ( ! strncasecmp(""READ"",tok[0],4) && ! strncasecmp(""PARA"",tok[1],4) ) { print_msg (v, ""skipping parameters in stream file""); skip = 1; continue; } else if ( ! strncasecmp(""READ"",tok[0],4) ) { print_msg (v, ""skipping unknown section in stream file""); skip = 1; continue; } if ( skip ) { if ( ! strncasecmp(""END"",tok[0],4) ) { debug_msg(""Recognized file end statement in skipped section.""); skip = 0; first = 1; } } else if ( ! strncasecmp(""END"",tok[0],4) ) { debug_msg(""Recognized file end statement.""); if ( stream ) { stream = 0; first = 1; } else { skipall = 1; } } else if ( ! strncasecmp(""RETURN"",tok[0],4) ) { debug_msg(""Recognized return statement.""); skipall = 1; } else if ( ! strncasecmp(""ACCE"",tok[0],4) ) { debug_msg(""Recognized acceptor statement.""); } else if ( ! strncasecmp(""DONO"",tok[0],4) ) { debug_msg(""Recognized donor statement.""); } else if ( ! strncasecmp(""BOND"",tok[0],4) || ! strncasecmp(""DOUB"",tok[0],4) || ! strncasecmp(""TRIP"",tok[0],4) ) { debug_msg(""Recognized bond statement.""); if ( ntok < 3 || (ntok-1)%2 ) { PRINT_ERROR(""Failed to parse bond statement.""); } else { for ( itok = 1; itok < ntok; itok += 2 ) { s1 = parse_atom(tok[itok],&i1,&j1); s2 = parse_atom(tok[itok+1],&i2,&j2); if ( topo_defs_bond(defs,0,0,s1,i1,j1,s2,i2,j2) ) PRINT_ERROR(""Failed to parse bond statement.""); } } } else if ( ! strncasecmp(""ANGL"",tok[0],4) || ! strncasecmp(""THET"",tok[0],4) ) { debug_msg(""Recognized angle statement.""); if ( ntok < 4 || (ntok-1)%3 ) { PRINT_ERROR(""Failed to parse angle statement.""); } else { for ( itok = 1; itok < ntok; itok += 3 ) { s1 = parse_atom(tok[itok],&i1,&j1); s2 = parse_atom(tok[itok+1],&i2,&j2); s3 = parse_atom(tok[itok+2],&i3,&j3); if ( topo_defs_angle(defs,0,0,s1,i1,j1,s2,i2,j2,s3,i3,j3) ) PRINT_ERROR(""Failed to parse angle statement.""); } } } else if ( ! strncasecmp(""DIHE"",tok[0],4) ) { debug_msg(""Recognized dihedral statement.""); if ( ntok < 5 || (ntok-1)%4 ) { PRINT_ERROR(""Failed to parse dihedral statement.""); } else { for ( itok = 1; itok < ntok; itok += 4 ) { s1 = parse_atom(tok[itok],&i1,&j1); s2 = parse_atom(tok[itok+1],&i2,&j2); s3 = parse_atom(tok[itok+2],&i3,&j3); s4 = parse_atom(tok[itok+3],&i4,&j4); if (topo_defs_dihedral(defs,0,0,s1,i1,j1,s2,i2,j2,s3,i3,j3,s4,i4,j4)) PRINT_ERROR(""Failed to parse dihedral statement.""); } } } else if ( ! strncasecmp(""IMPH"",tok[0],4) || ! strncasecmp(""IMPR"",tok[0],4) ) { debug_msg(""Recognized improper statement.""); if ( ntok < 5 || (ntok-1)%4 ) { PRINT_ERROR(""Failed to parse improper statement.""); } else { for ( itok = 1; itok < ntok; itok += 4 ) { s1 = parse_atom(tok[itok],&i1,&j1); s2 = parse_atom(tok[itok+1],&i2,&j2); s3 = parse_atom(tok[itok+2],&i3,&j3); s4 = parse_atom(tok[itok+3],&i4,&j4); if (topo_defs_improper(defs,0,0,s1,i1,j1,s2,i2,j2,s3,i3,j3,s4,i4,j4)) PRINT_ERROR(""Failed to parse improper statement.""); } } } else if ( ! strncasecmp(""CMAP"",tok[0],4) ) { debug_msg(""Recognized CMAP statement.""); if ( ntok != 9 ) { PRINT_ERROR(""Failed to parse CMAP statement.""); } else { const char* s[8]; int i[8], j[8]; for ( itok = 0; itok < 8; ++itok ) { s[itok] = parse_atom(tok[itok+1],&i[itok],&j[itok]); } if (topo_defs_cmap(defs,0,0,s,i,j)) PRINT_ERROR(""Failed to parse CMAP statement.""); } } else if ( ! strncasecmp(""DECL"",tok[0],4) ) { debug_msg(""Recognized atom declaration statement.""); } else if ( ! strncasecmp(""ATOM"",tok[0],4) ) { debug_msg(""Recognized atom statement.""); if ( ntok == 2 ) { s1 = parse_atom(tok[1],&i1,&j1); if ( topo_defs_atom(defs,0,0, s1,i1,j1,"""",0.0) ) { PRINT_ERROR(""Failed to parse atom statement.""); } } else if ( ntok != 2 && ntok < 4 ) { PRINT_ERROR(""Failed to parse atom statement.""); } else { s1 = parse_atom(tok[1],&i1,&j1); if ( topo_defs_atom(defs,0,0, s1,i1,j1,tok[2],atof(tok[3])) ) { PRINT_ERROR(""Failed to parse atom statement.""); } } if ( ntok > 4 ) { /* Parse explicit exclusions */ s1 = parse_atom(tok[1],&i1,&j1); for ( itok = 4; itok < ntok; ++itok ) { s2 = parse_atom(tok[itok],&i2,&j2); if ( topo_defs_exclusion(defs,0,0,s1,i1,j1,s2,i2,j2) ) PRINT_ERROR(""Failed to parse bond statement.""); } } } else if ( ! strncasecmp(""MASS"",tok[0],4) ) { debug_msg(""Recognized mass statement.""); if ( ntok < 4 || topo_defs_type(defs,tok[2],(ntok>4?tok[4]:""""),atof(tok[3]),atoi(tok[1])) ) { PRINT_ERROR(""Failed to parse mass statement.""); } } else if ( ! strncasecmp(""AUTO"",tok[0],4) ) { debug_msg(""Recognized autogenerate statement.""); for ( itok = 1; itok < ntok; itok += 1 ) { if ( ! strncasecmp(""ANGL"",tok[itok],4) ) { topo_defs_auto_angles(defs,1); } else if ( ! strncasecmp(""DIHE"",tok[itok],4) ) { topo_defs_auto_dihedrals(defs,1); } else { PRINT_ERROR(""Failed to parse autogenerate statement.""); } } } else if ( ! strncasecmp(""DEFA"",tok[0],4) ) { debug_msg(""Recognized default patch statement.""); if ( ntok < 3 || (ntok-1)%2 ) { PRINT_ERROR(""Failed to parse default patching statement.""); } else { i1 = i2 = 0; for ( itok = 1; itok < ntok; itok += 2 ) { if ( ! strncasecmp(""FIRS"",tok[itok],4) ) { i1 = topo_defs_default_patching_first(defs,tok[itok+1]); } else if ( ! strncasecmp(""LAST"",tok[itok],4) ) { i2 = topo_defs_default_patching_last(defs,tok[itok+1]); } else { PRINT_ERROR(""Failed to parse default patching statement.""); } } if ( i1 || i2 ) PRINT_ERROR(""Failed to parse default patching statement.""); } } else if ( ! strncasecmp(""BILD"",tok[0],4) || ! strncasecmp(""IC"",tok[0],4) ) { debug_msg(""Recognized internal coordinate statement.""); if ( ntok < 10 ) { PRINT_ERROR(""Failed to parse internal coordinate statement.""); } else { s1 = parse_atom(tok[1],&i1,&j1); s2 = parse_atom(tok[2],&i2,&j2); s3 = tok[3] + ( tok[3][0] == '*' ? 1 : 0 ); s3 = parse_atom(s3,&i3,&j3); s4 = parse_atom(tok[4],&i4,&j4); if ( topo_defs_conformation(defs,0,0, s1,i1,j1,s2,i2,j2,s3,i3,j3,s4,i4,j4, atof(tok[5]),atof(tok[6]),atof(tok[7]), (tok[3][0]=='*'?1:0),atof(tok[8]),atof(tok[9])) ) PRINT_ERROR(""Failed to parse internal coordinate statement.""); } } else if ( ! strncasecmp(""DELE"",tok[0],4) ) { debug_msg(""Recognized delete statement.""); if ( ntok < 2 ) { PRINT_ERROR(""Failed to parse delete statement.""); } else { if ( ! strncasecmp(""ATOM"",tok[1],4) ) { if ( ntok < 3 ) { PRINT_ERROR(""Failed to parse delete atom statement.""); } else { s1 = parse_atom(tok[2],&i1,&j1); if ( topo_defs_atom(defs,0,1, s1,i1,j1,""DEL"",0.0) ) { PRINT_ERROR(""Failed to parse delete atom statement.""); } } } else if ( ! strncasecmp(""ACCE"",tok[1],4) ) { ; } else if ( ! strncasecmp(""DONO"",tok[1],4) ) { ; } else if ( ! strncasecmp(""BOND"",tok[1],4) || ! strncasecmp(""DOUB"",tok[1],4) || ! strncasecmp(""TRIP"",tok[1],4) ) { if ( ntok < 4 || (ntok-2)%2 ) { PRINT_ERROR(""Failed to parse delete bond statement.""); } else { for ( itok = 2; itok < ntok; itok += 2 ) { s1 = parse_atom(tok[itok],&i1,&j1); s2 = parse_atom(tok[itok+1],&i2,&j2); if ( topo_defs_bond(defs,0,1,s1,i1,j1,s2,i2,j2) ) PRINT_ERROR(""Failed to parse delete bond statement.""); } } } else if ( ! strncasecmp(""ANGL"",tok[1],4) || ! strncasecmp(""THET"",tok[1],4) ) { if ( ntok < 5 || (ntok-2)%3 ) { PRINT_ERROR(""Failed to parse delete angle statement.""); } else { for ( itok = 2; itok < ntok; itok += 3 ) { s1 = parse_atom(tok[itok],&i1,&j1); s2 = parse_atom(tok[itok+1],&i2,&j2); s3 = parse_atom(tok[itok+2],&i3,&j3); if ( topo_defs_angle(defs,0,1,s1,i1,j1,s2,i2,j2,s3,i3,j3) ) PRINT_ERROR(""Failed to parse delete angle statement.""); } } } else if ( ! strncasecmp(""DIHE"",tok[1],4) ) { if ( ntok < 6 || (ntok-2)%4 ) { PRINT_ERROR(""Failed to parse delete dihedral statement.""); } else { for ( itok = 2; itok < ntok; itok += 4 ) { s1 = parse_atom(tok[itok],&i1,&j1); s2 = parse_atom(tok[itok+1],&i2,&j2); s3 = parse_atom(tok[itok+2],&i3,&j3); s4 = parse_atom(tok[itok+3],&i4,&j4); if (topo_defs_dihedral(defs,0,1,s1,i1,j1,s2,i2,j2,s3,i3,j3,s4,i4,j4)) PRINT_ERROR(""Failed to parse delete dihedral statement.""); } } } else if ( ! strncasecmp(""IMPH"",tok[1],4) || ! strncasecmp(""IMPR"",tok[1],4) ) { if ( ntok < 6 || (ntok-2)%4 ) { PRINT_ERROR(""Failed to parse delete improper statement.""); } else { for ( itok = 2; itok < ntok; itok += 4 ) { s1 = parse_atom(tok[itok],&i1,&j1); s2 = parse_atom(tok[itok+1],&i2,&j2); s3 = parse_atom(tok[itok+2],&i3,&j3); s4 = parse_atom(tok[itok+3],&i4,&j4); if (topo_defs_improper(defs,0,1,s1,i1,j1,s2,i2,j2,s3,i3,j3,s4,i4,j4)) PRINT_ERROR(""Failed to parse delete improper statement.""); } } } else if ( ! strncasecmp(""BILD"",tok[1],4) || ! strncasecmp(""IC"",tok[1],4) ) { if ( ntok < 6 ) { PRINT_ERROR(""Failed to parse delete internal coordinate statement.""); } else { s1 = parse_atom(tok[2],&i1,&j1); s2 = parse_atom(tok[3],&i2,&j2); s3 = tok[4] + ( tok[4][0] == '*' ? 1 : 0 ); s3 = parse_atom(s3,&i3,&j3); s4 = parse_atom(tok[5],&i4,&j4); if ( topo_defs_conformation(defs,0,1, s1,i1,j1,s2,i2,j2,s3,i3,j3,s4,i4,j4, 0,0,0,(tok[4][0]=='*'?1:0),0,0) ) PRINT_ERROR(""Failed to parse delete internal coordinate statement.""); } } else { PRINT_ERROR(""Failed to parse delete statement.""); } } } else if ( ! strncasecmp(""GROU"",tok[0],4) ) { debug_msg(""Recognized group statement.""); } else if ( ! strncasecmp(""PATC"",tok[0],4) ) { debug_msg(""Recognized patching statement.""); if ( ntok < 3 || (ntok-1)%2 ) { PRINT_ERROR(""Failed to parse patching statement.""); } else { i1 = i2 = 0; for ( itok = 1; itok < ntok; itok += 2 ) { if ( ! strncasecmp(""FIRS"",tok[itok],4) ) { i1 = topo_defs_patching_first(defs,0,tok[itok+1]); } else if ( ! strncasecmp(""LAST"",tok[itok],4) ) { i2 = topo_defs_patching_last(defs,0,tok[itok+1]); } else { PRINT_ERROR(""Failed to parse patching statement.""); } } if ( i1 || i2 ) PRINT_ERROR(""Failed to parse patching statement.""); } } else if ( ! strncasecmp(""RESI"",tok[0],4) ) { debug_msg(""Recognized residue statement.""); if ( ntok < 2 || topo_defs_residue(defs,tok[1],0) ) { PRINT_ERROR(""Failed to parse residue statement.""); } } else if ( ! strncasecmp(""PRES"",tok[0],4) ) { debug_msg(""Recognized patch residue statement.""); if ( ntok < 2 || topo_defs_residue(defs,tok[1],1) ) { PRINT_ERROR(""Failed to parse patch residue statement.""); } } else { debug_msg(""Ignoring lonepair statement""); } } topo_defs_end(defs); return 0; } ","C" "Biophysics","Eigenstate/psfgen","src/pdb_file.h",".h","1858","57"," /*************************************************************************** * DESCRIPTION: * * General routines to read .pdb files. * ***************************************************************************/ #ifndef READ_PDB_H #define READ_PDB_H #include #define PDB_RECORD_LENGTH 80 /* record type defines */ enum {PDB_REMARK, PDB_ATOM, PDB_UNKNOWN, PDB_END, PDB_EOF, PDB_CRYST1}; /* read the next record from the specified pdb file, and put the string found in the given string pointer (the caller must provide adequate (81 chars) buffer space); return the type of record found */ int read_pdb_record(FILE *f, char *retStr); /* get the CRYST1 information about the unit cell (but not space group) */ void get_pdb_cryst1(char *record, float *alpha, float *beta, float *gamma, float *a, float *b, float *c); /* Extract the x,y, and z coordinates from the given ATOM record. */ void get_pdb_coordinates(char *record, float *x, float *y, float *z, float *occup, float *beta); /* Break a pdb atom record into it's fields. The user must provide the necessary space to store the atom name, residue name, and segment name. Character strings will be null-terminated. Returns the atom serial number. */ int get_pdb_fields(char *record, char *name, char *resname, char *chain, char *segname, char *element, char *resid, char *insertion, float *x, float *y, float *z, float *occup, float *beta); /* Write a remark to a pdb file. */ void write_pdb_remark(FILE *outfile, const char *comment); /* Write end to a pdb file */ void write_pdb_end(FILE *outfile); /* Write a pdb file atom record */ void write_pdb_atom(FILE *outfile, int index,char *atomname,char *resname,int resid, char *insertion, float x, float y, float z, float occ, float beta, char *chain, char *segname, char *element); #endif ","Unknown" "Biophysics","Eigenstate/psfgen","src/hash.c",".c","6068","278","/* * hash.c - A simple hash table * * Uses null terminated strings as the keys for the table. * Stores an integer value with the string key. It would be * easy to change to use void *'s instead of ints. Maybe rewrite * as a C++ template?? * * Donated by John Stone */ #include #include #include #include ""hash.h"" #define HASH_LIMIT 0.5 /* * Local types */ typedef struct hash_node_t { int data; /* data in hash node */ const char * key; /* key for hash lookup */ struct hash_node_t *next; /* next node in hash chain */ } hash_node_t; /* * hash() - Hash function returns a hash number for a given key. * * tptr: Pointer to a hash table * key: The key to create a hash number for */ static int hash(hash_t *tptr, const char *key) { int i=0; int hashvalue; while (*key != '\0') i=(i<<3)+(*key++ - '0'); hashvalue = (((i*1103515249)>>tptr->downshift) & tptr->mask); if (hashvalue < 0) { hashvalue = 0; } return hashvalue; } /* * rebuild_table() - Create new hash table when old one fills up. * * tptr: Pointer to a hash table */ static void rebuild_table(hash_t *tptr) { hash_node_t **old_bucket, *old_hash, *tmp; int old_size, h, i; old_bucket=tptr->bucket; old_size=tptr->size; /* create a new table and rehash old buckets */ hash_init(tptr, old_size<<1); for (i=0; inext; h=hash(tptr, tmp->key); tmp->next=tptr->bucket[h]; tptr->bucket[h]=tmp; tptr->entries++; } /* while */ } /* for */ /* free memory used by old table */ free(old_bucket); return; } /* * hash_init() - Initialize a new hash table. * * tptr: Pointer to the hash table to initialize * buckets: The number of initial buckets to create */ void hash_init(hash_t *tptr, int buckets) { /* make sure we allocate something */ if (buckets==0) buckets=16; /* initialize the table */ tptr->entries=0; tptr->size=2; tptr->mask=1; tptr->downshift=29; /* ensure buckets is a power of 2 */ while (tptr->sizesize<<=1; tptr->mask=(tptr->mask<<1)+1; tptr->downshift--; } /* while */ /* allocate memory for table */ tptr->bucket=(hash_node_t **) calloc(tptr->size, sizeof(hash_node_t *)); return; } /* * hash_lookup() - Lookup an entry in the hash table and return a pointer to * it or HASH_FAIL if it wasn't found. * * tptr: Pointer to the hash table * key: The key to lookup */ int hash_lookup(hash_t *tptr, const char *key) { int h; hash_node_t *node; /* If key is null return failure */ if (!key) return HASH_FAIL; /* find the entry in the hash table */ h=hash(tptr, key); for (node=tptr->bucket[h]; node!=NULL; node=node->next) { if (!strcmp(node->key, key)) break; } /* return the entry if it exists, or HASH_FAIL */ return(node ? node->data : HASH_FAIL); } /* * hash_insert() - Insert an entry into the hash table. If the entry already * exists return a pointer to it, otherwise return HASH_FAIL. * * tptr: A pointer to the hash table * key: The key to insert into the hash table * data: A pointer to the data to insert into the hash table */ int hash_insert(hash_t *tptr, const char *key, int data) { int tmp; hash_node_t *node; int h; /* check to see if the entry exists */ if ((tmp=hash_lookup(tptr, key)) != HASH_FAIL) return(tmp); /* expand the table if needed */ while (tptr->entries>=HASH_LIMIT*tptr->size) rebuild_table(tptr); /* insert the new entry */ h=hash(tptr, key); node=(struct hash_node_t *) malloc(sizeof(hash_node_t)); node->data=data; node->key=key; node->next=tptr->bucket[h]; tptr->bucket[h]=node; tptr->entries++; return HASH_FAIL; } /* * hash_delete() - Remove an entry from a hash table and return a pointer * to its data or HASH_FAIL if it wasn't found. * * tptr: A pointer to the hash table * key: The key to remove from the hash table */ int hash_delete(hash_t *tptr, const char *key) { hash_node_t *node, *last; int data; int h; /* find the node to remove */ h=hash(tptr, key); for (node=tptr->bucket[h]; node; node=node->next) { if (!strcmp(node->key, key)) break; } /* Didn't find anything, return HASH_FAIL */ if (node==NULL) return HASH_FAIL; /* if node is at head of bucket, we have it easy */ if (node==tptr->bucket[h]) tptr->bucket[h]=node->next; else { /* find the node before the node we want to remove */ for (last=tptr->bucket[h]; last && last->next; last=last->next) { if (last->next==node) break; } last->next=node->next; } /* free memory and return the data */ data=node->data; free(node); return(data); } /* * hash_destroy() - Delete the entire table, and all remaining entries. * */ void hash_destroy(hash_t *tptr) { hash_node_t *node, *last; int i; for (i=0; isize; i++) { node = tptr->bucket[i]; while (node != NULL) { last = node; node = node->next; free(last); } } /* free the entire array of buckets */ if (tptr->bucket != NULL) { free(tptr->bucket); memset(tptr, 0, sizeof(hash_t)); } } /* * alos() - Find the average length of search. * * tptr: Pointer to a hash table */ static float alos(hash_t *tptr) { int i,j; float alos=0; hash_node_t *node; for (i=0; isize; i++) { for (node=tptr->bucket[i], j=0; node!=NULL; node=node->next, j++); if (j) alos+=((j*(j+1))>>1); } /* for */ return(tptr->entries ? alos/tptr->entries : 0); } /* * hash_stats() - Return a string with stats about a hash table. * * tptr: A pointer to the hash table */ char * hash_stats(hash_t *tptr) { static char buf[1024]; sprintf(buf, ""%u slots, %u entries, and %1.2f ALOS"", (int)tptr->size, (int)tptr->entries, alos(tptr)); return(buf); } ","C" "Biophysics","Eigenstate/psfgen","src/memarena.h",".h","340","17"," #ifndef MEMARENA_H #define MEMARENA_H struct memarena; typedef struct memarena memarena; memarena * memarena_create(void); void memarena_destroy(memarena *a); void memarena_blocksize(memarena *a, int blocksize); void * memarena_alloc(memarena *a, int size); void * memarena_alloc_aligned(memarena *a, int size, int alignment); #endif ","Unknown" "Biophysics","Eigenstate/psfgen","src/topo_mol.c",".c","96806","2927","// #include #include #include #include #include ""topo_defs_struct.h"" #include ""topo_mol_struct.h"" #if defined(_MSC_VER) #define strcasecmp stricmp #define strncasecmp strnicmp #endif topo_mol * topo_mol_create(topo_defs *defs) { topo_mol *mol; if ( ! defs ) return 0; if ( (mol = (topo_mol*) malloc(sizeof(topo_mol))) ) { mol->newerror_handler_data = 0; mol->newerror_handler = 0; mol->defs = defs; mol->npatch = 0; mol->patches = 0; mol->curpatch = 0; mol->segment_hash = hasharray_create( (void**) &(mol->segment_array), sizeof(topo_mol_segment_t*)); mol->buildseg = 0; mol->arena = memarena_create(); mol->angle_arena = memarena_create(); mol->dihedral_arena = memarena_create(); if ( ! mol->segment_hash || ! mol->arena ) { topo_mol_destroy(mol); return 0; } } return mol; } void topo_mol_destroy(topo_mol *mol) { int i,n; topo_mol_segment_t *s; if ( ! mol ) return; n = hasharray_count(mol->segment_hash); for ( i=0; isegment_array[i]; if ( ! s ) continue; hasharray_destroy(s->residue_hash); } hasharray_destroy(mol->segment_hash); memarena_destroy(mol->arena); memarena_destroy(mol->angle_arena); memarena_destroy(mol->dihedral_arena); free((void*)mol); } void topo_mol_error_handler(topo_mol *mol, void *v, void (*print_msg)(void *,const char *)) { if ( mol ) { mol->newerror_handler = print_msg; mol->newerror_handler_data = v; } } /* internal method */ static void topo_mol_log_error(topo_mol *mol, const char *msg) { if (mol && msg && mol->newerror_handler) mol->newerror_handler(mol->newerror_handler_data, msg); } static topo_mol_segment_t * topo_mol_get_seg(topo_mol *mol, const topo_mol_ident_t *target) { int iseg; char errmsg[64 + 3*NAMEMAXLEN]; if ( ! mol ) return 0; iseg = hasharray_index(mol->segment_hash,target->segid); if ( iseg == HASHARRAY_FAIL ) { sprintf(errmsg,""no segment %s"",target->segid); topo_mol_log_error(mol,errmsg); return 0; } return mol->segment_array[iseg]; } static topo_mol_residue_t * topo_mol_get_res(topo_mol *mol, const topo_mol_ident_t *target, int irel) { int nres, ires; topo_mol_segment_t *seg; topo_mol_residue_t *res; char errmsg[64 + 3*NAMEMAXLEN]; seg = topo_mol_get_seg(mol,target); if ( ! seg ) return 0; nres = hasharray_count(seg->residue_hash); ires = hasharray_index(seg->residue_hash,target->resid); if ( ires == HASHARRAY_FAIL ) { sprintf(errmsg,""no residue %s of segment %s"", target->resid,target->segid); topo_mol_log_error(mol,errmsg); return 0; } if ( (ires+irel) < 0 || (ires+irel) >= nres ) { res = seg->residue_array + ires; if ( irel < 0 ) sprintf(errmsg,""no residue %d before %s:%s of segment %s"", -1*irel,res->name,res->resid,target->segid); if ( irel > 0 ) sprintf(errmsg,""no residue %d past %s:%s of segment %s"", irel,res->name,res->resid,target->segid); topo_mol_log_error(mol,errmsg); return 0; } return (seg->residue_array + ires + irel); } static topo_mol_atom_t * topo_mol_get_atom(topo_mol *mol, const topo_mol_ident_t *target, int irel) { topo_mol_residue_t *res; topo_mol_atom_t *atom; char errmsg[64 + 3*NAMEMAXLEN]; res = topo_mol_get_res(mol,target,irel); if ( ! res ) return 0; for ( atom = res->atoms; atom; atom = atom->next ) { if ( ! strcmp(target->aname,atom->name) ) break; } if ( ! atom ) { sprintf(errmsg,""no atom %s in residue %s:%s of segment %s"", target->aname,res->name,res->resid,target->segid); topo_mol_log_error(mol,errmsg); } return atom; } static topo_mol_atom_t *topo_mol_get_atom_from_res( const topo_mol_residue_t *res, const char *aname) { topo_mol_atom_t *atom; for ( atom = res->atoms; atom; atom = atom->next ) { if ( ! strcmp(aname,atom->name) ) break; } return atom; } int topo_mol_segment(topo_mol *mol, const char *segid) { int i; topo_mol_segment_t *newitem; char errmsg[32 + NAMEMAXLEN]; if ( ! mol ) return -1; mol->buildseg = 0; if ( NAMETOOLONG(segid) ) return -2; if ( ( i = hasharray_index(mol->segment_hash,segid) ) != HASHARRAY_FAIL ) { sprintf(errmsg,""duplicate segment key %s"",segid); topo_mol_log_error(mol,errmsg); return -3; } else { i = hasharray_insert(mol->segment_hash,segid); if ( i == HASHARRAY_FAIL ) return -4; newitem = mol->segment_array[i] = (topo_mol_segment_t*) memarena_alloc(mol->arena,sizeof(topo_mol_segment_t)); if ( ! newitem ) return -5; } strcpy(newitem->segid,segid); newitem->residue_hash = hasharray_create( (void**) &(newitem->residue_array), sizeof(topo_mol_residue_t)); strcpy(newitem->pfirst,""""); strcpy(newitem->plast,""""); newitem->auto_angles = mol->defs->auto_angles; newitem->auto_dihedrals = mol->defs->auto_dihedrals; mol->buildseg = newitem; return 0; } int topo_mol_segment_first(topo_mol *mol, const char *rname) { if ( ! mol ) return -1; if ( ! mol->buildseg ) { topo_mol_log_error(mol,""no segment in progress for first patch""); return -1; } if ( NAMETOOLONG(rname) ) return -2; strcpy(mol->buildseg->pfirst,rname); return 0; } int topo_mol_segment_last(topo_mol *mol, const char *rname) { if ( ! mol ) return -1; if ( ! mol->buildseg ) { topo_mol_log_error(mol,""no segment in progress for last patch""); return -1; } if ( NAMETOOLONG(rname) ) return -2; strcpy(mol->buildseg->plast,rname); return 0; } int topo_mol_segment_auto_angles(topo_mol *mol, int autogen) { if ( ! mol ) return -1; if ( ! mol->buildseg ) { topo_mol_log_error(mol,""no segment in progress for auto angles""); return -1; } mol->buildseg->auto_angles = autogen; return 0; } int topo_mol_segment_auto_dihedrals(topo_mol *mol, int autogen) { if ( ! mol ) return -1; if ( ! mol->buildseg ) { topo_mol_log_error(mol,""no segment in progress for auto dihedrals""); return -1; } mol->buildseg->auto_dihedrals = autogen; return 0; } int topo_mol_residue(topo_mol *mol, const char *resid, const char *rname, const char *chain) { int i; topo_mol_segment_t *seg; topo_mol_residue_t *newitem; char errmsg[32 + NAMEMAXLEN]; if ( ! mol ) return -1; if ( ! mol->buildseg ) { topo_mol_log_error(mol,""no segment in progress for residue""); return -1; } seg = mol->buildseg; if ( NAMETOOLONG(resid) ) return -2; if ( NAMETOOLONG(rname) ) return -3; if ( hasharray_index(seg->residue_hash,resid) != HASHARRAY_FAIL ) { sprintf(errmsg,""duplicate residue key %s"",resid); topo_mol_log_error(mol,errmsg); return -3; } if ( hasharray_index(mol->defs->residue_hash,rname) == HASHARRAY_FAIL ) { sprintf(errmsg,""unknown residue type %s"",rname); topo_mol_log_error(mol,errmsg); } i = hasharray_insert(seg->residue_hash,resid); if ( i == HASHARRAY_FAIL ) return -4; newitem = &(seg->residue_array[i]); strcpy(newitem->resid,resid); strcpy(newitem->name,rname); strcpy(newitem->chain,chain); newitem->atoms = 0; return 0; } int topo_mol_mutate(topo_mol *mol, const char *resid, const char *rname) { int ires; topo_mol_segment_t *seg; topo_mol_residue_t *res; char errmsg[32 + 3*NAMEMAXLEN]; if ( ! mol ) return -1; if ( ! mol->buildseg ) { topo_mol_log_error(mol,""no segment in progress for mutate""); return -1; } seg = mol->buildseg; if ( NAMETOOLONG(resid) ) return -2; if ( NAMETOOLONG(rname) ) return -3; ires = hasharray_index(seg->residue_hash,resid); if ( ires == HASHARRAY_FAIL ) { sprintf(errmsg,""residue %s does not exist"",resid); topo_mol_log_error(mol,errmsg); return -1; } res = seg->residue_array + ires; sprintf(errmsg,""mutating residue %s from %s to %s"",resid,res->name,rname); topo_mol_log_error(mol,errmsg); if ( hasharray_index(mol->defs->residue_hash,rname) == HASHARRAY_FAIL ) { sprintf(errmsg,""unknown residue type %s"",rname); topo_mol_log_error(mol,errmsg); } strcpy(res->name,rname); return 0; } static topo_mol_atom_t * topo_mol_unlink_atom( topo_mol_atom_t **atoms, const char *aname) { topo_mol_atom_t **atom; topo_mol_atom_t *oldatom; if ( ! atoms ) return 0; for ( atom = atoms ; *atom; atom = &((*atom)->next) ) { if ( ! strcmp(aname,(*atom)->name) ) break; } oldatom = *atom; if ( *atom ) *atom = ((*atom)->next); return oldatom; } static topo_mol_atom_t * topo_mol_find_atom(topo_mol_atom_t **newatoms, topo_mol_atom_t *oldatoms, const char *aname) { topo_mol_atom_t *atom, **newatom; if ( ! oldatoms ) return 0; for ( atom = oldatoms; atom; atom = atom->next ) { if ( ! strcmp(aname,atom->name) ) break; } if ( atom && *newatoms != oldatoms ) { for ( newatom = newatoms; *newatom != oldatoms; newatom = &(*newatom)->next ); *newatom = atom->next; atom->next = *newatoms; *newatoms = oldatoms; } return atom; } static int topo_mol_add_atom(topo_mol *mol, topo_mol_atom_t **atoms, topo_mol_atom_t *oldatoms, topo_defs_atom_t *atomdef) { int idef; topo_mol_atom_t *atomtmp; topo_defs_type_t *atype; char errmsg[128]; if ( ! mol || ! atoms ) return -1; idef = hasharray_index(mol->defs->type_hash,atomdef->type); if ( idef == HASHARRAY_FAIL ) { sprintf(errmsg,""unknown atom type %s"",atomdef->type); topo_mol_log_error(mol,errmsg); return -3; } atomtmp = 0; if ( oldatoms ) atomtmp = topo_mol_find_atom(atoms, oldatoms, atomdef->name); if ( ! atomtmp ) { atomtmp = memarena_alloc(mol->arena,sizeof(topo_mol_atom_t)); if ( ! atomtmp ) return -2; strcpy(atomtmp->name,atomdef->name); atomtmp->bonds = 0; atomtmp->angles = 0; atomtmp->dihedrals = 0; atomtmp->impropers = 0; atomtmp->cmaps = 0; atomtmp->exclusions = 0; atomtmp->conformations = 0; atomtmp->x = 0; atomtmp->y = 0; atomtmp->z = 0; atomtmp->vx = 0; atomtmp->vy = 0; atomtmp->vz = 0; atomtmp->xyz_state = TOPO_MOL_XYZ_VOID; atomtmp->partition = 0; atomtmp->atomid = 0; atomtmp->next = *atoms; *atoms = atomtmp; } atomtmp->copy = 0; atomtmp->charge = atomdef->charge; strcpy(atomtmp->type,atomdef->type); atype = &(mol->defs->type_array[idef]); strcpy(atomtmp->element,atype->element); atomtmp->mass = atype->mass; return 0; } topo_mol_bond_t * topo_mol_bond_next( topo_mol_bond_t *tuple, topo_mol_atom_t *atom) { if ( tuple->atom[0] == atom ) return tuple->next[0]; if ( tuple->atom[1] == atom ) return tuple->next[1]; return 0; } topo_mol_angle_t * topo_mol_angle_next( topo_mol_angle_t *tuple, topo_mol_atom_t *atom) { if ( tuple->atom[0] == atom ) return tuple->next[0]; if ( tuple->atom[1] == atom ) return tuple->next[1]; if ( tuple->atom[2] == atom ) return tuple->next[2]; return 0; } topo_mol_dihedral_t * topo_mol_dihedral_next( topo_mol_dihedral_t *tuple, topo_mol_atom_t *atom) { if ( tuple->atom[0] == atom ) return tuple->next[0]; if ( tuple->atom[1] == atom ) return tuple->next[1]; if ( tuple->atom[2] == atom ) return tuple->next[2]; if ( tuple->atom[3] == atom ) return tuple->next[3]; return 0; } topo_mol_improper_t * topo_mol_improper_next( topo_mol_improper_t *tuple, topo_mol_atom_t *atom) { if ( tuple->atom[0] == atom ) return tuple->next[0]; if ( tuple->atom[1] == atom ) return tuple->next[1]; if ( tuple->atom[2] == atom ) return tuple->next[2]; if ( tuple->atom[3] == atom ) return tuple->next[3]; return 0; } topo_mol_cmap_t * topo_mol_cmap_next( topo_mol_cmap_t *tuple, topo_mol_atom_t *atom) { if ( tuple->atom[0] == atom ) return tuple->next[0]; if ( tuple->atom[1] == atom ) return tuple->next[1]; if ( tuple->atom[2] == atom ) return tuple->next[2]; if ( tuple->atom[3] == atom ) return tuple->next[3]; if ( tuple->atom[4] == atom ) return tuple->next[4]; if ( tuple->atom[5] == atom ) return tuple->next[5]; if ( tuple->atom[6] == atom ) return tuple->next[6]; if ( tuple->atom[7] == atom ) return tuple->next[7]; return 0; } topo_mol_exclusion_t * topo_mol_exclusion_next( topo_mol_exclusion_t *tuple, topo_mol_atom_t *atom) { if ( tuple->atom[0] == atom ) return tuple->next[0]; if ( tuple->atom[1] == atom ) return tuple->next[1]; return 0; } static topo_mol_conformation_t * topo_mol_conformation_next( topo_mol_conformation_t *tuple, topo_mol_atom_t *atom) { if ( tuple->atom[0] == atom ) return tuple->next[0]; if ( tuple->atom[1] == atom ) return tuple->next[1]; if ( tuple->atom[2] == atom ) return tuple->next[2]; if ( tuple->atom[3] == atom ) return tuple->next[3]; return 0; } static void topo_mol_destroy_atom(topo_mol_atom_t *atom) { topo_mol_bond_t *bondtmp; topo_mol_angle_t *angletmp; topo_mol_dihedral_t *dihetmp; topo_mol_improper_t *imprtmp; topo_mol_cmap_t *cmaptmp; topo_mol_exclusion_t *excltmp; topo_mol_conformation_t *conftmp; if ( ! atom ) return; for ( bondtmp = atom->bonds; bondtmp; bondtmp = topo_mol_bond_next(bondtmp,atom) ) { bondtmp->del = 1; } for ( angletmp = atom->angles; angletmp; angletmp = topo_mol_angle_next(angletmp,atom) ) { angletmp->del = 1; } for ( dihetmp = atom->dihedrals; dihetmp; dihetmp = topo_mol_dihedral_next(dihetmp,atom) ) { dihetmp->del = 1; } for ( imprtmp = atom->impropers; imprtmp; imprtmp = topo_mol_improper_next(imprtmp,atom) ) { imprtmp->del = 1; } for ( cmaptmp = atom->cmaps; cmaptmp; cmaptmp = topo_mol_cmap_next(cmaptmp,atom) ) { cmaptmp->del = 1; } for ( excltmp = atom->exclusions; excltmp; excltmp = topo_mol_exclusion_next(excltmp,atom) ) { excltmp->del = 1; } for ( conftmp = atom->conformations; conftmp; conftmp = topo_mol_conformation_next(conftmp,atom) ) { conftmp->del = 1; } } static void topo_mol_del_atom(topo_mol_residue_t *res, const char *aname) { if ( ! res ) return; topo_mol_destroy_atom(topo_mol_unlink_atom(&(res->atoms),aname)); } /* * The add_xxx_to_residues routines exist because topo_mol_end can do * more intelligent error checking than what's done in the add_xxx * routines. The add_xxx routines are called by topo_mol_patch, which * has to be more general (and more paranoid) about its input. Returning * nonzero from add_xxx_to_residues is always a serious error. */ static int add_bond_to_residues(topo_mol *mol, const topo_mol_residue_t *res1, const char *aname1, const topo_mol_residue_t *res2, const char *aname2) { topo_mol_bond_t *tuple; topo_mol_atom_t *a1, *a2; a1 = topo_mol_get_atom_from_res(res1, aname1); a2 = topo_mol_get_atom_from_res(res2, aname2); if (!a1 || !a2) return -1; tuple = memarena_alloc(mol->arena,sizeof(topo_mol_bond_t)); if ( ! tuple ) return -10; tuple->next[0] = a1->bonds; tuple->atom[0] = a1; tuple->next[1] = a2->bonds; tuple->atom[1] = a2; tuple->del = 0; a1->bonds = tuple; a2->bonds = tuple; return 0; } static int topo_mol_add_bond(topo_mol *mol, const topo_mol_ident_t *targets, int ntargets, topo_defs_bond_t *def) { topo_mol_bond_t *tuple; topo_mol_atom_t *a1, *a2; topo_mol_ident_t t1, t2; if (! mol) return -1; if ( def->res1 < 0 || def->res1 >= ntargets ) return -2; t1 = targets[def->res1]; t1.aname = def->atom1; a1 = topo_mol_get_atom(mol,&t1,def->rel1); if ( ! a1 ) return -3; if ( def->res2 < 0 || def->res2 >= ntargets ) return -4; t2 = targets[def->res2]; t2.aname = def->atom2; a2 = topo_mol_get_atom(mol,&t2,def->rel2); if ( ! a2 ) return -5; tuple = memarena_alloc(mol->arena,sizeof(topo_mol_bond_t)); if ( ! tuple ) return -10; tuple->next[0] = a1->bonds; tuple->atom[0] = a1; tuple->next[1] = a2->bonds; tuple->atom[1] = a2; tuple->del = 0; a1->bonds = tuple; a2->bonds = tuple; return 0; } static void topo_mol_del_bond(topo_mol *mol, const topo_mol_ident_t *targets, int ntargets, topo_defs_bond_t *def) { topo_mol_bond_t *tuple; topo_mol_atom_t *a1, *a2; topo_mol_ident_t t1, t2; if (! mol) return; if ( def->res1 < 0 || def->res1 >= ntargets ) return; t1 = targets[def->res1]; t1.aname = def->atom1; a1 = topo_mol_get_atom(mol,&t1,def->rel1); if ( ! a1 ) return; if ( def->res2 < 0 || def->res2 >= ntargets ) return; t2 = targets[def->res2]; t2.aname = def->atom2; a2 = topo_mol_get_atom(mol,&t2,def->rel2); for ( tuple = a1->bonds; tuple; tuple = topo_mol_bond_next(tuple,a1) ) { if ( tuple->atom[0] == a1 && tuple->atom[1] == a2 ) tuple->del = 1; if ( tuple->atom[0] == a2 && tuple->atom[1] == a1 ) tuple->del = 1; } } static int topo_mol_add_angle(topo_mol *mol, const topo_mol_ident_t *targets, int ntargets, topo_defs_angle_t *def) { topo_mol_angle_t *tuple; topo_mol_atom_t *a1, *a2, *a3; topo_mol_ident_t t1, t2, t3; if (! mol) return -1; if ( def->res1 < 0 || def->res1 >= ntargets ) return -2; t1 = targets[def->res1]; t1.aname = def->atom1; a1 = topo_mol_get_atom(mol,&t1,def->rel1); if ( ! a1 ) return -3; if ( def->res2 < 0 || def->res2 >= ntargets ) return -4; t2 = targets[def->res2]; t2.aname = def->atom2; a2 = topo_mol_get_atom(mol,&t2,def->rel2); if ( ! a2 ) return -5; if ( def->res3 < 0 || def->res3 >= ntargets ) return -6; t3 = targets[def->res3]; t3.aname = def->atom3; a3 = topo_mol_get_atom(mol,&t3,def->rel3); if ( ! a3 ) return -7; tuple = memarena_alloc(mol->angle_arena,sizeof(topo_mol_angle_t)); if ( ! tuple ) return -10; tuple->next[0] = a1->angles; tuple->atom[0] = a1; tuple->next[1] = a2->angles; tuple->atom[1] = a2; tuple->next[2] = a3->angles; tuple->atom[2] = a3; tuple->del = 0; a1->angles = tuple; a2->angles = tuple; a3->angles = tuple; return 0; } static void topo_mol_del_angle(topo_mol *mol, const topo_mol_ident_t *targets, int ntargets, topo_defs_angle_t *def) { topo_mol_angle_t *tuple; topo_mol_atom_t *a1, *a2, *a3; topo_mol_ident_t t1, t2, t3; if (! mol) return; if ( def->res1 < 0 || def->res1 >= ntargets ) return; t1 = targets[def->res1]; t1.aname = def->atom1; a1 = topo_mol_get_atom(mol,&t1,def->rel1); if ( ! a1 ) return; if ( def->res2 < 0 || def->res2 >= ntargets ) return; t2 = targets[def->res2]; t2.aname = def->atom2; a2 = topo_mol_get_atom(mol,&t2,def->rel2); if ( def->res3 < 0 || def->res3 >= ntargets ) return; t3 = targets[def->res3]; t3.aname = def->atom3; a3 = topo_mol_get_atom(mol,&t3,def->rel3); for ( tuple = a1->angles; tuple; tuple = topo_mol_angle_next(tuple,a1) ) { if ( tuple->atom[0] == a1 && tuple->atom[1] == a2 && tuple->atom[2] == a3 ) tuple->del = 1; if ( tuple->atom[0] == a3 && tuple->atom[1] == a2 && tuple->atom[2] == a1 ) tuple->del = 1; } } static int topo_mol_add_dihedral(topo_mol *mol, const topo_mol_ident_t *targets, int ntargets, topo_defs_dihedral_t *def) { topo_mol_dihedral_t *tuple; topo_mol_atom_t *a1, *a2, *a3, *a4; topo_mol_ident_t t1, t2, t3, t4; if (! mol) return -1; if ( def->res1 < 0 || def->res1 >= ntargets ) return -2; t1 = targets[def->res1]; t1.aname = def->atom1; a1 = topo_mol_get_atom(mol,&t1,def->rel1); if ( ! a1 ) return -3; if ( def->res2 < 0 || def->res2 >= ntargets ) return -4; t2 = targets[def->res2]; t2.aname = def->atom2; a2 = topo_mol_get_atom(mol,&t2,def->rel2); if ( ! a2 ) return -5; if ( def->res3 < 0 || def->res3 >= ntargets ) return -6; t3 = targets[def->res3]; t3.aname = def->atom3; a3 = topo_mol_get_atom(mol,&t3,def->rel3); if ( ! a3 ) return -7; if ( def->res4 < 0 || def->res4 >= ntargets ) return -8; t4 = targets[def->res4]; t4.aname = def->atom4; a4 = topo_mol_get_atom(mol,&t4,def->rel4); if ( ! a4 ) return -9; tuple = memarena_alloc(mol->dihedral_arena,sizeof(topo_mol_dihedral_t)); if ( ! tuple ) return -10; tuple->next[0] = a1->dihedrals; tuple->atom[0] = a1; tuple->next[1] = a2->dihedrals; tuple->atom[1] = a2; tuple->next[2] = a3->dihedrals; tuple->atom[2] = a3; tuple->next[3] = a4->dihedrals; tuple->atom[3] = a4; tuple->del = 0; a1->dihedrals = tuple; a2->dihedrals = tuple; a3->dihedrals = tuple; a4->dihedrals = tuple; return 0; } static void topo_mol_del_dihedral(topo_mol *mol, const topo_mol_ident_t *targets, int ntargets, topo_defs_dihedral_t *def) { topo_mol_dihedral_t *tuple; topo_mol_atom_t *a1, *a2, *a3, *a4; topo_mol_ident_t t1, t2, t3, t4; if (! mol) return; if ( def->res1 < 0 || def->res1 >= ntargets ) return; t1 = targets[def->res1]; t1.aname = def->atom1; a1 = topo_mol_get_atom(mol,&t1,def->rel1); if ( ! a1 ) return; if ( def->res2 < 0 || def->res2 >= ntargets ) return; t2 = targets[def->res2]; t2.aname = def->atom2; a2 = topo_mol_get_atom(mol,&t2,def->rel2); if ( def->res3 < 0 || def->res3 >= ntargets ) return; t3 = targets[def->res3]; t3.aname = def->atom3; a3 = topo_mol_get_atom(mol,&t3,def->rel3); if ( def->res4 < 0 || def->res4 >= ntargets ) return; t4 = targets[def->res4]; t4.aname = def->atom4; a4 = topo_mol_get_atom(mol,&t4,def->rel4); for ( tuple = a1->dihedrals; tuple; tuple = topo_mol_dihedral_next(tuple,a1) ) { if ( tuple->atom[0] == a1 && tuple->atom[1] == a2 && tuple->atom[2] == a3 && tuple->atom[3] == a4 ) tuple->del = 1; if ( tuple->atom[0] == a4 && tuple->atom[1] == a3 && tuple->atom[2] == a2 && tuple->atom[3] == a1 ) tuple->del = 1; } } static int add_improper_to_residues(topo_mol *mol, const topo_mol_residue_t *res1, const char *aname1, const topo_mol_residue_t *res2, const char *aname2, const topo_mol_residue_t *res3, const char *aname3, const topo_mol_residue_t *res4, const char *aname4) { topo_mol_improper_t *tuple; topo_mol_atom_t *a1, *a2, *a3, *a4; a1 = topo_mol_get_atom_from_res(res1, aname1); a2 = topo_mol_get_atom_from_res(res2, aname2); a3 = topo_mol_get_atom_from_res(res3, aname3); a4 = topo_mol_get_atom_from_res(res4, aname4); if (!a1 || !a2 || !a3 || !a4) return -1; tuple = memarena_alloc(mol->arena,sizeof(topo_mol_improper_t)); if ( ! tuple ) return -10; tuple->next[0] = a1->impropers; tuple->atom[0] = a1; tuple->next[1] = a2->impropers; tuple->atom[1] = a2; tuple->next[2] = a3->impropers; tuple->atom[2] = a3; tuple->next[3] = a4->impropers; tuple->atom[3] = a4; tuple->del = 0; a1->impropers = tuple; a2->impropers = tuple; a3->impropers = tuple; a4->impropers = tuple; return 0; } static int topo_mol_add_improper(topo_mol *mol, const topo_mol_ident_t *targets, int ntargets, topo_defs_improper_t *def) { topo_mol_improper_t *tuple; topo_mol_atom_t *a1, *a2, *a3, *a4; topo_mol_ident_t t1, t2, t3, t4; if (! mol) return -1; if ( def->res1 < 0 || def->res1 >= ntargets ) return -2; t1 = targets[def->res1]; t1.aname = def->atom1; a1 = topo_mol_get_atom(mol,&t1,def->rel1); if ( ! a1 ) return -3; if ( def->res2 < 0 || def->res2 >= ntargets ) return -4; t2 = targets[def->res2]; t2.aname = def->atom2; a2 = topo_mol_get_atom(mol,&t2,def->rel2); if ( ! a2 ) return -5; if ( def->res3 < 0 || def->res3 >= ntargets ) return -6; t3 = targets[def->res3]; t3.aname = def->atom3; a3 = topo_mol_get_atom(mol,&t3,def->rel3); if ( ! a3 ) return -7; if ( def->res4 < 0 || def->res4 >= ntargets ) return -8; t4 = targets[def->res4]; t4.aname = def->atom4; a4 = topo_mol_get_atom(mol,&t4,def->rel4); if ( ! a4 ) return -9; tuple = memarena_alloc(mol->arena,sizeof(topo_mol_improper_t)); if ( ! tuple ) return -10; tuple->next[0] = a1->impropers; tuple->atom[0] = a1; tuple->next[1] = a2->impropers; tuple->atom[1] = a2; tuple->next[2] = a3->impropers; tuple->atom[2] = a3; tuple->next[3] = a4->impropers; tuple->atom[3] = a4; tuple->del = 0; a1->impropers = tuple; a2->impropers = tuple; a3->impropers = tuple; a4->impropers = tuple; return 0; } static void topo_mol_del_improper(topo_mol *mol, const topo_mol_ident_t *targets, int ntargets, topo_defs_improper_t *def) { topo_mol_improper_t *tuple; topo_mol_atom_t *a1, *a2, *a3, *a4; topo_mol_ident_t t1, t2, t3, t4; if (! mol) return; if ( def->res1 < 0 || def->res1 >= ntargets ) return; t1 = targets[def->res1]; t1.aname = def->atom1; a1 = topo_mol_get_atom(mol,&t1,def->rel1); if ( ! a1 ) return; if ( def->res2 < 0 || def->res2 >= ntargets ) return; t2 = targets[def->res2]; t2.aname = def->atom2; a2 = topo_mol_get_atom(mol,&t2,def->rel2); if ( def->res3 < 0 || def->res3 >= ntargets ) return; t3 = targets[def->res3]; t3.aname = def->atom3; a3 = topo_mol_get_atom(mol,&t3,def->rel3); if ( def->res4 < 0 || def->res4 >= ntargets ) return; t4 = targets[def->res4]; t4.aname = def->atom4; a4 = topo_mol_get_atom(mol,&t4,def->rel4); for ( tuple = a1->impropers; tuple; tuple = topo_mol_improper_next(tuple,a1) ) { if ( tuple->atom[0] == a1 && tuple->atom[1] == a2 && tuple->atom[2] == a3 && tuple->atom[3] == a4 ) tuple->del = 1; if ( tuple->atom[0] == a4 && tuple->atom[1] == a3 && tuple->atom[2] == a2 && tuple->atom[3] == a1 ) tuple->del = 1; } } static int add_cmap_to_residues(topo_mol *mol, const topo_mol_residue_t *resl[8], const char *anamel[8]) { int i; topo_mol_cmap_t *tuple; topo_mol_atom_t *al[8]; if (! mol) return -1; for ( i=0; i<8; ++i ) { al[i] = topo_mol_get_atom_from_res(resl[i], anamel[i]); if (!al[i]) return -2-2*i; } tuple = memarena_alloc(mol->arena,sizeof(topo_mol_cmap_t)); if ( ! tuple ) return -20; for ( i=0; i<8; ++i ) { tuple->next[i] = al[i]->cmaps; tuple->atom[i] = al[i]; } for ( i=0; i<8; ++i ) { /* This must be in a separate loop because atoms may be repeated. */ al[i]->cmaps = tuple; } tuple->del = 0; return 0; } static int topo_mol_add_cmap(topo_mol *mol, const topo_mol_ident_t *targets, int ntargets, topo_defs_cmap_t *def) { int i; topo_mol_cmap_t *tuple; topo_mol_atom_t *al[8]; topo_mol_ident_t tl[8]; if (! mol) return -1; for ( i=0; i<8; ++i ) { if ( def->resl[i] < 0 || def->resl[i] >= ntargets ) return -2-2*i; tl[i] = targets[def->resl[i]]; tl[i].aname = def->atoml[i]; al[i] = topo_mol_get_atom(mol,&tl[i],def->rell[i]); if ( ! al[i] ) return -3-2*i; } tuple = memarena_alloc(mol->arena,sizeof(topo_mol_cmap_t)); if ( ! tuple ) return -20; for ( i=0; i<8; ++i ) { tuple->next[i] = al[i]->cmaps; tuple->atom[i] = al[i]; } for ( i=0; i<8; ++i ) { /* This must be in a separate loop because atoms may be repeated. */ al[i]->cmaps = tuple; } tuple->del = 0; return 0; } static void topo_mol_del_cmap(topo_mol *mol, const topo_mol_ident_t *targets, int ntargets, topo_defs_cmap_t *def) { int i; topo_mol_cmap_t *tuple; topo_mol_atom_t *al[8]; topo_mol_ident_t tl[8]; if (! mol) return; for ( i=0; i<8; ++i ) { if ( def->resl[i] < 0 || def->resl[i] >= ntargets ) return; tl[i] = targets[def->resl[i]]; tl[i].aname = def->atoml[i]; al[i] = topo_mol_get_atom(mol,&tl[i],def->rell[i]); if ( ! al[i] ) return; } for ( tuple = al[0]->cmaps; tuple; tuple = topo_mol_cmap_next(tuple,al[0]) ) { int match1, match2; match1 = 0; for ( i=0; i<4 && (tuple->atom[i] == al[i]); ++i ); if ( i == 4 ) match1 = 1; for ( i=0; i<4 && (tuple->atom[i] == al[3-i]); ++i ); if ( i == 4 ) match1 = 1; match2 = 0; for ( i=0; i<4 && (tuple->atom[4+i] == al[4+i]); ++i ); if ( i == 4 ) match2 = 1; for ( i=0; i<4 && (tuple->atom[4+i] == al[7-i]); ++i ); if ( i == 4 ) match2 = 1; if ( match1 && match2 ) tuple->del = 1; } } static int add_exclusion_to_residues(topo_mol *mol, const topo_mol_residue_t *res1, const char *aname1, const topo_mol_residue_t *res2, const char *aname2) { topo_mol_exclusion_t *tuple; topo_mol_atom_t *a1, *a2; a1 = topo_mol_get_atom_from_res(res1, aname1); a2 = topo_mol_get_atom_from_res(res2, aname2); if (!a1 || !a2) return -1; tuple = memarena_alloc(mol->arena,sizeof(topo_mol_exclusion_t)); if ( ! tuple ) return -10; tuple->next[0] = a1->exclusions; tuple->atom[0] = a1; tuple->next[1] = a2->exclusions; tuple->atom[1] = a2; tuple->del = 0; a1->exclusions = tuple; a2->exclusions = tuple; return 0; } static int topo_mol_add_exclusion(topo_mol *mol, const topo_mol_ident_t *targets, int ntargets, topo_defs_exclusion_t *def) { topo_mol_exclusion_t *tuple; topo_mol_atom_t *a1, *a2; topo_mol_ident_t t1, t2; if (! mol) return -1; if ( def->res1 < 0 || def->res1 >= ntargets ) return -2; t1 = targets[def->res1]; t1.aname = def->atom1; a1 = topo_mol_get_atom(mol,&t1,def->rel1); if ( ! a1 ) return -3; if ( def->res2 < 0 || def->res2 >= ntargets ) return -4; t2 = targets[def->res2]; t2.aname = def->atom2; a2 = topo_mol_get_atom(mol,&t2,def->rel2); if ( ! a2 ) return -5; tuple = memarena_alloc(mol->arena,sizeof(topo_mol_exclusion_t)); if ( ! tuple ) return -10; tuple->next[0] = a1->exclusions; tuple->atom[0] = a1; tuple->next[1] = a2->exclusions; tuple->atom[1] = a2; tuple->del = 0; a1->exclusions = tuple; a2->exclusions = tuple; return 0; } static void topo_mol_del_exclusion(topo_mol *mol, const topo_mol_ident_t *targets, int ntargets, topo_defs_exclusion_t *def) { topo_mol_exclusion_t *tuple; topo_mol_atom_t *a1, *a2; topo_mol_ident_t t1, t2; if (! mol) return; if ( def->res1 < 0 || def->res1 >= ntargets ) return; t1 = targets[def->res1]; t1.aname = def->atom1; a1 = topo_mol_get_atom(mol,&t1,def->rel1); if ( ! a1 ) return; if ( def->res2 < 0 || def->res2 >= ntargets ) return; t2 = targets[def->res2]; t2.aname = def->atom2; a2 = topo_mol_get_atom(mol,&t2,def->rel2); for ( tuple = a1->exclusions; tuple; tuple = topo_mol_exclusion_next(tuple,a1) ) { if ( tuple->atom[0] == a1 && tuple->atom[1] == a2 ) tuple->del = 1; if ( tuple->atom[0] == a2 && tuple->atom[1] == a1 ) tuple->del = 1; } } static int add_conformation_to_residues(topo_mol *mol, const topo_mol_residue_t *res1, const char *aname1, const topo_mol_residue_t *res2, const char *aname2, const topo_mol_residue_t *res3, const char *aname3, const topo_mol_residue_t *res4, const char *aname4, topo_defs_conformation_t *def) { topo_mol_conformation_t *tuple; topo_mol_atom_t *a1, *a2, *a3, *a4; a1 = topo_mol_get_atom_from_res(res1, aname1); a2 = topo_mol_get_atom_from_res(res2, aname2); a3 = topo_mol_get_atom_from_res(res3, aname3); a4 = topo_mol_get_atom_from_res(res4, aname4); if (!a1 || !a2 || !a3 || !a4) return -1; tuple = memarena_alloc(mol->arena,sizeof(topo_mol_conformation_t)); if ( ! tuple ) return -10; tuple->next[0] = a1->conformations; tuple->atom[0] = a1; tuple->next[1] = a2->conformations; tuple->atom[1] = a2; tuple->next[2] = a3->conformations; tuple->atom[2] = a3; tuple->next[3] = a4->conformations; tuple->atom[3] = a4; tuple->del = 0; tuple->improper = def->improper; tuple->dist12 = def->dist12; tuple->angle123 = def->angle123; tuple->dihedral = def->dihedral; tuple->angle234 = def->angle234; tuple->dist34 = def->dist34; a1->conformations = tuple; a2->conformations = tuple; a3->conformations = tuple; a4->conformations = tuple; return 0; } static int topo_mol_add_conformation(topo_mol *mol, const topo_mol_ident_t *targets, int ntargets, topo_defs_conformation_t *def) { topo_mol_conformation_t *tuple; topo_mol_atom_t *a1, *a2, *a3, *a4; topo_mol_ident_t t1, t2, t3, t4; if (! mol) return -1; if ( def->res1 < 0 || def->res1 >= ntargets ) return -2; t1 = targets[def->res1]; t1.aname = def->atom1; a1 = topo_mol_get_atom(mol,&t1,def->rel1); if ( ! a1 ) return -3; if ( def->res2 < 0 || def->res2 >= ntargets ) return -4; t2 = targets[def->res2]; t2.aname = def->atom2; a2 = topo_mol_get_atom(mol,&t2,def->rel2); if ( ! a2 ) return -5; if ( def->res3 < 0 || def->res3 >= ntargets ) return -6; t3 = targets[def->res3]; t3.aname = def->atom3; a3 = topo_mol_get_atom(mol,&t3,def->rel3); if ( ! a3 ) return -7; if ( def->res4 < 0 || def->res4 >= ntargets ) return -8; t4 = targets[def->res4]; t4.aname = def->atom4; a4 = topo_mol_get_atom(mol,&t4,def->rel4); if ( ! a4 ) return -9; tuple = memarena_alloc(mol->arena,sizeof(topo_mol_conformation_t)); if ( ! tuple ) return -10; tuple->next[0] = a1->conformations; tuple->atom[0] = a1; tuple->next[1] = a2->conformations; tuple->atom[1] = a2; tuple->next[2] = a3->conformations; tuple->atom[2] = a3; tuple->next[3] = a4->conformations; tuple->atom[3] = a4; tuple->del = 0; tuple->improper = def->improper; tuple->dist12 = def->dist12; tuple->angle123 = def->angle123; tuple->dihedral = def->dihedral; tuple->angle234 = def->angle234; tuple->dist34 = def->dist34; a1->conformations = tuple; a2->conformations = tuple; a3->conformations = tuple; a4->conformations = tuple; return 0; } static void topo_mol_del_conformation(topo_mol *mol, const topo_mol_ident_t *targets, int ntargets, topo_defs_conformation_t *def) { topo_mol_conformation_t *tuple; topo_mol_atom_t *a1, *a2, *a3, *a4; topo_mol_ident_t t1, t2, t3, t4; if (! mol) return; if ( def->res1 < 0 || def->res1 >= ntargets ) return; t1 = targets[def->res1]; t1.aname = def->atom1; a1 = topo_mol_get_atom(mol,&t1,def->rel1); if ( ! a1 ) return; if ( def->res2 < 0 || def->res2 >= ntargets ) return; t2 = targets[def->res2]; t2.aname = def->atom2; a2 = topo_mol_get_atom(mol,&t2,def->rel2); if ( def->res3 < 0 || def->res3 >= ntargets ) return; t3 = targets[def->res3]; t3.aname = def->atom3; a3 = topo_mol_get_atom(mol,&t3,def->rel3); if ( def->res4 < 0 || def->res4 >= ntargets ) return; t4 = targets[def->res4]; t4.aname = def->atom4; a4 = topo_mol_get_atom(mol,&t4,def->rel4); for ( tuple = a1->conformations; tuple; tuple = topo_mol_conformation_next(tuple,a1) ) { if ( tuple->improper == def->improper && tuple->atom[0] == a1 && tuple->atom[1] == a2 && tuple->atom[2] == a3 && tuple->atom[3] == a4 ) tuple->del = 1; if ( tuple->improper == def->improper && tuple->atom[0] == a4 && tuple->atom[1] == a3 && tuple->atom[2] == a2 && tuple->atom[3] == a1 ) tuple->del = 1; } } static int topo_mol_auto_angles(topo_mol *mol, topo_mol_segment_t *segp); static int topo_mol_auto_dihedrals(topo_mol *mol, topo_mol_segment_t *segp); int topo_mol_end(topo_mol *mol) { int i,n; int idef; topo_defs *defs; topo_mol_segment_t *seg; topo_mol_residue_t *res; topo_defs_residue_t *resdef; topo_defs_atom_t *atomdef; topo_defs_bond_t *bonddef; topo_defs_angle_t *angldef; topo_defs_dihedral_t *dihedef; topo_defs_improper_t *imprdef; topo_defs_cmap_t *cmapdef; topo_defs_exclusion_t *excldef; topo_defs_conformation_t *confdef; topo_mol_ident_t target; char errmsg[128]; int firstdefault=0, lastdefault=0; if ( ! mol ) return -1; if ( ! mol->buildseg ) { topo_mol_log_error(mol,""no segment in progress for end""); return -1; } seg = mol->buildseg; mol->buildseg = 0; defs = mol->defs; /* add atoms */ n = hasharray_count(seg->residue_hash); for ( i=0; iresidue_array[i]); idef = hasharray_index(defs->residue_hash,res->name); if ( idef == HASHARRAY_FAIL ) { sprintf(errmsg,""unknown residue type %s"",res->name); topo_mol_log_error(mol,errmsg); return -1; } resdef = &(mol->defs->residue_array[idef]); if ( resdef->patch ) { sprintf(errmsg,""unknown residue type %s"",res->name); topo_mol_log_error(mol,errmsg); return -1; } /* patches */ if ( i==0 && ! strlen(seg->pfirst) ) { strcpy(seg->pfirst,resdef->pfirst); firstdefault = 1; } if ( i==(n-1) && ! strlen(seg->plast) ) { strcpy(seg->plast,resdef->plast); lastdefault = 1; } for ( atomdef = resdef->atoms; atomdef; atomdef = atomdef->next ) { if ( topo_mol_add_atom(mol,&(res->atoms),0,atomdef) ) { sprintf(errmsg,""add atom failed in residue %s:%s"",res->name,res->resid); topo_mol_log_error(mol,errmsg); return -8; } } } for ( i=0; iresidue_array[i]); idef = hasharray_index(defs->residue_hash,res->name); if ( idef == HASHARRAY_FAIL ) { sprintf(errmsg,""unknown residue type %s"",res->name); topo_mol_log_error(mol,errmsg); return -1; } resdef = &(mol->defs->residue_array[idef]); target.segid = seg->segid; target.resid = res->resid; for ( bonddef = resdef->bonds; bonddef; bonddef = bonddef->next ) { int ires1, ires2; if (bonddef->res1 != 0 || bonddef->res2 != 0) { /* * XXX This should be caught much earlier, like when the topology * file is initially read in. */ sprintf(errmsg, ""ERROR: Bad bond definition %s %s-%s; skipping."", res->name, bonddef->atom1, bonddef->atom2); topo_mol_log_error(mol, errmsg); continue; } ires1=bonddef->rel1+i; ires2=bonddef->rel2+i; if (ires1 < 0 || ires2 < 0 || ires1 >= n || ires2 >= n) { sprintf(errmsg, ""Info: skipping bond %s-%s at %s of segment."", bonddef->atom1, bonddef->atom2, i==0 ? ""beginning"" : ""end""); topo_mol_log_error(mol, errmsg); continue; } if (add_bond_to_residues(mol, &(seg->residue_array[ires1]), bonddef->atom1, &(seg->residue_array[ires2]), bonddef->atom2)) { sprintf(errmsg, ""ERROR: Missing atoms for bond %s(%d) %s(%d) in residue %s:%s"", bonddef->atom1,bonddef->rel1,bonddef->atom2,bonddef->rel2, res->name,res->resid); topo_mol_log_error(mol, errmsg); } } if ( seg->auto_angles && resdef->angles ) { sprintf(errmsg,""Warning: explicit angles in residue %s:%s will be deleted during autogeneration"",res->name,res->resid); topo_mol_log_error(mol,errmsg); } for ( angldef = resdef->angles; angldef; angldef = angldef->next ) { if ( topo_mol_add_angle(mol,&target,1,angldef) ) { sprintf(errmsg,""Warning: add angle failed in residue %s:%s"",res->name,res->resid); topo_mol_log_error(mol,errmsg); } } if ( seg->auto_dihedrals && resdef->dihedrals) { sprintf(errmsg,""Warning: explicit dihedrals in residue %s:%s will be deleted during autogeneration"",res->name,res->resid); topo_mol_log_error(mol,errmsg); } for ( dihedef = resdef->dihedrals; dihedef; dihedef = dihedef->next ) { if ( topo_mol_add_dihedral(mol,&target,1,dihedef) ) { sprintf(errmsg,""Warning: add dihedral failed in residue %s:%s"",res->name,res->resid); topo_mol_log_error(mol,errmsg); } } for ( imprdef = resdef->impropers; imprdef; imprdef = imprdef->next ) { int ires1, ires2, ires3, ires4; if (imprdef->res1 != 0 || imprdef->res2 != 0 || imprdef->res3 != 0 || imprdef->res4 != 0) { sprintf(errmsg, ""ERROR: Bad improper definition %s %s-%s-%s-%s; skipping."", res->name, imprdef->atom1, imprdef->atom2, imprdef->atom3, imprdef->atom4); topo_mol_log_error(mol, errmsg); continue; } ires1=imprdef->rel1+i; ires2=imprdef->rel2+i; ires3=imprdef->rel3+i; ires4=imprdef->rel4+i; if (ires1 < 0 || ires2 < 0 || ires3 < 0 || ires4 < 0 || ires1 >= n || ires2 >= n || ires3 >= n || ires4 >= n) { sprintf(errmsg,""Info: skipping improper %s-%s-%s-%s at %s of segment."", imprdef->atom1, imprdef->atom2, imprdef->atom3, imprdef->atom4, i==0 ? ""beginning"" : ""end""); topo_mol_log_error(mol, errmsg); continue; } if (add_improper_to_residues(mol, &(seg->residue_array[ires1]), imprdef->atom1, &(seg->residue_array[ires2]), imprdef->atom2, &(seg->residue_array[ires3]), imprdef->atom3, &(seg->residue_array[ires4]), imprdef->atom4)) { sprintf(errmsg, ""ERROR: Missing atoms for improper %s(%d) %s(%d) %s(%d) %s(%d)\n\tin residue %s:%s"", imprdef->atom1,imprdef->rel1,imprdef->atom2,imprdef->rel2, imprdef->atom3,imprdef->rel3,imprdef->atom4,imprdef->rel4, res->name,res->resid); topo_mol_log_error(mol, errmsg); } } for ( cmapdef = resdef->cmaps; cmapdef; cmapdef = cmapdef->next ) { int j, iresl[8]; const topo_mol_residue_t *resl[8]; const char *atoml[8]; for ( j=0; j<8 && (cmapdef->resl[j] == 0); ++j ); if ( j != 8 ) { sprintf(errmsg, ""ERROR: Bad cross-term definition %s %s-%s-%s-%s-%s-%s-%s-%s; skipping."", res->name, cmapdef->atoml[0], cmapdef->atoml[1], cmapdef->atoml[2], cmapdef->atoml[3], cmapdef->atoml[4], cmapdef->atoml[5], cmapdef->atoml[6], cmapdef->atoml[7]); topo_mol_log_error(mol, errmsg); continue; } for ( j=0; j<8; ++j ) { iresl[j] = cmapdef->rell[j]+i; } for ( j=0; j<8 && (iresl[j] >= 0) && (iresl[j] < n); ++j ); if ( j != 8 ) { sprintf(errmsg,""Info: skipping cross-term %s-%s-%s-%s-%s-%s-%s-%s at %s of segment."", cmapdef->atoml[0], cmapdef->atoml[1], cmapdef->atoml[2], cmapdef->atoml[3], cmapdef->atoml[4], cmapdef->atoml[5], cmapdef->atoml[6], cmapdef->atoml[7], i==0 ? ""beginning"" : ""end""); topo_mol_log_error(mol, errmsg); continue; } for ( j=0; j<8; ++j ) { resl[j] = &seg->residue_array[iresl[j]]; atoml[j] = cmapdef->atoml[j]; } if (add_cmap_to_residues(mol, resl, atoml) ) { sprintf(errmsg, ""ERROR: Missing atoms for cross-term %s(%d) %s(%d) %s(%d) %s(%d) %s(%d) %s(%d) %s(%d) %s(%d)\n\tin residue %s:%s"", cmapdef->atoml[0],cmapdef->rell[0], cmapdef->atoml[1],cmapdef->rell[1], cmapdef->atoml[2],cmapdef->rell[2], cmapdef->atoml[3],cmapdef->rell[3], cmapdef->atoml[4],cmapdef->rell[4], cmapdef->atoml[5],cmapdef->rell[5], cmapdef->atoml[6],cmapdef->rell[6], cmapdef->atoml[7],cmapdef->rell[7], res->name,res->resid); topo_mol_log_error(mol, errmsg); } } for ( excldef = resdef->exclusions; excldef; excldef = excldef->next ) { int ires1, ires2; if (excldef->res1 != 0 || excldef->res2 != 0) { sprintf(errmsg, ""ERROR: Bad exclusion definition %s %s-%s; skipping."", res->name, excldef->atom1, excldef->atom2); topo_mol_log_error(mol, errmsg); continue; } ires1=excldef->rel1+i; ires2=excldef->rel2+i; if (ires1 < 0 || ires2 < 0 || ires1 >= n || ires2 >= n) { sprintf(errmsg, ""Info: skipping exclusion %s-%s at %s of segment."", excldef->atom1, excldef->atom2, i==0 ? ""beginning"" : ""end""); topo_mol_log_error(mol, errmsg); continue; } if (add_exclusion_to_residues(mol, &(seg->residue_array[ires1]), excldef->atom1, &(seg->residue_array[ires2]), excldef->atom2)) { sprintf(errmsg, ""ERROR: Missing atoms for exclusion %s(%d) %s(%d) in residue %s:%s"", excldef->atom1,excldef->rel1,excldef->atom2,excldef->rel2, res->name,res->resid); topo_mol_log_error(mol, errmsg); } } for ( confdef = resdef->conformations; confdef; confdef = confdef->next ) { int ires1, ires2, ires3, ires4; if (confdef->res1 != 0 || confdef->res2 != 0 || confdef->res3 != 0 || confdef->res4 != 0) { sprintf(errmsg, ""ERROR: Bad conformation definition %s %s-%s-%s-%s; skipping."", res->name, confdef->atom1, confdef->atom2, confdef->atom3, confdef->atom4); topo_mol_log_error(mol, errmsg); continue; } ires1=confdef->rel1+i; ires2=confdef->rel2+i; ires3=confdef->rel3+i; ires4=confdef->rel4+i; if (ires1 < 0 || ires2 < 0 || ires3 < 0 || ires4 < 0 || ires1 >= n || ires2 >= n || ires3 >= n || ires4 >= n) { sprintf(errmsg,""Info: skipping conformation %s-%s-%s-%s at %s of segment."", confdef->atom1, confdef->atom2, confdef->atom3, confdef->atom4, i==0 ? ""beginning"" : ""end""); topo_mol_log_error(mol, errmsg); continue; } if (add_conformation_to_residues(mol, &(seg->residue_array[ires1]), confdef->atom1, &(seg->residue_array[ires2]), confdef->atom2, &(seg->residue_array[ires3]), confdef->atom3, &(seg->residue_array[ires4]), confdef->atom4, confdef)) { sprintf(errmsg, ""Warning: missing atoms for conformation %s %s-%s-%s-%s; skipping."", res->name, confdef->atom1, confdef->atom2, confdef->atom3, confdef->atom4); topo_mol_log_error(mol, errmsg); } } } /* apply patches, last then first because dipeptide patch ACED depends on CT3 atom NT */ res = &(seg->residue_array[n-1]); if ( ! strlen(seg->plast) ) strcpy(seg->plast,""NONE""); target.segid = seg->segid; target.resid = res->resid; if ( topo_mol_patch(mol, &target, 1, seg->plast, 0, seg->auto_angles, seg->auto_dihedrals, lastdefault) ) return -10; res = &(seg->residue_array[0]); if ( ! strlen(seg->pfirst) ) strcpy(seg->pfirst,""NONE""); target.segid = seg->segid; target.resid = res->resid; if ( topo_mol_patch(mol, &target, 1, seg->pfirst, 1, seg->auto_angles, seg->auto_dihedrals, firstdefault) ) return -11; if (seg->auto_angles && topo_mol_auto_angles(mol, seg)) return -12; if (seg->auto_dihedrals && topo_mol_auto_dihedrals(mol, seg)) return -13; return 0; } int topo_mol_regenerate_resids(topo_mol *mol) { int ires, nres, iseg, nseg, npres; int prevresid, resid, npatchresptrs, ipatch; topo_mol_segment_t *seg; topo_mol_residue_t *res; topo_mol_patch_t **patchptr, *patch; topo_mol_patchres_t *patchres, **patchresptrs; char newresid[NAMEMAXLEN+20], (*newpatchresids)[NAMEMAXLEN]; if (! mol) return -1; nseg = hasharray_count(mol->segment_hash); npatchresptrs=0; /* clean patches so only valid items remain */ for ( patchptr = &(mol->patches); *patchptr; ) { npres=0; for ( patchres = (*patchptr)->patchresids; patchres; patchres = patchres->next ) { ++npres; /* Test the existence of segid:resid for the patch */ if (!topo_mol_validate_patchres(mol,(*patchptr)->pname,patchres->segid, patchres->resid)) { break; } } if ( patchres ) { /* remove patch from list */ *patchptr = (*patchptr)->next; continue; } npatchresptrs += npres; patchptr = &((*patchptr)->next); /* continue to next patch */ } patchresptrs = malloc(npatchresptrs * sizeof(topo_mol_patchres_t*)); if ( ! patchresptrs ) return -5; newpatchresids = calloc(npatchresptrs, NAMEMAXLEN); if ( ! newpatchresids ) return -6; for ( ipatch=0, patch = mol->patches; patch; patch = patch->next ) { for ( patchres = patch->patchresids; patchres; patchres = patchres->next ) { patchresptrs[ipatch++] = patchres; } } for ( iseg=0; isegsegment_array[iseg]; if ( ! seg ) continue; nres = hasharray_count(seg->residue_hash); if ( hasharray_clear(seg->residue_hash) == HASHARRAY_FAIL ) return -2; prevresid = -100000; for ( ires=0; iresresidue_array[ires]); resid = atoi(res->resid); if ( resid <= prevresid ) resid = prevresid + 1; sprintf(newresid, ""%d"", resid); if ( NAMETOOLONG(newresid) ) return -3; if ( strcmp(res->resid, newresid) ) { /* changed, need to check patches */ for ( ipatch=0; ipatch < npatchresptrs; ++ipatch ) { if ( ( ! strcmp(seg->segid, patchresptrs[ipatch]->segid) ) && ( ! strcmp(res->resid, patchresptrs[ipatch]->resid) ) ) { sprintf(newpatchresids[ipatch], ""%d"", resid); } } } sprintf(res->resid, ""%d"", resid); if ( hasharray_reinsert(seg->residue_hash,res->resid,ires) != ires ) return -4; prevresid = resid; } } for ( ipatch=0; ipatch < npatchresptrs; ++ipatch ) { if ( newpatchresids[ipatch][0] ) { strcpy(patchresptrs[ipatch]->resid,newpatchresids[ipatch]); } } free(patchresptrs); free(newpatchresids); return 0; } int topo_mol_regenerate_angles(topo_mol *mol) { int errval; if ( mol ) { memarena_destroy(mol->angle_arena); mol->angle_arena = memarena_create(); } errval = topo_mol_auto_angles(mol,0); if ( errval ) { char errmsg[128]; sprintf(errmsg,""Error code %d"",errval); topo_mol_log_error(mol,errmsg); } return errval; } int topo_mol_regenerate_dihedrals(topo_mol *mol) { int errval; if ( mol ) { memarena_destroy(mol->dihedral_arena); mol->dihedral_arena = memarena_create(); } errval = topo_mol_auto_dihedrals(mol,0); if ( errval ) { char errmsg[128]; sprintf(errmsg,""Error code %d"",errval); topo_mol_log_error(mol,errmsg); } return errval; } static int is_hydrogen(topo_mol_atom_t *atom) { return ( atom->mass < 3.5 && atom->name[0] == 'H' ); } static int is_oxygen(topo_mol_atom_t *atom) { return ( atom->mass > 14.5 && atom->mass < 18.5 && atom->name[0] == 'O' ); } static int topo_mol_auto_angles(topo_mol *mol, topo_mol_segment_t *segp) { int ires, nres, iseg, nseg; topo_mol_segment_t *seg; topo_mol_residue_t *res; topo_mol_bond_t *b1, *b2; topo_mol_angle_t *tuple; topo_mol_atom_t *atom, *a1, *a2, *a3; if (! mol) return -1; nseg = segp ? 1 : hasharray_count(mol->segment_hash); for ( iseg=0; isegsegment_array[iseg]; if ( ! seg ) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { if ( ! segp ) { atom->angles = NULL; } for ( tuple = atom->angles; tuple; tuple = topo_mol_angle_next(tuple,atom) ) { tuple->del = 1; } } } } for ( iseg=0; isegsegment_array[iseg]; if ( ! seg ) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { a2 = atom; for ( b1 = atom->bonds; b1; b1 = topo_mol_bond_next(b1,atom) ) { if ( b1->del ) continue; if ( b1->atom[0] == atom ) a1 = b1->atom[1]; else if ( b1->atom[1] == atom ) a1 = b1->atom[0]; else return -5; b2 = b1; while ( (b2 = topo_mol_bond_next(b2,atom)) ) { if ( b2->del ) continue; if ( b2->atom[0] == atom ) a3 = b2->atom[1]; else if ( b2->atom[1] == atom ) a3 = b2->atom[0]; else return -6; if ( is_hydrogen(a2) && ( ! topo_mol_bond_next(b2,atom) ) && ( ( is_hydrogen(a1) && is_oxygen(a3) ) || ( is_hydrogen(a3) && is_oxygen(a1) ) ) ) continue; /* extra H-H bond on water */ tuple = memarena_alloc(mol->angle_arena,sizeof(topo_mol_angle_t)); if ( ! tuple ) return -10; tuple->next[0] = a1->angles; tuple->atom[0] = a1; tuple->next[1] = a2->angles; tuple->atom[1] = a2; tuple->next[2] = a3->angles; tuple->atom[2] = a3; tuple->del = 0; a1->angles = tuple; a2->angles = tuple; a3->angles = tuple; } } } } } return 0; } static int topo_mol_auto_dihedrals(topo_mol *mol, topo_mol_segment_t *segp) { int ires, nres, iseg, nseg, found, atomid, count1, count2; topo_mol_segment_t *seg; topo_mol_residue_t *res; topo_mol_angle_t *g1, *g2; topo_mol_dihedral_t *tuple; topo_mol_atom_t *atom, *a1=0, *a2=0, *a3=0, *a4=0; if (! mol) return -1; nseg = segp ? 1 : hasharray_count(mol->segment_hash); for ( iseg=0; isegsegment_array[iseg]; if ( ! seg ) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { if ( ! segp ) { atom->dihedrals = NULL; } for ( tuple = atom->dihedrals; tuple; tuple = topo_mol_dihedral_next(tuple,atom) ) { tuple->del = 1; } } } } /* number atoms, needed to avoid duplicate dihedrals below */ /* assumes no inter-segment bonds if segp is non-null */ atomid = 0; for ( iseg=0; isegsegment_array[iseg]; if ( ! seg ) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { atom->atomid = ++atomid; } } } count1 = count2 = 0; for ( iseg=0; isegsegment_array[iseg]; if ( ! seg ) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { for ( g1 = atom->angles; g1; g1 = topo_mol_angle_next(g1,atom) ) { if ( g1->del ) continue; if ( g1->atom[1] != atom ) continue; for ( g2 = atom->angles; g2; g2 = topo_mol_angle_next(g2,atom) ) { if ( g2->del ) continue; if ( g2->atom[1] == atom ) continue; found = 0; if ( g2->atom[0] == atom ) { /* XBX BXX */ if ( g2->atom[1] == g1->atom[0] ) { /* CBA BCD */ a1 = g1->atom[2]; a2 = g1->atom[1]; /* == g2->atom[0] */ a3 = g1->atom[0]; /* == g2->atom[1] */ a4 = g2->atom[2]; found = ( a1->atomid < a4->atomid ); if ( a1 != a4 ) ++count2; } else if ( g2->atom[1] == g1->atom[2] ) { /* ABC BCD */ a1 = g1->atom[0]; a2 = g1->atom[1]; /* == g2->atom[0] */ a3 = g1->atom[2]; /* == g2->atom[1] */ a4 = g2->atom[2]; found = ( a1->atomid < a4->atomid ); if ( a1 != a4 ) ++count2; } } else if ( g2->atom[2] == atom ) { /* XBX XXB */ if ( g2->atom[1] == g1->atom[0] ) { /* CBA DCB */ a1 = g1->atom[2]; a2 = g1->atom[1]; /* == g2->atom[2] */ a3 = g1->atom[0]; /* == g2->atom[1] */ a4 = g2->atom[0]; found = ( a1->atomid < a4->atomid ); if ( a1 != a4 ) ++count2; } else if ( g2->atom[1] == g1->atom[2] ) { /* ABC DCB */ a1 = g1->atom[0]; a2 = g1->atom[1]; /* == g2->atom[2] */ a3 = g1->atom[2]; /* == g2->atom[1] */ a4 = g2->atom[0]; found = ( a1->atomid < a4->atomid ); if ( a1 != a4 ) ++count2; } } else return -6; if ( ! found ) continue; ++count1; tuple = memarena_alloc(mol->dihedral_arena,sizeof(topo_mol_dihedral_t)); if ( ! tuple ) return -10; tuple->next[0] = a1->dihedrals; tuple->atom[0] = a1; tuple->next[1] = a2->dihedrals; tuple->atom[1] = a2; tuple->next[2] = a3->dihedrals; tuple->atom[2] = a3; tuple->next[3] = a4->dihedrals; tuple->atom[3] = a4; tuple->del = 0; a1->dihedrals = tuple; a2->dihedrals = tuple; a3->dihedrals = tuple; a4->dihedrals = tuple; } } } } } if ( count2 != 2 * count1 ) return -15; /* missing dihedrals */ return 0; } int topo_mol_patch(topo_mol *mol, const topo_mol_ident_t *targets, int ntargets, const char *rname, int prepend, int warn_angles, int warn_dihedrals, int deflt) { int idef; topo_defs_residue_t *resdef; topo_defs_atom_t *atomdef; topo_defs_bond_t *bonddef; topo_defs_angle_t *angldef; topo_defs_dihedral_t *dihedef; topo_defs_improper_t *imprdef; topo_defs_cmap_t *cmapdef; topo_defs_conformation_t *confdef; topo_mol_residue_t *res, *oldres; topo_mol_atom_t *oldatoms = NULL; char errmsg[128]; if ( ! mol ) return -1; if ( mol->buildseg ) return -2; if ( ! mol->defs ) return -3; idef = hasharray_index(mol->defs->residue_hash,rname); if ( idef == HASHARRAY_FAIL ) { sprintf(errmsg,""unknown patch type %s"",rname); topo_mol_log_error(mol,errmsg); return -4; } resdef = &(mol->defs->residue_array[idef]); if ( ! resdef->patch ) { sprintf(errmsg,""unknown patch type %s"",rname); topo_mol_log_error(mol,errmsg); return -5; } oldres = 0; for ( atomdef = resdef->atoms; atomdef; atomdef = atomdef->next ) { if ( atomdef->res < 0 || atomdef->res >= ntargets ) return -6; res = topo_mol_get_res(mol,&targets[atomdef->res],atomdef->rel); if ( ! res ) return -7; if ( atomdef->del ) { topo_mol_del_atom(res,atomdef->name); oldres = 0; continue; } if ( res != oldres ) { oldres = res; oldatoms = res->atoms; } if ( atomdef->type[0] == '\0' ) { topo_mol_find_atom(&(res->atoms), oldatoms, atomdef->name); } else if ( topo_mol_add_atom(mol,&(res->atoms), oldatoms, atomdef) ) { sprintf(errmsg,""add atom failed in patch %s"",rname); topo_mol_log_error(mol,errmsg); return -8; } } for ( bonddef = resdef->bonds; bonddef; bonddef = bonddef->next ) { if ( bonddef->del ) topo_mol_del_bond(mol,targets,ntargets,bonddef); else if ( topo_mol_add_bond(mol,targets,ntargets,bonddef) ) { sprintf(errmsg,""Warning: add bond failed in patch %s"",rname); topo_mol_log_error(mol,errmsg); } } if ( warn_angles && resdef->angles ) { sprintf(errmsg,""Warning: explicit angles in patch %s will be deleted during autogeneration"",rname); topo_mol_log_error(mol,errmsg); } for ( angldef = resdef->angles; angldef; angldef = angldef->next ) { if ( angldef->del ) topo_mol_del_angle(mol,targets,ntargets,angldef); else if ( topo_mol_add_angle(mol,targets,ntargets,angldef) ) { sprintf(errmsg,""Warning: add angle failed in patch %s"",rname); topo_mol_log_error(mol,errmsg); } } if ( warn_dihedrals && resdef->dihedrals ) { sprintf(errmsg,""Warning: explicit dihedrals in patch %s will be deleted during autogeneration"",rname); topo_mol_log_error(mol,errmsg); } for ( dihedef = resdef->dihedrals; dihedef; dihedef = dihedef->next ) { if ( dihedef->del ) topo_mol_del_dihedral(mol,targets,ntargets,dihedef); else if ( topo_mol_add_dihedral(mol,targets,ntargets,dihedef) ) { sprintf(errmsg,""Warning: add dihedral failed in patch %s"",rname); topo_mol_log_error(mol,errmsg); } } for ( imprdef = resdef->impropers; imprdef; imprdef = imprdef->next ) { if ( imprdef->del ) topo_mol_del_improper(mol,targets,ntargets,imprdef); else if ( topo_mol_add_improper(mol,targets,ntargets,imprdef) ) { sprintf(errmsg,""Warning: add improper failed in patch %s"",rname); topo_mol_log_error(mol,errmsg); } } for ( cmapdef = resdef->cmaps; cmapdef; cmapdef = cmapdef->next ) { if ( cmapdef->del ) topo_mol_del_cmap(mol,targets,ntargets,cmapdef); else if ( topo_mol_add_cmap(mol,targets,ntargets,cmapdef) ) { sprintf(errmsg,""Warning: add cross-term failed in patch %s"",rname); topo_mol_log_error(mol,errmsg); } } for ( confdef = resdef->conformations; confdef; confdef = confdef->next ) { if ( confdef->del ) topo_mol_del_conformation(mol,targets,ntargets,confdef); else if ( topo_mol_add_conformation(mol,targets,ntargets,confdef) ) { sprintf(errmsg,""Warning: add conformation failed in patch %s"",rname); topo_mol_log_error(mol,errmsg); } } if (strncasecmp(rname,""NONE"",4)) { int ret; ret = topo_mol_add_patch(mol,rname,deflt); if (ret<0) { sprintf(errmsg,""Warning: Listing patch %s failed!"",rname); topo_mol_log_error(mol,errmsg); } for ( idef=0; idefarena, natoms*sizeof(topo_mol_atom_t*)); natoms = 0; /* walk all targets */ for (itarget=0; itargetresid) { /* whole segment */ seg = topo_mol_get_seg(mol,target); if ( ! seg ) return -2; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { if ( ipass ) atoms[natoms] = atom; ++natoms; } } continue; } if (!target->aname) { /* whole residue */ res = topo_mol_get_res(mol,target,0); if ( ! res ) return -3; for ( atom = res->atoms; atom; atom = atom->next ) { if ( ipass ) atoms[natoms] = atom; ++natoms; } continue; } /* one atom */ atom = topo_mol_get_atom(mol,target,0); if ( ! atom ) return -4; if ( ipass ) atoms[natoms] = atom; ++natoms; } } /* make one copy on each pass through loop */ for (icopy=1; icopycopy ) { topo_mol_log_error(mol,""an atom occurs twice in the selection""); return -20; } newatom = memarena_alloc(mol->arena,sizeof(topo_mol_atom_t)); if ( ! newatom ) return -5; memcpy(newatom,atom,sizeof(topo_mol_atom_t)); atom->next = newatom; atom->copy = newatom; newatom->bonds = 0; newatom->angles = 0; newatom->dihedrals = 0; newatom->impropers = 0; newatom->cmaps = 0; newatom->exclusions = 0; newatom->conformations = 0; } /* copy associated bonds, etc. */ for (iatom=0; iatombonds; bondtmp; bondtmp = topo_mol_bond_next(bondtmp,atom) ) { topo_mol_bond_t *tuple; if ( bondtmp->del ) continue; if ( bondtmp->atom[0] == atom || ( ! bondtmp->atom[0]->copy ) ) ; else continue; tuple = memarena_alloc(mol->arena,sizeof(topo_mol_bond_t)); if ( ! tuple ) return -6; a1 = bondtmp->atom[0]->copy; if ( ! a1 ) a1 = bondtmp->atom[0]; a2 = bondtmp->atom[1]->copy; if ( ! a2 ) a2 = bondtmp->atom[1]; tuple->next[0] = a1->bonds; tuple->atom[0] = a1; tuple->next[1] = a2->bonds; tuple->atom[1] = a2; tuple->del = 0; a1->bonds = tuple; a2->bonds = tuple; } for ( angletmp = atom->angles; angletmp; angletmp = topo_mol_angle_next(angletmp,atom) ) { topo_mol_angle_t *tuple; if ( angletmp->del ) continue; if ( angletmp->atom[0] == atom || ( ! angletmp->atom[0]->copy && ( angletmp->atom[1] == atom || ( ! angletmp->atom[1]->copy ) ) ) ) ; else continue; tuple = memarena_alloc(mol->angle_arena,sizeof(topo_mol_angle_t)); if ( ! tuple ) return -7; a1 = angletmp->atom[0]->copy; if ( ! a1 ) a1 = angletmp->atom[0]; a2 = angletmp->atom[1]->copy; if ( ! a2 ) a2 = angletmp->atom[1]; a3 = angletmp->atom[2]->copy; if ( ! a3 ) a3 = angletmp->atom[2]; tuple->next[0] = a1->angles; tuple->atom[0] = a1; tuple->next[1] = a2->angles; tuple->atom[1] = a2; tuple->next[2] = a3->angles; tuple->atom[2] = a3; tuple->del = 0; a1->angles = tuple; a2->angles = tuple; a3->angles = tuple; } for ( dihetmp = atom->dihedrals; dihetmp; dihetmp = topo_mol_dihedral_next(dihetmp,atom) ) { topo_mol_dihedral_t *tuple; if ( dihetmp->del ) continue; if ( dihetmp->atom[0] == atom || ( ! dihetmp->atom[0]->copy && ( dihetmp->atom[1] == atom || ( ! dihetmp->atom[1]->copy && ( dihetmp->atom[2] == atom || ( ! dihetmp->atom[2]->copy ) ) ) ) ) ) ; else continue; tuple = memarena_alloc(mol->dihedral_arena,sizeof(topo_mol_dihedral_t)); if ( ! tuple ) return -8; a1 = dihetmp->atom[0]->copy; if ( ! a1 ) a1 = dihetmp->atom[0]; a2 = dihetmp->atom[1]->copy; if ( ! a2 ) a2 = dihetmp->atom[1]; a3 = dihetmp->atom[2]->copy; if ( ! a3 ) a3 = dihetmp->atom[2]; a4 = dihetmp->atom[3]->copy; if ( ! a4 ) a4 = dihetmp->atom[3]; tuple->next[0] = a1->dihedrals; tuple->atom[0] = a1; tuple->next[1] = a2->dihedrals; tuple->atom[1] = a2; tuple->next[2] = a3->dihedrals; tuple->atom[2] = a3; tuple->next[3] = a4->dihedrals; tuple->atom[3] = a4; tuple->del = 0; a1->dihedrals = tuple; a2->dihedrals = tuple; a3->dihedrals = tuple; a4->dihedrals = tuple; } for ( imprtmp = atom->impropers; imprtmp; imprtmp = topo_mol_improper_next(imprtmp,atom) ) { topo_mol_improper_t *tuple; if ( imprtmp->del ) continue; if ( imprtmp->atom[0] == atom || ( ! imprtmp->atom[0]->copy && ( imprtmp->atom[1] == atom || ( ! imprtmp->atom[1]->copy && ( imprtmp->atom[2] == atom || ( ! imprtmp->atom[2]->copy ) ) ) ) ) ) ; else continue; tuple = memarena_alloc(mol->arena,sizeof(topo_mol_improper_t)); if ( ! tuple ) return -9; a1 = imprtmp->atom[0]->copy; if ( ! a1 ) a1 = imprtmp->atom[0]; a2 = imprtmp->atom[1]->copy; if ( ! a2 ) a2 = imprtmp->atom[1]; a3 = imprtmp->atom[2]->copy; if ( ! a3 ) a3 = imprtmp->atom[2]; a4 = imprtmp->atom[3]->copy; if ( ! a4 ) a4 = imprtmp->atom[3]; tuple->next[0] = a1->impropers; tuple->atom[0] = a1; tuple->next[1] = a2->impropers; tuple->atom[1] = a2; tuple->next[2] = a3->impropers; tuple->atom[2] = a3; tuple->next[3] = a4->impropers; tuple->atom[3] = a4; tuple->del = 0; a1->impropers = tuple; a2->impropers = tuple; a3->impropers = tuple; a4->impropers = tuple; } for ( cmaptmp = atom->cmaps; cmaptmp; cmaptmp = topo_mol_cmap_next(cmaptmp,atom) ) { topo_mol_atom_t *al[8]; topo_mol_cmap_t *tuple; int ia, skip; if ( cmaptmp->del ) continue; skip = 0; for ( ia = 0; ia < 8; ++ia ) { if ( cmaptmp->atom[ia] == atom ) { skip = 0; break; } if ( cmaptmp->atom[ia]->copy ) { skip = 1; break; } } if ( skip ) continue; tuple = memarena_alloc(mol->arena,sizeof(topo_mol_cmap_t)); if ( ! tuple ) return -9; for ( ia = 0; ia < 8; ++ia ) { topo_mol_atom_t *ai; ai = cmaptmp->atom[ia]->copy; if ( ! ai ) ai = cmaptmp->atom[ia]; al[ia] = ai; tuple->next[ia] = ai->cmaps; tuple->atom[ia] = ai; } for ( ia = 0; ia < 8; ++ia ) { /* This must be in a separate loop because atoms may be repeated. */ al[ia]->cmaps = tuple; } tuple->del = 0; } for ( excltmp = atom->exclusions; excltmp; excltmp = topo_mol_exclusion_next(excltmp,atom) ) { topo_mol_exclusion_t *tuple; if ( excltmp->del ) continue; if ( excltmp->atom[0] == atom || ( ! excltmp->atom[0]->copy ) ) ; else continue; tuple = memarena_alloc(mol->arena,sizeof(topo_mol_exclusion_t)); if ( ! tuple ) return -6; a1 = excltmp->atom[0]->copy; if ( ! a1 ) a1 = excltmp->atom[0]; a2 = excltmp->atom[1]->copy; if ( ! a2 ) a2 = excltmp->atom[1]; tuple->next[0] = a1->exclusions; tuple->atom[0] = a1; tuple->next[1] = a2->exclusions; tuple->atom[1] = a2; tuple->del = 0; a1->exclusions = tuple; a2->exclusions = tuple; } for ( conftmp = atom->conformations; conftmp; conftmp = topo_mol_conformation_next(conftmp,atom) ) { topo_mol_conformation_t *tuple; if ( conftmp->del ) continue; if ( conftmp->atom[0] == atom || ( ! conftmp->atom[0]->copy && ( conftmp->atom[1] == atom || ( ! conftmp->atom[1]->copy && ( conftmp->atom[2] == atom || ( ! conftmp->atom[2]->copy ) ) ) ) ) ) ; else continue; tuple = memarena_alloc(mol->arena,sizeof(topo_mol_conformation_t)); if ( ! tuple ) return -10; a1 = conftmp->atom[0]->copy; if ( ! a1 ) a1 = conftmp->atom[0]; a2 = conftmp->atom[1]->copy; if ( ! a2 ) a2 = conftmp->atom[1]; a3 = conftmp->atom[2]->copy; if ( ! a3 ) a3 = conftmp->atom[2]; a4 = conftmp->atom[3]->copy; if ( ! a4 ) a4 = conftmp->atom[3]; tuple->next[0] = a1->conformations; tuple->atom[0] = a1; tuple->next[1] = a2->conformations; tuple->atom[1] = a2; tuple->next[2] = a3->conformations; tuple->atom[2] = a3; tuple->next[3] = a4->conformations; tuple->atom[3] = a4; tuple->del = 0; tuple->improper = conftmp->improper; tuple->dist12 = conftmp->dist12; tuple->angle123 = conftmp->angle123; tuple->dihedral = conftmp->dihedral; tuple->angle234 = conftmp->angle234; tuple->dist34 = conftmp->dist34; a1->conformations = tuple; a2->conformations = tuple; a3->conformations = tuple; a4->conformations = tuple; } } /* clean up copy pointers */ for (iatom=0; iatompartition == 0 ) atom->partition = 1; atom->copy->partition = atom->partition + 1; atoms[iatom] = atom->copy; atom->copy = 0; } } /* icopy */ return 0; /* success */ } /* API function */ int topo_mol_delete_atom(topo_mol *mol, const topo_mol_ident_t *target) { topo_mol_residue_t *res; topo_mol_segment_t *seg; int ires, iseg; if (!mol) return 1; iseg = hasharray_index(mol->segment_hash,target->segid); if ( iseg == HASHARRAY_FAIL ) { char errmsg[50]; sprintf(errmsg,""no segment %s"",target->segid); topo_mol_log_error(mol,errmsg); return 1; } seg = mol->segment_array[iseg]; if (!target->resid) { /* Delete this segment */ int nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); atom = res->atoms; while (atom) { topo_mol_destroy_atom(atom); atom = atom->next; } res->atoms = 0; } hasharray_destroy(seg->residue_hash); mol->segment_array[iseg] = 0; if (hasharray_delete(mol->segment_hash, target->segid) < 0) { topo_mol_log_error(mol, ""Unable to delete segment""); } return 0; } ires = hasharray_index(seg->residue_hash,target->resid); if ( ires == HASHARRAY_FAIL ) { char errmsg[50]; sprintf(errmsg,""no residue %s of segment %s"", target->resid,target->segid); topo_mol_log_error(mol,errmsg); return 1; } res = seg->residue_array+ires; if (!target->aname) { /* Must destroy all atoms in residue, since there may be bonds between this residue and other atoms */ topo_mol_atom_t *atom = res->atoms; while (atom) { topo_mol_destroy_atom(atom); atom = atom->next; } res->atoms = 0; hasharray_delete(seg->residue_hash, target->resid); return 0; } /* Just delete one atom */ topo_mol_destroy_atom(topo_mol_unlink_atom(&(res->atoms),target->aname)); return 0; } int topo_mol_set_name(topo_mol *mol, const topo_mol_ident_t *target, const char *name) { topo_mol_residue_t *res; topo_mol_atom_t *atom; if ( ! mol ) return -1; if ( ! target ) return -2; res = topo_mol_get_res(mol,target,0); if ( ! res ) return -3; for ( atom = res->atoms; atom; atom = atom->next ) { if ( ! strcmp(target->aname,atom->name) ) break; } if ( ! atom ) return -3; strcpy(atom->name,name); return 0; } int topo_mol_set_resname(topo_mol *mol, const topo_mol_ident_t *target, const char *rname) { topo_mol_residue_t *res; if ( ! mol ) return -1; if ( ! target ) return -2; res = topo_mol_get_res(mol,target,0); if ( ! res ) return -3; strcpy(res->name,rname); return 0; } int topo_mol_set_segid(topo_mol *mol, const topo_mol_ident_t *target, const char *segid) { int iseg, iseg2; topo_mol_segment_t *seg; if ( ! mol ) return -1; if ( ! target ) return -2; seg = topo_mol_get_seg(mol,target); if ( ! seg ) return -3; iseg = hasharray_delete(mol->segment_hash, seg->segid); if ( iseg < 0) { topo_mol_log_error(mol, ""Unable to delete segment""); return -4; } strcpy(seg->segid,segid); iseg2 = hasharray_reinsert(mol->segment_hash, seg->segid, iseg); if ( iseg != iseg2 ) { topo_mol_log_error(mol, ""Unable to insert segment""); return -5; } return 0; } int topo_mol_set_element(topo_mol *mol, const topo_mol_ident_t *target, const char *element, int replace) { topo_mol_residue_t *res; topo_mol_atom_t *atom; if ( ! mol ) return -1; if ( ! target ) return -2; res = topo_mol_get_res(mol,target,0); if ( ! res ) return -3; for ( atom = res->atoms; atom; atom = atom->next ) { if ( ! strcmp(target->aname,atom->name) ) break; } if ( ! atom ) return -3; if ( replace || ! strlen(atom->element) ) { strcpy(atom->element,element); } return 0; } int topo_mol_set_chain(topo_mol *mol, const topo_mol_ident_t *target, const char *chain, int replace) { topo_mol_residue_t *res; if ( ! mol ) return -1; if ( ! target ) return -2; res = topo_mol_get_res(mol,target,0); if ( ! res ) return -3; if ( replace || ! strlen(res->chain) ) { strcpy(res->chain,chain); } return 0; } int topo_mol_set_xyz(topo_mol *mol, const topo_mol_ident_t *target, double x, double y, double z) { topo_mol_residue_t *res; topo_mol_atom_t *atom; if ( ! mol ) return -1; if ( ! target ) return -2; res = topo_mol_get_res(mol,target,0); if ( ! res ) return -3; for ( atom = res->atoms; atom; atom = atom->next ) { if ( ! strcmp(target->aname,atom->name) ) break; } if ( ! atom ) return -3; atom->x = x; atom->y = y; atom->z = z; atom->xyz_state = TOPO_MOL_XYZ_SET; return 0; } int topo_mol_set_vel(topo_mol *mol, const topo_mol_ident_t *target, double vx, double vy, double vz) { topo_mol_residue_t *res; topo_mol_atom_t *atom; if ( ! mol ) return -1; if ( ! target ) return -2; res = topo_mol_get_res(mol,target,0); if ( ! res ) return -3; for ( atom = res->atoms; atom; atom = atom->next ) { if ( ! strcmp(target->aname,atom->name) ) break; } if ( ! atom ) return -3; atom->vx = vx; atom->vy = vy; atom->vz = vz; return 0; } int topo_mol_set_mass(topo_mol *mol, const topo_mol_ident_t *target, double mass) { topo_mol_residue_t *res; topo_mol_atom_t *atom; if ( ! mol ) return -1; if ( ! target ) return -2; res = topo_mol_get_res(mol,target,0); if ( ! res ) return -3; for ( atom = res->atoms; atom; atom = atom->next ) { if ( ! strcmp(target->aname,atom->name) ) break; } if ( ! atom ) return -3; atom->mass = mass; return 0; } int topo_mol_set_charge(topo_mol *mol, const topo_mol_ident_t *target, double charge) { topo_mol_residue_t *res; topo_mol_atom_t *atom; if ( ! mol ) return -1; if ( ! target ) return -2; res = topo_mol_get_res(mol,target,0); if ( ! res ) return -3; for ( atom = res->atoms; atom; atom = atom->next ) { if ( ! strcmp(target->aname,atom->name) ) break; } if ( ! atom ) return -3; atom->charge = charge; return 0; } int topo_mol_set_bfactor(topo_mol *mol, const topo_mol_ident_t *target, double bfactor) { topo_mol_residue_t *res; topo_mol_atom_t *atom; if ( ! mol ) return -1; if ( ! target ) return -2; res = topo_mol_get_res(mol,target,0); if ( ! res ) return -3; for ( atom = res->atoms; atom; atom = atom->next ) { if ( ! strcmp(target->aname,atom->name) ) break; } if ( ! atom ) return -3; atom->partition = bfactor; return 0; } /* XXX Unused */ int topo_mol_clear_xyz(topo_mol *mol, const topo_mol_ident_t *target) { topo_mol_atom_t *atom; if ( ! mol ) return -1; if ( ! target ) return -2; atom = topo_mol_get_atom(mol,target,0); if ( ! atom ) return -3; atom->x = 0; atom->y = 0; atom->z = 0; atom->xyz_state = TOPO_MOL_XYZ_VOID; return 0; } int topo_mol_guess_xyz(topo_mol *mol) { char msg[128]; int iseg,nseg,ires,nres,ucount,i,nk,nu,gcount,gwild,okwild,wcount,hcount; int ipass; topo_mol_segment_t *seg; topo_mol_residue_t *res; topo_mol_atom_t *atom, *a1, *a2, *a3; topo_mol_atom_t *ka[4]; topo_mol_atom_t *ua[4]; topo_mol_bond_t *bondtmp; topo_mol_angle_t *angletmp; double dihedral, angle234, dist34; topo_mol_atom_t **uatoms; topo_mol_conformation_t *conf; double r12x,r12y,r12z,r12,r23x,r23y,r23z,r23,ix,iy,iz,jx,jy,jz,kx,ky,kz; double tx,ty,tz,a,b,c; if ( ! mol ) return -1; ucount = 0; hcount = 0; nseg = hasharray_count(mol->segment_hash); for ( iseg=0; isegsegment_array[iseg]; if (! seg) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { if ( atom->xyz_state != TOPO_MOL_XYZ_SET ) { ++ucount; if ( atom->mass > 2.5 ) ++hcount; } } } } sprintf(msg,""Info: guessing coordinates for %d atoms (%d non-hydrogen)"", ucount, hcount); topo_mol_log_error(mol,msg); uatoms = (topo_mol_atom_t**) malloc(ucount*sizeof(topo_mol_atom_t*)); if ( ! uatoms ) return -2; ucount = 0; nseg = hasharray_count(mol->segment_hash); for ( iseg=0; isegsegment_array[iseg]; if (! seg) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { if ( atom->xyz_state != TOPO_MOL_XYZ_SET ) uatoms[ucount++] = atom; } } } for ( i=0; ixyz_state = TOPO_MOL_XYZ_VOID; /* everything below based on atom 4 unknown, all others known */ /* from the CHARMM docs: Normal IC table entry: I \ \ J----K \ \ L values (Rij),(Tijk),(Pijkl),(Tjkl),(Rkl) Improper type of IC table entry: I L \ / \ / *K | | J values (Rik),(Tikj),(Pijkl),T(jkl),(Rkl) */ #ifndef M_PI #define M_PI 3.14159265358979323846 #endif gcount = 1; okwild = 0; wcount = 0; hcount = 0; while ( gcount || ! okwild ) { if ( gcount == 0 ) { if ( okwild ) break; else okwild = 1; } gcount = 0; for ( i=0; ixyz_state != TOPO_MOL_XYZ_VOID ) continue; for ( conf = atom->conformations; conf; conf = topo_mol_conformation_next(conf,atom) ) { if ( conf->del ) continue; else if ( conf->atom[0] == atom && conf->atom[1]->xyz_state != TOPO_MOL_XYZ_VOID && conf->atom[2]->xyz_state != TOPO_MOL_XYZ_VOID && conf->atom[3]->xyz_state != TOPO_MOL_XYZ_VOID ) { if ( conf->improper ) { a1 = conf->atom[3]; a2 = conf->atom[1]; a3 = conf->atom[2]; dist34 = conf->dist12; angle234 = conf->angle123 * (M_PI/180.0); dihedral = -1.0 * conf->dihedral * (M_PI/180.0); } else { a1 = conf->atom[3]; a2 = conf->atom[2]; a3 = conf->atom[1]; dist34 = conf->dist12; angle234 = conf->angle123 * (M_PI/180.0); dihedral = conf->dihedral * (M_PI/180.0); } } else if ( conf->atom[3] == atom && conf->atom[2]->xyz_state != TOPO_MOL_XYZ_VOID && conf->atom[1]->xyz_state != TOPO_MOL_XYZ_VOID && conf->atom[0]->xyz_state != TOPO_MOL_XYZ_VOID ) { if ( conf->improper ) { a1 = conf->atom[0]; a2 = conf->atom[1]; a3 = conf->atom[2]; dist34 = conf->dist34; angle234 = conf->angle234 * (M_PI/180.0); dihedral = conf->dihedral * (M_PI/180.0); } else { a1 = conf->atom[0]; a2 = conf->atom[1]; a3 = conf->atom[2]; dist34 = conf->dist34; angle234 = conf->angle234 * (M_PI/180.0); dihedral = conf->dihedral * (M_PI/180.0); } } else continue; gwild = 0; if ( dist34 == 0.0 ) { dist34 = 1.0; gwild = 1; } if ( angle234 == 0.0 ) { angle234 = 109.0*M_PI/180.0; gwild = 1; } r12x = a2->x - a1->x; r12y = a2->y - a1->y; r12z = a2->z - a1->z; r23x = a3->x - a2->x; r23y = a3->y - a2->y; r23z = a3->z - a2->z; a = sqrt(r23x*r23x + r23y*r23y + r23z*r23z); if ( a == 0.0 ) gwild = 1; else a = 1.0 / a; ix = a * r23x; iy = a * r23y; iz = a * r23z; tx = r12y*r23z - r12z*r23y; ty = r12z*r23x - r12x*r23z; tz = r12x*r23y - r12y*r23x; a = sqrt(tx*tx + ty*ty + tz*tz); if ( a == 0.0 ) gwild = 1; else a = 1.0 / a; kx = a * tx; ky = a * ty; kz = a * tz; tx = ky*iz - kz*iy; ty = kz*ix - kx*iz; tz = kx*iy - ky*ix; a = sqrt(tx*tx + ty*ty + tz*tz); if ( a == 0.0 ) gwild = 1; else a = 1.0 / a; jx = a * tx; jy = a * ty; jz = a * tz; a = -1.0 * dist34 * cos(angle234); b = dist34 * sin(angle234) * cos(dihedral); c = dist34 * sin(angle234) * sin(dihedral); if ( gwild && ! okwild ) continue; if ( okwild ) { ++wcount; if ( atom->mass > 2.5 ) ++hcount; } atom->x = a3->x + a * ix + b * jx + c * kx; atom->y = a3->y + a * iy + b * jy + c * ky; atom->z = a3->z + a * iz + b * jz + c * kz; atom->xyz_state = okwild ? TOPO_MOL_XYZ_BADGUESS : TOPO_MOL_XYZ_GUESS; ++gcount; break; /* don't re-guess this atom */ } } } /* look for bad angles due to swapped atom names */ for ( i=0; ixyz_state == TOPO_MOL_XYZ_VOID || atom->xyz_state == TOPO_MOL_XYZ_SET ) continue; for ( angletmp = atom->angles; angletmp; angletmp = topo_mol_angle_next(angletmp,atom) ) { if ( angletmp->del ) continue; if ( angletmp->atom[0] == atom ) { a1 = angletmp->atom[2]; a2 = angletmp->atom[1]; } else if ( angletmp->atom[2] == atom ) { a1 = angletmp->atom[0]; a2 = angletmp->atom[1]; } else continue; /* only use set atoms, don't hid topology file errors */ if ( a1->xyz_state != TOPO_MOL_XYZ_SET ) continue; if ( a2->xyz_state != TOPO_MOL_XYZ_SET ) continue; r12x = a2->x - a1->x; r12y = a2->y - a1->y; r12z = a2->z - a1->z; r12 = sqrt(r12x*r12x + r12y*r12y + r12z*r12z); r23x = atom->x - a2->x; r23y = atom->y - a2->y; r23z = atom->z - a2->z; r23 = sqrt(r23x*r23x + r23y*r23y + r23z*r23z); /* assume wrong if angle is less than 45 degrees */ if ( r12x*r23x + r12y*r23y + r12z*r23z < r12 * r23 * -0.7 ) { sprintf(msg, ""Warning: failed to guess coordinate due to bad angle %s %s %s"", a1->name, a2->name, atom->name); topo_mol_log_error(mol, msg); if ( atom->xyz_state == TOPO_MOL_XYZ_BADGUESS ) { --wcount; if ( atom->mass > 2.5 ) --hcount; } --gcount; atom->xyz_state = TOPO_MOL_XYZ_VOID; break; } } } /* fallback rules for atoms without conformation records */ for ( ipass=0; ipass<2; ++ipass ) { /* don't do entire chain */ for ( i=0; ixyz_state != TOPO_MOL_XYZ_VOID ) continue; /* pick heaviest known atom we are bonded to (to deal with water) */ a1 = 0; for ( bondtmp = atom->bonds; bondtmp; bondtmp = topo_mol_bond_next(bondtmp,atom) ) { if ( bondtmp->atom[0] == atom ) a2 = bondtmp->atom[1]; else a2 = bondtmp->atom[0]; if ( a2->xyz_state == TOPO_MOL_XYZ_VOID ) continue; if ( a1 == 0 || a2->mass > a1->mass ) a1 = a2; } if ( a1 == 0 ) continue; atom = a1; /* find all bonded atoms known and unknown coordinates */ nk = 0; nu = 0; for ( bondtmp = atom->bonds; bondtmp; bondtmp = topo_mol_bond_next(bondtmp,atom) ) { if ( bondtmp->del ) continue; if ( bondtmp->atom[0] == atom ) a2 = bondtmp->atom[1]; else a2 = bondtmp->atom[0]; if ( a2->xyz_state == TOPO_MOL_XYZ_VOID ) { if ( nu < 4 ) ua[nu++] = a2; } else { if ( nk < 4 ) ka[nk++] = a2; } } if ( ipass ) { /* hydrogens only on second pass */ int j = 0; for ( j=0; jmass < 2.5; ++j ); if ( j != nu ) continue; } if ( nu + nk > 4 ) continue; /* no intuition beyond this case */ if ( nk == 0 ) { /* not bonded to any known atoms */ a1 = ua[0]; a1->x = atom->x + 1.0; a1->y = atom->y; a1->z = atom->z; a1->xyz_state = TOPO_MOL_XYZ_BADGUESS; ++gcount; ++wcount; if ( a1->mass > 2.5 ) ++hcount; continue; } if ( nk == 1 ) { /* bonded to one known atom */ a1 = ka[0]; ix = a1->x - atom->x; iy = a1->y - atom->y; iz = a1->z - atom->z; a = sqrt(ix*ix+iy*iy+iz*iz); if ( a ) a = 1.0 / a; else continue; ix *= a; iy *= a; iz *= a; jx = -1.0 * iy; jy = ix; jz = 0; if ( jx*jx + jy*jy + jz*jz < 0.1 ) { jx = 0; jy = -1.0 * iz; jz = iy; } a = sqrt(jx*jx+jy*jy+jz*jz); if ( a ) a = 1.0 / a; else continue; jx *= a; jy *= a; jz *= a; if ( nu == 1 ) { /* one unknown atom */ a = cos(109.0*M_PI/180.0); b = sin(109.0*M_PI/180.0); a2 = ua[0]; a2->x = atom->x + a * ix + b * jx; a2->y = atom->y + a * iy + b * jy; a2->z = atom->z + a * iz + b * jz; a2->xyz_state = TOPO_MOL_XYZ_BADGUESS; ++gcount; ++wcount; if ( a2->mass > 2.5 ) ++hcount; } else if ( nu == 2 ) { /* two unknown atoms */ a = cos(120.0*M_PI/180.0); b = sin(120.0*M_PI/180.0); a1 = ua[0]; a2 = ua[1]; a1->x = atom->x + a * ix + b * jx; a1->y = atom->y + a * iy + b * jy; a1->z = atom->z + a * iz + b * jz; a2->x = atom->x + a * ix - b * jx; a2->y = atom->y + a * iy - b * jy; a2->z = atom->z + a * iz - b * jz; a1->xyz_state = TOPO_MOL_XYZ_BADGUESS; ++gcount; ++wcount; if ( a1->mass > 2.5 ) ++hcount; a2->xyz_state = TOPO_MOL_XYZ_BADGUESS; ++gcount; ++wcount; if ( a2->mass > 2.5 ) ++hcount; } else { /* three unknown atoms */ a1 = ua[0]; a2 = ua[1]; a3 = ua[2]; /* only handle this case if at least two are hydrogens */ if ( a1->mass > 2.5 && a2->mass > 2.5 ) continue; if ( a1->mass > 2.5 && a3->mass > 2.5 ) continue; if ( a2->mass > 2.5 && a3->mass > 2.5 ) continue; kx = iy*jz - iz*jy; ky = iz*jx - ix*jz; kz = ix*jy - iy*jx; a = sqrt(kx*kx+ky*ky+kz*kz); if ( a ) a = 1.0 / a; else continue; kx *= a; ky *= a; kz *= a; a = cos(109.0*M_PI/180.0); b = sin(109.0*M_PI/180.0); a1->x = atom->x + a * ix + b * jx; a1->y = atom->y + a * iy + b * jy; a1->z = atom->z + a * iz + b * jz; c = b * sin(120.0*M_PI/180.0); b *= cos(120.0*M_PI/180.0); a2->x = atom->x + a * ix + b * jx + c * kx; a2->y = atom->y + a * iy + b * jy + c * ky; a2->z = atom->z + a * iz + b * jz + c * kz; a3->x = atom->x + a * ix + b * jx - c * kx; a3->y = atom->y + a * iy + b * jy - c * ky; a3->z = atom->z + a * iz + b * jz - c * kz; a1->xyz_state = TOPO_MOL_XYZ_BADGUESS; ++gcount; ++wcount; if ( a1->mass > 2.5 ) ++hcount; a2->xyz_state = TOPO_MOL_XYZ_BADGUESS; ++gcount; ++wcount; if ( a2->mass > 2.5 ) ++hcount; a3->xyz_state = TOPO_MOL_XYZ_BADGUESS; ++gcount; ++wcount; if ( a3->mass > 2.5 ) ++hcount; } continue; } if ( nk == 2 ) { /* bonded to two known atoms */ a1 = ka[0]; ix = a1->x - atom->x; iy = a1->y - atom->y; iz = a1->z - atom->z; a = sqrt(ix*ix+iy*iy+iz*iz); if ( a ) a = 1.0 / a; else continue; ix *= a; iy *= a; iz *= a; jx = ix; jy = iy; jz = iz; a1 = ka[1]; ix = a1->x - atom->x; iy = a1->y - atom->y; iz = a1->z - atom->z; a = sqrt(ix*ix+iy*iy+iz*iz); if ( a ) a = 1.0 / a; else continue; ix *= a; iy *= a; iz *= a; kx = jx - ix; ky = jy - iy; kz = jz - iz; jx += ix; jy += iy; jz += iz; a = sqrt(jx*jx+jy*jy+jz*jz); if ( a ) a = 1.0 / a; else continue; jx *= a; jy *= a; jz *= a; if ( nu == 1 ) { /* one unknown atom */ a2 = ua[0]; a2->x = atom->x - jx; a2->y = atom->y - jy; a2->z = atom->z - jz; a2->xyz_state = TOPO_MOL_XYZ_BADGUESS; ++gcount; ++wcount; if ( a2->mass > 2.5 ) ++hcount; } else { /* two unknown atoms */ a1 = ua[0]; a2 = ua[1]; /* only handle this case if both are hydrogens */ if ( a1->mass > 2.5 || a2->mass > 2.5 ) continue; a = sqrt(kx*kx+ky*ky+kz*kz); if ( a ) a = 1.0 / a; else continue; kx *= a; ky *= a; kz *= a; ix = jy*kz - jz*ky; iy = jz*kx - jx*kz; iz = jx*ky - jy*kx; a = sqrt(ix*ix+iy*iy+iz*iz); if ( a ) a = 1.0 / a; else continue; ix *= a; iy *= a; iz *= a; angle234 = (180.0-0.5*109.0)*M_PI/180.0; a = sin(angle234); b = cos(angle234); a1->x = atom->x + a * ix + b * jx; a1->y = atom->y + a * iy + b * jy; a1->z = atom->z + a * iz + b * jz; a2->x = atom->x - a * ix + b * jx; a2->y = atom->y - a * iy + b * jy; a2->z = atom->z - a * iz + b * jz; a1->xyz_state = TOPO_MOL_XYZ_BADGUESS; ++gcount; ++wcount; if ( a1->mass > 2.5 ) ++hcount; a2->xyz_state = TOPO_MOL_XYZ_BADGUESS; ++gcount; ++wcount; if ( a2->mass > 2.5 ) ++hcount; } continue; } if ( nk == 3 ) { /* bonded to three known atoms */ a1 = ka[0]; ix = a1->x - atom->x; iy = a1->y - atom->y; iz = a1->z - atom->z; a = sqrt(ix*ix+iy*iy+iz*iz); if ( a ) a = 1.0 / a; else continue; ix *= a; iy *= a; iz *= a; jx = ix; jy = iy; jz = iz; a1 = ka[1]; ix = a1->x - atom->x; iy = a1->y - atom->y; iz = a1->z - atom->z; a = sqrt(ix*ix+iy*iy+iz*iz); if ( a ) a = 1.0 / a; else continue; ix *= a; iy *= a; iz *= a; jx += ix; jy += iy; jz += iz; a1 = ka[2]; ix = a1->x - atom->x; iy = a1->y - atom->y; iz = a1->z - atom->z; a = sqrt(ix*ix+iy*iy+iz*iz); if ( a ) a = 1.0 / a; else continue; ix *= a; iy *= a; iz *= a; jx += ix; jy += iy; jz += iz; a = sqrt(jx*jx+jy*jy+jz*jz); if ( a ) a = 1.0 / a; else continue; a2 = ua[0]; a2->x = atom->x - a * jx; a2->y = atom->y - a * jy; a2->z = atom->z - a * jz; a2->xyz_state = TOPO_MOL_XYZ_BADGUESS; ++gcount; ++wcount; if ( a2->mass > 2.5 ) ++hcount; continue; } } } gcount = 0; for ( i=0; ixyz_state == TOPO_MOL_XYZ_VOID ) ++gcount; } if ( wcount ) { sprintf(msg,""Warning: poorly guessed coordinates for %d atoms (%d non-hydrogen):"", wcount, hcount); topo_mol_log_error(mol,msg); for ( iseg=0; isegsegment_array[iseg]; if (! seg) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { if ( atom->xyz_state == TOPO_MOL_XYZ_BADGUESS) { sprintf(msg, ""Warning: poorly guessed coordinate for atom %s\t %s:%s\t %s"", atom->name, res->name, res->resid, seg->segid); topo_mol_log_error(mol, msg); } } } } } if ( gcount ) { sprintf(msg,""Warning: failed to guess coordinates for %d atoms"",gcount); topo_mol_log_error(mol,msg); } free((void*)uatoms); return 0; } /* Copied and modified from topo_mol_segment */ int topo_mol_add_patch(topo_mol *mol, const char *pname, int deflt) { topo_mol_patch_t **patches; topo_mol_patch_t *patchtmp; if ( ! mol ) return -1; if ( NAMETOOLONG(pname) ) return -2; patches = &(mol->patches); patchtmp = 0; patchtmp = memarena_alloc(mol->arena,sizeof(topo_mol_patch_t)); if ( ! patchtmp ) return -3; strcpy(patchtmp->pname,pname); patchtmp->patchresids = 0; patchtmp->npres = 0; patchtmp->deflt = deflt; patchtmp->next = 0; /* printf(""add_patch %i %s;\n"", mol->npatch, patchtmp->pname); */ if (mol->npatch==0) { *patches = patchtmp; } else { mol->curpatch->next = patchtmp; } mol->curpatch = patchtmp; mol->npatch++; return 0; } /* Copied and modified from topo_mol_residue */ int topo_mol_add_patchres(topo_mol *mol, const topo_mol_ident_t *target) { topo_mol_patch_t *patch; topo_mol_patchres_t **patchres; topo_mol_patchres_t *patchrestmp; if ( ! mol ) return -1; if ( NAMETOOLONG(target->segid) ) return -2; if ( NAMETOOLONG(target->resid) ) return -2; patch = mol->curpatch; patchres = &(patch->patchresids); patchrestmp = 0; patchrestmp = memarena_alloc(mol->arena,sizeof(topo_mol_patchres_t)); if ( ! patchrestmp ) return -3; strcpy(patchrestmp->segid,target->segid); strcpy(patchrestmp->resid,target->resid); /* printf(""add_patchres %i %s:%s;\n"", patch->npres, patchrestmp->segid, patchrestmp->resid); */ patch->npres++; /* patchrestmp->next = *patchres; old code builds list in reverse order */ patchrestmp->next = NULL; while ( *patchres ) { patchres = &((*patchres)->next); } *patchres = patchrestmp; return 0; } /* Test the existence of segid:resid for the patch */ int topo_mol_validate_patchres(topo_mol *mol, const char *pname, const char *segid, const char *resid) { topo_mol_ident_t target; topo_mol_segment_t *seg; topo_mol_residue_t *res; target.segid = segid; target.resid = resid; seg = topo_mol_get_seg(mol,&target); if ( ! seg ) { char errmsg[50]; sprintf(errmsg,""Segment %s not exsisting, skipping patch %s.\n"",segid,pname); topo_mol_log_error(mol,errmsg); return 0; } res = topo_mol_get_res(mol,&target,0); if ( ! res ) { char errmsg[50]; sprintf(errmsg,""Residue %s:%s not exsisting, skipping patch %s.\n"",segid,resid,pname); topo_mol_log_error(mol,errmsg); return 0; } return 1; } ","C" "Biophysics","Eigenstate/psfgen","src/hash.h",".h","1020","42","/* * hash.h - A simple hash table * * Uses null terminated strings as the keys for the table. * Stores an integer value with the string key. It would be * easy to change to use void *'s instead of ints. Maybe rewrite * as a C++ template?? * * Donated by John Stone */ #ifndef HASH_H #define HASH_H #ifdef __cplusplus extern ""C"" { #endif typedef struct hash_t { struct hash_node_t **bucket; /* array of hash nodes */ int size; /* size of the array */ int entries; /* number of entries in table */ int downshift; /* shift cound, used in hash function */ int mask; /* used to select bits for hashing */ } hash_t; #define HASH_FAIL -1 void hash_init(hash_t *, int); int hash_lookup (hash_t *, const char *); int hash_insert (hash_t *, const char *, int); int hash_delete (hash_t *, const char *); void hash_destroy(hash_t *); char *hash_stats (hash_t *); #ifdef __cplusplus } #endif #endif ","Unknown" "Biophysics","Eigenstate/psfgen","src/topo_mol_struct.h",".h","3744","157"," #ifndef TOPO_DEFS_MOL_H #define TOPO_DEFS_MOL_H #include ""hasharray.h"" #include ""memarena.h"" #include ""topo_defs_struct.h"" #include ""topo_mol.h"" #define NAMEMAXLEN 10 #define NAMETOOLONG(X) ( strlen(X) >= NAMEMAXLEN ) struct topo_mol_atom_t; typedef struct topo_mol_bond_t { struct topo_mol_bond_t *next[2]; struct topo_mol_atom_t *atom[2]; int del; } topo_mol_bond_t; typedef struct topo_mol_angle_t { struct topo_mol_angle_t *next[3]; struct topo_mol_atom_t *atom[3]; int del; } topo_mol_angle_t; typedef struct topo_mol_dihedral_t { struct topo_mol_dihedral_t *next[4]; struct topo_mol_atom_t *atom[4]; int del; } topo_mol_dihedral_t; typedef struct topo_mol_improper_t { struct topo_mol_improper_t *next[4]; struct topo_mol_atom_t *atom[4]; int del; } topo_mol_improper_t; typedef struct topo_mol_cmap_t { struct topo_mol_cmap_t *next[8]; struct topo_mol_atom_t *atom[8]; int del; } topo_mol_cmap_t; typedef struct topo_mol_exclusion_t { struct topo_mol_exclusion_t *next[2]; struct topo_mol_atom_t *atom[2]; int del; } topo_mol_exclusion_t; typedef struct topo_mol_conformation_t { struct topo_mol_conformation_t *next[4]; struct topo_mol_atom_t *atom[4]; int del; int improper; double dist12, angle123, dihedral, angle234, dist34; } topo_mol_conformation_t; #define TOPO_MOL_XYZ_VOID 0 #define TOPO_MOL_XYZ_SET 1 #define TOPO_MOL_XYZ_GUESS 2 #define TOPO_MOL_XYZ_BADGUESS 3 typedef struct topo_mol_atom_t { struct topo_mol_atom_t *next; struct topo_mol_atom_t *copy; topo_mol_bond_t *bonds; topo_mol_angle_t *angles; topo_mol_dihedral_t *dihedrals; topo_mol_improper_t *impropers; topo_mol_cmap_t *cmaps; topo_mol_exclusion_t *exclusions; topo_mol_conformation_t *conformations; char name[NAMEMAXLEN]; char type[NAMEMAXLEN]; char element[NAMEMAXLEN]; double mass; double charge; double x,y,z; double vx,vy,vz; int xyz_state; int partition; int atomid; } topo_mol_atom_t; typedef struct topo_mol_residue_t { char resid[NAMEMAXLEN]; char name[NAMEMAXLEN]; char chain[NAMEMAXLEN]; topo_mol_atom_t *atoms; } topo_mol_residue_t; typedef struct topo_mol_segment_t { char segid[NAMEMAXLEN]; topo_mol_residue_t *residue_array; hasharray *residue_hash; int auto_angles; int auto_dihedrals; char pfirst[NAMEMAXLEN]; char plast[NAMEMAXLEN]; } topo_mol_segment_t; typedef struct topo_mol_patchres_t { struct topo_mol_patchres_t *next; char segid[NAMEMAXLEN]; char resid[NAMEMAXLEN]; } topo_mol_patchres_t; typedef struct topo_mol_patch_t { struct topo_mol_patch_t *next; char pname[NAMEMAXLEN]; int npres; int deflt; topo_mol_patchres_t *patchresids; } topo_mol_patch_t; struct topo_mol { void *newerror_handler_data; void (*newerror_handler)(void *, const char *); topo_defs *defs; int npatch; topo_mol_patch_t *patches; topo_mol_patch_t *curpatch; topo_mol_segment_t **segment_array; hasharray *segment_hash; topo_mol_segment_t *buildseg; memarena *arena; memarena *angle_arena; memarena *dihedral_arena; }; topo_mol_bond_t * topo_mol_bond_next( topo_mol_bond_t *tuple, topo_mol_atom_t *atom); topo_mol_angle_t * topo_mol_angle_next( topo_mol_angle_t *tuple, topo_mol_atom_t *atom); topo_mol_dihedral_t * topo_mol_dihedral_next( topo_mol_dihedral_t *tuple, topo_mol_atom_t *atom); topo_mol_improper_t * topo_mol_improper_next( topo_mol_improper_t *tuple, topo_mol_atom_t *atom); topo_mol_cmap_t * topo_mol_cmap_next( topo_mol_cmap_t *tuple, topo_mol_atom_t *atom); topo_mol_exclusion_t * topo_mol_exclusion_next( topo_mol_exclusion_t *tuple, topo_mol_atom_t *atom); #endif ","Unknown" "Biophysics","Eigenstate/psfgen","src/tcl_psfgen.c",".c","68117","2079"," #include #include #include #include #include ""psfgen.h"" #include ""charmm_parse_topo_defs.h"" #include ""topo_mol_output.h"" #include ""topo_mol_pluginio.h"" #include ""pdb_file_extract.h"" #include ""psf_file_extract.h"" #include ""topo_defs_struct.h"" #include ""topo_mol_struct.h"" #include ""extract_alias.h"" #if defined(_MSC_VER) #define strcasecmp stricmp #define strncasecmp strnicmp #endif #if defined(NAMD_TCL) || ! defined(NAMD_VERSION) #include /* Tcl 8.4 migration. */ #ifndef CONST84 # define CONST84 #endif void newhandle_msg(void *v, const char *msg); void newhandle_msg_ex(void *v, const char *msg, int prepend, int newline); #ifndef NAMD_VERSION /* * Provide user feedback and warnings beyond result values. * If we are running interactively, Tcl_Main will take care of echoing results * to the console. If we run a script, we need to output the results * ourselves. */ void newhandle_msg(void *v, const char *msg) { Tcl_Interp *interp = (Tcl_Interp *)v; const char *words[3] = {""puts"", ""-nonewline"", ""psfgen) ""}; char *script = NULL; // prepend ""psfgen) "" to all output script = Tcl_Merge(3, words); Tcl_Eval(interp,script); Tcl_Free(script); // emit the output words[1] = msg; script = Tcl_Merge(2, words); Tcl_Eval(interp,script); Tcl_Free(script); } /* * Same as above but allow user control over prepending of ""psfgen) "" * and newlines. */ void newhandle_msg_ex(void *v, const char *msg, int prepend, int newline) { Tcl_Interp *interp = (Tcl_Interp *)v; const char *words[3] = {""puts"", ""-nonewline"", ""psfgen) ""}; char *script = NULL; if (prepend) { // prepend ""psfgen) "" to all output script = Tcl_Merge(3, words); Tcl_Eval(interp,script); Tcl_Free(script); } // emit the output if (newline) { words[1] = msg; script = Tcl_Merge(2, words); } else { words[2] = msg; script = Tcl_Merge(3, words); } Tcl_Eval(interp,script); Tcl_Free(script); } #endif /* * Kills molecule to prevent user from saving bogus output. */ void psfgen_kill_mol(Tcl_Interp *interp, psfgen_data *data) { if (data->mol) { Tcl_AppendResult(interp, ""\nMOLECULE DESTROYED BY FATAL ERROR! Use resetpsf to start over."", NULL); } topo_mol_destroy(data->mol); data->mol = 0; } int psfgen_test_mol(Tcl_Interp *interp, psfgen_data *data) { if (! data->mol) { Tcl_AppendResult(interp, ""\nMOLECULE MISSING! Use resetpsf to start over."", NULL); return -1; } return 0; } #define PSFGEN_TEST_MOL(INTERP,DATA) \ if ( psfgen_test_mol(INTERP,DATA) ) return TCL_ERROR /* This function gets called if/when the Tcl interpreter is deleted. */ static void psfgen_deleteproc(ClientData cd, Tcl_Interp *interp) { int *countptr; psfgen_data *data = (psfgen_data *)cd; topo_mol_destroy(data->mol); topo_defs_destroy(data->defs); stringhash_destroy(data->aliases); free(data); countptr = Tcl_GetAssocData(interp, ""Psfgen_count"", 0); if (countptr) { countptr[1] += 1; /* num destroyed */ } } void psfgen_data_delete_pointer(ClientData cd, Tcl_Interp *interp) { psfgen_data **dataptr = (psfgen_data **)cd; free(dataptr); } static void count_delete_proc(ClientData data, Tcl_Interp *interp) { free(data); } psfgen_data* psfgen_data_create(Tcl_Interp *interp) { char namebuf[128]; int *countptr; int id; psfgen_data *data; countptr = Tcl_GetAssocData(interp, ""Psfgen_count"", 0); if (!countptr) { countptr = (int *)malloc(2*sizeof(int)); Tcl_SetAssocData(interp, ""Psfgen_count"", count_delete_proc, (ClientData)countptr); countptr[0] = 0; /* num created */ countptr[1] = 0; /* num destroyed */ } id = *countptr; data = (psfgen_data *)malloc(sizeof(psfgen_data)); data->defs = topo_defs_create(); topo_defs_error_handler(data->defs,interp,newhandle_msg); data->aliases = stringhash_create(); data->mol = topo_mol_create(data->defs); topo_mol_error_handler(data->mol,interp,newhandle_msg); data->id = id; data->in_use = 0; data->all_caps = 1; *countptr = id+1; sprintf(namebuf,""Psfgen_%d"",id); Tcl_SetAssocData(interp,namebuf,psfgen_deleteproc,(ClientData)data); return data; } void psfgen_data_reset(Tcl_Interp *interp, psfgen_data *data) { topo_mol_destroy(data->mol); topo_defs_destroy(data->defs); stringhash_destroy(data->aliases); data->defs = topo_defs_create(); topo_defs_error_handler(data->defs,interp,newhandle_msg); data->aliases = stringhash_create(); data->mol = topo_mol_create(data->defs); topo_mol_error_handler(data->mol,interp,newhandle_msg); data->all_caps = 1; } int tcl_psfcontext(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_topology(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_segment(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_residue(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_mutate(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_multiply(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_coord(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_psfset(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_auto(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_regenerate(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_alias(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_pdb(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_coordpdb(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_guesscoord(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_readpsf(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_readplugin(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_writepsf(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_writepdb(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_writenamdbin(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_writeplugin(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_first(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_last(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_patch(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_resetpsf(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); int tcl_delatom(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]); #if defined(PSFGENTCLDLL_EXPORTS) && defined(_WIN32) # undef TCL_STORAGE_CLASS # define TCL_STORAGE_CLASS DLLEXPORT #define WIN32_LEAN_AND_MEAN /* Exclude rarely-used stuff from Windows headers */ #include BOOL APIENTRY DllMain( HANDLE hModule, DWORD ul_reason_for_call, LPVOID lpReserved ) { return TRUE; } EXTERN int Psfgen_Init(Tcl_Interp *interp) { #else int Psfgen_Init(Tcl_Interp *interp) { #endif /* Create psfgen data structures; keep in interp so that other libraries * can access them. */ psfgen_data **data; Tcl_SetAssocData(interp, (char *)""Psfgen_count"",0,(ClientData)0); data = (psfgen_data **)malloc(sizeof(psfgen_data *)); Tcl_SetAssocData(interp, (char *)""Psfgen_pointer"", psfgen_data_delete_pointer,(ClientData)data); *data = psfgen_data_create(interp); (*data)->in_use++; Tcl_CreateCommand(interp,""psfcontext"",tcl_psfcontext, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""topology"",tcl_topology, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""readpsf"",tcl_readpsf, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""readmol"",tcl_readplugin, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""segment"",tcl_segment, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""residue"",tcl_residue, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""mutate"",tcl_mutate, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""multiply"",tcl_multiply, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""coord"",tcl_coord, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""psfset"",tcl_psfset, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""auto"",tcl_auto, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""regenerate"",tcl_regenerate, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""alias"",tcl_alias, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""pdbalias"",tcl_alias, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""pdb"",tcl_pdb, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""coordpdb"",tcl_coordpdb, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""guesscoord"",tcl_guesscoord, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""writepsf"",tcl_writepsf, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""writepdb"",tcl_writepdb, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""writenamdbin"",tcl_writenamdbin, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""writemol"",tcl_writeplugin, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""first"",tcl_first, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""last"",tcl_last, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""patch"",tcl_patch, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""resetpsf"", tcl_resetpsf, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_CreateCommand(interp,""delatom"", tcl_delatom, (ClientData)data, (Tcl_CmdDeleteProc*)NULL); Tcl_PkgProvide(interp, ""psfgen"", ""1.7""); #ifdef NAMD_VERSION { char buf[1024]; sprintf(buf, ""puts \""PSFGEN [package require psfgen] from NAMD %s for %s\"""", NAMD_VERSION, NAMD_PLATFORM); Tcl_Eval(interp, buf); } #endif return TCL_OK; } int psfgen_static_init(Tcl_Interp *interp) { Tcl_StaticPackage(0,""psfgen"",Psfgen_Init,0); return Tcl_Eval(interp,""package ifneeded psfgen 1.7 {load {} psfgen}""); } /* Old-style calls: set n [psfcontext new] $n is old context (0) psfcontext new delete old context (1) is deleted set m [psfcontext] $m is current context (2) set m [psfcontext $n] $m is old context (2) psfcontext $m delete old context (0) is deleted How they would have to be used: set mycontext [psfcontext [psfcontext new]] proc a { } { global mycontext set oldcontext [psfcontext $mycontext] set retcode [catch { ... error ... } result] } psfcontext $oldcontext if { $retcode } { error $result; } else { return $result } } psfcontext [psfcontext $mycontext] delete New-style calls and usage: psfcontext reset (clears all state from current context) set mycontext [psfcontext create] psfcontext eval $mycontext { ... } psfcontext delete $mycontext psfcontext stats (returns numbers of contexts created and destroyed) */ int tcl_psfcontext(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { int oldid, newid; int delold = 0; psfgen_data **cur = (psfgen_data **)data; char oldidstr[128]; oldid = (*cur)->id; sprintf(oldidstr,""%d"",oldid); if ( argc == 1 ) { Tcl_SetResult(interp,oldidstr,TCL_VOLATILE); return TCL_OK; } if ( argc == 2 && ! strcmp(argv[1],""stats"") ) { char msg[128]; int nc, nd, *countptr; nc = 0; nd = 0; countptr = Tcl_GetAssocData(interp, ""Psfgen_count"", 0); if (countptr) { nc = countptr[0]; nd = countptr[1]; } sprintf(msg,""%d created %d destroyed"",countptr[0],countptr[1]); Tcl_SetResult(interp,msg,TCL_VOLATILE); return TCL_OK; } if ( argc == 2 && ! strcmp(argv[1],""allcaps"") ) { newhandle_msg(interp,""mapping names to all caps on input""); (*cur)->all_caps = 1; return TCL_OK; } if ( argc == 2 && ! strcmp(argv[1],""mixedcase"") ) { newhandle_msg(interp,""preserving case of names on input""); (*cur)->all_caps = 0; return TCL_OK; } if ( argc == 2 && ! strcmp(argv[1],""reset"") ) { newhandle_msg(interp,""clearing structure, topology, and aliases""); if ( ! (*cur)->all_caps ) { newhandle_msg(interp,""mapping names to all caps on input""); } psfgen_data_reset(interp,*cur); return TCL_OK; } if ( argc == 2 && ! strcmp(argv[1],""create"") ) { char msg[128]; psfgen_data *newdata = psfgen_data_create(interp); sprintf(msg,""%d"",newdata->id); Tcl_SetResult(interp,msg,TCL_VOLATILE); return TCL_OK; } if ( argc == 3 && ! strcmp(argv[1],""delete"") ) { if (Tcl_GetInt(interp,argv[2],&newid) == TCL_OK) { char newkey[128]; psfgen_data *newdata; sprintf(newkey,""Psfgen_%d"",newid); if ((newdata = Tcl_GetAssocData(interp,newkey,0)) != NULL) { if ( newdata->in_use ) { Tcl_SetResult(interp,""specified context in use"",TCL_VOLATILE); return TCL_ERROR; } Tcl_DeleteAssocData(interp,newkey); sprintf(newkey,""deleted %d"",newid); Tcl_SetResult(interp,newkey,TCL_VOLATILE); return TCL_OK; } } Tcl_SetResult(interp,""specified context does not exist"",TCL_VOLATILE); return TCL_ERROR; } if ( argc > 1 && ! strcmp(argv[1],""eval"") ) { psfgen_data *newdata, *olddata; char newkey[128]; int retval; if ( argc != 4 ) { Tcl_SetResult(interp, ""usage: psfcontext eval ?context? { ?commmands? }"",TCL_VOLATILE); return TCL_ERROR; } if (Tcl_GetInt(interp,argv[2],&newid) != TCL_OK) { Tcl_SetResult(interp,""specified context does not exist"",TCL_VOLATILE); return TCL_ERROR; } sprintf(newkey,""Psfgen_%d"",newid); newdata = Tcl_GetAssocData(interp,newkey,0); if ( ! newdata ) { Tcl_SetResult(interp,""specified context does not exist"",TCL_VOLATILE); return TCL_ERROR; } olddata = *cur; *cur = newdata; (*cur)->in_use++; newdata = 0; /* Tcl_Eval might delete this context and change *cur */ retval = Tcl_Eval(interp,argv[3]); (*cur)->in_use--; *cur = olddata; return retval; } if ( argc == 3 ) { if ( strcmp(argv[2],""delete"") == 0 ) { delold = 1; } else { Tcl_SetResult(interp,""second argument must be delete"",TCL_VOLATILE); psfgen_kill_mol(interp,*cur); return TCL_ERROR; } } if ( delold && (*cur)->in_use > 1 ) { Tcl_SetResult(interp,""current context in use"",TCL_VOLATILE); psfgen_kill_mol(interp,*cur); return TCL_ERROR; } if ( argc > 3 ) { Tcl_SetResult(interp,""too many arguments specified"",TCL_VOLATILE); psfgen_kill_mol(interp,*cur); return TCL_ERROR; } if (strcmp(argv[1],""new"") == 0) { psfgen_data *newdata = psfgen_data_create(interp); (*cur)->in_use--; *cur = newdata; (*cur)->in_use++; } else if (Tcl_GetInt(interp,argv[1],&newid) == TCL_OK) { psfgen_data *newdata; char newkey[128]; if ( newid == oldid ) { if ( delold ) { Tcl_SetResult(interp,""specified context same as current"",TCL_VOLATILE); psfgen_kill_mol(interp,*cur); return TCL_ERROR; } else { Tcl_SetResult(interp,oldidstr,TCL_VOLATILE); return TCL_OK; } } sprintf(newkey,""Psfgen_%d"",newid); if ( (newdata = Tcl_GetAssocData(interp,newkey,0)) ) { (*cur)->in_use--; *cur = newdata; (*cur)->in_use++; } else { Tcl_SetResult(interp,""specified context does not exist"",TCL_VOLATILE); psfgen_kill_mol(interp,*cur); return TCL_ERROR; } } else { Tcl_SetResult(interp,""first argument must be existing context or new"",TCL_VOLATILE); psfgen_kill_mol(interp,*cur); return TCL_ERROR; } if ( delold ) { char oldkey[128]; sprintf(oldkey,""Psfgen_%d"",oldid); Tcl_DeleteAssocData(interp,oldkey); sprintf(oldkey,""deleted %d"",oldid); Tcl_SetResult(interp,oldkey,TCL_VOLATILE); return TCL_OK; } else { Tcl_SetResult(interp,oldidstr,TCL_VOLATILE); return TCL_OK; } } int tcl_topology(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { FILE *defs_file; const char *filename; char msg[2048]; int itopo,ntopo; psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); if ( argc == 1 ) { Tcl_SetResult(interp,""no topology file specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc >= 2 && !strcasecmp(argv[1], ""alias"") ) { psfgen_data *psf = *(psfgen_data **)data; topo_defs *defs = psf->defs; int pos,pos2; const char *name; if ( argc != 4 ) { Tcl_SetResult(interp,""usage: topology alias newname oldname"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } pos = hasharray_index(defs->residue_hash, argv[3]); if ( pos == HASHARRAY_FAIL ) { sprintf(msg,""ERROR: unknown residue name %s in topology alias\n"",argv[3]); Tcl_SetResult(interp,msg,TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } pos2 = hasharray_index(defs->residue_hash, argv[2]); if ( pos2 != HASHARRAY_FAIL ) { if ( pos2 == pos ) { sprintf(msg,""redundant alias of residue %s to %s in topology definitions"",argv[2],argv[3]); newhandle_msg(interp,msg); return TCL_OK; } sprintf(msg,""ERROR: existing residue name %s in topology alias\n"",argv[2]); Tcl_SetResult(interp,msg,TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } sprintf(msg,""aliasing residue %s to %s in topology definitions"",argv[2],argv[3]); newhandle_msg(interp,msg); hasharray_reinsert(defs->residue_hash, argv[2], pos); return TCL_OK; } if ( argc > 2 ) { Tcl_SetResult(interp,""too many arguments specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if (argc == 2 && !strcasecmp(argv[1], ""residues"") ) { psfgen_data *psf = *(psfgen_data **)data; topo_defs *defs = psf->defs; /* Return a list of the known residue definitions */ int n = hasharray_count(defs->residue_hash); int i; for (i=0; iresidue_array[i].patch) Tcl_AppendElement(interp, defs->residue_array[i].name); } return TCL_OK; } else if (argc == 2 && !strcasecmp(argv[1], ""patches"") ) { psfgen_data *psf = *(psfgen_data **)data; topo_defs *defs = psf->defs; /* Return a list of the known residue definitions */ int n = hasharray_count(defs->residue_hash); int i; for (i=0; iresidue_array[i].patch) Tcl_AppendElement(interp, defs->residue_array[i].name); } return TCL_OK; } else if (argc == 2 && !strcasecmp(argv[1], ""list"") ) { psfgen_data *psf = *(psfgen_data **)data; topo_defs *defs = psf->mol->defs; topo_defs_topofile_t *topo; ntopo = hasharray_count(defs->topo_hash); for ( itopo=0; itopotopo_array[itopo]); Tcl_AppendElement(interp, topo->filename); } return TCL_OK; } filename = argv[1]; if ( ! ( defs_file = fopen(filename,""r"") ) ) { sprintf(msg,""ERROR: Unable to open topology file %s\n"",filename); Tcl_SetResult(interp,msg,TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } else { sprintf(msg,""reading topology file %s\n"",filename); newhandle_msg(interp,msg); charmm_parse_topo_defs(psf->defs,defs_file,psf->all_caps,interp,newhandle_msg); topo_defs_add_topofile(psf->defs, filename); fclose(defs_file); } return TCL_OK; } int tcl_readpsf(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { FILE *psf_file, *pdb_file, *namdbin_file, *velnamdbin_file; int retval, i; const char *filename, *pdbfilename, *namdbinfilename, *velnamdbinfilename; char msg[2048]; psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); if ( argc == 1 ) { Tcl_SetResult(interp,""no psf file specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc > 8 ) { Tcl_SetResult(interp,""too many arguments specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc > 2 && (argc < 4 || (strcmp(argv[2],""pdb"")&&strcmp(argv[2],""namdbin"")) ) ) { Tcl_SetResult(interp,""coordinate file arguments should be \""[pdb|namdbin] \"""",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc > 4 && (argc < 6 || (strcmp(argv[2],""pdb"")&&strcmp(argv[2],""namdbin"")) || (strcmp(argv[4],""namdbin"")&&strcmp(argv[4],""velnamdbin"")) ) ) { Tcl_SetResult(interp,""binary coordinate file arguments should be \""namdbin \"""",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc > 6 && (argc < 8 || strcmp(argv[2],""pdb"") || strcmp(argv[4],""namdbin"") || strcmp(argv[6],""velnamdbin"") ) ) { Tcl_SetResult(interp,""binary velocity file arguments should be \""velnamdbin \"""",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } filename = argv[1]; pdbfilename = 0; for ( i=3; imol, psf_file, pdb_file, namdbin_file, velnamdbin_file, interp, newhandle_msg); fclose(psf_file); if ( pdb_file ) fclose(pdb_file); if ( namdbin_file ) fclose(namdbin_file); if ( velnamdbin_file ) fclose(velnamdbin_file); if (retval) { psfgen_kill_mol(interp,psf); return TCL_ERROR; } return TCL_OK; } int tcl_readplugin(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { const char *filename, *pluginname; const char *coorpluginname=0; const char *coorfilename=0; char msg[2048]; psfgen_data *psf = *(psfgen_data **)data; char *segid=NULL; int curarg; int coordinatesonly=0; int residuesonly=0; PSFGEN_TEST_MOL(interp,psf); if ( argc < 3 ) { Tcl_SetResult(interp,""missing file format and/or input filename"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } pluginname = argv[1]; filename = argv[2]; sprintf(msg,""Info: reading file %s using plugin %s"", filename, pluginname); newhandle_msg(interp,msg); for (curarg=3; curargall_caps); sprintf(msg, ""Info: read mode: coordinates for segment %s"", segid); newhandle_msg(interp,msg); } } else if (!strcmp(argv[curarg], ""coordinatesonly"")) { coordinatesonly=1; newhandle_msg(interp, ""Info: read mode: coordinates only""); } else if (!strcmp(argv[curarg], ""residuesonly"")) { residuesonly=1; newhandle_msg(interp, ""Info: read mode: residue sequence only""); } else { /* positional arguments for second coordinate file */ if ( curarg == 3 ) coorpluginname = argv[3]; if ( curarg == 4 ) coorfilename = argv[4]; } } if ( coorpluginname && coorpluginname ) { sprintf(msg,""Info: reading coordinates from file %s using plugin %s"", coorfilename, coorpluginname); newhandle_msg(interp,msg); } if ( topo_mol_read_plugin(psf->mol, pluginname, filename, coorpluginname, coorfilename, segid, psf->aliases, psf->all_caps, coordinatesonly, residuesonly, interp, newhandle_msg) ) { if (segid != NULL) free(segid); Tcl_AppendResult(interp,""ERROR: failed reading file"", NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if (segid != NULL) free(segid); return TCL_OK; } int tcl_segment(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { char msg[2048]; char *seg; psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); /* * special case query commands: 'segment segids', 'segment first ', * 'segment last ', 'segment resids ', * 'segment residue ' */ if (argc == 2 && !strcasecmp(argv[1], ""segids"")) { topo_mol *mol = psf->mol; if (mol) { int i, n=hasharray_count(mol->segment_hash); for (i=0; isegment_array[i]->segid); } return TCL_OK; } /* Return nothing when there's no molecule */ } else if (argc == 3 && !strcasecmp(argv[1], ""first"")) { topo_mol *mol = psf->mol; int segindex = (mol ? hasharray_index(mol->segment_hash, argv[2]) : HASHARRAY_FAIL); if (segindex != HASHARRAY_FAIL) { topo_mol_segment_t *seg = mol->segment_array[segindex]; Tcl_SetResult(interp, seg->pfirst, TCL_VOLATILE); return TCL_OK; } Tcl_AppendResult(interp, ""Invalid segid: "", argv[2], NULL); return TCL_ERROR; } else if (argc == 3 && !strcasecmp(argv[1], ""last"")) { topo_mol *mol = psf->mol; int segindex = (mol ? hasharray_index(mol->segment_hash, argv[2]) : HASHARRAY_FAIL); if (segindex != HASHARRAY_FAIL) { topo_mol_segment_t *seg = mol->segment_array[segindex]; Tcl_SetResult(interp, seg->plast, TCL_VOLATILE); return TCL_OK; } Tcl_AppendResult(interp, ""Invalid segid: "", argv[2], NULL); return TCL_ERROR; } else if (argc == 3 && !strcasecmp(argv[1], ""resids"")) { topo_mol *mol = psf->mol; int segindex = (mol ? hasharray_index(mol->segment_hash, argv[2]) : HASHARRAY_FAIL); if (segindex != HASHARRAY_FAIL) { topo_mol_segment_t *seg = mol->segment_array[segindex]; int n = hasharray_count(seg->residue_hash); int i; for (i=0; iresidue_hash, seg->residue_array[i].resid) != HASHARRAY_FAIL) { Tcl_AppendElement(interp, seg->residue_array[i].resid); } } return TCL_OK; } Tcl_AppendResult(interp, ""Invalid segid: "", argv[2], NULL); return TCL_ERROR; } else if (argc == 4 && !strcasecmp(argv[1], ""residue"")) { topo_mol *mol = psf->mol; int segindex = (mol ? hasharray_index(mol->segment_hash, argv[2]) : HASHARRAY_FAIL); if (segindex != HASHARRAY_FAIL) { topo_mol_segment_t *seg = mol->segment_array[segindex]; int resindex = hasharray_index(seg->residue_hash, argv[3]); if (resindex == HASHARRAY_FAIL) { Tcl_AppendResult(interp, ""Invalid resid '"", argv[3], ""' for segment '"", argv[1], ""'."", NULL); return TCL_ERROR; } Tcl_SetResult(interp, seg->residue_array[resindex].name, TCL_VOLATILE); return TCL_OK; } Tcl_AppendResult(interp, ""Invalid segid: "", argv[2], NULL); return TCL_ERROR; } else if (argc == 4 && !strcasecmp(argv[1], ""atoms"")) { topo_mol *mol = psf->mol; int segindex = (mol ? hasharray_index(mol->segment_hash, argv[2]) : HASHARRAY_FAIL); if (segindex != HASHARRAY_FAIL) { topo_mol_atom_t *atoms; topo_mol_segment_t *seg = mol->segment_array[segindex]; int resindex = hasharray_index(seg->residue_hash, argv[3]); if (resindex == HASHARRAY_FAIL) { Tcl_AppendResult(interp, ""Invalid resid '"", argv[3], ""' for segment '"", argv[1], ""'."", NULL); return TCL_ERROR; } atoms = seg->residue_array[resindex].atoms; while (atoms) { Tcl_AppendElement(interp, atoms->name); atoms = atoms->next; } return TCL_OK; } Tcl_AppendResult(interp, ""Invalid segid: "", argv[2], NULL); return TCL_ERROR; } else if (argc == 5 && (!strcasecmp(argv[1], ""coordinates"") || !strcasecmp(argv[1], ""velocities"") || !strcasecmp(argv[1], ""mass"") || !strcasecmp(argv[1], ""charge"") || !strcasecmp(argv[1], ""atomid"") ) ) { topo_mol *mol = psf->mol; int segindex = (mol ? hasharray_index(mol->segment_hash, argv[2]) : HASHARRAY_FAIL); if (segindex != HASHARRAY_FAIL) { topo_mol_atom_t *atoms; topo_mol_segment_t *seg = mol->segment_array[segindex]; int resindex = hasharray_index(seg->residue_hash, argv[3]); if (resindex == HASHARRAY_FAIL) { Tcl_AppendResult(interp, ""Invalid resid '"", argv[3], ""' for segment '"", argv[1], ""'."", NULL); return TCL_ERROR; } /* * XXX Ouch, no hasharray for atom names */ atoms = seg->residue_array[resindex].atoms; while (atoms) { if (!strcmp(atoms->name, argv[4])) { if (!strcasecmp(argv[1], ""coordinates"")) { #if TCL_MINOR_VERSION >= 6 char buf[512]; sprintf(buf, ""%f %f %f"", atoms->x, atoms->y, atoms->z); Tcl_AppendResult(interp, buf, NULL); #else sprintf(interp->result, ""%f %f %f"", atoms->x, atoms->y, atoms->z); #endif return TCL_OK; } else if (!strcasecmp(argv[1], ""velocities"")) { #if TCL_MINOR_VERSION >= 6 char buf[512]; sprintf(buf, ""%f %f %f"", atoms->vx, atoms->vy, atoms->vz); Tcl_AppendResult(interp, buf, NULL); #else sprintf(interp->result, ""%f %f %f"", atoms->vx, atoms->vy, atoms->vz); #endif return TCL_OK; } else if (!strcasecmp(argv[1], ""mass"")) { #if TCL_MINOR_VERSION >= 6 char buf[512]; sprintf(buf, ""%f"", atoms->mass); Tcl_AppendResult(interp, buf, NULL); #else sprintf(interp->result, ""%f"", atoms->mass); #endif return TCL_OK; } else if (!strcasecmp(argv[1], ""charge"")) { #if TCL_MINOR_VERSION >= 6 char buf[512]; sprintf(buf, ""%f"", atoms->charge); Tcl_AppendResult(interp, buf, NULL); #else sprintf(interp->result, ""%f"", atoms->charge); #endif return TCL_OK; } else if (!strcasecmp(argv[1], ""atomid"")) { #if TCL_MINOR_VERSION >= 6 char buf[512]; sprintf(buf, ""%d"", atoms->atomid); Tcl_AppendResult(interp, buf, NULL); #else sprintf(interp->result, ""%d"", atoms->atomid); #endif return TCL_OK; } } atoms = atoms->next; } Tcl_AppendResult(interp, ""Invalid atom name '"", argv[4], ""' for segid '"", argv[2], ""', resid '"", argv[3], ""'."", NULL); return TCL_ERROR; } Tcl_AppendResult(interp, ""Invalid segid: "", argv[2], NULL); return TCL_ERROR; } /* * Fall through to segment-building commands */ if ( argc < 3 ) { Tcl_SetResult(interp,""arguments: segname { commmands }"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc > 3 ) { Tcl_SetResult(interp,""too many arguments specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } seg=strtoupper(argv[1], psf->all_caps); if ( strlen(seg) > 7 ) { Tcl_SetResult(interp,""segment name more than 7 characters"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } sprintf(msg,""building segment %s"",seg); newhandle_msg(interp,msg); if ( topo_mol_segment(psf->mol,seg) ) { free(seg); Tcl_AppendResult(interp,""ERROR: failed on segment"",NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } free(seg); if ( Tcl_Eval(interp,argv[2]) != TCL_OK ) { Tcl_AppendResult(interp,""\nERROR: failed while building segment"",NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } newhandle_msg_ex(interp, ""Info: generating structure..."", 1, 0); if ( topo_mol_end(psf->mol) ) { newhandle_msg_ex(interp, ""failed!"", 0, 1); Tcl_AppendResult(interp,""ERROR: failed on end of segment"",NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } newhandle_msg_ex(interp, ""segment complete."", 0, 1); return TCL_OK; } int tcl_residue(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { char *resid, *resname, *chain; psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); if ( argc < 3 ) { Tcl_SetResult(interp,""arguments: resid resname ?chain?"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc > 4 ) { Tcl_SetResult(interp,""too many arguments specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } resid=strtoupper(argv[1], psf->all_caps); resname=strtoupper(argv[2], psf->all_caps); chain=strtoupper(argc==4 ? argv[3] : """", psf->all_caps); if ( topo_mol_residue(psf->mol,resid,resname,chain) ) { free(resid); free(resname); Tcl_AppendResult(interp,""ERROR: failed on residue"",NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } free(resid); free(resname); free(chain); return TCL_OK; } int tcl_mutate(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { psfgen_data *psf = *(psfgen_data **)data; char *resid, *resname; PSFGEN_TEST_MOL(interp,psf); if ( argc < 3 ) { Tcl_SetResult(interp,""arguments: resid resname"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc > 3 ) { Tcl_SetResult(interp,""too many arguments specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } resid=strtoupper(argv[1], psf->all_caps); resname=strtoupper(argv[2], psf->all_caps); if ( topo_mol_mutate(psf->mol,resid, resname) ) { free(resid); free(resname); Tcl_AppendResult(interp,""ERROR: failed on mutate"",NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } free(resid); free(resname); return TCL_OK; } int tcl_multiply(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { int i, ncopies, ierr; topo_mol_ident_t *targets; char **tmp; char msg[2048]; psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); if ( argc<3 || Tcl_GetInt(interp,argv[1],&ncopies) != TCL_OK || ncopies<2 ) { Tcl_SetResult(interp,""arguments: ncopies segid?:resid?:atomname? ..."",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } targets = (topo_mol_ident_t *) Tcl_Alloc((argc-2)*sizeof(topo_mol_ident_t)); if ( ! targets ) { Tcl_SetResult(interp,""memory allocation failed"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } tmp = (char **) Tcl_Alloc((argc-2)*sizeof(char *)); if (!tmp) { Tcl_Free((char *)targets); Tcl_SetResult(interp,""memory allocation failed"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } sprintf(msg,""generating %d copies of selected atoms"",ncopies); newhandle_msg(interp,msg); for ( i=2; iall_caps); targets[i-2].segid = ctmp = tmp[i-2]; targets[i-2].resid = ctmp = splitcolon(ctmp); targets[i-2].aname = splitcolon(ctmp); } ierr = topo_mol_multiply_atoms(psf->mol,targets,(argc-2),ncopies); for (i=2; i 5 ) { Tcl_SetResult(interp,""too many arguments specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( sscanf(argv[4],""%lf %lf %lf"",&x,&y,&z) != 3 ) { Tcl_SetResult(interp,""arguments: segid resid atomname { x y z }"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } segid=strtoupper(argv[1], psf->all_caps); resid=strtoupper(argv[2], psf->all_caps); atomname=strtoupper(argv[3], psf->all_caps); target.segid = segid; target.resid = resid; target.aname = atomname; rc = topo_mol_set_xyz(psf->mol,&target,x,y,z); free(segid); free(resid); free(atomname); if (rc) { Tcl_AppendResult(interp,""ERROR: failed on coord"",NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } return TCL_OK; } int tcl_psfset(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { topo_mol_ident_t target; psfgen_data *psf = *(psfgen_data **)data; char *segid, *resid, *aname; int rc; /* We will horribly abuse notation here and use these for any vector quantity and just use x for scalar quantities. */ double x, y, z; PSFGEN_TEST_MOL(interp, psf); /* psfset [] */ if ( argc > 6 ) { Tcl_SetResult(interp, ""Too many arguments specified"", TCL_VOLATILE); psfgen_kill_mol(interp, psf); return TCL_ERROR; } if (argc < 4 ) { Tcl_SetResult(interp, ""arguments: attribute segid [resid [aname]] value"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } rc = 0; segid = strtoupper(argv[2], psf->all_caps); target.segid = segid; if (argc == 4) { if (!strcasecmp(argv[1], ""segid"")) { rc = topo_mol_set_segid(psf->mol, &target, argv[3]); } else { Tcl_AppendResult(interp, ""Invalid segment attribute: "", argv[1], NULL); rc = -1; } } else { resid = strtoupper(argv[3], psf->all_caps); target.resid = resid; if (argc == 5) { if (!strcasecmp(argv[1], ""resname"")) { rc = topo_mol_set_resname(psf->mol, &target, argv[4]); } else { Tcl_AppendResult(interp, ""Invalid residue attribute: "", argv[1], NULL); rc = -2; } } else { aname = strtoupper(argv[4], psf->all_caps); target.aname = aname; if (!strcasecmp(argv[1], ""name"")) { rc = topo_mol_set_name(psf->mol, &target, argv[5]); } else if (!strcasecmp(argv[1], ""mass"")) { if (sscanf(argv[5], ""%lf"", &x) != 1 ) { Tcl_SetResult(interp, ""mass must be float value"", TCL_VOLATILE); rc = -3; } if (!rc) rc = topo_mol_set_mass(psf->mol, &target, x); } else if (!strcasecmp(argv[1], ""charge"")) { if (sscanf(argv[5], ""%lf"", &x) != 1 ) { Tcl_SetResult(interp, ""charge must be float value"", TCL_VOLATILE); rc = -3; } if (!rc) rc = topo_mol_set_charge(psf->mol, &target, x); } else if (!strcasecmp(argv[1], ""beta"")) { if (sscanf(argv[5], ""%lf"", &x) != 1 ) { Tcl_SetResult(interp, ""bfactor must be float value"", TCL_VOLATILE); rc = -3; } if (!rc) rc = topo_mol_set_bfactor(psf->mol, &target, x); } else if (!strcasecmp(argv[1], ""coord"")) { if ( sscanf(argv[5],""%lf %lf %lf"", &x, &y, &z) != 3 ) { Tcl_SetResult(interp, ""coord must be 3 float values"", TCL_VOLATILE); rc = -4; } if (!rc) rc = topo_mol_set_xyz(psf->mol, &target, x, y, z); } else if (!strcasecmp(argv[1], ""vel"")) { if ( sscanf(argv[5],""%lf %lf %lf"", &x, &y, &z) != 3 ) { Tcl_SetResult(interp, ""vel must be 3 float values"", TCL_VOLATILE); rc = -4; } if (!rc) rc = topo_mol_set_vel(psf->mol, &target, x, y, z); } else { Tcl_AppendResult(interp, ""Invalid atom attribute: "", argv[1], NULL); rc = -5; } free(aname); } free(resid); } free(segid); if (rc) { psfgen_kill_mol(interp, psf); return TCL_ERROR; } return TCL_OK; } int tcl_auto(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { int i, angles, dihedrals; psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); if ( argc < 2 ) { Tcl_SetResult(interp,""arguments: ?angles? ?dihedrals? ?none?"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } angles = 0; dihedrals = 0; for ( i = 1; i < argc; ++i ) { if ( ! strcmp(argv[i],""angles"") ) angles = 1; else if ( ! strcmp(argv[i],""dihedrals"") ) dihedrals = 1; else if ( strcmp(argv[i],""none"") ) { Tcl_SetResult(interp,""arguments: ?angles? ?dihedrals? ?none?"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } } if ( angles ) newhandle_msg(interp,""enabling angle autogeneration""); else newhandle_msg(interp,""disabling angle autogeneration""); if ( topo_mol_segment_auto_angles(psf->mol,angles) ) { Tcl_AppendResult(interp,""ERROR: failed setting angle autogen"",NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( dihedrals ) newhandle_msg(interp,""enabling dihedral autogeneration""); else newhandle_msg(interp,""disabling dihedral autogeneration""); if ( topo_mol_segment_auto_dihedrals(psf->mol,dihedrals) ) { Tcl_AppendResult(interp,""ERROR: failed setting dihedral autogen"",NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } return TCL_OK; } int tcl_regenerate(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { int i, angles, dihedrals, resids; psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); if ( argc < 2 ) { Tcl_SetResult(interp,""arguments: ?angles? ?dihedrals? ?resids?"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } angles = 0; dihedrals = 0; resids = 0; for ( i = 1; i < argc; ++i ) { if ( ! strcmp(argv[i],""angles"") ) angles = 1; else if ( ! strcmp(argv[i],""dihedrals"") ) dihedrals = 1; else if ( ! strcmp(argv[i],""resids"") ) resids = 1; else { Tcl_SetResult(interp,""arguments: ?angles? ?dihedrals? ?resids?"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } } if ( angles ) { newhandle_msg(interp,""regenerating all angles""); if ( topo_mol_regenerate_angles(psf->mol) ) { Tcl_AppendResult(interp,""ERROR: angle regeneration failed"",NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } } if ( dihedrals ) { newhandle_msg(interp,""regenerating all dihedrals""); if ( topo_mol_regenerate_dihedrals(psf->mol) ) { Tcl_AppendResult(interp,""ERROR: dihedral regeneration failed"",NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } } if ( resids ) { newhandle_msg(interp,""regenerating all resids""); if ( topo_mol_regenerate_resids(psf->mol) ) { Tcl_AppendResult(interp,""ERROR: resid regeneration failed"",NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } } return TCL_OK; } int tcl_alias(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { char msg[2048]; psfgen_data *psf = *(psfgen_data **)data; int rc; PSFGEN_TEST_MOL(interp,psf); if ( argc < 2 ) { Tcl_SetResult(interp,""arguments: atom | residue ..."",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( ! strcmp(argv[1],""residue"") ) { char *altres, *realres; if ( argc < 4 ) { Tcl_SetResult(interp,""arguments: residue altres realres"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } altres=strtoupper(argv[2], psf->all_caps); realres=strtoupper(argv[3], psf->all_caps); sprintf(msg,""aliasing residue %s to %s"",argv[2],argv[3]); newhandle_msg(interp,msg); rc = extract_alias_residue_define(psf->aliases,altres, realres); free(altres); free(realres); if (rc) { Tcl_AppendResult(interp,""ERROR: failed on residue alias"",NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } } else if ( ! strcmp(argv[1],""atom"") ) { char *resname, *altatom, *realatom; if ( argc < 5 ) { Tcl_SetResult(interp,""arguments: atom resname altatom realatom"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } resname=strtoupper(argv[2], psf->all_caps); altatom=strtoupper(argv[3], psf->all_caps); realatom=strtoupper(argv[4], psf->all_caps); sprintf(msg,""aliasing residue %s atom %s to %s"",argv[2],argv[3],argv[4]); newhandle_msg(interp,msg); rc=extract_alias_atom_define(psf->aliases,resname,altatom,realatom); free(resname); free(altatom); free(realatom); if (rc) { Tcl_AppendResult(interp,""ERROR: failed on atom alias"",NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } } return TCL_OK; } int tcl_pdb(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { FILE *res_file; const char *filename; char msg[2048]; psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); if ( argc == 1 ) { Tcl_SetResult(interp,""no pdb file specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc > 2 ) { Tcl_SetResult(interp,""too many arguments specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } filename = argv[1]; if ( ! ( res_file = fopen(filename,""r"") ) ) { sprintf(msg,""ERROR: Unable to open pdb file %s to read residues\n"",filename); Tcl_SetResult(interp,msg,TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } else { sprintf(msg,""reading residues from pdb file %s"",filename); newhandle_msg(interp,msg); if ( pdb_file_extract_residues(psf->mol,res_file,psf->aliases,psf->all_caps,interp,newhandle_msg) ) { Tcl_AppendResult(interp,""ERROR: failed on reading residues from pdb file"",NULL); fclose(res_file); psfgen_kill_mol(interp,psf); return TCL_ERROR; } fclose(res_file); } return TCL_OK; } int tcl_coordpdb(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { FILE *res_file, *namdbin_file; const char *filename; char msg[2048]; int rc; psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); if ( argc < 2 ) { Tcl_SetResult(interp,""arguments: pdbfile ?segid? [namdbin ]"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc > 3 && strcmp(argv[argc-2],""namdbin"") ) { Tcl_SetResult(interp,""arguments: pdbfile ?segid? [namdbin ]"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc > 5 ) { Tcl_SetResult(interp,""too many arguments specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } filename = argv[1]; if ( ! ( res_file = fopen(filename,""r"") ) ) { sprintf(msg,""ERROR: Unable to open pdb file %s to read coordinates\n"",filename); Tcl_SetResult(interp,msg,TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } else { char *segid; namdbin_file = 0; if (argc == 3 || argc == 5) { /* Read only coordinates for given segid */ sprintf(msg,""reading coordinates from pdb file %s for segment %s"",filename,argv[2]); newhandle_msg(interp,msg); segid = strtoupper(argv[2], psf->all_caps); } else { /* Read all segid's in pdb file */ sprintf(msg,""reading coordinates from pdb file %s"",filename); newhandle_msg(interp,msg); segid = NULL; } if ( argc > 3 ) { const char *namdbinfilename = argv[argc-1]; if ( ! ( namdbin_file = fopen(namdbinfilename,""rb"") ) ) { fclose(res_file); sprintf(msg,""ERROR: Unable to open namdbin file %s"",namdbinfilename); Tcl_SetResult(interp,msg,TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } sprintf(msg,""reading coordinates from namdbin file %s"",namdbinfilename); newhandle_msg(interp,msg); } rc=pdb_file_extract_coordinates(psf->mol,res_file,namdbin_file,segid,psf->aliases,psf->all_caps,interp,newhandle_msg); if (segid) free(segid); if (rc) { Tcl_AppendResult(interp,""ERROR: failed on reading coordinates from pdb file"",NULL); if ( namdbin_file ) Tcl_AppendResult(interp,"" and namdbin file"",NULL); fclose(res_file); psfgen_kill_mol(interp,psf); return TCL_ERROR; } fclose(res_file); } return TCL_OK; } int tcl_guesscoord(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); if ( argc > 1 ) { Tcl_SetResult(interp,""too many arguments specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( topo_mol_guess_xyz(psf->mol) ) { Tcl_AppendResult(interp,""ERROR: failed on guessing coordinates"",NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } return TCL_OK; } int tcl_writepsf(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { FILE *res_file; const char *filename; int charmmfmt, nocmap, nopatches, i; char msg[2048]; psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); if ( argc == 1 ) { Tcl_SetResult(interp,""no psf file specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc > 5 ) { Tcl_SetResult(interp,""too many arguments specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } charmmfmt = 0; nocmap = 0; nopatches = 0; for ( i = 1; i < argc-1; ++i ) { if ( strcmp(argv[i],""charmm"") == 0 ) charmmfmt = 1; else if ( strcmp(argv[i],""x-plor"") == 0 ) charmmfmt = 0; else if ( strcmp(argv[i],""cmap"") == 0 ) nocmap = 0; else if ( strcmp(argv[i],""nocmap"") == 0 ) nocmap = 1; else if ( strcmp(argv[i],""nopatches"") == 0 ) nopatches = 1; else { sprintf(msg,""ERROR: Unknown psf file format %s (not charmm or x-plor, cmap or nocmap).\n"",argv[i]); Tcl_SetResult(interp,msg,TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } } filename = argv[argc-1]; if ( ! ( res_file = fopen(filename,""w"") ) ) { sprintf(msg,""ERROR: Unable to open psf file %s to write structure\n"",filename); Tcl_SetResult(interp,msg,TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } sprintf(msg,""Info: writing psf file %s%s%s"",filename, nocmap?"" without cross-terms"":"""", charmmfmt?"" in CHARMM format"":""""); newhandle_msg(interp,msg); if ( topo_mol_write_psf(psf->mol,res_file,charmmfmt,nocmap,nopatches,interp,newhandle_msg) ) { Tcl_AppendResult(interp,""ERROR: failed on writing structure to psf file"",NULL); fclose(res_file); psfgen_kill_mol(interp,psf); return TCL_ERROR; } fclose(res_file); newhandle_msg(interp, ""Info: psf file complete.""); return TCL_OK; } int tcl_writepdb(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { FILE *res_file; const char *filename; char msg[2048]; psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); if ( argc == 1 ) { Tcl_SetResult(interp,""no pdb file specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc > 2 ) { Tcl_SetResult(interp,""too many arguments specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } filename = argv[1]; if ( ! ( res_file = fopen(filename,""w"") ) ) { sprintf(msg,""ERROR: Unable to open pdb file %s to write coordinates\n"",filename); Tcl_SetResult(interp,msg,TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } sprintf(msg,""Info: writing pdb file %s"",filename); newhandle_msg(interp,msg); if ( topo_mol_write_pdb(psf->mol,res_file,interp,newhandle_msg) ) { Tcl_AppendResult(interp,""ERROR: failed on writing coordinates to pdb file"",NULL); fclose(res_file); psfgen_kill_mol(interp,psf); return TCL_ERROR; } fclose(res_file); newhandle_msg(interp, ""Info: pdb file complete.""); return TCL_OK; } int tcl_writenamdbin(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { FILE *res_file, *vel_file; const char *filename, *velfilename; char msg[2048]; psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); if ( argc == 1 ) { Tcl_SetResult(interp,""no namdbin file specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc > 4 ) { Tcl_SetResult(interp,""too many arguments specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } filename = argv[1]; if ( argc == 3 || ( argc == 4 && strcmp(argv[2],""velnamdbin"") ) ) { Tcl_SetResult(interp,""usage: writenamdbin [velnamdbin ]"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } velfilename = 0; if ( argc == 4 ) velfilename = argv[3]; if ( ! ( res_file = fopen(filename,""wb"") ) ) { sprintf(msg,""ERROR: Unable to open namdbin file %s to write coordinates\n"",filename); Tcl_SetResult(interp,msg,TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } vel_file = 0; if ( velfilename ) { if ( ! ( vel_file = fopen(velfilename,""wb"") ) ) { sprintf(msg,""ERROR: Unable to open velnamdbin file %s to write velocities\n"",velfilename); Tcl_SetResult(interp,msg,TCL_VOLATILE); fclose(res_file); psfgen_kill_mol(interp,psf); return TCL_ERROR; } } sprintf(msg,""Info: writing namdbin file %s"",filename); if ( vel_file ) sprintf(msg,""Info: writing velnamdbin file %s"",velfilename); newhandle_msg(interp,msg); if ( topo_mol_write_namdbin(psf->mol,res_file,vel_file,interp,newhandle_msg) ) { Tcl_AppendResult(interp,""ERROR: failed on writing coordinates to namdbin file"",NULL); fclose(res_file); if ( vel_file ) fclose(vel_file); psfgen_kill_mol(interp,psf); return TCL_ERROR; } fclose(res_file); newhandle_msg(interp, ""Info: namdbin file complete.""); if ( vel_file ) { fclose(vel_file); newhandle_msg(interp, ""Info: velnamdbin file complete.""); } return TCL_OK; } int tcl_writeplugin(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { const char *filename, *pluginname; char msg[2048]; struct image_spec images; psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); images.na = 1; images.nb = 1; images.nc = 1; images.ax = 0.; images.ay = 0.; images.az = 0.; images.bx = 0.; images.by = 0.; images.bz = 0.; images.cx = 0.; images.cy = 0.; images.cz = 0.; if ( argc == 1 ) { Tcl_SetResult(interp,""arguments: format filename ?na { x y z }? ?nb { x y z }? ?nc { x y z }?"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc < 3 ) { Tcl_SetResult(interp,""missing file format and/or output filename"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } pluginname = argv[1]; filename = argv[2]; if ( argc > 3 ) { if ( sscanf(argv[3],""%d"",&images.na) != 1 || images.na < 1 ) { Tcl_SetResult(interp,""image count not a positive integer"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc == 4 ) { Tcl_SetResult(interp,""image count without offset vector"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( sscanf(argv[4],""%lf %lf %lf"",&images.ax,&images.ay,&images.az) != 3 ) { Tcl_SetResult(interp,""bad image offset vector format"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } } if ( argc > 5 ) { if ( sscanf(argv[5],""%d"",&images.nb) != 1 || images.nb < 1 ) { Tcl_SetResult(interp,""image count not a positive integer"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc == 6 ) { Tcl_SetResult(interp,""image count without offset vector"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( sscanf(argv[6],""%lf %lf %lf"",&images.bx,&images.by,&images.bz) != 3 ) { Tcl_SetResult(interp,""bad image offset vector format"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } } if ( argc > 7 ) { if ( sscanf(argv[7],""%d"",&images.nc) != 1 || images.nc < 1 ) { Tcl_SetResult(interp,""image count not a positive integer"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc == 8 ) { Tcl_SetResult(interp,""image count without offset vector"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( sscanf(argv[8],""%lf %lf %lf"",&images.cx,&images.cy,&images.cz) != 3 ) { Tcl_SetResult(interp,""bad image offset vector format"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } } if ( argc > 9 ) { Tcl_SetResult(interp,""too many arguments specified"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } sprintf(msg,""Info: writing file %s using plugin %s"", filename, pluginname); newhandle_msg(interp,msg); if ( topo_mol_write_plugin(psf->mol, pluginname, filename, &images, interp, newhandle_msg) ) { Tcl_AppendResult(interp,""ERROR: failed writing to file"", NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } newhandle_msg(interp, ""Info: file complete.""); return TCL_OK; } int tcl_first(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { char msg[2048]; char *first; psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); if ( argc != 2 ) { Tcl_SetResult(interp,""argument: presname"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } first = strtoupper(argv[1], psf->all_caps); sprintf(msg,""setting patch for first residue to %s"",first); newhandle_msg(interp,msg); if ( topo_mol_segment_first(psf->mol,first) ) { free(first); Tcl_AppendResult(interp,""ERROR: failed to set patch for first residue"",NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } free(first); return TCL_OK; } int tcl_last(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { char msg[2048]; char *last; psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); if ( argc != 2 ) { Tcl_SetResult(interp,""argument: presname"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } last=strtoupper(argv[1], psf->all_caps); sprintf(msg,""setting patch for last residue to %s"",last); newhandle_msg(interp,msg); if ( topo_mol_segment_last(psf->mol,last) ) { free(last); Tcl_AppendResult(interp,""ERROR: failed to set patch for last residue"",NULL); psfgen_kill_mol(interp,psf); return TCL_ERROR; } free(last); return TCL_OK; } static int tcl_num_patch_targets(psfgen_data *psf, Tcl_Interp *interp, const char *presname) { topo_defs_residue_t *resdef; topo_defs_atom_t *atomdef; topo_defs_bond_t *bonddef; topo_defs_angle_t *angledef; topo_defs_dihedral_t *diheddef; topo_defs_improper_t *imprdef; topo_defs_exclusion_t *excldef; int idef; topo_defs *defs = psf->defs; int maxres = 0; { char *pres = strtoupper(presname, psf->all_caps); idef = hasharray_index(defs->residue_hash, pres); free(pres); } if (idef == HASHARRAY_FAIL) { Tcl_AppendResult(interp, ""No such patch residue: '"", presname, ""'."", NULL); return TCL_ERROR; } resdef = &(defs->residue_array[idef]); if (!resdef->patch) { Tcl_AppendResult(interp, ""Residue '"", presname, ""' is not patch."", NULL); return TCL_ERROR; } for (atomdef = resdef->atoms; atomdef; atomdef = atomdef->next) { if (atomdef->res > maxres) maxres = atomdef->res; } for (bonddef = resdef->bonds; bonddef; bonddef = bonddef->next) { if (bonddef->res1 > maxres) maxres = bonddef->res1; if (bonddef->res2 > maxres) maxres = bonddef->res2; } for (angledef = resdef->angles; angledef; angledef = angledef->next) { if (angledef->res1 > maxres) maxres = angledef->res1; if (angledef->res2 > maxres) maxres = angledef->res2; if (angledef->res3 > maxres) maxres = angledef->res3; } for (diheddef = resdef->dihedrals; diheddef; diheddef = diheddef->next) { if (diheddef->res1 > maxres) maxres = diheddef->res1; if (diheddef->res2 > maxres) maxres = diheddef->res2; if (diheddef->res3 > maxres) maxres = diheddef->res3; if (diheddef->res4 > maxres) maxres = diheddef->res4; } for (imprdef = resdef->impropers; imprdef; imprdef = imprdef->next) { if (imprdef->res1 > maxres) maxres = imprdef->res1; if (imprdef->res2 > maxres) maxres = imprdef->res2; if (imprdef->res3 > maxres) maxres = imprdef->res3; if (imprdef->res4 > maxres) maxres = imprdef->res4; } for (excldef = resdef->exclusions; excldef; excldef = excldef->next) { if (excldef->res1 > maxres) maxres = excldef->res1; if (excldef->res2 > maxres) maxres = excldef->res2; } Tcl_SetObjResult(interp, Tcl_NewIntObj(maxres+1)); return TCL_OK; } int tcl_patch(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { int i, j, rc, ipres, listall=0; topo_mol_ident_t targets[10]; char *tmp[10]; char *pres; char msg[2048]; topo_mol_patch_t *patch; topo_mol_patchres_t *patchres; Tcl_Obj *tcl_result; psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); tcl_result = Tcl_NewListObj(0, NULL); if (argc == 3 && !strcasecmp(argv[1], ""targets"")) { return tcl_num_patch_targets(psf, interp, argv[2]); } if ( argc == 2 && (!strcasecmp(argv[1], ""list"") || !strcasecmp(argv[1], ""listall""))) { if (!strcasecmp(argv[1], ""listall"")) listall = 1; for ( patch = psf->mol->patches; patch; patch = patch->next ) { Tcl_Obj *patchlist = Tcl_NewListObj(0,NULL); ipres = 0; /* Only list all patches when 'patch listall' was invoked */ if (patch->deflt && !listall) continue; for ( patchres = patch->patchresids; patchres; patchres = patchres->next ) { /* Test the existence of segid:resid for the patch */ if (!topo_mol_validate_patchres(psf->mol, patch->pname, patchres->segid, patchres->resid)) { break; }; if (ipres==0) { Tcl_ListObjAppendElement(interp, patchlist, Tcl_NewStringObj(patch->pname, -1)); } Tcl_ListObjAppendElement(interp, patchlist, Tcl_NewStringObj(patchres->segid, -1)); Tcl_ListObjAppendElement(interp, patchlist, Tcl_NewStringObj(patchres->resid, -1)); ipres++; } Tcl_ListObjAppendElement(interp, tcl_result, patchlist); } Tcl_SetObjResult(interp, tcl_result); return TCL_OK; } if ( argc < 2 ) { Tcl_SetResult(interp,""arguments: list | presname segid:resid ..."",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } if ( argc > 10 ) { Tcl_SetResult(interp,""too many targets for patch"",TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } pres=strtoupper(argv[1], psf->all_caps); sprintf(msg,""applying patch %s to %d residue(s)"",pres,(argc-2)); newhandle_msg(interp,msg); for ( i=2; iall_caps); targets[i-2].segid = tmp[i-2]; targets[i-2].resid = splitcolon(tmp[i-2]); targets[i-2].aname = 0; if ( ! targets[i-2].resid ) { for (j=0; jmol,targets,(argc-2),pres,0,0,0,0); free(pres); for (j=0; jmol); psf->mol = topo_mol_create(psf->defs); topo_mol_error_handler(psf->mol,interp,newhandle_msg); return TCL_OK; } int tcl_delatom(ClientData data, Tcl_Interp *interp, int argc, CONST84 char *argv[]) { topo_mol_ident_t target; psfgen_data *psf = *(psfgen_data **)data; PSFGEN_TEST_MOL(interp,psf); if ( argc < 2 ) { Tcl_SetResult(interp,""arguments: segid [ resid? [ aname? ]]"", TCL_VOLATILE); psfgen_kill_mol(interp,psf); return TCL_ERROR; } target.segid = argv[1]; target.resid = argc > 2 ? argv[2] : 0; target.aname = argc > 3 ? argv[3] : 0; if (topo_mol_delete_atom(psf->mol, &target)) { Tcl_AppendResult(interp, ""ERROR: failed to delete atom"", NULL); psfgen_kill_mol(interp, psf); return TCL_ERROR; } return TCL_OK; } #endif ","C" "Biophysics","Eigenstate/psfgen","src/extract_alias.c",".c","2099","65"," #include #include #include ""stringhash.h"" #include ""extract_alias.h"" int extract_alias_residue_define(stringhash *h, const char *altres, const char *realres) { if ( ! h || ! altres || ! realres || stringhash_insert(h,altres,realres) == STRINGHASH_FAIL ) { return EXTRACT_ALIAS_FAIL; } return 0; } int extract_alias_atom_define(stringhash *h, const char *resname, const char *altatom, const char *realatom) { char resatom[24]; const char *resname2; if ( ! h || ! resname || ! altatom || ! realatom ) return EXTRACT_ALIAS_FAIL; if ( strlen(resname) + strlen(altatom) > 20 ) return EXTRACT_ALIAS_FAIL; sprintf(resatom,""%s %s"",resname,altatom); if ( stringhash_insert(h,resatom,realatom) == STRINGHASH_FAIL ) { return EXTRACT_ALIAS_FAIL; } resname2 = extract_alias_residue_check(h,resname); if ( resname == resname2 ) return 0; resname = resname2; if ( strlen(resname) + strlen(altatom) > 20 ) return EXTRACT_ALIAS_FAIL; sprintf(resatom,""%s %s"",resname,altatom); if ( stringhash_insert(h,resatom,realatom) == STRINGHASH_FAIL ) { return EXTRACT_ALIAS_FAIL; } return 0; } const char * extract_alias_residue_check(stringhash *h, const char *resname) { const char *realres; if ( ! h || ! resname ) return resname; realres = stringhash_lookup(h,resname); if ( realres != STRINGHASH_FAIL ) return realres; return resname; } const char * extract_alias_atom_check(stringhash *h, const char *resname, const char *atomname) { char resatom[24]; const char *realatom; if ( ! h || ! resname || ! atomname ) return atomname; if ( strlen(resname) + strlen(atomname) < 20 ) { sprintf(resatom,""%s %s"",resname,atomname); realatom = stringhash_lookup(h,resatom); if ( realatom != STRINGHASH_FAIL ) return realatom; } resname = extract_alias_residue_check(h,resname); if ( strlen(resname) + strlen(atomname) < 20 ) { sprintf(resatom,""%s %s"",resname,atomname); realatom = stringhash_lookup(h,resatom); if ( realatom != STRINGHASH_FAIL ) return realatom; } return atomname; } ","C" "Biophysics","Eigenstate/psfgen","src/charmm_parse_topo_defs.h",".h","272","13"," #ifndef CHARMM_PARSE_TOPO_DEFS_H #define CHARMM_PARSE_TOPO_DEFS_H #include #include ""topo_defs.h"" int charmm_parse_topo_defs(topo_defs *defs, FILE *file, int all_caps, void *v, void (*print_msg)(void *,const char *)); #endif ","Unknown" "Biophysics","Eigenstate/psfgen","src/python_psfgen.h",".h","220","13","#ifndef PYTHON_PSFGEN_H #define PYTHON_PSFGEN_H #include ""Python.h"" // Compatibility header for python 2.6+ to python 3 #if PY_MAJOR_VERSION < 3 #include ""bytesobject.h"" #endif //extern PyObject* initpsfgen(); #endif ","Unknown" "Biophysics","Eigenstate/psfgen","src/topo_defs.c",".c","19388","608"," #include #include #include #include ""topo_defs_struct.h"" topo_defs * topo_defs_create(void) { topo_defs *defs; if ( (defs = (topo_defs*) malloc(sizeof(topo_defs))) ) { defs->newerror_handler_data = 0; defs->newerror_handler = 0; defs->auto_angles = 0; defs->auto_dihedrals = 0; defs->cmaps_present = 0; strcpy(defs->pfirst,""""); strcpy(defs->plast,""""); defs->buildres = 0; defs->buildres_no_errors = 0; defs->topo_hash = hasharray_create( (void**) &(defs->topo_array), sizeof(topo_defs_topofile_t)); defs->type_hash = hasharray_create( (void**) &(defs->type_array), sizeof(topo_defs_type_t)); defs->residue_hash = hasharray_create( (void**) &(defs->residue_array), sizeof(topo_defs_residue_t)); defs->arena = memarena_create(); if ( ! defs->type_hash || ! defs->residue_hash || ! defs->arena || ! defs->topo_hash || topo_defs_residue(defs,""NONE"",1) || topo_defs_residue(defs,""None"",1) || topo_defs_residue(defs,""none"",1) ) { topo_defs_destroy(defs); return 0; } topo_defs_end(defs); } return defs; } void topo_defs_destroy(topo_defs *defs) { int i,n; struct topo_defs_atom_t *a, *a2; struct topo_defs_bond_t *b, *b2; struct topo_defs_angle_t *an, *an2; struct topo_defs_dihedral_t *di, *di2; struct topo_defs_improper_t *im, *im2; struct topo_defs_cmap_t *cm, *cm2; struct topo_defs_exclusion_t *ex, *ex2; struct topo_defs_conformation_t *c, *c2; if ( ! defs ) return; hasharray_destroy(defs->topo_hash); hasharray_destroy(defs->type_hash); n = hasharray_count(defs->residue_hash); for ( i=0; iresidue_array[i].atoms; while ( a ) { a2 = a->next; free((void*)a); a = a2; } b = defs->residue_array[i].bonds; while ( b ) { b2 = b->next; free((void*)b); b = b2; } an = defs->residue_array[i].angles; while ( an ) { an2 = an->next; free((void*)an); an = an2; } di = defs->residue_array[i].dihedrals; while ( di ) { di2 = di->next; free((void*)di); di = di2; } im = defs->residue_array[i].impropers; while ( im ) { im2 = im->next; free((void*)im); im = im2; } cm = defs->residue_array[i].cmaps; while ( cm ) { cm2 = cm->next; free((void*)cm); cm = cm2; } ex = defs->residue_array[i].exclusions; while ( ex ) { ex2 = ex->next; free((void*)ex); ex = ex2; } c = defs->residue_array[i].conformations; while ( c ) { c2 = c->next; free((void*)c); c = c2; } } hasharray_destroy(defs->residue_hash); memarena_destroy(defs->arena); free((void*)defs); } void topo_defs_error_handler(topo_defs *defs, void *v, void (*print_msg)(void *, const char *)) { if ( defs ) { defs->newerror_handler = print_msg; defs->newerror_handler_data = v; } } /* internal method */ void topo_defs_log_error(topo_defs *defs, const char *msg) { if (defs && msg && defs->newerror_handler) { defs->newerror_handler(defs->newerror_handler_data, msg); } } void topo_defs_auto_angles(topo_defs *defs, int autogen) { if ( defs ) defs->auto_angles = ! ! autogen; } void topo_defs_auto_dihedrals(topo_defs *defs, int autogen) { if ( defs ) defs->auto_dihedrals = ! ! autogen; } int topo_defs_type(topo_defs *defs, const char *atype, const char *element, double mass, int id) { int i; topo_defs_type_t *newitem; char errmsg[64 + NAMEMAXLEN]; if ( ! defs ) return -1; if ( NAMETOOLONG(atype) ) return -2; if ( NAMETOOLONG(element) ) return -3; if ( ( i = hasharray_index(defs->type_hash,atype) ) != HASHARRAY_FAIL ) { sprintf(errmsg,""duplicate type key %s"",atype); topo_defs_log_error(defs,errmsg); newitem = &defs->type_array[i]; } else { i = hasharray_insert(defs->type_hash,atype); if ( i == HASHARRAY_FAIL ) return -4; newitem = &defs->type_array[i]; strcpy(newitem->name,atype); } newitem->id = id; strcpy(newitem->element,element); newitem->mass = mass; return 0; } int topo_defs_residue(topo_defs *defs, const char *rname, int patch) { int i; topo_defs_residue_t *newitem; char errmsg[64 + NAMEMAXLEN]; if ( ! defs ) return -1; defs->buildres = 0; defs->buildres_no_errors = 0; if ( NAMETOOLONG(rname) ) return -2; if ( ( i = hasharray_index(defs->residue_hash,rname) ) != HASHARRAY_FAIL ) { char *oldname = defs->residue_array[i].name; if ( strcmp(rname,oldname) ) { sprintf(errmsg,""replacing residue alias %s for %s with new residue %s"",rname,oldname,rname); topo_defs_log_error(defs,errmsg); hasharray_delete(defs->residue_hash,rname); } else { sprintf(errmsg,""duplicate residue key %s will be ignored"",rname); topo_defs_log_error(defs,errmsg); /* newitem = &defs->residue_array[i]; */ defs->buildres_no_errors = 1; return 0; } } i = hasharray_insert(defs->residue_hash,rname); if ( i == HASHARRAY_FAIL ) return -4; newitem = &defs->residue_array[i]; strcpy(newitem->name,rname); newitem->patch = patch; newitem->atoms = 0; newitem->bonds = 0; newitem->angles = 0; newitem->dihedrals = 0; newitem->impropers = 0; newitem->cmaps = 0; newitem->exclusions = 0; newitem->conformations = 0; strcpy(newitem->pfirst,defs->pfirst); strcpy(newitem->plast,defs->plast); defs->buildres = newitem; return 0; } int topo_defs_end(topo_defs *defs) { if ( ! defs ) return -1; defs->buildres = 0; defs->buildres_no_errors = 0; return 0; } int topo_defs_atom(topo_defs *defs, const char *rname, int del, const char *aname, int ares, int arel, const char *atype, double charge) { topo_defs_atom_t *newitem; if ( ! defs ) return -1; if ( ! defs->buildres ) { if ( defs->buildres_no_errors ) return 0; topo_defs_log_error(defs,""no residue in progress for atom""); return -1; } if ( NAMETOOLONG(aname) ) return -2; if ( NAMETOOLONG(atype) ) return -3; if ( ares && ! defs->buildres->patch ) return -4; if ( arel && ! defs->buildres->patch ) return -4; if ( del && ! defs->buildres->patch ) return -5; newitem = (topo_defs_atom_t*) malloc(sizeof(topo_defs_atom_t)); if ( ! newitem ) return -6; newitem->res = ares; newitem->rel = arel; newitem->del = del; newitem->charge = charge; strcpy(newitem->name,aname); strcpy(newitem->type,atype); newitem->next = defs->buildres->atoms; defs->buildres->atoms = newitem; return 0; } int topo_defs_bond(topo_defs *defs, const char *rname, int del, const char *a1name, int a1res, int a1rel, const char *a2name, int a2res, int a2rel) { topo_defs_bond_t *newitem; if ( ! defs ) return -1; if ( ! defs->buildres ) { if ( defs->buildres_no_errors ) return 0; topo_defs_log_error(defs,""no residue in progress for bond""); return -1; } if ( NAMETOOLONG(a1name) ) return -2; if ( NAMETOOLONG(a2name) ) return -3; if ( del && ! defs->buildres->patch ) return -4; if ( ( a1res || a2res ) && ! defs->buildres->patch ) return -4; for ( newitem=defs->buildres->bonds; newitem; newitem=newitem->next ) { char errmsg[128]; if ( newitem->res1 != a1res ) continue; if ( newitem->rel1 != a1rel ) continue; if ( newitem->res2 != a2res ) continue; if ( newitem->rel2 != a2rel ) continue; if ( newitem->del != del ) continue; if ( strcmp(newitem->atom1,a1name) ) continue; if ( strcmp(newitem->atom2,a2name) ) continue; sprintf(errmsg, ""duplicate bond %s %s in residue %s"", a1name, a2name, defs->buildres->name); topo_defs_log_error(defs,errmsg); return -6; } for ( newitem=defs->buildres->bonds; newitem; newitem=newitem->next ) { char errmsg[128]; if ( newitem->res1 != a2res ) continue; if ( newitem->rel1 != a2rel ) continue; if ( newitem->res2 != a1res ) continue; if ( newitem->rel2 != a1rel ) continue; if ( newitem->del != del ) continue; if ( strcmp(newitem->atom1,a2name) ) continue; if ( strcmp(newitem->atom2,a1name) ) continue; sprintf(errmsg, ""duplicate bond %s %s in residue %s"", a1name, a2name, defs->buildres->name); topo_defs_log_error(defs,errmsg); return -7; } if ( ( a1res == a2res ) && ( a1rel == a2rel ) && ! strcmp(a1name,a2name) ) { char errmsg[128]; sprintf(errmsg, ""self bond %s %s in residue %s"", a1name, a2name, defs->buildres->name); topo_defs_log_error(defs,errmsg); return -8; } newitem = (topo_defs_bond_t*) malloc(sizeof(topo_defs_bond_t)); if ( ! newitem ) return -5; newitem->res1 = a1res; newitem->rel1 = a1rel; newitem->res2 = a2res; newitem->rel2 = a2rel; newitem->del = del; strcpy(newitem->atom1,a1name); strcpy(newitem->atom2,a2name); newitem->next = defs->buildres->bonds; defs->buildres->bonds = newitem; return 0; } int topo_defs_angle(topo_defs *defs, const char *rname, int del, const char *a1name, int a1res, int a1rel, const char *a2name, int a2res, int a2rel, const char *a3name, int a3res, int a3rel) { topo_defs_angle_t *newitem; if ( ! defs ) return -1; if ( ! defs->buildres ) { if ( defs->buildres_no_errors ) return 0; topo_defs_log_error(defs,""no residue in progress for angle""); return -1; } if ( NAMETOOLONG(a1name) ) return -2; if ( NAMETOOLONG(a2name) ) return -3; if ( NAMETOOLONG(a3name) ) return -4; if ( del && ! defs->buildres->patch ) return -5; if ( ( a1res || a2res || a3res ) && ! defs->buildres->patch ) return -6; newitem = (topo_defs_angle_t*) malloc(sizeof(topo_defs_angle_t)); if ( ! newitem ) return -7; newitem->res1 = a1res; newitem->rel1 = a1rel; newitem->res2 = a2res; newitem->rel2 = a2rel; newitem->res3 = a3res; newitem->rel3 = a3rel; newitem->del = del; strcpy(newitem->atom1,a1name); strcpy(newitem->atom2,a2name); strcpy(newitem->atom3,a3name); newitem->next = defs->buildres->angles; defs->buildres->angles = newitem; return 0; } int topo_defs_dihedral(topo_defs *defs, const char *rname, int del, const char *a1name, int a1res, int a1rel, const char *a2name, int a2res, int a2rel, const char *a3name, int a3res, int a3rel, const char *a4name, int a4res, int a4rel) { topo_defs_dihedral_t *newitem; if ( ! defs ) return -1; if ( ! defs->buildres ) { if ( defs->buildres_no_errors ) return 0; topo_defs_log_error(defs,""no residue in progress for dihedral""); return -1; } if ( NAMETOOLONG(a1name) ) return -2; if ( NAMETOOLONG(a2name) ) return -3; if ( NAMETOOLONG(a3name) ) return -4; if ( NAMETOOLONG(a4name) ) return -5; if ( del && ! defs->buildres->patch ) return -6; if ( ( a1res || a2res || a3res || a4res ) && ! defs->buildres->patch ) return -7; newitem = (topo_defs_dihedral_t*) malloc(sizeof(topo_defs_dihedral_t)); if ( ! newitem ) return -8; newitem->res1 = a1res; newitem->rel1 = a1rel; newitem->res2 = a2res; newitem->rel2 = a2rel; newitem->res3 = a3res; newitem->rel3 = a3rel; newitem->res4 = a4res; newitem->rel4 = a4rel; newitem->del = del; strcpy(newitem->atom1,a1name); strcpy(newitem->atom2,a2name); strcpy(newitem->atom3,a3name); strcpy(newitem->atom4,a4name); newitem->next = defs->buildres->dihedrals; defs->buildres->dihedrals = newitem; return 0; } int topo_defs_improper(topo_defs *defs, const char *rname, int del, const char *a1name, int a1res, int a1rel, const char *a2name, int a2res, int a2rel, const char *a3name, int a3res, int a3rel, const char *a4name, int a4res, int a4rel) { topo_defs_improper_t *newitem; if ( ! defs ) return -1; if ( ! defs->buildres ) { if ( defs->buildres_no_errors ) return 0; topo_defs_log_error(defs,""no residue in progress for improper""); return -1; } if ( NAMETOOLONG(a1name) ) return -2; if ( NAMETOOLONG(a2name) ) return -3; if ( NAMETOOLONG(a3name) ) return -4; if ( NAMETOOLONG(a4name) ) return -5; if ( del && ! defs->buildres->patch ) return -6; if ( ( a1res || a2res || a3res || a4res ) && ! defs->buildres->patch ) return -7; newitem = (topo_defs_improper_t*) malloc(sizeof(topo_defs_improper_t)); if ( ! newitem ) return -8; newitem->res1 = a1res; newitem->rel1 = a1rel; newitem->res2 = a2res; newitem->rel2 = a2rel; newitem->res3 = a3res; newitem->rel3 = a3rel; newitem->res4 = a4res; newitem->rel4 = a4rel; newitem->del = del; strcpy(newitem->atom1,a1name); strcpy(newitem->atom2,a2name); strcpy(newitem->atom3,a3name); strcpy(newitem->atom4,a4name); newitem->next = defs->buildres->impropers; defs->buildres->impropers = newitem; return 0; } int topo_defs_cmap(topo_defs *defs, const char *rname, int del, const char* const anamel[8], const int aresl[8], const int arell[8]) { int i; topo_defs_cmap_t *newitem; if ( ! defs ) return -1; if ( ! defs->buildres ) { if ( defs->buildres_no_errors ) return 0; topo_defs_log_error(defs,""no residue in progress for cmap""); return -1; } for ( i=0; i<8; ++i ) { if ( NAMETOOLONG(anamel[i]) ) return -2-i; } if ( del && ! defs->buildres->patch ) return -10; if ( ( aresl[0] || aresl[1] || aresl[2] || aresl[3] || aresl[4] || aresl[5] || aresl[6] || aresl[7] ) && ! defs->buildres->patch ) return -11; newitem = (topo_defs_cmap_t*) malloc(sizeof(topo_defs_cmap_t)); if ( ! newitem ) return -12; for ( i=0; i<8; ++i ) { newitem->resl[i] = aresl[i]; newitem->rell[i] = arell[i]; strcpy(newitem->atoml[i],anamel[i]); } newitem->del = del; newitem->next = defs->buildres->cmaps; defs->buildres->cmaps = newitem; if ( ! defs->cmaps_present ) { topo_defs_log_error(defs,""cross-term entries present in topology definitions""); } defs->cmaps_present = 1; return 0; } int topo_defs_exclusion(topo_defs *defs, const char *rname, int del, const char *a1name, int a1res, int a1rel, const char *a2name, int a2res, int a2rel) { topo_defs_exclusion_t *newitem; if ( ! defs ) return -1; if ( ! defs->buildres ) { if ( defs->buildres_no_errors ) return 0; topo_defs_log_error(defs,""no residue in progress for explicit exclusion""); return -1; } if ( NAMETOOLONG(a1name) ) return -2; if ( NAMETOOLONG(a2name) ) return -3; if ( del && ! defs->buildres->patch ) return -4; if ( ( a1res || a2res ) && ! defs->buildres->patch ) return -4; newitem = (topo_defs_exclusion_t*) malloc(sizeof(topo_defs_exclusion_t)); if ( ! newitem ) return -5; newitem->res1 = a1res; newitem->rel1 = a1rel; newitem->res2 = a2res; newitem->rel2 = a2rel; newitem->del = del; strcpy(newitem->atom1,a1name); strcpy(newitem->atom2,a2name); newitem->next = defs->buildres->exclusions; defs->buildres->exclusions = newitem; return 0; } int topo_defs_conformation(topo_defs *defs, const char *rname, int del, const char *a1name, int a1res, int a1rel, const char *a2name, int a2res, int a2rel, const char *a3name, int a3res, int a3rel, const char *a4name, int a4res, int a4rel, double dist12, double angle123, double dihedral, int improper, double angle234, double dist34) { topo_defs_conformation_t *newitem; if ( ! defs ) return -1; if ( ! defs->buildres ) { if ( defs->buildres_no_errors ) return 0; topo_defs_log_error(defs,""no residue in progress for conformation""); return -1; } if ( NAMETOOLONG(a1name) ) return -2; if ( NAMETOOLONG(a2name) ) return -3; if ( NAMETOOLONG(a3name) ) return -4; if ( NAMETOOLONG(a4name) ) return -5; if ( del && ! defs->buildres->patch ) return -6; if ( ( a1res || a2res || a3res || a4res ) && ! defs->buildres->patch ) return -7; newitem = (topo_defs_conformation_t*)malloc(sizeof(topo_defs_conformation_t)); if ( ! newitem ) return -8; newitem->res1 = a1res; newitem->rel1 = a1rel; newitem->res2 = a2res; newitem->rel2 = a2rel; newitem->res3 = a3res; newitem->rel3 = a3rel; newitem->res4 = a4res; newitem->rel4 = a4rel; newitem->del = del; newitem->improper = improper; newitem->dist12 = dist12; newitem->angle123 = angle123; newitem->dihedral = dihedral; newitem->angle234 = angle234; newitem->dist34 = dist34; strcpy(newitem->atom1,a1name); strcpy(newitem->atom2,a2name); strcpy(newitem->atom3,a3name); strcpy(newitem->atom4,a4name); newitem->next = defs->buildres->conformations; defs->buildres->conformations = newitem; return 0; } int topo_defs_default_patching_first(topo_defs *defs, const char *pname) { if ( ! defs ) return -1; if ( NAMETOOLONG(pname) ) return -2; strcpy(defs->pfirst,pname); return 0; } int topo_defs_default_patching_last(topo_defs *defs, const char *pname) { if ( ! defs ) return -1; if ( NAMETOOLONG(pname) ) return -2; strcpy(defs->plast,pname); return 0; } int topo_defs_patching_first(topo_defs *defs, const char *rname, const char *pname) { if ( ! defs ) return -1; if ( ! defs->buildres ) { if ( defs->buildres_no_errors ) return 0; topo_defs_log_error(defs,""no residue in progress for patching""); return -1; } if ( NAMETOOLONG(pname) ) return -2; strcpy(defs->buildres->pfirst,pname); return 0; } int topo_defs_patching_last(topo_defs *defs, const char *rname, const char *pname) { if ( ! defs ) return -1; if ( ! defs->buildres ) { if ( defs->buildres_no_errors ) return 0; topo_defs_log_error(defs,""no residue in progress for patching""); return -1; } if ( NAMETOOLONG(pname) ) return -2; strcpy(defs->buildres->plast,pname); return 0; } /* int topo_defs_add_topofile(topo_defs *defs, const char *filename) { */ /* topo_defs_topofile_t **topofiles; */ /* topo_defs_topofile_t *topofiletmp; */ /* if ( ! defs ) return -1; */ /* if ( strlen(filename)>=256 ) return -2; */ /* topofiles = &(defs->topofiles); */ /* topofiletmp = 0; */ /* topofiletmp = memarena_alloc(defs->arena,sizeof(topo_defs_topofile_t)); */ /* if ( ! topofiletmp ) return -3; */ /* strcpy(topofiletmp->filename,filename); */ /* printf(""add_topo %i %s;\n"", defs->ntopo, topofiletmp->filename); */ /* defs->ntopo++; */ /* topofiletmp->next = *topofiles; */ /* *topofiles = topofiletmp; */ /* return 0; */ /* } */ int topo_defs_add_topofile(topo_defs *defs, const char *filename) { /* topo_defs_topofile_t **topofiles; */ /* topo_defs_topofile_t *topofiletmp; */ /* if ( ! defs ) return -1; */ /* if ( strlen(filename)>=256 ) return -2; */ /* topofiles = &(defs->topofiles); */ /* topofiletmp = 0; */ /* topofiletmp = memarena_alloc(defs->arena,sizeof(topo_defs_topofile_t)); */ /* if ( ! topofiletmp ) return -3; */ /* strcpy(topofiletmp->filename,filename); */ /* printf(""add_topo %i %s;\n"", defs->ntopo, topofiletmp->filename); */ /* defs->ntopo++; */ /* topofiletmp->next = *topofiles; */ /* *topofiles = topofiletmp; */ /* return 0; */ int i; topo_defs_topofile_t *newitem; char errmsg[64 + 256]; if ( ! defs ) return -1; if ( strlen(filename)>=256 ) return -2; if ( ( i = hasharray_index(defs->topo_hash,filename) ) != HASHARRAY_FAIL ) { sprintf(errmsg,""duplicate topology file %s"",filename); topo_defs_log_error(defs,errmsg); newitem = &defs->topo_array[i]; } else { i = hasharray_insert(defs->topo_hash,filename); if ( i == HASHARRAY_FAIL ) return -4; newitem = &defs->topo_array[i]; strcpy(newitem->filename,filename); } return 0; } ","C" "Biophysics","Eigenstate/psfgen","src/charmm_file.h",".h","209","14"," #ifndef CHARMM_FILE_H #define CHARMM_FILE_H #include int charmm_get_tokens(char **tok, int toklen, char *sbuf, int sbuflen, char *lbuf, int *lineno, FILE *stream, int all_caps); #endif ","Unknown" "Biophysics","Eigenstate/psfgen","src/topo_mol_output.h",".h","558","19"," #ifndef TOPO_MOL_OUTPUT_H #define TOPO_MOL_OUTPUT_H #include #include ""topo_mol.h"" int topo_mol_write_pdb(topo_mol *mol, FILE *file, void *, void (*print_msg)(void *, const char *)); int topo_mol_write_namdbin(topo_mol *mol, FILE *file, FILE *velfile, void *, void (*print_msg)(void *, const char *)); int topo_mol_write_psf(topo_mol *mol, FILE *file, int charmmfmt, int nocmap, int nopatches, void *, void (*print_msg)(void *, const char *)); #endif ","Unknown" "Biophysics","Eigenstate/psfgen","src/tcl_main.c",".c","1686","77"," #if defined(NAMD_TCL) || ! defined(NAMD_VERSION) #include extern int Psfgen_Init(Tcl_Interp *); int main(int argc, char *argv[]) { Tcl_Main(argc, argv, Psfgen_Init); return 0; } #ifdef NAMD_VERSION /* * Provide user feedback and warnings beyond result values. * If we are running interactively, Tcl_Main will take care of echoing results * to the console. If we run a script, we need to output the results * ourselves. */ void newhandle_msg(void *v, const char *msg) { Tcl_Interp *interp = (Tcl_Interp *)v; const char *words[3] = {""puts"", ""-nonewline"", ""psfgen) ""}; char *script = NULL; // prepend ""psfgen) "" to all output script = Tcl_Merge(3, words); Tcl_Eval(interp,script); Tcl_Free(script); // emit the output words[1] = msg; script = Tcl_Merge(2, words); Tcl_Eval(interp,script); Tcl_Free(script); } /* * Same as above but allow user control over prepending of ""psfgen) "" * and newlines. */ void newhandle_msg_ex(void *v, const char *msg, int prepend, int newline) { Tcl_Interp *interp = (Tcl_Interp *)v; const char *words[3] = {""puts"", ""-nonewline"", ""psfgen) ""}; char *script = NULL; if (prepend) { // prepend ""psfgen) "" to all output script = Tcl_Merge(3, words); Tcl_Eval(interp,script); Tcl_Free(script); } // emit the output if (newline) { words[1] = msg; script = Tcl_Merge(2, words); } else { words[2] = msg; script = Tcl_Merge(3, words); } Tcl_Eval(interp,script); Tcl_Free(script); } #endif #else #include int main(int argc, char **argv) { fprintf(stderr,""%s unavailable on this platform (no Tcl)\n"",argv[0]); exit(-1); } #endif ","C" "Biophysics","Eigenstate/psfgen","src/stringhash.h",".h","426","21"," #ifndef STRINGHASH_H #define STRINGHASH_H struct stringhash; typedef struct stringhash stringhash; stringhash * stringhash_create(void); void stringhash_destroy(stringhash *h); const char* stringhash_insert(stringhash *h, const char *key, const char *data); #define STRINGHASH_FAIL 0 const char* stringhash_lookup(stringhash *h, const char *key); const char* stringhash_delete(stringhash *h, const char *key); #endif ","Unknown" "Biophysics","Eigenstate/psfgen","src/hasharray.c",".c","2620","116"," #include #include #include ""hash.h"" #include ""memarena.h"" #include ""hasharray.h"" struct hasharray { memarena *keyarena; hash_t hash; int count; int alloc; int itemsize; void **itemarray; }; hasharray * hasharray_create(void **itemarray, int itemsize) { hasharray * a; if ( (a = (hasharray*) malloc(sizeof(hasharray))) ) { a->count = 0; a->alloc = 0; a->itemsize = itemsize; a->itemarray = itemarray; *(a->itemarray) = 0; if ( ! ( a->keyarena = memarena_create() ) ) { free((void*)a); return 0; } hash_init(&(a->hash),0); } return a; } int hasharray_clear(hasharray *a) { if ( ! a ) return HASHARRAY_FAIL; hash_destroy(&(a->hash)); memarena_destroy(a->keyarena); if ( ! ( a->keyarena = memarena_create() ) ) { return HASHARRAY_FAIL; } hash_init(&(a->hash),0); return 0; } void hasharray_destroy(hasharray *a) { if ( ! a ) return; hash_destroy(&(a->hash)); memarena_destroy(a->keyarena); if ( *(a->itemarray) ) { free(*(a->itemarray)); *(a->itemarray) = 0; } free((void*)a); } int hasharray_reinsert(hasharray *a, const char *key, int pos) { int i; char *s; if ( ! a ) return HASHARRAY_FAIL; i = hash_lookup(&(a->hash),key); if ( i != HASH_FAIL ) return i; i = pos; if ( ! ( s = memarena_alloc(a->keyarena,strlen(key)+1) ) ) { return HASHARRAY_FAIL; } strcpy(s,key); hash_insert(&(a->hash),s,i); return i; } int hasharray_insert(hasharray *a, const char *key) { int i; int new_alloc; void *new_array; char *s; if ( ! a ) return HASHARRAY_FAIL; i = hash_lookup(&(a->hash),key); if ( i != HASH_FAIL ) return i; i = a->count; a->count++; if ( a->count > a->alloc ) { if ( a->alloc ) new_alloc = a->alloc * 2; else new_alloc = 8; new_array = realloc(*(a->itemarray), new_alloc * (size_t) a->itemsize); if ( new_array ) { *(a->itemarray) = new_array; a->alloc = new_alloc; } else return HASHARRAY_FAIL; } if ( ! ( s = memarena_alloc(a->keyarena,strlen(key)+1) ) ) { return HASHARRAY_FAIL; } strcpy(s,key); hash_insert(&(a->hash),s,i); return i; } int hasharray_delete(hasharray *a, const char *key) { if (!a) return HASHARRAY_FAIL; /* I think this should be assert(a) */ return hash_delete(&(a->hash), key); } int hasharray_index(hasharray *a, const char *key) { int i; if ( ! a ) return HASHARRAY_FAIL; i = hash_lookup(&(a->hash),key); if ( i == HASH_FAIL ) i = HASHARRAY_FAIL; return i; } int hasharray_count(hasharray *a) { if ( ! a ) return HASHARRAY_FAIL; return a->count; } ","C" "Biophysics","Eigenstate/psfgen","src/psf_file.c",".c","5263","231","#include #include #include ""psf_file.h"" #define PSF_RECORD_LENGTH 160 /* * Read in the beginning of the bond/angle/dihed/etc information, * but don't read in the data itself. Returns the number of the record type * for the molecule. If error, returns (-1). */ int psf_start_block(FILE *file, const char *blockname) { char inbuf[PSF_RECORD_LENGTH+2]; int nrec = -1; /* keep reading the next line until a line with blockname appears */ do { if(inbuf != fgets(inbuf, PSF_RECORD_LENGTH+1, file)) { /* EOF encountered with no blockname line found ==> error, return (-1) */ return (-1); } if(strlen(inbuf) > 0 && strstr(inbuf, blockname)) nrec = atoi(inbuf); } while (nrec == -1); return nrec; } /* return # of atoms, or negative if error */ int psf_start_atoms(FILE *file) { char inbuf[PSF_RECORD_LENGTH+2]; int natom = 0; /* skip comments; get number of atoms */ /* Taken from VMD's ReadPSF */ do { if (inbuf != fgets(inbuf, PSF_RECORD_LENGTH+1, file)) { /* EOF with no NATOM */ return -1; } if (strlen(inbuf) > 0) { if (!strstr(inbuf, ""REMARKS"")) { if (strstr(inbuf, ""NATOM"")) { natom = atoi(inbuf); } } } } while (!natom); return natom; } int psf_get_atom(FILE *f, char *name, char *atype, char *resname, char *segname, char *resid, double *q, double *m) { char inbuf[PSF_RECORD_LENGTH+2]; int i,num, read_count; if(inbuf != fgets(inbuf, PSF_RECORD_LENGTH+1, f)) { return(-1); } read_count = sscanf(inbuf, ""%d %8s %8s %8s %8s %8s %lf %lf"", &num, segname, resid, resname, name, atype, q, m); if (read_count != 8) { fprintf(stderr,""BAD ATOM LINE IN PSF FILE:\n: %s\n"", inbuf); return -1; } return num; } static int atoifw(char **ptr, int fw) { char *op = *ptr; int ival = 0; int iws = 0; char tmpc; sscanf(op, ""%d%n"", &ival, &iws); if ( iws == fw ) { /* ""12345678 123..."" or "" 1234567 123..."" */ *ptr += iws; } else if ( iws < fw ) { /* left justified? */ while ( iws < fw && op[iws] == ' ' ) ++iws; *ptr += iws; } else if ( iws < 2*fw ) { /* "" 12345678 123..."" */ *ptr += iws; } else { /* "" 123456712345678"" or ""1234567812345678"" */ tmpc = op[fw]; op[fw] = '\0'; ival = atoi(op); op[fw] = tmpc; *ptr += fw; } return ival; } int psf_get_bonds(FILE *f, int fw, int n, int *bonds) { char inbuf[PSF_RECORD_LENGTH+2]; char *bondptr = NULL; int i=0; while (i #include ""topo_mol.h"" #include ""stringhash.h"" int topo_mol_read_plugin(topo_mol *mol, const char *pluginname, const char *filename, const char *coorpluginname, const char *coorfilename, const char *segid, stringhash *h, int all_caps, int coordinatesonly, int residuesonly, void *, void (*print_msg)(void *, const char *)); struct image_spec { int na, nb, nc; double ax, ay, az; double bx, by, bz; double cx, cy, cz; }; int topo_mol_write_plugin(topo_mol *mol, const char *pluginname, const char *filename, struct image_spec *images, void *, void (*print_msg)(void *, const char *)); #endif ","Unknown" "Biophysics","Eigenstate/psfgen","src/psf_file_extract.c",".c","24657","868","#include #include #include ""psf_file.h"" #include ""psf_file_extract.h"" #include ""pdb_file.h"" #include ""topo_mol_struct.h"" /* General note: in a few places I read various arrays in reverse order. That's because I want psf files emitted by psfgen to have all the atoms, bonds, etc. in the same order as in the original psf file. We have to reverse it because adding to a linked list reverses the order. Actually, if the original psf file comes from some other program, then we might change the order of the bonds, angles, etc. but we can at least guarantee that if we read a psf file written by psfgen, then write it out again, the output will match the input exactly. */ /* Read in all psf atom information using this struct */ struct psfatom { char name[10]; char atype[10]; char resname[10]; char segname[10]; char resid[10]; char element[3]; double charge, mass; }; typedef struct psfatom psfatom; #define PSF_RECORD_LENGTH 200 static int extract_patches(FILE *file, topo_mol *mol) { char inbuf[PSF_RECORD_LENGTH+2]; int npatch = 0; /* Read comments; get patch info */ while (!feof(file)) { if (inbuf != fgets(inbuf, PSF_RECORD_LENGTH+1, file)) { /* EOF with no NATOM */ return -1; } if (strlen(inbuf) > 0) { if (strstr(inbuf, ""REMARKS"")) { char *pbuf; if (strstr(inbuf, ""REMARKS topology "")) { char topofile[256]; pbuf = strstr(inbuf, ""topology""); pbuf=pbuf+strlen(""topology""); sscanf(pbuf, ""%s"", topofile); topo_defs_add_topofile(mol->defs, topofile); } if (strstr(inbuf, ""REMARKS patch "") || strstr(inbuf, ""REMARKS defaultpatch "")) { char pres[NAMEMAXLEN], segres[2*NAMEMAXLEN]; char s[NAMEMAXLEN], r[NAMEMAXLEN]; topo_mol_ident_t target; pbuf = strstr(inbuf, ""patch""); pbuf=pbuf+5; sscanf(pbuf, ""%s"", pres); if (strcmp(pres,""----"")) { if (strstr(inbuf, ""REMARKS defaultpatch"")) { topo_mol_add_patch(mol,pres,1); } else { topo_mol_add_patch(mol,pres,0); } } pbuf = strstr(pbuf, pres)+strlen(pres); while (sscanf(pbuf, ""%s"", segres)==1) { int slen; slen = strcspn(segres,"":""); strncpy(s, segres, slen); s[slen] = '\0'; strcpy(r, strchr(segres,':')+1); target.segid = s; target.resid = r; topo_mol_add_patchres(mol,&target); pbuf = strstr(pbuf,segres)+strlen(segres); } npatch++; } } else { if (strstr(inbuf, ""NATOM"")) { rewind(file); return npatch; } } } } ; return npatch; } static int extract_segment_extra_data(FILE *file, topo_mol *mol) { char inbuf[PSF_RECORD_LENGTH+2]; /* Read comments; get patch info */ while (!feof(file)) { if (inbuf != fgets(inbuf, PSF_RECORD_LENGTH+1, file)) { /* EOF with no NATOM */ return -1; } if (strlen(inbuf) > 0) { if (strstr(inbuf, ""REMARKS"")) { char *pbuf; if (strstr(inbuf, ""REMARKS segment "")) { char segid[NAMEMAXLEN], pfirst[NAMEMAXLEN], plast[NAMEMAXLEN]; char angles[20], diheds[20], tmp[NAMEMAXLEN]; topo_mol_segment_t *seg = NULL; int id; pbuf = strstr(inbuf, ""segment""); pbuf += strlen(""segment""); sscanf(pbuf, ""%s %s %s %s %s %s %s %s %s"", segid, tmp, tmp, pfirst, tmp, plast, tmp, angles, diheds); if ( (id = hasharray_index(mol->segment_hash, segid)) != HASHARRAY_FAIL) { /* Then the segment exists. Look it up and return it. */ seg = mol->segment_array[id]; strcpy(strchr(pfirst,';'),""""); strcpy(strchr(plast, ';'),""""); strcpy(seg->pfirst,pfirst); strcpy(seg->plast, plast); seg->auto_angles = 0; if (!strcmp(angles,""angles"")) { seg->auto_angles = 1; } seg->auto_dihedrals = 0; if (!strcmp(diheds,""dihedrals"")) { seg->auto_dihedrals = 1; } } } } } } return 0; } static int extract_bonds(FILE *file, int fw, topo_mol *mol, int natoms, topo_mol_atom_t **molatomlist) { int *bonds; int i, nbonds; /* Build bonds */ nbonds = psf_start_block(file, ""NBOND""); if (nbonds < 0) { return -1; } bonds = (int *)malloc(2*nbonds*sizeof(int)); if (psf_get_bonds(file, fw, nbonds, bonds)) { free(bonds); return -1; } for (i=nbonds-1; i >= 0; i--) { topo_mol_atom_t *atom1, *atom2; topo_mol_bond_t *tuple; int ind1, ind2; ind1 = bonds[2*i]-1; ind2 = bonds[2*i+1]-1; if (ind1 < 0 || ind2 < 0 || ind1 >= natoms || ind2 >= natoms) { /* Bad indices, abort now */ free(bonds); return -1; } atom1 = molatomlist[ind1]; atom2 = molatomlist[ind2]; tuple = memarena_alloc(mol->arena,sizeof(topo_mol_bond_t)); tuple->next[0] = atom1->bonds; tuple->atom[0] = atom1; tuple->next[1] = atom2->bonds; tuple->atom[1] = atom2; tuple->del = 0; atom1->bonds = tuple; atom2->bonds = tuple; } free(bonds); return 0; } static int extract_angles(FILE *file, int fw, topo_mol *mol, int natoms, topo_mol_atom_t **molatomlist) { int i, nangles; int *angles; nangles = psf_start_block(file, ""NTHETA""); if (nangles < 0) return -1; angles = (int *)malloc(3*nangles*sizeof(int)); if (psf_get_angles(file, fw, nangles, angles)) { free(angles); return -1; } for (i=nangles-1; i >= 0; i--) { topo_mol_atom_t *atom1, *atom2, *atom3; topo_mol_angle_t *tuple; atom1 = molatomlist[angles[3*i]-1]; atom2 = molatomlist[angles[3*i+1]-1]; atom3 = molatomlist[angles[3*i+2]-1]; tuple = memarena_alloc(mol->angle_arena,sizeof(topo_mol_angle_t)); tuple->next[0] = atom1->angles; tuple->atom[0] = atom1; tuple->next[1] = atom2->angles; tuple->atom[1] = atom2; tuple->next[2] = atom3->angles; tuple->atom[2] = atom3; tuple->del = 0; atom1->angles = tuple; atom2->angles = tuple; atom3->angles = tuple; } free(angles); return 0; } static int extract_dihedrals(FILE *file, int fw, topo_mol *mol, int natoms, topo_mol_atom_t **molatomlist) { int i, ndihedrals; int *dihedrals; ndihedrals = psf_start_block(file, ""NPHI""); if (ndihedrals < 0) return -1; dihedrals = (int *)malloc(4*ndihedrals*sizeof(int)); if (psf_get_dihedrals(file, fw, ndihedrals, dihedrals)) { free(dihedrals); return -1; } for (i=ndihedrals-1; i >= 0; i--) { topo_mol_atom_t *atom1, *atom2, *atom3, *atom4; topo_mol_dihedral_t *tuple; atom1 = molatomlist[dihedrals[4*i]-1]; atom2 = molatomlist[dihedrals[4*i+1]-1]; atom3 = molatomlist[dihedrals[4*i+2]-1]; atom4 = molatomlist[dihedrals[4*i+3]-1]; tuple = memarena_alloc(mol->dihedral_arena,sizeof(topo_mol_dihedral_t)); tuple->next[0] = atom1->dihedrals; tuple->atom[0] = atom1; tuple->next[1] = atom2->dihedrals; tuple->atom[1] = atom2; tuple->next[2] = atom3->dihedrals; tuple->atom[2] = atom3; tuple->next[3] = atom4->dihedrals; tuple->atom[3] = atom4; tuple->del = 0; atom1->dihedrals = tuple; atom2->dihedrals = tuple; atom3->dihedrals = tuple; atom4->dihedrals = tuple; } free(dihedrals); return 0; } static int extract_impropers(FILE *file, int fw, topo_mol *mol, int natoms, topo_mol_atom_t **molatomlist) { int i, nimpropers; int *impropers; nimpropers = psf_start_block(file, ""NIMPHI""); if (nimpropers < 0) return -1; impropers = (int *)malloc(4*nimpropers*sizeof(int)); if (psf_get_impropers(file, fw, nimpropers, impropers)) { free(impropers); return -1; } for (i=nimpropers-1; i >= 0; i--) { topo_mol_atom_t *atom1, *atom2, *atom3, *atom4; topo_mol_improper_t *tuple; atom1 = molatomlist[impropers[4*i]-1]; atom2 = molatomlist[impropers[4*i+1]-1]; atom3 = molatomlist[impropers[4*i+2]-1]; atom4 = molatomlist[impropers[4*i+3]-1]; tuple = memarena_alloc(mol->arena,sizeof(topo_mol_improper_t)); tuple->next[0] = atom1->impropers; tuple->atom[0] = atom1; tuple->next[1] = atom2->impropers; tuple->atom[1] = atom2; tuple->next[2] = atom3->impropers; tuple->atom[2] = atom3; tuple->next[3] = atom4->impropers; tuple->atom[3] = atom4; tuple->del = 0; atom1->impropers = tuple; atom2->impropers = tuple; atom3->impropers = tuple; atom4->impropers = tuple; } free(impropers); return 0; } static int extract_cmaps(FILE *file, int fw, topo_mol *mol, int natoms, topo_mol_atom_t **molatomlist) { int i, j, ncmaps; int *cmaps; ncmaps = psf_start_block(file, ""NCRTERM""); if (ncmaps < 0) { return 1; } cmaps = (int *)malloc(8*ncmaps*sizeof(int)); if (psf_get_cmaps(file, fw, ncmaps, cmaps)) { free(cmaps); return -1; } for (i=ncmaps-1; i >= 0; i--) { topo_mol_atom_t *atoml[8]; topo_mol_cmap_t *tuple; tuple = memarena_alloc(mol->arena,sizeof(topo_mol_cmap_t)); for ( j = 0; j < 8; ++j ) { atoml[j] = molatomlist[cmaps[8*i+j]-1]; tuple->next[j] = atoml[j]->cmaps; tuple->atom[j] = atoml[j]; } tuple->del = 0; for ( j = 0; j < 8; ++j ) { atoml[j]->cmaps = tuple; } } free(cmaps); return 0; } static int extract_exclusions(FILE *file, int fw, topo_mol *mol, int natoms, topo_mol_atom_t **molatomlist) { int *exclusions, *exclusion_indices; int i, j, nexclusions; int exclusion_index = 0; /* Read explicit exclusion list */ nexclusions = psf_start_block(file, ""NNB""); if (nexclusions < 0) { return -1; } exclusions = (int *)malloc(nexclusions*sizeof(int)); exclusion_indices = (int *)malloc(natoms*sizeof(int)); if (psf_get_exclusions(file, fw, nexclusions, exclusions, natoms, exclusion_indices)) { free(exclusions); free(exclusion_indices); return -1; } for (i=0; i < natoms; i++) { topo_mol_atom_t *atom1, *atom2; topo_mol_exclusion_t *excl; atom1 = molatomlist[i]; if (exclusion_indices[i] > nexclusions || exclusion_indices[i] < 0) { free(exclusions); free(exclusion_indices); printf(""lol3[%d]\n"", i); return -1; } for (j = exclusion_indices[i]-1; j >= exclusion_index; j--) { int ind2 = exclusions[j] - 1; if (ind2 < 0 || ind2 >= natoms) { free(exclusions); free(exclusion_indices); return -1; } atom2 = molatomlist[ind2]; excl = memarena_alloc(mol->arena,sizeof(topo_mol_exclusion_t)); excl->next[0] = atom1->exclusions; excl->atom[0] = atom1; excl->next[1] = atom2->exclusions; excl->atom[1] = atom2; excl->del = 0; atom1->exclusions = excl; atom2->exclusions = excl; } exclusion_index = exclusion_indices[i]; } free(exclusions); free(exclusion_indices); return 0; } /* Return the segment corresponding to the given segname. If the segname doesn't exist, add it. Return NULL on error. */ static topo_mol_segment_t *get_segment(topo_mol *mol, const char *segname) { int id; topo_mol_segment_t *seg = NULL; if ( (id = hasharray_index(mol->segment_hash, segname)) != HASHARRAY_FAIL) { /* Then the segment exists. Look it up and return it. */ seg = mol->segment_array[id]; } else { /* Must create new segment */ id = hasharray_insert(mol->segment_hash, segname); if (id != HASHARRAY_FAIL) { seg = mol->segment_array[id] = (topo_mol_segment_t *) malloc(sizeof(topo_mol_segment_t)); strcpy(seg->segid, segname); seg->residue_hash = hasharray_create( (void**) &(seg->residue_array), sizeof(topo_mol_residue_t)); strcpy(seg->pfirst,""""); strcpy(seg->plast,""""); seg->auto_angles = 0; seg->auto_dihedrals = 0; } } return seg; } /* Return a new residue with the given resid. Add it to the given segment. If the resid already exists, return NULL. Return NULL if there's a problem. */ static topo_mol_residue_t *get_residue(topo_mol_segment_t *seg, const char *resid) { int id; topo_mol_residue_t *res; /* Check that the residue doesn't already exist */ if ( hasharray_index(seg->residue_hash,resid) != HASHARRAY_FAIL ) { return NULL; } id = hasharray_insert(seg->residue_hash, resid); if (id == HASHARRAY_FAIL) { return NULL; } res = &(seg->residue_array[id]); strcpy(res->resid, resid); return res; } int psf_file_extract(topo_mol *mol, FILE *file, FILE *pdbfile, FILE *namdbinfile, FILE *velnamdbinfile, void *v, void (*print_msg)(void *, const char *)) { int i, natoms, charmmext; psfatom *atomlist; double *atomcoords, *atomvels; topo_mol_atom_t **molatomlist; long filepos; char inbuf[PSF_RECORD_LENGTH+2]; /* Read header flags */ if (feof(file) || (inbuf != fgets(inbuf, PSF_RECORD_LENGTH+1, file))) { print_msg(v,""ERROR: Unable to read psf file""); return -1; } if ( strncmp(inbuf, ""PSF"", 3) ) { print_msg(v,""ERROR: File does not begin with PSF - wrong format?""); return -1; } charmmext = ( strstr(inbuf, ""EXT"") ? 1 : 0 ); /* Read patch info from REMARKS */ extract_patches(file, mol); natoms = psf_start_atoms(file); if (natoms < 0) { print_msg(v,""ERROR: Unable to read psf file""); return -1; } atomlist = (psfatom *)malloc(natoms * sizeof(psfatom)); /* Read in all atoms */ for (i=0; ielement,""""); if (psf_get_atom(file, atom->name,atom->atype,atom->resname, atom->segname, atom->resid, &atom->charge, &atom->mass) < 0) { print_msg(v,""error reading atoms from psf file""); free(atomlist); return -1; } } /* Optionally read coordinates, insertion code, and element symbol from PDB file */ atomcoords = 0; if ( pdbfile ) { char record[PDB_RECORD_LENGTH+2]; int indx, insertions; float x,y,z,o,b; char name[8], resname[8], chain[8]; char segname[8], element[8], resid[8], insertion[8]; atomcoords = (double *)malloc(natoms * 3 * sizeof(double)); insertions = 0; i=0; do { if((indx = read_pdb_record(pdbfile, record)) == PDB_ATOM) { psfatom *atom = atomlist + i; if ( i >= natoms ) { print_msg(v,""too many atoms in pdb file""); free(atomlist); free(atomcoords); return -1; } get_pdb_fields(record, name, resname, chain, segname, element, resid, insertion, &x, &y, &z, &o, &b); if ( strncmp(atom->name,name,4) || strncmp(atom->resname,resname,4) || strncmp(atom->segname,segname,4) ) { print_msg(v,""atom mismatch in pdb file""); print_msg(v,record); free(atomlist); free(atomcoords); return -1; } if ( insertion[0] != ' ' && insertion[0] != '\0' ) { if ( ( strlen(atom->resid ) <= 4 ) && strncmp(atom->resid,resid,4) ) { strncpy(atom->resid,resid,7); atom->resid[7] = 0; ++insertions; } if ( atom->resid[strlen(atom->resid)-1] != insertion[0] ) { strncat(atom->resid,insertion,1); } } strncpy(atom->element,element,3); atom->element[2] = 0; atomcoords[i*3 ] = x; atomcoords[i*3 + 1] = y; atomcoords[i*3 + 2] = z; ++i; } } while (indx != PDB_END && indx != PDB_EOF); if ( insertions ) { char buf[80]; sprintf(buf, ""Found %d mismatched resids with insertion codes in pdb file"", insertions); print_msg(v,buf); } if ( i < natoms ) { print_msg(v,""too few atoms in pdb file""); free(atomlist); free(atomcoords); return -1; } } if ( namdbinfile ) { int numatoms; int filen; int wrongendian; char lenbuf[4]; char tmpc; if ( ! atomcoords ) { atomcoords = (double *)malloc(natoms * 3L * sizeof(double)); } fseek(namdbinfile,0,SEEK_END); numatoms = (ftell(namdbinfile)-4)/24; if (numatoms < 1) { print_msg(v,""namdbin file is too short""); free(atomlist); free(atomcoords); return -1; } fseek(namdbinfile,0,SEEK_SET); fread(&filen, sizeof(int), 1, namdbinfile); wrongendian = 0; if (filen != numatoms) { wrongendian = 1; memcpy(lenbuf, (const char *)&filen, 4); tmpc = lenbuf[0]; lenbuf[0] = lenbuf[3]; lenbuf[3] = tmpc; tmpc = lenbuf[1]; lenbuf[1] = lenbuf[2]; lenbuf[2] = tmpc; memcpy((char *)&filen, lenbuf, 4); } if (filen != numatoms) { print_msg(v,""inconsistent atom count in namdbin file""); free(atomlist); free(atomcoords); return -1; } if (numatoms < natoms) { print_msg(v,""too few atoms in namdbin file""); free(atomlist); free(atomcoords); return -1; } if (numatoms > natoms) { print_msg(v,""too many atoms in namdbin file""); free(atomlist); free(atomcoords); return -1; } if (wrongendian) { print_msg(v,""namdbin file appears to be other-endian""); } if (fread(atomcoords, sizeof(double), 3L * natoms, namdbinfile) != (size_t)(3L * natoms)) { print_msg(v,""error reading data from namdbin file""); free(atomlist); free(atomcoords); return -1; } if (wrongendian) { int i; char tmp0, tmp1, tmp2, tmp3; char *cdata = (char *) atomcoords; print_msg(v,""converting other-endian data from namdbin file""); for ( i=0; i<3*natoms; ++i, cdata+=8 ) { tmp0 = cdata[0]; tmp1 = cdata[1]; tmp2 = cdata[2]; tmp3 = cdata[3]; cdata[0] = cdata[7]; cdata[1] = cdata[6]; cdata[2] = cdata[5]; cdata[3] = cdata[4]; cdata[7] = tmp0; cdata[6] = tmp1; cdata[5] = tmp2; cdata[4] = tmp3; } } } atomvels = 0; if ( velnamdbinfile ) { int numatoms; int filen; int wrongendian; char lenbuf[4]; char tmpc; fseek(velnamdbinfile,0,SEEK_END); numatoms = (ftell(velnamdbinfile)-4)/24; if (numatoms < 1) { print_msg(v,""velnamdbin file is too short""); free(atomlist); free(atomcoords); return -1; } fseek(velnamdbinfile,0,SEEK_SET); fread(&filen, sizeof(int), 1, velnamdbinfile); wrongendian = 0; if (filen != numatoms) { wrongendian = 1; memcpy(lenbuf, (const char *)&filen, 4); tmpc = lenbuf[0]; lenbuf[0] = lenbuf[3]; lenbuf[3] = tmpc; tmpc = lenbuf[1]; lenbuf[1] = lenbuf[2]; lenbuf[2] = tmpc; memcpy((char *)&filen, lenbuf, 4); } if (filen != numatoms) { print_msg(v,""inconsistent atom count in namdbin file""); free(atomlist); free(atomcoords); return -1; } if (numatoms < natoms) { print_msg(v,""too few atoms in namdbin file""); free(atomlist); free(atomcoords); return -1; } if (numatoms > natoms) { print_msg(v,""too many atoms in namdbin file""); free(atomlist); free(atomcoords); return -1; } if (wrongendian) { print_msg(v,""namdbin file appears to be other-endian""); } atomvels = (double *)malloc(natoms * 3L * sizeof(double)); if (fread(atomvels, sizeof(double), 3L * natoms, velnamdbinfile) != (size_t)(3L * natoms)) { print_msg(v,""error reading data from namdbin file""); free(atomlist); free(atomcoords); free(atomvels); return -1; } if (wrongendian) { long i; char tmp0, tmp1, tmp2, tmp3; char *cdata = (char *) atomcoords; print_msg(v,""converting other-endian data from namdbin file""); for ( i=0; i<3L*natoms; ++i, cdata+=8 ) { tmp0 = cdata[0]; tmp1 = cdata[1]; tmp2 = cdata[2]; tmp3 = cdata[3]; cdata[0] = cdata[7]; cdata[1] = cdata[6]; cdata[2] = cdata[5]; cdata[3] = cdata[4]; cdata[7] = tmp0; cdata[6] = tmp1; cdata[5] = tmp2; cdata[4] = tmp3; } } } molatomlist = (topo_mol_atom_t **)malloc(natoms * sizeof(topo_mol_atom_t *)); i=0; while (i < natoms) { topo_mol_segment_t *seg; topo_mol_residue_t *res; topo_mol_atom_t *atomtmp; int firstatom, j; const char *resid, *segname; resid = atomlist[i].resid; segname = atomlist[i].segname; seg = get_segment(mol, segname); if (!seg) { print_msg(v,""ERROR: unable to get segment!""); break; } res = get_residue(seg, resid); if (!res) { char *buf; int len = strlen(resid) + strlen(segname); buf = (char *)malloc((50 + len)*sizeof(char)); sprintf(buf, ""Unable to add (duplicate?) residue %s:%s"", segname, resid); print_msg(v,buf); free(buf); break; } strcpy(res->name, atomlist[i].resname); strcpy(res->chain, """"); res->atoms = 0; firstatom = i; while (iarena, sizeof(topo_mol_atom_t)); atomtmp->bonds = 0; atomtmp->angles = 0; atomtmp->dihedrals = 0; atomtmp->impropers = 0; atomtmp->cmaps = 0; atomtmp->exclusions = 0; atomtmp->conformations = 0; strcpy(atomtmp->name, atomlist[i].name); strcpy(atomtmp->type, atomlist[i].atype); strcpy(atomtmp->element, atomlist[i].element); atomtmp->mass = atomlist[i].mass; atomtmp->charge = atomlist[i].charge; if (atomcoords) { atomtmp->x = atomcoords[i*3 ]; atomtmp->y = atomcoords[i*3 + 1]; atomtmp->z = atomcoords[i*3 + 2]; atomtmp->xyz_state = TOPO_MOL_XYZ_SET; } else { atomtmp->x = 0; atomtmp->y = 0; atomtmp->z = 0; atomtmp->xyz_state = TOPO_MOL_XYZ_VOID; } if (atomvels) { atomtmp->vx = atomvels[i*3 ]; atomtmp->vy = atomvels[i*3 + 1]; atomtmp->vz = atomvels[i*3 + 2]; } else { atomtmp->vx = 0; atomtmp->vy = 0; atomtmp->vz = 0; } atomtmp->partition = 0; atomtmp->copy = 0; atomtmp->atomid = 0; /* Save pointer to atom in my table so I can put in the bond information without having find the atom. */ molatomlist[i] = atomtmp; i++; } for (j=i-1; j >= firstatom; j--) { /* Add new atoms to head of linked list in reverse order, so that the linked list is in the order they appear in the psf file. */ atomtmp = molatomlist[j]; atomtmp->next = res->atoms; res->atoms = atomtmp; } } if (atomcoords) free(atomcoords); atomcoords = 0; if (atomvels) free(atomvels); atomvels = 0; /* Check to see if we broke out of the loop prematurely */ if (i != natoms) { free(atomlist); free(molatomlist); return -1; } /* Get the segment patch first,last and auto angles,dihedrals info from psf */ /* We have to rewind the file and read the info now since it has to be added to */ /* the existing segments which have just been read. */ filepos = ftell(file); rewind(file); extract_segment_extra_data(file, mol); fseek(file, filepos, SEEK_SET); if (extract_bonds(file, (charmmext ? 10 : 8), mol, natoms, molatomlist)) { print_msg(v,""Error processing bonds""); free(atomlist); free(molatomlist); return -1; } if (extract_angles(file, (charmmext ? 10 : 8), mol, natoms, molatomlist)) { print_msg(v,""Error processing angles""); free(atomlist); free(molatomlist); return -1; } if (extract_dihedrals(file, (charmmext ? 10 : 8), mol, natoms, molatomlist)) { print_msg(v,""Error processing dihedrals""); free(atomlist); free(molatomlist); return -1; } if (extract_impropers(file, (charmmext ? 10 : 8), mol, natoms, molatomlist)) { print_msg(v,""Error processing impropers""); free(atomlist); free(molatomlist); return -1; } if (extract_exclusions(file, (charmmext ? 10 : 8), mol, natoms, molatomlist)) { print_msg(v,""Error processing explicit exclusions""); free(atomlist); free(molatomlist); return -1; } switch (extract_cmaps(file, (charmmext ? 10 : 8), mol, natoms, molatomlist)) { case 0: break; case 1: print_msg(v,""psf file does not contain cross-terms""); break; default: print_msg(v,""Error processing cross-terms""); free(atomlist); free(molatomlist); return -1; } free(atomlist); free(molatomlist); return 0; } ","C" "Biophysics","Eigenstate/psfgen","src/charmm_file.c",".c","1794","72"," #include #include #include ""charmm_file.h"" /* In addition to stream from which to read data, takes token buffer, max number of tokens, string buffer, and length of buffer. Strips comments and ignores lines containing no tokens. Reports legend lines (starting with *) with null first token. Returns number of tokens read or zero for end of file. */ int charmm_get_tokens(char **tok, int toklen, char *sbuf, int sbuflen, char *lbuf, int *lineno, FILE *stream, int all_caps) { int ntok; int fullline; char *s; char c2[2]; ntok = 0; fullline = 0; /* Make compiler happy */ while ( ! ntok ) { s = fgets(sbuf, sbuflen, stream); if ( ! s ) return 0; /* EOF */ if ( lbuf ) { char *l; for ( s = sbuf, l = lbuf; *s; ++s, ++l ) { *l = *s; } *l = *s; } if ( lineno ) ++(*lineno); for ( s = sbuf; *s; ++s ) { fullline = ( *s == '\n' ); } if ( ! fullline ) do { s = fgets(c2, 2, stream); } while ( s && *s && *s != '\n' ); s = sbuf; while ( *s && isspace(*s) ) ++s; if ( *s == '*' ) { *s = 0; tok[ntok] = s; ++ntok; ++s; tok[ntok] = s; ++ntok; while ( s && *s && *s != '\n' ) ++s; *s = 0; break; } if ( *s == '!' || *s == '\n' ) *s = 0; while ( *s ) { if ( ntok < toklen ) { tok[ntok] = s; ++ntok; } /* in a token */ while ( *s && *s != '!' && *s != '\n' && ! isspace(*s) ) { if ( all_caps ) *s = toupper(*s); ++s; } if ( *s == '!' || *s == '\n' ) *s = 0; if ( ! *s ) break; /* no more tokens found on this line */ *s = 0; ++s; while ( *s && isspace(*s) ) ++s; if ( *s == '!' || *s == '\n' ) *s = 0; } } return ntok; } ","C" "Biophysics","Eigenstate/psfgen","src/extract_alias.h",".h","508","23"," #ifndef EXTRACT_ALIAS_H #define EXTRACT_ALIAS_H #include ""stringhash.h"" #define EXTRACT_ALIAS_FAIL -1 int extract_alias_residue_define(stringhash *h, const char *altres, const char *realres); int extract_alias_atom_define(stringhash *h, const char *resname, const char *altatom, const char *realatom); const char * extract_alias_residue_check(stringhash *h, const char *resname); const char * extract_alias_atom_check(stringhash *h, const char *resname, const char *atomname); #endif ","Unknown" "Biophysics","Eigenstate/psfgen","src/psfgen.h",".h","938","47"," /* psfgen.h * Defines set of data structures used in creation of molecule structures * Exported here so that new modules can be written to interface with psfgen */ #ifndef PSFGEN_H #define PSFGEN_H #include ""topo_defs.h"" #include ""topo_mol.h"" #include ""stringhash.h"" /* psfgen-specific data */ struct psfgen_data { int id, in_use, all_caps; topo_defs *defs; topo_mol *mol; stringhash *aliases; FILE* outstream; }; typedef struct psfgen_data psfgen_data; // Emit a compile error if int is not 32 bits //(void)sizeof(char[1 - 2*!!(sizeof(int) != 4)]); // Some utility functions char* strtoupper(const char *str, int all_caps) { char *s, *tmp; tmp = strdup(str); if ( all_caps ) { s=tmp; while ( *s ) { *s = toupper(*s); ++s; } } return tmp; } char* splitcolon(char *s) { if ( s ) { while ( *s && *s != ':' ) { ++s; } if ( *s ) *(s++) = 0; else s = 0; } return s; } #endif /* PSFGEN_H */ ","Unknown" "Biophysics","Eigenstate/psfgen","src/pdb_file_extract.c",".c","6234","198","#include #include #include #include ""pdb_file_extract.h"" #include ""pdb_file.h"" #include ""extract_alias.h"" #if defined(_MSC_VER) #define snprintf _snprintf #endif static void strtoupper(char *s) { while ( *s ) { *s = toupper(*s); ++s; } } int pdb_file_extract_residues(topo_mol *mol, FILE *file, stringhash *h, int all_caps, void *v,void (*print_msg)(void *,const char *)) { char record[PDB_RECORD_LENGTH+2]; int indx; float x,y,z,o,b; char name[8], resname[8], chain[8]; char segname[8], element[8], resid[8], insertion[8]; char oldresid[8]; const char *realres; char msg[128]; int rcount; rcount = 0; oldresid[0] = '\0'; do { if((indx = read_pdb_record(file, record)) == PDB_ATOM) { get_pdb_fields(record, name, resname, chain, segname, element, resid, insertion, &x, &y, &z, &o, &b); if ( strcmp(oldresid,resid) ) { strcpy(oldresid,resid); ++rcount; if ( all_caps ) strtoupper(resname); if ( all_caps ) strtoupper(chain); realres = extract_alias_residue_check(h,resname); if ( topo_mol_residue(mol,resid,realres,chain) ) { sprintf(msg,""ERROR: failed on residue %s from pdb file"",resname); print_msg(v,msg); } } } } while (indx != PDB_END && indx != PDB_EOF); sprintf(msg,""extracted %d residues from pdb file"",rcount); print_msg(v,msg); return 0; } int pdb_file_extract_coordinates(topo_mol *mol, FILE *file, FILE *namdbinfile, const char *segid, stringhash *h, int all_caps, void *v,void (*print_msg)(void *,const char *)) { char record[PDB_RECORD_LENGTH+2]; int indx; topo_mol_ident_t target; char msg[128]; unsigned int utmp; char stmp[128]; int numatoms = 0; int pdbnatoms = 0; double *atomcoords = 0; if ( namdbinfile ) { int filen; int wrongendian; fseek(namdbinfile,0,SEEK_END); numatoms = (ftell(namdbinfile)-4)/24; if (numatoms < 1) { print_msg(v,""namdbin file is too short""); return -1; } fseek(namdbinfile,0,SEEK_SET); fread(&filen, sizeof(int), 1, namdbinfile); wrongendian = 0; if (filen != numatoms) { char lenbuf[4]; char tmpc; wrongendian = 1; memcpy(lenbuf, (const char *)&filen, 4); tmpc = lenbuf[0]; lenbuf[0] = lenbuf[3]; lenbuf[3] = tmpc; tmpc = lenbuf[1]; lenbuf[1] = lenbuf[2]; lenbuf[2] = tmpc; memcpy((char *)&filen, lenbuf, 4); } if (filen != numatoms) { print_msg(v,""inconsistent atom count in namdbin file""); return -1; } if (wrongendian) { print_msg(v,""namdbin file appears to be other-endian""); } atomcoords = (double *)malloc(numatoms * 3 * sizeof(double)); if (fread(atomcoords, sizeof(double), 3 * numatoms, namdbinfile) != (size_t)(3 * numatoms)) { print_msg(v,""error reading data from namdbin file""); free(atomcoords); return -1; } if (wrongendian) { int i; char tmp0, tmp1, tmp2, tmp3; char *cdata = (char *) atomcoords; print_msg(v,""converting other-endian data from namdbin file""); for ( i=0; i<3*numatoms; ++i, cdata+=8 ) { tmp0 = cdata[0]; tmp1 = cdata[1]; tmp2 = cdata[2]; tmp3 = cdata[3]; cdata[0] = cdata[7]; cdata[1] = cdata[6]; cdata[2] = cdata[5]; cdata[3] = cdata[4]; cdata[7] = tmp0; cdata[6] = tmp1; cdata[5] = tmp2; cdata[4] = tmp3; } } } target.segid = segid; pdbnatoms = 0; do { if((indx = read_pdb_record(file, record)) == PDB_ATOM) { float xf,yf,zf,o,b; double x,y,z; char name[8], altname[8], resname[8], chain[8]; char segname[8], element[8], resid[8], insertion[8]; int found; get_pdb_fields(record, name, resname, chain, segname, element, resid, insertion, &xf, &yf, &zf, &o, &b); x = xf; y=yf; z=zf; if ( namdbinfile ) { if (pdbnatoms >= numatoms) { print_msg(v,""too few atoms in namdbin file""); free(atomcoords); return -1; } x = atomcoords[pdbnatoms*3 ]; y = atomcoords[pdbnatoms*3 + 1]; z = atomcoords[pdbnatoms*3 + 2]; ++pdbnatoms; } target.resid = resid; if ( all_caps ) strtoupper(resname); if ( all_caps ) strtoupper(name); if ( all_caps ) strtoupper(chain); target.aname = extract_alias_atom_check(h,resname,name); /* Use PDB segid if no segid given */ if (!segid) { target.segid = segname; } found = ! topo_mol_set_xyz(mol,&target,x,y,z); /* Try reversing order so 1HE2 in pdb matches HE21 in topology */ if ( ! found && sscanf(name,""%u%s"",&utmp,stmp) == 2 ) { snprintf(altname,8,""%s%u"",stmp,utmp); target.aname = altname; if ( ! topo_mol_set_xyz(mol,&target,x,y,z) ) { found = 1; /* too much information sprintf(msg,""Warning: changed atom name for atom %s\t %s:%s\t %s to %s"",name,resname,resid,segid ? segid : segname,altname); print_msg(v,msg); */ } } if ( ! found ) { sprintf(msg,""Warning: failed to set coordinate for atom %s\t %s:%s\t %s"",name,resname,resid,segid ? segid : segname); print_msg(v,msg); } else { /* only try element and chain if coordinates succeeds */ if ( strlen(element) && topo_mol_set_element(mol,&target,element,0) ) { sprintf(msg,""Warning: failed to set element for atom %s\t %s:%s\t %s"",name,resname,resid,segid ? segid : segname); print_msg(v,msg); } if ( strlen(chain) && topo_mol_set_chain(mol,&target,chain,0) ) { sprintf(msg,""Warning: failed to set chain for atom %s\t %s:%s\t %s"",name,resname,resid,segid ? segid : segname); print_msg(v,msg); } } } } while (indx != PDB_END && indx != PDB_EOF); if ( namdbinfile ) { free(atomcoords); if (numatoms > pdbnatoms) { print_msg(v,""too many atoms in namdbin file""); return -1; } } return 0; } ","C" "Biophysics","Eigenstate/psfgen","src/psf_file_extract.h",".h","289","13"," #ifndef PSF_FILE_READ_H #define PSF_FILE_READ_H #include #include ""topo_mol.h"" int psf_file_extract(topo_mol *mol, FILE *file, FILE *pdbfile, FILE *namdbinfile, FILE *velnamdbinfile, void *, void (*print_msg)(void *, const char *)); #endif ","Unknown" "Biophysics","Eigenstate/psfgen","src/memarena.c",".c","1754","87"," #include #include ""memarena.h"" struct memarena_stack_t; typedef struct memarena_stack_t memarena_stack_t; struct memarena_stack_t { memarena_stack_t * next; void * data; }; struct memarena { memarena_stack_t * stack; int newblocksize; int size, used; }; memarena * memarena_create(void) { memarena * a; if ( (a = (memarena*) malloc(sizeof(memarena))) ) { a->stack = 0; a->newblocksize = 128000; a->size = 0; a->used = 0; } return a; } void memarena_destroy(memarena *a) { memarena_stack_t * s; if ( ! a ) return; while ( a->stack ) { s = a->stack; a->stack = s->next; free((void*)s->data); free((void*)s); } free((void*)a); } void memarena_blocksize(memarena *a, int blocksize) { a->newblocksize = blocksize; } void * memarena_alloc(memarena *a, int size) { memarena_stack_t * s; void * m; if ( size > a->newblocksize / 2 ) { s = (memarena_stack_t*) malloc(sizeof(memarena_stack_t)); if ( ! s ) return 0; s->data = malloc(size); if ( ! s->data ) { free((void*)s); return 0; } if ( a->stack ) { s->next = a->stack->next; a->stack->next = s; } else { s->next = 0; a->stack = s; } return s->data; } else if ( a->used + size > a->size ) { s = (memarena_stack_t*) malloc(sizeof(memarena_stack_t)); if ( ! s ) return 0; s->next = a->stack; s->data = malloc(a->newblocksize); if ( ! s->data ) { free((void*)s); return 0; } a->stack = s; a->size = a->newblocksize; a->used = 0; } m = (void*) ( (char*) a->stack->data + a->used ); a->used += size; return m; } void * memarena_alloc_aligned(memarena *a, int size, int alignment) { return 0; } ","C" "Biophysics","Eigenstate/psfgen","src/hasharray.h",".h","529","25"," #ifndef HASHARRAY_H #define HASHARRAY_H struct hasharray; typedef struct hasharray hasharray; hasharray * hasharray_create(void **itemarray, int itemsize); int hasharray_clear(hasharray *a); void hasharray_destroy(hasharray *a); int hasharray_reinsert(hasharray *a, const char *key, int pos); int hasharray_insert(hasharray *a, const char *key); int hasharray_delete(hasharray *a, const char *key); #define HASHARRAY_FAIL -1 int hasharray_index(hasharray *a, const char *key); int hasharray_count(hasharray *a); #endif ","Unknown" "Biophysics","Eigenstate/psfgen","src/topo_mol_output.c",".c","18657","589"," #include #include #include ""topo_mol_output.h"" #include ""topo_mol_struct.h"" #include ""pdb_file.h"" int topo_mol_write_pdb(topo_mol *mol, FILE *file, void *v, void (*print_msg)(void *, const char *)) { char buf[128], insertion[2]; int iseg,nseg,ires,nres,atomid,resid; int has_guessed_atoms = 0; double x,y,z,o,b; topo_mol_segment_t *seg; topo_mol_residue_t *res; topo_mol_atom_t *atom; if ( ! mol ) return -1; write_pdb_remark(file,""original generated coordinate pdb file""); atomid = 0; nseg = hasharray_count(mol->segment_hash); for ( iseg=0; isegsegment_array[iseg]; if (! seg) continue; if ( strlen(seg->segid) > 4 ) { sprintf(buf, ""warning: truncating segid %s to 4 characters allowed by pdb format"", seg->segid); print_msg(v,buf); } nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { /* Paranoid: make sure x,y,z,o are set. */ x = y = z = 0.0; o = -1.0; ++atomid; switch ( atom->xyz_state ) { case TOPO_MOL_XYZ_SET: x = atom->x; y = atom->y; z = atom->z; o = 1.0; break; case TOPO_MOL_XYZ_GUESS: case TOPO_MOL_XYZ_BADGUESS: x = atom->x; y = atom->y; z = atom->z; o = 0.0; has_guessed_atoms = 1; break; default: print_msg(v,""ERROR: Internal error, atom has invalid state.""); print_msg(v,""ERROR: Treating as void.""); /* Yes, fall through */ case TOPO_MOL_XYZ_VOID: x = y = z = 0.0; o = -1.0; break; } b = atom->partition; insertion[0] = 0; insertion[1] = 0; sscanf(res->resid, ""%d%c"", &resid, insertion); write_pdb_atom(file,atomid,atom->name,res->name,resid,insertion, (float)x,(float)y,(float)z,(float)o,(float)b,res->chain, seg->segid,atom->element); } } } write_pdb_end(file); if (has_guessed_atoms) { print_msg(v, ""Info: Atoms with guessed coordinates will have occupancy of 0.0.""); } return 0; } int topo_mol_write_namdbin(topo_mol *mol, FILE *file, FILE *velfile, void *v, void (*print_msg)(void *, const char *)) { int iseg,nseg,ires,nres; int has_void_atoms = 0; int numatoms; double x,y,z,xyz[3]; topo_mol_segment_t *seg; topo_mol_residue_t *res; topo_mol_atom_t *atom; if ( ! mol ) return -1; numatoms = 0; nseg = hasharray_count(mol->segment_hash); for ( iseg=0; isegsegment_array[iseg]; if (! seg) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { ++numatoms; } } } if ( fwrite(&numatoms, sizeof(int), 1, file) != 1 ) { print_msg(v, ""error writing namdbin file""); return -2; } if ( velfile ) { if ( fwrite(&numatoms, sizeof(int), 1, velfile) != 1 ) { print_msg(v, ""error writing velnamdbin file""); return -4; } } for ( iseg=0; isegsegment_array[iseg]; if (! seg) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { /* Paranoid: make sure x,y,z are set. */ x = y = z = 0.0; switch ( atom->xyz_state ) { case TOPO_MOL_XYZ_SET: case TOPO_MOL_XYZ_GUESS: case TOPO_MOL_XYZ_BADGUESS: x = atom->x; y = atom->y; z = atom->z; break; default: print_msg(v,""ERROR: Internal error, atom has invalid state.""); print_msg(v,""ERROR: Treating as void.""); /* Yes, fall through */ case TOPO_MOL_XYZ_VOID: x = y = z = 0.0; has_void_atoms = 1; break; } xyz[0] = x; xyz[1] = y; xyz[2] = z; if ( fwrite(xyz, sizeof(double), 3, file) != 3 ) { print_msg(v, ""error writing namdbin file""); return -3; } if ( velfile ) { xyz[0] = atom->vx; xyz[1] = atom->vy; xyz[2] = atom->vz; if ( fwrite(xyz, sizeof(double), 3, velfile) != 3 ) { print_msg(v, ""error writing velnamdbin file""); return -5; } } } } } if (has_void_atoms) { print_msg(v, ""Warning: Atoms with unknown coordinates written at 0. 0. 0.""); } return 0; } int topo_mol_write_psf(topo_mol *mol, FILE *file, int charmmfmt, int nocmap, int nopatches, void *v, void (*print_msg)(void *, const char *)) { char buf[128]; int iseg,nseg,ires,nres,atomid; int namdfmt, charmmext; topo_mol_segment_t *seg; topo_mol_residue_t *res; topo_mol_atom_t *atom; topo_mol_bond_t *bond; int nbonds; topo_mol_angle_t *angl; int nangls; topo_mol_dihedral_t *dihe; int ndihes; topo_mol_improper_t *impr; int nimprs; topo_mol_cmap_t *cmap; int ncmaps; topo_mol_exclusion_t *excl; int nexcls; int numinline; int npres,ipres,ntopo,itopo; topo_defs_topofile_t *topo; topo_mol_patch_t *patch; topo_mol_patchres_t *patchres; char defpatch[10]; fpos_t ntitle_pos, save_pos; char ntitle_fmt[128]; int ntitle_count; strcpy(defpatch,""""); if ( ! mol ) return -1; namdfmt = 0; charmmext = 0; atomid = 0; nbonds = 0; nangls = 0; ndihes = 0; nimprs = 0; ncmaps = 0; nexcls = 0; nseg = hasharray_count(mol->segment_hash); for ( iseg=0; isegsegment_array[iseg]; if (! seg) continue; if ( strlen(seg->segid) > 4 ) { charmmext = 1; } nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); if (strlen(res->resid) > 4) { charmmext = 1; } for ( atom = res->atoms; atom; atom = atom->next ) { atom->atomid = ++atomid; if (strlen(atom->name) > 4) { charmmext = 1; } if ((! charmmfmt) && (strlen(atom->type) > 4)) { charmmext = 1; } if ((! charmmfmt) && (strlen(atom->type) > 6)) { namdfmt = 1; } for ( bond = atom->bonds; bond; bond = topo_mol_bond_next(bond,atom) ) { if ( bond->atom[0] == atom && ! bond->del ) { ++nbonds; } } for ( angl = atom->angles; angl; angl = topo_mol_angle_next(angl,atom) ) { if ( angl->atom[0] == atom && ! angl->del ) { ++nangls; } } for ( dihe = atom->dihedrals; dihe; dihe = topo_mol_dihedral_next(dihe,atom) ) { if ( dihe->atom[0] == atom && ! dihe->del ) { ++ndihes; } } for ( impr = atom->impropers; impr; impr = topo_mol_improper_next(impr,atom) ) { if ( impr->atom[0] == atom && ! impr->del ) { ++nimprs; } } for ( cmap = atom->cmaps; cmap; cmap = topo_mol_cmap_next(cmap,atom) ) { if ( cmap->atom[0] == atom && ! cmap->del ) { ++ncmaps; } } for ( excl = atom->exclusions; excl; excl = topo_mol_exclusion_next(excl,atom) ) { if ( excl->atom[0] == atom && ! excl->del ) { ++nexcls; } } } } } sprintf(buf,""total of %d atoms"",atomid); print_msg(v,buf); sprintf(buf,""total of %d bonds"",nbonds); print_msg(v,buf); sprintf(buf,""total of %d angles"",nangls); print_msg(v,buf); sprintf(buf,""total of %d dihedrals"",ndihes); print_msg(v,buf); sprintf(buf,""total of %d impropers"",nimprs); print_msg(v,buf); sprintf(buf,""total of %d explicit exclusions"",nexcls); print_msg(v,buf); if ( namdfmt ) { charmmext = 0; } else if ( atomid > 9999999 ) { charmmext = 1; } if ( namdfmt ) { print_msg(v,""Structure requires space-delimited NAMD PSF format""); } else if ( charmmext ) { print_msg(v,""Structure requires EXTended PSF format""); } ntitle_fmt[0] = '\0'; strcat(ntitle_fmt, ""PSF""); if ( namdfmt ) strcat(ntitle_fmt, "" NAMD""); if ( charmmext ) strcat(ntitle_fmt, "" EXT""); if ( nocmap ) { sprintf(buf,""total of %d cross-terms (not written to file)"",ncmaps); } else { sprintf(buf,""total of %d cross-terms"",ncmaps); if ( ncmaps ) { strcat(ntitle_fmt, "" CMAP""); } else { nocmap = 1; } } print_msg(v,buf); strcat(ntitle_fmt, ""\n\n%8d !NTITLE\n""); fgetpos(file,&ntitle_pos); fprintf(file,ntitle_fmt,1); ntitle_count = 1; if ( charmmfmt ) fprintf(file,"" REMARKS %s\n"",""original generated structure charmm psf file""); else fprintf(file,"" REMARKS %s\n"",""original generated structure x-plor psf file""); if (mol->npatch) { ntitle_count++; fprintf(file,"" REMARKS %i patches were applied to the molecule.\n"", mol->npatch); } ntopo = hasharray_count(mol->defs->topo_hash); for ( itopo=0; itopodefs->topo_array[itopo]); ntitle_count++; fprintf(file,"" REMARKS topology %s \n"", topo->filename); } nseg = hasharray_count(mol->segment_hash); for ( iseg=0; isegsegment_array[iseg]; if (! seg) continue; strcpy(angles,""none""); strcpy(diheds,""""); if (seg->auto_angles) strcpy(angles,""angles""); if (seg->auto_dihedrals) strcpy(diheds,""dihedrals""); ntitle_count++; fprintf(file,"" REMARKS segment %s { first %s; last %s; auto %s %s }\n"", seg->segid, seg->pfirst, seg->plast, angles, diheds); } if (!nopatches) { for ( patch = mol->patches; patch; patch = patch->next ) { strcpy(defpatch,""""); if (patch->deflt) strcpy(defpatch,""default""); npres = patch->npres; ipres = 0; for ( patchres = patch->patchresids; patchres; patchres = patchres->next ) { /* Test the existence of segid:resid for the patch */ if (!topo_mol_validate_patchres(mol,patch->pname,patchres->segid, patchres->resid)) { break; } } if ( patchres ) continue; for ( patchres = patch->patchresids; patchres; patchres = patchres->next ) { if (ipres==0) { ntitle_count++; fprintf(file,"" REMARKS %spatch %s "", defpatch, patch->pname); } if (ipres>0 && !ipres%6) { ntitle_count++; fprintf(file,""\n REMARKS patch ---- ""); } fprintf(file,""%s:%s "", patchres->segid, patchres->resid); if (ipres==npres-1) fprintf(file,""\n""); ipres++; } } } fprintf(file,""\n""); fgetpos(file,&save_pos); fsetpos(file,&ntitle_pos); fprintf(file,ntitle_fmt,ntitle_count); fsetpos(file,&save_pos); fprintf(file,""%8d !NATOM\n"",atomid); for ( iseg=0; isegsegment_array[iseg]; if (! seg) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); strncpy(resid,res->resid,9); resid[ charmmext ? 8 : 4 ] = '\0'; if ( charmmfmt ) for ( atom = res->atoms; atom; atom = atom->next ) { int idef,typeid; idef = hasharray_index(mol->defs->type_hash,atom->type); if ( idef == HASHARRAY_FAIL ) { sprintf(buf,""unknown atom type %s"",atom->type); print_msg(v,buf); return -3; } typeid = mol->defs->type_array[idef].id; fprintf(file, ( charmmext ? ""%10d %-8s %-8s %-8s %-8s %4d %10.6f %10.4f %10d\n"" : ""%8d %-4s %-4s %-4s %-4s %4d %10.6f %10.4f %10d\n"" ), atom->atomid, seg->segid,resid,res->name, atom->name,typeid,atom->charge,atom->mass,0); } else for ( atom = res->atoms; atom; atom = atom->next ) { fprintf(file, ( charmmext ? ""%10d %-8s %-8s %-8s %-8s %-6s %10.6f %10.4f %10d\n"" : ""%8d %-4s %-4s %-4s %-4s %-4s %10.6f %10.4f %10d\n"" ), atom->atomid, seg->segid,resid,res->name, atom->name,atom->type,atom->charge,atom->mass,0); } } } fprintf(file,""\n""); fprintf(file,""%8d !NBOND: bonds\n"",nbonds); numinline = 0; for ( iseg=0; isegsegment_array[iseg]; if (! seg) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { for ( bond = atom->bonds; bond; bond = topo_mol_bond_next(bond,atom) ) { if ( bond->atom[0] == atom && ! bond->del ) { if ( numinline == 4 ) { fprintf(file,""\n""); numinline = 0; } fprintf(file, ( charmmext ? "" %9d %9d"" : "" %7d %7d""), atom->atomid,bond->atom[1]->atomid); ++numinline; } } } } } fprintf(file,""\n\n""); fprintf(file,""%8d !NTHETA: angles\n"",nangls); numinline = 0; for ( iseg=0; isegsegment_array[iseg]; if (! seg) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { for ( angl = atom->angles; angl; angl = topo_mol_angle_next(angl,atom) ) { if ( angl->atom[0] == atom && ! angl->del ) { if ( numinline == 3 ) { fprintf(file,""\n""); numinline = 0; } fprintf(file, ( charmmext ? "" %9d %9d %9d"" : "" %7d %7d %7d""),atom->atomid, angl->atom[1]->atomid,angl->atom[2]->atomid); ++numinline; } } } } } fprintf(file,""\n\n""); fprintf(file,""%8d !NPHI: dihedrals\n"",ndihes); numinline = 0; for ( iseg=0; isegsegment_array[iseg]; if (! seg) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { for ( dihe = atom->dihedrals; dihe; dihe = topo_mol_dihedral_next(dihe,atom) ) { if ( dihe->atom[0] == atom && ! dihe->del ) { if ( numinline == 2 ) { fprintf(file,""\n""); numinline = 0; } fprintf(file, ( charmmext ? "" %9d %9d %9d %9d"" : "" %7d %7d %7d %7d""),atom->atomid, dihe->atom[1]->atomid,dihe->atom[2]->atomid, dihe->atom[3]->atomid); ++numinline; } } } } } fprintf(file,""\n\n""); fprintf(file,""%8d !NIMPHI: impropers\n"",nimprs); numinline = 0; for ( iseg=0; isegsegment_array[iseg]; if (! seg) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { for ( impr = atom->impropers; impr; impr = topo_mol_improper_next(impr,atom) ) { if ( impr->atom[0] == atom && ! impr->del ) { if ( numinline == 2 ) { fprintf(file,""\n""); numinline = 0; } fprintf(file, ( charmmext ? "" %9d %9d %9d %9d"" : "" %7d %7d %7d %7d""),atom->atomid, impr->atom[1]->atomid,impr->atom[2]->atomid, impr->atom[3]->atomid); ++numinline; } } } } } fprintf(file,""\n\n""); fprintf(file,""%8d !NDON: donors\n\n\n"",0); fprintf(file,""%8d !NACC: acceptors\n\n\n"",0); fprintf(file,""%8d !NNB\n"",nexcls); /* Print atom numbers for exclusions */ numinline = 0; for ( iseg=0; isegsegment_array[iseg]; if (! seg) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { for ( excl = atom->exclusions; excl; excl = topo_mol_exclusion_next(excl,atom) ) { if ( excl->atom[0] == atom && ! excl->del ) { if ( numinline == 8 ) { fprintf(file,""\n""); numinline = 0; } fprintf(file,(charmmext?"" %9d"":"" %7d""),excl->atom[1]->atomid); ++numinline; } } } } } fprintf(file,""\n""); /* Print exclusion indices for every atom */ nexcls = 0; numinline = 0; for ( iseg=0; isegsegment_array[iseg]; if (! seg) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { for ( excl = atom->exclusions; excl; excl = topo_mol_exclusion_next(excl,atom) ) { if ( excl->atom[0] == atom && ! excl->del ) { ++nexcls; } } if ( numinline == 8 ) { fprintf(file,""\n""); numinline = 0; } fprintf(file,(charmmext?"" %9d"":"" %7d""),nexcls); ++numinline; } } } fprintf(file,""\n\n""); fprintf(file,(charmmext?""%8d %7d !NGRP\n%10d%10d%10d\n\n"":""%8d %7d !NGRP\n%8d%8d%8d\n\n""),1,0,0,0,0); if ( ! nocmap ) { fprintf(file,""%8d !NCRTERM: cross-terms\n"",ncmaps); for ( iseg=0; isegsegment_array[iseg]; if (! seg) continue; nres = hasharray_count(seg->residue_hash); for ( ires=0; iresresidue_array[ires]); for ( atom = res->atoms; atom; atom = atom->next ) { for ( cmap = atom->cmaps; cmap; cmap = topo_mol_cmap_next(cmap,atom) ) { if ( cmap->atom[0] == atom && ! cmap->del ) { fprintf(file,( charmmext ? "" %9d %9d %9d %9d %9d %9d %9d %9d\n"" : "" %7d %7d %7d %7d %7d %7d %7d %7d\n""),atom->atomid, cmap->atom[1]->atomid,cmap->atom[2]->atomid, cmap->atom[3]->atomid,cmap->atom[4]->atomid, cmap->atom[5]->atomid,cmap->atom[6]->atomid, cmap->atom[7]->atomid); } } } } } fprintf(file,""\n""); } return 0; } ","C" "Biophysics","Eigenstate/psfgen","src/topo_defs_struct.h",".h","3262","149"," #ifndef TOPO_DEFS_STRUCT_H #define TOPO_DEFS_STRUCT_H #include ""memarena.h"" #include ""hasharray.h"" #include ""topo_defs.h"" #define NAMEMAXLEN 10 #define NAMETOOLONG(X) ( strlen(X) >= NAMEMAXLEN ) typedef struct topo_defs_type_t { char name[NAMEMAXLEN]; char element[NAMEMAXLEN]; int id; double mass; } topo_defs_type_t; typedef struct topo_defs_atom_t { struct topo_defs_atom_t *next; char name[NAMEMAXLEN]; char type[NAMEMAXLEN]; double charge; int res, rel; int del; } topo_defs_atom_t; typedef struct topo_defs_bond_t { struct topo_defs_bond_t *next; char atom1[NAMEMAXLEN]; char atom2[NAMEMAXLEN]; int res1, rel1; int res2, rel2; int del; } topo_defs_bond_t; typedef struct topo_defs_angle_t { struct topo_defs_angle_t *next; char atom1[NAMEMAXLEN]; char atom2[NAMEMAXLEN]; char atom3[NAMEMAXLEN]; int res1, rel1; int res2, rel2; int res3, rel3; int del; } topo_defs_angle_t; typedef struct topo_defs_dihedral_t { struct topo_defs_dihedral_t *next; char atom1[NAMEMAXLEN]; char atom2[NAMEMAXLEN]; char atom3[NAMEMAXLEN]; char atom4[NAMEMAXLEN]; int res1, rel1; int res2, rel2; int res3, rel3; int res4, rel4; int del; } topo_defs_dihedral_t; typedef struct topo_defs_improper_t { struct topo_defs_improper_t *next; char atom1[NAMEMAXLEN]; char atom2[NAMEMAXLEN]; char atom3[NAMEMAXLEN]; char atom4[NAMEMAXLEN]; int res1, rel1; int res2, rel2; int res3, rel3; int res4, rel4; int del; } topo_defs_improper_t; typedef struct topo_defs_cmap_t { struct topo_defs_cmap_t *next; char atoml[8][NAMEMAXLEN]; int resl[8], rell[8]; int del; } topo_defs_cmap_t; typedef struct topo_defs_exclusion_t { struct topo_defs_exclusion_t *next; char atom1[NAMEMAXLEN]; char atom2[NAMEMAXLEN]; int res1, rel1; int res2, rel2; int del; } topo_defs_exclusion_t; typedef struct topo_defs_conformation_t { struct topo_defs_conformation_t *next; char atom1[NAMEMAXLEN]; char atom2[NAMEMAXLEN]; char atom3[NAMEMAXLEN]; char atom4[NAMEMAXLEN]; int res1, rel1; int res2, rel2; int res3, rel3; int res4, rel4; int del; int improper; double dist12, angle123, dihedral, angle234, dist34; } topo_defs_conformation_t; typedef struct topo_defs_residue_t { char name[NAMEMAXLEN]; int patch; topo_defs_atom_t *atoms; topo_defs_bond_t *bonds; topo_defs_angle_t *angles; topo_defs_dihedral_t *dihedrals; topo_defs_improper_t *impropers; topo_defs_cmap_t *cmaps; topo_defs_exclusion_t *exclusions; topo_defs_conformation_t *conformations; char pfirst[NAMEMAXLEN]; char plast[NAMEMAXLEN]; } topo_defs_residue_t; typedef struct topo_defs_topofile_t { /* struct topo_defs_topofile_t *next; */ char filename[256]; } topo_defs_topofile_t; struct topo_defs { void *newerror_handler_data; void (*newerror_handler)(void *, const char *); int auto_angles; int auto_dihedrals; int cmaps_present; char pfirst[NAMEMAXLEN]; char plast[NAMEMAXLEN]; topo_defs_topofile_t *topo_array; hasharray *topo_hash; topo_defs_type_t *type_array; hasharray *type_hash; topo_defs_residue_t *residue_array; hasharray *residue_hash; topo_defs_residue_t *buildres; int buildres_no_errors; memarena *arena; }; #endif ","Unknown" "Biophysics","Eigenstate/psfgen","src/pdb_file_extract.h",".h","538","18"," #ifndef PDB_FILE_EXTRACT_H #define PDB_FILE_EXTRACT_H #include #include ""stringhash.h"" #include ""topo_mol.h"" int pdb_file_extract_residues(topo_mol *mol, FILE *file, stringhash *h, int all_caps, void *, void (*print_msg)(void *,const char *)); int pdb_file_extract_coordinates(topo_mol *mol, FILE *file, FILE *namdbinfile, const char *segid, stringhash *h, int all_caps, void *,void (*print_msg)(void *,const char *)); #endif ","Unknown" "Biophysics","Eigenstate/psfgen","src/topo_defs.h",".h","2648","76"," #ifndef TOPO_DEFS_H #define TOPO_DEFS_H struct topo_defs; typedef struct topo_defs topo_defs; topo_defs * topo_defs_create(void); void topo_defs_destroy(topo_defs *defs); void topo_defs_error_handler(topo_defs *defs, void *, void (*print_msg)(void *, const char *)); void topo_defs_auto_angles(topo_defs *defs, int autogen); void topo_defs_auto_dihedrals(topo_defs *defs, int autogen); int topo_defs_type(topo_defs *defs, const char *atype, const char *element, double mass, int id); int topo_defs_residue(topo_defs *defs, const char *rname, int patch); int topo_defs_end(topo_defs *defs); int topo_defs_atom(topo_defs *defs, const char *rname, int del, const char *aname, int ares, int arel, const char *atype, double charge); int topo_defs_bond(topo_defs *defs, const char *rname, int del, const char *a1name, int a1res, int a1rel, const char *a2name, int a2res, int a2rel); int topo_defs_angle(topo_defs *defs, const char *rname, int del, const char *a1name, int a1res, int a1rel, const char *a2name, int a2res, int a2rel, const char *a3name, int a3res, int a3rel); int topo_defs_dihedral(topo_defs *defs, const char *rname, int del, const char *a1name, int a1res, int a1rel, const char *a2name, int a2res, int a2rel, const char *a3name, int a3res, int a3rel, const char *a4name, int a4res, int a4rel); int topo_defs_improper(topo_defs *defs, const char *rname, int del, const char *a1name, int a1res, int a1rel, const char *a2name, int a2res, int a2rel, const char *a3name, int a3res, int a3rel, const char *a4name, int a4res, int a4rel); int topo_defs_cmap(topo_defs *defs, const char *rname, int del, const char* const anamel[8], const int aresl[8], const int arell[8]); int topo_defs_exclusion(topo_defs *defs, const char *rname, int del, const char *a1name, int a1res, int a1rel, const char *a2name, int a2res, int a2rel); int topo_defs_conformation(topo_defs *defs, const char *rname, int del, const char *a1name, int a1res, int a1rel, const char *a2name, int a2res, int a2rel, const char *a3name, int a3res, int a3rel, const char *a4name, int a4res, int a4rel, double dist12, double angle123, double dihedral, int improper, double angle234, double dist34); int topo_defs_default_patching_first(topo_defs *defs, const char *pname); int topo_defs_default_patching_last(topo_defs *defs, const char *pname); int topo_defs_patching_first(topo_defs *defs, const char *rname, const char *pname); int topo_defs_patching_last(topo_defs *defs, const char *rname, const char *pname); int topo_defs_add_topofile(topo_defs *defs, const char *filename); #endif ","Unknown" "Biophysics","Eigenstate/psfgen","psfgen/__init__.py",".py","76","5","from .psfgen import PsfGen __version__ = ""1.0.5"" __author__ = ""Robin Betz"" ","Python" "Biophysics","Eigenstate/psfgen","psfgen/psfgen.py",".py","25868","725"," import _psfgen import sys # Definitions for psf file types CHARMM=""charmm"" XPLOR=""x-plor"" # Definitions for auto arguments AUTO_ANGLES, AUTO_DIHEDRALS, AUTO_NONE = ""angles"", ""dihedrals"", ""none"" class PsfGen(object): """""" A Psf generator object. Represents the state of a single molecular system, with its own set of loaded topologies, residue and/or atom aliases, segments, and coordinates. """""" def __init__(self, output=sys.stdout, case_sensitive=False): """""" Creates a PsfGen object. Args: outstream (str or stream object): Where to write output. Defaults to stdout. Must have fileno() attribute, or if a string, file will be opened. case_sensitive (bool): Whether or not residue names and definitions are considered to be case sensitive """""" if isinstance(output, str): self.output = open(output, 'wb') elif hasattr(output, ""fileno""): self.output = output else: raise ValueError(""output argument must be a str or open file"") self._fileno = self.output.fileno() self._data = _psfgen.init_mol(outfd=self._fileno) self._read_topos = False # Cannot change case sensitivity if true self._allcaps = not case_sensitive _psfgen.set_allcaps(psfstate=self._data, allcaps=not case_sensitive) #=========================================================================== def __del__(self): if not self.output.closed and self.output is not sys.stdout: self.output.close() _psfgen.del_mol(self._data); #=========================================================================== # This property decorator lets the case sensitivity be a boolean attribute # of the PsfGen instance that calls the C code to update the internal # psfgen_data* object when set. @property def case_sensitive(self): """""" Determines whether or not residue and other names have case sensitivity. Defaults to False. Can only be changed before reading in any topology files. """""" return not self._allcaps @case_sensitive.setter def case_sensitive(self, value): if not isinstance(value, bool): raise ValueError(""case_sensitive must be a boolean value"") if self._read_topos: raise ValueError(""Cannot change case sensitivity value after "" ""reading in topology files"") _psfgen.set_allcaps(psfstate=self._data, allcaps=not value) self._allcaps = value @case_sensitive.deleter def case_sensitive(self): del self._allcaps #=========================================================================== def read_topology(self, filename): """""" Parses a charmm format topology file into current library. Args: filename (str): File to parse Raises: FileNotFoundError: If the file cannot be opened for reading ValueError: If an error occurs during parsing """""" _psfgen.parse_topology(psfstate=self._data, filename=filename) self._read_topos = True #=========================================================================== def alias_residue(self, top_resname, pdb_resname): """""" Set a correspondence between a residue name in a PDB file and in the defined topologies. The topology residue names should be treated as the canonical set here. Args: top_resname (str): Resname in topology file pdb_resname (str): Equivalent resname in PDB files """""" _psfgen.alias(psfstate=self._data, type=""residue"", newname=top_resname, name=pdb_resname) #=========================================================================== def alias_atom(self, resname, top_atomname, pdb_atomname): """""" Set a correspondence between an atom name in a specific residue in a PDB file and in the defined topologies. Args: resname (str): Residue name in which to make alias top_atomname (str): Atom name in the topology file pdb_atomname (str): Equivalent atom name in PDB file """""" _psfgen.alias(psfstate=self._data, type=""atom"", resname=resname, newname=top_atomname, name=pdb_atomname) #=========================================================================== def get_segids(self): """""" Obtain all the currently defined segment IDs. Returns: (list of str): All defined segids in current molecule """""" return _psfgen.query_segment(psfstate=self._data, task=""segids"") #=========================================================================== def get_resids(self, segid): """""" Obtain all currently defined resids in a given segment Args: segid (str): Segment ID to query Returns: (list of str): All defined resids in given segment """""" return _psfgen.query_segment(psfstate=self._data, task=""resids"", segid=segid) #=========================================================================== def get_patches(self, list_defaults=True, list_all=False): """""" Obtain information about available or applied patches in the current system state. Args: list_defaults (bool): If True, default patches will be listed too. Otherwise only explicitly applied patches will be shown. Defaults to True list_all (bool): List all available patches, not just applied ones. For psfgen internal reasons, ""NONE"", ""None"", and ""none"" will appear in this list. Returns: (list of 3-tuple): (patchname, segid, resid) of all applied patches """""" if list_all: return _psfgen.query_system(self._data, task=""patches"") return _psfgen.get_patches(self._data, listall=list_defaults) #=========================================================================== def get_resname(self, segid, resid): """""" Obtains the residue name given a resid and segment Args: segid (str): Segment ID to query resid (str or int): Residue ID to query Returns: (str): Residue name """""" # Handle integer resid, just turn it into a string if isinstance(resid, int): resid = str(resid) return _psfgen.query_segment(psfstate=self._data, task=""residue"", segid=segid, resid=resid) #=========================================================================== def get_atom_names(self, segid, resid): """""" Obtains atom names in a given residue Args: segid (str): Segment ID to query resid (str or int): Residue ID to query Returns: (list of str): Atom names in residue """""" if isinstance(resid, int): resid = str(resid) return _psfgen.query_atoms(psfstate=self._data, segid=segid, resid=resid, task=""name"") #=========================================================================== def get_masses(self, segid, resid): """""" Obtains atom masses in a given residue Args: segid (str): Segment ID to query resid (str or int): Residue ID to query Returns: (list of float): Atom masses in residue """""" if isinstance(resid, int): resid = str(resid) return _psfgen.query_atoms(psfstate=self._data, segid=segid, resid=resid, task=""mass"") #=========================================================================== def get_charges(self, segid, resid): """""" Obtains atom charges in a given residue Args: segid (str): Segment ID to query resid (str or int): Residue ID to query Returns: (list of float): Atom charges in residue """""" if isinstance(resid, int): resid = str(resid) return _psfgen.query_atoms(psfstate=self._data, segid=segid, resid=resid, task=""charge"") #=========================================================================== def get_atom_indices(self, segid, resid): """""" Obtains atom indices/IDs in a given residue Args: segid (str): Segment ID to query resid (str or int): Residue ID to query Returns: (list of int): Atom IDs in residue """""" if isinstance(resid, int): resid = str(resid) return _psfgen.query_atoms(psfstate=self._data, segid=segid, resid=resid, task=""atomid"") #=========================================================================== def get_coordinates(self, segid, resid): """""" Obtains atom coordinates in a given residue Args: segid (str): Segment ID to query resid (str or int): Residue ID to query Returns: (list of 3-tuple): (x,y,z) position of all atoms in residue """""" if isinstance(resid, int): resid = str(resid) return _psfgen.query_atoms(psfstate=self._data, segid=segid, resid=resid, task=""coordinates"") #=========================================================================== def get_velocities(self, segid, resid): """""" Obtains atom velocities in a given residue, if set Args: segid (str): Segment ID to query resid (str or int): Residue ID to query Returns: (list of 3-tuple): (vx,vy,vz) velocities of all atoms in residue """""" if isinstance(resid, int): resid = str(resid) return _psfgen.query_atoms(psfstate=self._data, segid=segid, resid=resid, task=""velocities"") #=========================================================================== def get_first(self, segid): """""" Get the name of the patch applied to the beginning of a given segment Args: segid (str): Segment ID to query Returns: (str): Patch name, or None """""" return _psfgen.query_segment(psfstate=self._data, task=""first"", segid=segid) #=========================================================================== def get_last(self, segid): """""" Get the name of the patch applied to the end of a given segment Args: segid (str): Segment ID to query Returns: (str): Patch name, or None """""" return _psfgen.query_segment(psfstate=self._data, task=""last"", segid=segid) #=========================================================================== def get_topologies(self): """""" Get all loaded topology files Returns: (list of str): Filenames that have been loaded """""" return _psfgen.query_system(psfstate=self._data, task=""topologies"") #=========================================================================== def get_residue_types(self): """""" Get all defined residues Returns: (list of str): Defined residue types from current topologies """""" return _psfgen.query_system(psfstate=self._data, task=""residues"") #=========================================================================== def add_segment(self, segid, first=""none"", last=""none"", pdbfile=None, auto_angles=True, auto_dihedrals=True, residues=None, mutate=None): """""" Adds a new segment to the internal molecule state. Args: segid (str): Name/ID of the new segment first (str): Patch to apply to first residue in segment, or None for topology file default setting last (str): Patch to apply to last residue in segment, or None for topology file in default setting pdbfile (str): PDB file to read residue information from, or None to create an empty segment auto_angles (bool): If angles should be autogenerated. auto_dihedrals (bool): If dihedrals should be autogenerated. residues (list of 2 or 3-tuple): (resid, residue, [chain]) of residues to append to the end of the segment. Chain can be None or unset in this tuple to use the current chain. mutate (list of 2 tuple): (resid, resname) of residues to alter. The given residue IDs will be set to the given residue name. """""" if self.get_segids() and segid in self.get_segids(): raise ValueError(""Duplicate segID '%s'"" % segid) _psfgen.add_segment(psfstate=self._data, segid=segid, pdbfile=pdbfile, first=first, last=last, auto_angles=auto_angles, auto_dihedrals=auto_dihedrals, residues=residues, mutate=mutate) #=========================================================================== def read_coords(self, filename, segid): """""" Reads in coordinates from a PDB file, matching segment, residue, and atom names to the current segment. Args: filename (str): Filename of PDB file to read segid (str): Segment ID to assign coordinates to """""" if self.get_segids() and segid not in self.get_segids(): raise ValueError(""Can't read coordinates for segment '%s' as "" ""it is undefined."" % segid) _psfgen.read_coords(psfstate=self._data, filename=filename, segid=segid) #=========================================================================== def set_position(self, segid, resid, atomname, position): """""" Sets the coordinates of a given atom to new values. Args: segid (str): Segment ID of atom resid (str or int): Residue ID of atom atomname (str): Atom name position (3-tuple or 3-list of double): New x, y, and z coordinates for atom """""" if isinstance(resid, int): resid = str(resid) if isinstance(position, list): position = tuple(position) _psfgen.set_coord(psfstate=self._data, segid=segid, resid=resid, aname=atomname, position=position) #=========================================================================== def set_velocity(self, segid, resid, atomname, velocity): """""" Sets the velocity of a given atom to new values Args: segid (str): Segment ID of atom resid (str or int): Residue ID of atom atomname (str): Atom name velocity (3 membered list or tuple of double): New vx, vy, vz velocities for atom """""" if isinstance(resid, int): resid = str(resid) if isinstance(velocity, list): velocity = tuple(velocity) _psfgen.set_atom_attr(psfstate=self._data, segid=segid, resid=resid, aname=atomname, attribute=""vel"", value=velocity) #=========================================================================== def set_segid(self, segid, new_segid): """""" Renames a segment. Args: segid (str): Segment ID to change new_segid (str): New segment ID """""" _psfgen.set_atom_attr(psfstate=self._data, segid=segid, attribute=""segid"", value=new_segid) #=========================================================================== def set_resname(self, segid, resid, new_resname): """""" Renames a residue Args: segid (str): Segment ID of residue to update resid (str or int): Residue ID to update new_resname (str): New residue name """""" if isinstance(resid, int): resid = str(resid) _psfgen.set_atom_attr(psfstate=self._data, segid=segid, resid=resid, attribute=""resname"", value=new_resname) #=========================================================================== def set_atom_name(self, segid, resid, atomname, new_atomname): """""" Renames an atom Args: segid (str): Segment ID of atom to update resid (str or int): Residue ID of atom to update atomname (str): Name of atom to update new_atomname (str): New atom name """""" if isinstance(resid, int): resid = str(resid) _psfgen.set_atom_attr(psfstate=self._data, segid=segid, resid=resid, aname=atomname, attribute=""name"", value=new_atomname) #=========================================================================== def set_mass(self, segid, resid, atomname, mass): """""" Updates the mass of an atom Args: segid (str): Segment ID of atom to update resid (str or int): Residue ID of atom to update atomname (str): Name of atom to update mass (float): New mass """""" if isinstance(resid, int): resid = str(resid) _psfgen.set_atom_attr(psfstate=self._data, segid=segid, resid=resid, aname=atomname, attribute=""mass"", value=mass) #=========================================================================== def set_charge(self, segid, resid, atomname, charge): """""" Updates the charge of an atom Args: segid (str): Segment ID of atom to update resid (str or int): Residue ID of atom to update atomname (str): Name of atom to update charge (float): New charge """""" if isinstance(resid, int): resid = str(resid) _psfgen.set_atom_attr(psfstate=self._data, segid=segid, resid=resid, aname=atomname, attribute=""charge"", value=charge) #=========================================================================== def set_beta(self, segid, resid, atomname, beta): """""" Updates the beta-factor of an atom Args: segid (str): Segment ID of atom to update resid (str or int): Residue ID of atom to update atomname (str): Name of atom to update beta (float): New beta factor """""" if isinstance(resid, int): resid = str(resid) _psfgen.set_atom_attr(psfstate=self._data, segid=segid, resid=resid, aname=atomname, attribute=""beta"", value=beta) #=========================================================================== def guess_coords(self): """""" Sets unset coordinates using geometric assumptions """""" _psfgen.guess_coords(self._data) #=========================================================================== def patch(self, patchname, targets): """""" Applies a patch to the molecule. Args: patchname (str): Name of the patch to apply targets (list of 2 tuple): (segid, resid) to apply patch to """""" _psfgen.patch(psfstate=self._data, patchname=patchname, targets=targets) #=========================================================================== def delete_atoms(self, segid, resid=None, atomname=None): """""" Deletes atoms from the molecule, with options for increasing specificity. As many atoms as match the passed options will be deleted, so for example if only segid is present, an entire segment will be removed. Args: segid (str): Segment ID of atom(s) to delete resid (str or int): Residue ID of atom(s) to delete, or None to delete entire matching segment atomname (str): Atom name to delete, or None to delete entire matching segment or residue """""" if isinstance(resid, int): resid = str(resid) _psfgen.delete_atoms(psfstate=self._data, segid=segid, resid=resid, aname=atomname) #=========================================================================== def regenerate_angles(self): """""" Removes angles and regenerates them from bonds. Can be used after patching. """""" _psfgen.regenerate(self._data, task=""angles"") #=========================================================================== def regenerate_dihedrals(self): """""" Removes dihedrals and regenerates them from angles. Can be used after patching. Usually, you should call `regenerate_angles` first. """""" _psfgen.regenerate(self._data, task=""dihedrals"") #=========================================================================== def regenerate_resids(self): """""" Regenerates residue IDs by removing insertion codes and minimially modifying them for uniqueness. """""" _psfgen.regenerate(self._data, task=""resids"") #=========================================================================== def read_psf(self, filename, pdbfile=None, namdbinfile=None, velnamdbinfile=None): """""" Reads structure information from a PSF file and adds it to the internal molecule state. Can also read insertion codes and coordinates from a PDB file, and/or coordinates from a NAMD binary file, if atoms are in the same order. Can read velocities from a NAMD binary file as well. The PSF file is read in and also kind of interpreted: topology files in the REMARKS section are loaded, and a new segment is created with the segid specified in the PSF file. Note that if the topology files cannot be found, they will still be listed as ""loaded"" in the internal PsfGen state. Args: filename (str): PSF file to read pdbfile (str): PDB file to obtain coordinates, elements, and insertion codes from. Atoms must be in same order as the PSF. namdbinfile (str): Binary NAMD file to read coordinates from. Will take priority over coordinates in pdbfile, if specified. Atoms must be in the same order as the PSF. velnamdbinfile (str): Binary NAMD file to read velocities from. Atoms must be in the same order as the PSF. """""" _psfgen.read_psf(psfstate=self._data, filename=filename, pdbfile=pdbfile, namdbinfile=namdbinfile, velnamdbinfile=velnamdbinfile) #=========================================================================== def write_psf(self, filename, type=XPLOR): """""" Writes the current molecule state out as a psf file Args: filename (str): Filename to write to type (str): Type of psf file to write, in [""charmm"", ""x-plor""] """""" _psfgen.write_psf(psfstate=self._data, filename=filename, type=type) #=========================================================================== def write_pdb(self, filename): """""" Writes the current molecule state out as a pdb file Args: filename (str): Filename to write to """""" _psfgen.write_pdb(psfstate=self._data, filename=filename) #=========================================================================== def write_namdbin(self, filename, velocity_filename=None): """""" Writes the current molecule state as a NAMD binary file. This file format can only contain coordinate information for each atom. Optionally write velocities to another NAMD binary file. Args: filename (str): Filename to write to velocity_filename (str): If present, filename to write velocities to """""" _psfgen.write_namdbin(psfstate=self._data, filename=filename, velocity_filename=velocity_filename) #=========================================================================== def query_segment(self, task, segid=None, resid=None): """""" Ask for information about a segment. Args: task (str): In [first, last, residue, resids, segids] depending on what information is desired. segid (str): Segment ID to query resid (str): Residue ID to query, if task is ""residue"" Returns: (str or list of str): Requested information """""" return _psfgen.segment(psfstate=self._data, task=task, segid=segid, resid=resid) #=========================================================================== ","Python" "Biophysics","Eigenstate/psfgen","psfgen/test/test_relaxin.py",".py","14944","434","#/usr/bin/env python """""" Tests a simple protein with many disulfides: disulfides between two identical resids on different chains, disulfides on the same chain, and unrelated disulfides on different chains. """""" import pytest import os from vmd import atomsel, molecule dir = os.path.dirname(__file__) #============================================================================== def check_correctness(molid): """""" Verifies molecule is sane """""" molecule.set_top(molid) # Check the protein is there with the correct capping groups assert len(atomsel(""protein or resname ACE NMA NME"")) == 828 assert len(set(atomsel(""protein"").fragment)) == 2 assert len(set(atomsel(""resname ACE NMA NME"").residue)) == 4 # Check for 6 cysteines, 2 with same resid assert len(set(atomsel(""resname CYS CYX"").residue)) == 6 # Check connectivity between cysteines is correct for res in set(atomsel(""resname CYS CYX"").residue): assert len(atomsel(""residue %d"" % res)) == 10 assert len(atomsel(""residue %d and name SG"" % res)) == 1 idxs = atomsel(""residue %d and name SG"" % res).bonds[0] assert set(atomsel(""index %s"" % "" "".join(str(i) for i in idxs)).name) \ == set([""CB"", ""SG""]) #============================================================================== def test_query(): """""" Tests that query functions work correctly """""" from psfgen import PsfGen gen = PsfGen(output=os.devnull) os.chdir(dir) gen.read_topology(""top_all36_caps.rtf"") gen.read_topology(""top_all36_prot.rtf"") gen.add_segment(segid=""P0"", pdbfile=""psf_protein_P0.pdb"") gen.read_coords(segid=""P0"", filename=""psf_protein_P0.pdb"") gen.add_segment(segid=""P1"", pdbfile=""psf_protein_P1.pdb"") gen.read_coords(segid=""P1"", filename=""psf_protein_P1.pdb"") gen.patch(patchname=""DISU"", targets=[(""P0"",""10""), (""P0"",""15"")]) assert gen.get_topologies() == [""top_all36_caps.rtf"", ""top_all36_prot.rtf""] # Check residue names query resnames = gen.get_residue_types() assert len(resnames) == 26 assert ""CYS"" in resnames assert ""TIP3"" not in resnames # Check patches query patches = gen.get_patches(list_all=True) assert len(patches) == 25 assert ""CYSD"" in patches assert ""SEP"" not in patches # Check segids query assert gen.get_segids() == [""P0"", ""P1""] # Check resids query assert gen.get_resids(""P0"") == [str(_) for _ in range(1, 26)] assert gen.get_resids(""P1"") == [str(_) for _ in range(0, 31)] # Check resname query, with str or int assert gen.get_resname(segid=""P0"", resid=""2"") == ""LEU"" assert gen.get_resname(segid=""P1"", resid=29) == ""SER"" # Check applied patches query assert gen.get_patches() == [(""DISU"",""P0"",""10""), (""DISU"",""P0"",""15"")] assert gen.get_first(segid=""P0"") is None assert gen.get_last(segid=""P1"") is None # Check atom queries assert gen.get_atom_names(segid=""P0"", resid=""10"") \ == ['N', 'HN', 'CA', 'HA', 'CB', 'HB1', 'HB2', 'SG', 'C', 'O'] assert set(gen.get_masses(segid=""P0"", resid=1)) == {1.008, 12.011, 15.999} assert gen.get_atom_indices(segid=""P1"", resid=0) == list(range(1,7)) assert set(gen.get_charges(segid=""P0"", resid=""10"")) \ == {-0.47, 0.07, 0.09, 0.31, -0.1, -0.08, 0.51, -0.51} # Check coordinates and velocities assert len(gen.get_coordinates(segid=""P1"", resid=25)) == 17 assert set(gen.get_velocities(segid=""P1"", resid=1)) == {(0.,0.,0.)} #============================================================================== def test_set(): """""" Tests that setters work correctly """""" from psfgen import PsfGen os.chdir(dir) gen = PsfGen(output=os.devnull) gen.read_topology(""top_all36_caps.rtf"") gen.read_topology(""top_all36_prot.rtf"") gen.add_segment(segid=""P"", pdbfile=""psf_protein_P1.pdb"") assert gen.get_segids() == [""P""] # Set segid gen.set_segid(segid=""P"", new_segid=""P1"") assert gen.get_segids() == [""P1""] gen.read_coords(segid=""P1"", filename=""psf_protein_P1.pdb"") # Set resname assert gen.get_resname(segid=""P1"", resid=""1"") == ""ASP"" gen.set_resname(segid=""P1"", resid=""1"", new_resname=""ASH"") assert gen.get_resname(segid=""P1"", resid=""1"") == ""ASH"" # Set charge gen.set_charge(segid=""P1"", resid=""1"", atomname=""O"", charge=-1.) assert -1.0 in gen.get_charges(segid=""P1"", resid=""1"") # Set atom name gen.set_atom_name(segid=""P1"", resid=""1"", atomname=""N"", new_atomname=""NO"") assert ""N"" not in gen.get_atom_names(segid=""P1"", resid=""1"") assert ""NO"" in gen.get_atom_names(segid=""P1"", resid=""1"") # Set coord gen.set_position(segid=""P1"", resid=""1"", atomname=""HN"", position=(0.,0.,-1.)) assert (0., 0., -1.) in gen.get_coordinates(segid=""P1"", resid=""1"") # Set velocity gen.set_velocity(segid=""P1"", resid=""1"", atomname=""NO"", velocity=(5., 5., 3.,)) assert (5., 5., 3.,) in gen.get_velocities(segid=""P1"", resid=""1"") #============================================================================== def test_alias(): """""" Tests atom and residue aliases, either at the topology or the PDB level """""" from psfgen import PsfGen os.chdir(dir) gen = PsfGen(output=os.devnull) gen.read_topology(""top_all36_caps.rtf"") gen.read_topology(""top_all36_prot.rtf"") gen.alias_residue(top_resname=""LEU"", pdb_resname=""LEX"") gen.alias_residue(top_resname=""ARG"", pdb_resname=""AAA"") gen.alias_atom(top_atomname=""N"", pdb_atomname=""NOOO"", resname=""PHE"") gen.add_segment(segid=""P"", pdbfile=""protein_newnames.pdb"") gen.read_coords(segid=""P"", filename=""psf_protein_P0.pdb"") assert gen.get_resname(segid=""P"", resid=2) == ""LEU"" assert gen.get_resname(segid=""P"", resid=5) == ""ALA"" assert ""N"" in gen.get_atom_names(segid=""P"", resid=23) #============================================================================== def test_ends(tmpdir): """""" Tests adding patches to the beginning and end, as well as adding residues in the segment """""" from psfgen import PsfGen p = str(tmpdir.mkdir(""mutation"")) os.chdir(dir) gen = PsfGen(output=os.devnull) gen.read_topology(""top_all36_prot.rtf"") # Add neutral N-terminus # Add an alanine then a protonated glutamate at the C-terminus. gen.add_segment(segid=""P"", pdbfile=""protein_nocaps.pdb"", first=""NTER"", last=""GLUP"", residues=[(""25"", ""ALA""), (""26"", ""GLU"")]) # Set coordinates and regenerate angles and dihedrals gen.read_coords(segid=""P"", filename=""protein_nocaps.pdb"") gen.guess_coords() # Check internal state assert gen.get_resids(""P"") == [str(_) for _ in range(2, 27)] assert gen.get_resname(segid=""P"", resid=25) == ""ALA"" assert gen.get_patches(list_defaults=True) == [('GLUP', 'P', '26'), ('NTER', 'P', '2')] assert gen.get_first(segid=""P"") == ""NTER"" assert gen.get_last(segid=""P"") == ""GLUP"" # Output os.chdir(p) gen.write_psf(filename=""output.psf"") gen.write_pdb(filename=""output.pdb"") # Check all resids are present and that 2 extra ones were added m = molecule.load(""psf"", ""output.psf"", ""pdb"", ""output.pdb"") assert list(set(atomsel(""all"").resid)) == list(range(2, 27)) assert len(atomsel(""all"")) == 382 assert set(atomsel(""resid 25"").resname) == set([""ALA""]) # Check patches were applied correctly assert ""HT1"" in atomsel(""resid 2"").name assert ""HN"" not in atomsel(""resid 2"").name assert ""HE2"" in atomsel(""resid 26"").name # Check all coordinates are set assert 0.0 not in atomsel(""all"").x assert 0.0 not in atomsel(""all"").y assert 0.0 not in atomsel(""all"").z molecule.delete(m) #============================================================================== def test_mutation(tmpdir): """""" Tests mutation of L2A in chain 0. Also as a result tests guessing coordinates """""" from psfgen import PsfGen p = str(tmpdir.mkdir(""mutation"")) os.chdir(dir) gen = PsfGen(output=os.devnull) gen.read_topology(""top_all36_caps.rtf"") gen.read_topology(""top_all36_prot.rtf"") gen.add_segment(segid=""P0"", pdbfile=""psf_protein_P0.pdb"", mutate=[(""2"", ""ALA"")]) gen.read_coords(segid=""P0"", filename=""psf_protein_P0.pdb"") gen.patch(patchname=""DISU"", targets=[(""P0"",""10""), (""P0"",""15"")]) # Guess coordinates for ALA mutation gen.guess_coords() # Set one specific coordinate gen.set_position(segid=""P0"", resid=""2"", atomname=""HB1"", position=(1.0,2.0,3.0)) # Regenerate gen.regenerate_angles() gen.regenerate_dihedrals() # Write os.chdir(p) gen.write_psf(filename=""output.psf"") gen.write_pdb(filename=""output.pdb"") # Check results with vmd-python m = molecule.load(""psf"", ""output.psf"", ""pdb"", ""output.pdb"") assert len(set(atomsel(""protein"").fragment)) == 1 assert len(set(atomsel(""resname ACE NMA NME"").residue)) == 2 # Test mutation happened and resid 2 is ALA not LEU assert set(atomsel(""resid 2"").resname) == set([""ALA""]) # Check coordinate guessing happened and HB3 has a nonzero position assert atomsel(""resid 2 and name HB3"").x != [0.0] assert atomsel(""resid 2 and name HB3"").y != [0.0] assert atomsel(""resid 2 and name HB3"").z != [0.0] # Check manual coordinate setting happened assert atomsel(""resid 2 and name HB1"").x == [1.0] assert atomsel(""resid 2 and name HB1"").y == [2.0] assert atomsel(""resid 2 and name HB1"").z == [3.0] molecule.delete(m) #=============================================================================== def test_delete(): """""" Tests removing atoms """""" from psfgen import PsfGen os.chdir(dir) gen = PsfGen(output=os.devnull) gen.read_topology(""top_all36_caps.rtf"") gen.read_topology(""top_all36_prot.rtf"") gen.add_segment(segid=""P0"", pdbfile=""psf_protein_P0.pdb"") gen.read_coords(segid=""P0"", filename=""psf_protein_P0.pdb"") # Delete a specific atom assert ""CAY"" in gen.get_atom_names(segid=""P0"", resid=1) gen.delete_atoms(segid=""P0"", resid=1, atomname=""CAY"") assert ""CAY"" not in gen.get_atom_names(segid=""P0"", resid=1) # Try deleting a capping group assert gen.get_resids(""P0"") == [str(_) for _ in range(1,26)] gen.delete_atoms(segid=""P0"", resid=1) assert gen.get_resids(""P0"") == [str(_) for _ in range(2,26)] # Add and then delete a segment gen.add_segment(segid=""DELETE"", pdbfile=""psf_protein_P1.pdb"") assert gen.get_segids() == [""P0"", ""DELETE""] gen.delete_atoms(segid=""DELETE"") assert gen.get_segids() == [""P0""] #=============================================================================== def test_case_sensitivity(): """""" Tests setting case sensitivity. Do this with 2 objects because you can't change the setting after reading in topology files. """""" from psfgen import PsfGen os.chdir(dir) gen = PsfGen(case_sensitive=True, output=os.devnull) gen.read_topology(""top_casesensitive.rtf"") assert gen.get_residue_types() == [""ACE"", ""Ace""] # Can't change case sensitivity after topologies have been read with pytest.raises(ValueError): gen.case_sensitive = False del gen gen = PsfGen(case_sensitive=True, output=os.devnull) gen.case_sensitive = False gen.read_topology(""top_casesensitive.rtf"") assert gen.get_residue_types() == [""ACE""] #=============================================================================== def test_single_chain(tmpdir): """""" Tests simple realistic system building """""" from psfgen import PsfGen p = str(tmpdir.mkdir(""single_chain"")) os.chdir(dir) gen = PsfGen(output=os.devnull) gen.read_topology(""top_all36_caps.rtf"") gen.read_topology(""top_all36_prot.rtf"") gen.read_topology(""top_water_ions.rtf"") # Read protein gen.add_segment(segid=""P0"", pdbfile=""psf_protein_P0.pdb"") gen.read_coords(segid=""P0"", filename=""psf_protein_P0.pdb"") gen.add_segment(segid=""P1"", pdbfile=""psf_protein_P1.pdb"") gen.read_coords(segid=""P1"", filename=""psf_protein_P1.pdb"") # Read waters, with 10k atoms per file to avoid PDB limitations gen.add_segment(segid=""W0"", pdbfile=""psf_wat_0.pdb"") gen.read_coords(segid=""W0"", filename=""psf_wat_0.pdb"") gen.add_segment(segid=""W1"", pdbfile=""psf_wat_1.pdb"") gen.read_coords(segid=""W1"", filename=""psf_wat_1.pdb"") # Read ions gen.add_segment(segid=""I"", pdbfile=""psf_ions.pdb"") gen.read_coords(segid=""I"", filename=""psf_ions.pdb"") # Add disulfides gen.patch(patchname=""DISU"", targets=[(""P0"",""10""), (""P0"",""15"")]) gen.patch(patchname=""DISU"", targets=[(""P0"",""24""), (""P1"",""23"")]) gen.patch(patchname=""DISU"", targets=[(""P0"",""11""), (""P1"",""11"")]) # Regenerate gen.regenerate_angles() gen.regenerate_dihedrals() # Write os.chdir(p) gen.write_psf(filename=""output.psf"") gen.write_pdb(filename=""output.pdb"") # Load as a molecule with vmd-python and check it's correct m = molecule.load(""psf"", ""output.psf"", ""pdb"", ""output.pdb"") check_correctness(m) molecule.delete(m) #=============================================================================== def test_formats(tmpdir): """""" Tests read/write of psf/namdbin files """""" from psfgen import PsfGen p = str(tmpdir.mkdir(""formats"")) os.chdir(dir) gen = PsfGen(output=os.devnull) gen.read_topology(""top_all36_caps.rtf"") gen.read_topology(""top_all36_prot.rtf"") gen.add_segment(segid=""P0"", pdbfile=""psf_protein_P0.pdb"") gen.read_coords(segid=""P0"", filename=""psf_protein_P0.pdb"") gen.add_segment(segid=""P1"", pdbfile=""psf_protein_P1.pdb"") gen.read_coords(segid=""P1"", filename=""psf_protein_P1.pdb"") # Write a PSF and a NAMD binary file gen.write_psf(filename=os.path.join(p, ""pdbin.psf"")) gen.write_namdbin(filename=os.path.join(p, ""pdbin.bin"")) del gen # Read in the PSF and NAMD binary file. Topology files should be # automatically loaded, too. Read in coordinates also as velocities # to test the velocity read in as well. gen = PsfGen(output=os.devnull) os.chdir(p) gen.read_psf(filename=os.path.join(p, ""pdbin.psf""), namdbinfile=os.path.join(p, ""pdbin.bin""), velnamdbinfile=os.path.join(p, ""pdbin.bin"")) assert gen.get_topologies() == [""top_all36_caps.rtf"", ""top_all36_prot.rtf""] assert gen.get_segids() == [""P0"", ""P1""] assert gen.get_coordinates(segid=""P0"", resid=1) \ == gen.get_velocities(segid=""P0"", resid=1) #============================================================================== ","Python" "Biophysics","Eigenstate/psfgen","docs/conf.py",".py","5205","174","# -*- coding: utf-8 -*- # # Configuration file for the Sphinx documentation builder. # # This file does only contain a selection of the most common options. For a # full list see the documentation: # http://www.sphinx-doc.org/en/master/config # -- Path setup -------------------------------------------------------------- # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. # import os import sys sys.path.insert(0, os.path.abspath(""../psfgen/"")) # -- Project information ----------------------------------------------------- project = 'psfgen' copyright = '2018, Robin Betz' author = 'Robin Betz' # The short X.Y version version = '' # The full version, including alpha/beta/rc tags release = '0.0.0a1' # -- General configuration --------------------------------------------------- # If your documentation needs a minimal Sphinx version, state it here. # # needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. extensions = [ 'sphinx.ext.autodoc', 'sphinx.ext.autosummary', 'sphinx.ext.githubpages', 'sphinxcontrib.napoleon', ] autosummary_generate = True napoleon_numpy_docstring = False napoleon_use_rtype = False autodoc_default_flags = ['members', 'inherited-members'] numpydoc_class_members_toctree = False # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # The suffix(es) of source filenames. # You can specify multiple suffix as a list of string: # # source_suffix = ['.rst', '.md'] source_suffix = '.rst' # The master toctree document. master_doc = 'index' # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. # # This is also used if you do content translation via gettext catalogs. # Usually you set ""language"" from the command line for these cases. language = None # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. # This pattern also affects html_static_path and html_extra_path . exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store'] # The name of the Pygments (syntax highlighting) style to use. pygments_style = 'sphinx' # -- Options for HTML output ------------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. # import sphinx_rtd_theme html_theme = 'sphinx_rtd_theme' # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. # # html_theme_options = {} # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named ""default.css"" will overwrite the builtin ""default.css"". html_static_path = ['_static'] html_context = { 'css_files': [ '_static/theme_overrides.css', ], } # Custom sidebar templates, must be a dictionary that maps document names # to template names. # # The default sidebars (for documents that don't match any pattern) are # defined by theme itself. Builtin themes are using these templates by # default: ``['localtoc.html', 'relations.html', 'sourcelink.html', # 'searchbox.html']``. # # html_sidebars = {} # -- Options for HTMLHelp output --------------------------------------------- # Output file base name for HTML help builder. htmlhelp_basename = 'psfgendoc' # -- Options for LaTeX output ------------------------------------------------ latex_elements = { # The paper size ('letterpaper' or 'a4paper'). # # 'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). # # 'pointsize': '10pt', # Additional stuff for the LaTeX preamble. # # 'preamble': '', # Latex figure (float) alignment # # 'figure_align': 'htbp', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ (master_doc, 'psfgen.tex', 'psfgen Documentation', 'Robin Betz', 'manual'), ] # -- Options for manual page output ------------------------------------------ # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ (master_doc, 'psfgen', 'psfgen Documentation', [author], 1) ] # -- Options for Texinfo output ---------------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ (master_doc, 'psfgen', 'psfgen Documentation', author, 'psfgen', 'One line description of project.', 'Miscellaneous'), ] # -- Extension configuration ------------------------------------------------- ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/_gmx_check.py",".py","3748","95","import subprocess import logging import re logger = logging.getLogger(__name__) def check_gromacs_installation(): try: result = subprocess.run(['gmx', '--version'], stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True) if result.returncode == 0: installed_version = get_gromacs_version() if installed_version is None: raise RuntimeError(""⚠️ GROMACS was found, but the version could not be determined. "" ""Please run `gmx --version` manually and verify your installation."") min_supported = ""2022"" max_supported = ""2026"" if is_version_in_range(min_version=min_supported, max_version=max_supported): logger.info(f""✅ Compatible GROMACS version detected: {installed_version}"") else: raise RuntimeError( f""🚫 Unsupported GROMACS version detected: {installed_version}. "" f""Supported versions are >= {min_supported} and < {max_supported}. "" ""👉 Please install a compatible GROMACS release."" ) else: logger.warning( ""🤔 Oops! It seems that GROMACS is in the system PATH but failed to run properly. "" ""I really hope that you source GROMACS in the global_config[extra_directives][dependencies]. "" ""If not, this will get awkward. 🤞"" ) except FileNotFoundError: logger.warning( ""😅 Oops! It seems that GROMACS is not installed or not found in the system PATH. "" ""I really hope that you source GROMACS in the global_config[extra_directives][dependencies]. "" ""If not, this will get awkward. 🤞"" ) def get_gromacs_version(): """"""Return GROMACS version string if installed, otherwise None."""""" try: result = subprocess.run(['gmx', '--version'], stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True) if result.returncode == 0: # Extract version number (usually appears like: ""GROMACS version: 2022.3"") match = re.search(r'GROMACS version:\s*([\d\.]+)', result.stdout) if match: return match.group(1) else: logger.warning(""⚠️ Could not parse GROMACS version from output."") return None else: return None except FileNotFoundError: return None def is_version_in_range(min_version: str | None = None, max_version: str | None = None) -> bool: """""" Check if the installed GROMACS version lies within an optional [min_version, max_version) range. target_version should be a string like '2022' or '2022.6'. Parameters ---------- min_version : str | None, optional inclusive lower bound (>=), by default None max_version : str | None, optional exclusive upper bound (<), by default None Returns ------- bool True if installed version is in range """""" def parse(v): return tuple(map(int, v.split("".""))) installed_version = get_gromacs_version() if installed_version is None: return False # GROMACS not installed or version not detected try: inst = parse(installed_version) if min_version is not None and inst < parse(min_version): return False if max_version is not None and inst >= parse(max_version): return False return True except ValueError: logger.warning(f""⚠️ Could not compare versions (installed: {installed_version}, "" f""min={min_version}, max={max_version}"") return False ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/runners.py",".py","18777","380","import copy import glob import os from pathlib import Path from typing import List, Union from warnings import warn from bindflow._gmx_check import check_gromacs_installation from bindflow._version import __version__ from bindflow.free_energy import gather_results from bindflow.orchestration.flow_builder import approach_flow from bindflow.orchestration.generate_scheduler import Scheduler, SlurmScheduler from bindflow.utils import tools import logging logger = logging.getLogger(__name__) # Next line consider to remove and let the users set it up if they need it. # As it is now it blocks in INFO level. logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(name)s - %(message)s') PathLike = Union[os.PathLike, str, bytes] def calculate( calculation_type: str, protein: Union[tools.PathLike, dict], ligands: Union[tools.PathLike, List[dict]], membrane: Union[tools.PathLike, dict, None] = None, cofactor: Union[tools.PathLike, dict, None] = None, cofactor_on_protein: bool = True, water_model: str = 'amber/tip3p', custom_ff_path: Union[None, PathLike] = None, host_name: str = 'Protein', host_selection: str = 'protein and name CA', fix_protein: bool = True, hmr_factor: Union[float, None] = 2.5, dt_max: float = 0.004, threads: int = 12, num_jobs: int = 10000, replicas: int = 3, scheduler_class: Scheduler = SlurmScheduler, debug: bool = False, job_prefix: Union[None, str] = None, out_root_folder_path: tools.PathLike = 'bindflow-out', submit: bool = False, global_config: dict = None ) -> None: """"""Main function of BindFlow to execute the workflow Parameters ---------- calculation_type : str Any of (case-insensitive): * ""fep"": For Free Energy Perturbation simulations * ""mmpbsa"": For Molecular Molecular Mechanic Poisson-Boltzmann/Generalized-Born Surface Area MM(PB/GB)SA simulations protein : Union[tools.PathLike, dict] This could be the path to the PDB file of the protein which will be processed through GMX with amber99sb-ildn; or a dictionary with the specific definition of the protein. In case a dictionary is provided, it should have: * conf -> The path of the protein PDB/GRO file [mandatory] * top -> GROMACS topology [optional], by default None. Should be a single file topology with all the force field information and without the position restraint included. However, in case, you need to use an include statement such as: include ""./charmm36-jul2022.ff/forcefield.itp"" You must change the statement to the absolute path: include ""{prefix of the absolute path}/charmm36-jul2022.ff/forcefield.itp"" And copy the charmm36-jul2022.ff to custom_ff_path and set this parameter accordingly. If not you may get some errors about files not founded. The force field directory must end with the suffix "".ff"". * ff * code -> GMX force field code [optional], by default amber99sb-ildn You can use your custom force field, but custom_ff_path must be provided ligands : Union[tools.PathLike, List[dict]] This is a list of either path to the MOL/SDF file of the ligands which will be processed through TOFF with openff_unconstrained-2.0.0.offxml; or a dictionary which expose more options to use with the TOFF Python library; or a combination of both. In case the element is a dictionary, it should have: * conf -> The path of the small molecule MOL/SDF file [mandatory]. In case that top is provided, this must be a .gro, a ValueError will be raised if it is not the case the molecule will not get its parameters. * top -> GROMACS topology [optional]. Must be a single file topology with all the force field information and without the position restraint included, by default None * ff: * type -> openff, gaff or espaloma * code -> force field code [optional], by default depending on type * openff -> openff_unconstrained-2.0.0.offxml * gaff -> gaff-2.11 * espaloma -> espaloma-0.3.1 With this parameter you can access different small molecule force fields membrane : Union[tools.PathLike, dict, None], optional This is either None (default); a path to the PDB file of the membrane which will be processed through GMX with SLipid2020; or a dictionary with the specific definition of the protein. In case a dictionary is provided, it should have: * conf -> The path of the membrane PDB file [mandatory]. If provided, the PDB must have a correct definition of the CRYST1. This information will be used for the solvation step. The membrane must be already correctly placed around the protein. Servers like CHARM-GUI can be used on this step. * top -> GROMACS topology [optional], by default None. Should be a single file topology with all the force field information and without the position restraint included. However, in case, you need to use an include statement such as: include ""./amber-lipids14.ff/forcefield.itp"" You must change the statement to the absolute path: include ""{prefix of the absolute path}/amber-lipids14.ff/forcefield.itp"" And copy theamber-lipids14.ff to custom_ff_path and set this parameter accordingly. If not You may get some errors about files not founded. The force field directory must end with the suffix "".ff"". * ff * code -> GMX force field code [optional], by default Slipids_2020 You can use yoru custom force field, but custom_ff_path must be provided cofactor : Union[tools.PathLike, dict, None], optional This is either None (default); a path to the MOL/SDF file of the ligands which will be processed through TOFF with openff_unconstrained-2.0.0.offxml; or a dictionary which expose more options to use with the TOFF Python library In case the element is a dictionary, it should have: * conf -> The path of the small molecule MOL/SDF file [mandatory]. In case that top is provided, this must be a .gro, a ValueError will be raised if it is not the case the molecule will not get its parameters. * top -> GROMACS topology [optional]. Must be a single file topology with all the force field information and without the position restraint included, by default None * ff: * type -> openff, gaff or espaloma * code -> force field code [optional], by default depending on type * openff -> openff_unconstrained-2.0.0.offxml * gaff -> gaff-2.11 * espaloma -> espaloma-0.3.1 With this parameter you can access different small molecule force fields * is_water -> If presents and set to True; it is assumed that this is a water system and that will change the settles section (if any) to tip3p-like triangular constraints. This is needed for compatibility with GROMACS. Check here: https://gromacs.bioexcel.eu/t/how-to-treat-specific-water-molecules-as-ligand/3470/9 cofactor_on_protein : bool, optional It is used during the index generation for membrane systems. It only works if cofactor_mol is provided. If True, the cofactor will be part of the protein and the ligand if False will be part of the solvent and ions. This is used mainly for the thermostat. By default True water_model : str, optional The water force field to use, by default amber/tip3p. if you would like to use the flexible definition of the CHARMM TIP3P you must define FLEXIBLE and CHARMM_TIP3P in the define statement of the mdp file custom_ff_path : Union[None, PathLike], optional All the custom force field must be in this directory. The class will set: os.environ[""GMXLIB""] = os.path.abspath(custom_ff_path) host_name : str, optional The group name for the host in the configuration file, by default ""Protein"". This is used for making index, solvate the system and working with trajectories host_selection : str, optional MDAnalysis selection to define the host (receptor or protein), by default 'protein and name CA'. This is used for Boresch restraint detection. fix_protein : bool, optional If True, `pdbfixer` will be applied with flags `--add-atoms=all --replace-nonstandard` and `gmx editconf` will the `-ignh` flag. This is needed to avoid possible issues when processing the structure through GROMACS. To kept an specific protonation state is advised to input the full definition of the protein (.top, .gro) or a PDB with the atom-naming (mainly H-naming) consistent with your selected force field. This should be used for protein mainly, by default True hmr_factor : Union[float, None], optional The Hydrogen Mass Factor to use, by default 2.5. .. warning:: For provided topologies if hmr_factor is set, it will pass any way. So for topology files with already HMR, this should be None. And all the topologies should be provided protein, cofactors, membrane, ligands with the HMR already done dt_max : float, optional This is the maximum integration time step that will be used by any MD simulation step This will be override by the specific MDP step definition through the the definitions in the global_config, by default 0.004 threads : int, optional This is the maximum number of CPUs/threads to use by any Snakemake rule. E.g. `gmx mdrun` will run with this amount of threads, by default 12 num_jobs : int, optional This is the maximum Snakemake concurrent jobs, by default 10000. When you launch in a HPC (e.g.Slurm) you can use (if your system allows it) a high number; In this case Snakemake counts as running jobs both those ones actually running and the pending ones. In the other hand, if (for testing or any other use) the FrontEnd is been used, this parameter should be set to the amount of CPUs that you would like to allocate for the entire workflow. This will prevent to overheat your machine. For example in a workstation of 12 CPus, if you set threads = 4, then num_jobs should be 3. replicas : int, optional The number of independent repeats of the entire workflow (the building of the system is not repeated), by default 3 scheduler_class : Scheduler, optional This is a class to schedule the jobs and specify how to handle computational resources, by default SlurmScheduler The module :mod:`bindflow.orchestration.generate_scheduler` presents the template class :class:`bindflow.orchestration.generate_scheduler.Scheduler` which can be used to create customized Scheduler based on user needs. :mod:`bindflow.orchestration.generate_scheduler` also contains the following functional and already tested schedular: #. :class:`bindflow.orchestration.generate_scheduler.SlurmScheduler`: To interact with `Slurm `_ #. :class:`bindflow.orchestration.generate_scheduler.FrontEnd`: To execute the workflow in a frontend-like computer. E.g. LAPTOP, workstation, etc. debug : bool, optional If True more stuff will be printed, by default False job_prefix : Union[None, str], optional A prefix to identify the jobs in the HPc cluster queue, by default None out_root_folder_path : tools.PathLike Where the workflow is going to run, by default bindflow-out submit : bool, optional If True the workflow will woke alive, by default False global_config : dict, optional The rest of the configuration and fine tunning of the workflow goes here, by default {} Raises ------ ValueError In case of invalid global_config ValueError In case the ligand paths are not found ValueError In case wrong calculation_type RuntimeError For incompatible GROMACS version """""" logger.info(f""✨ You are using BindFlow: {__version__}"") if global_config is None: global_config = dict() if calculation_type.lower() not in ['fep', 'mmpbsa']: raise ValueError(f""calculation_type must be one of: [fep, mmpbsa] (case-insensitive).\nProvided: {calculation_type}"") else: calculation_type = calculation_type.lower() check_gromacs_installation() out_root_folder_path = Path(out_root_folder_path) # Make internal copy of configuration _global_config = copy.deepcopy(global_config) # Check the validity of the provided user configuration file check_config = tools.config_validator(global_config=_global_config) if not check_config[0]: raise ValueError(check_config[1]) if hmr_factor: if hmr_factor > 4: warn(f""{hmr_factor =}. It should be lower or equal than 4 (preferred 3) to avoid instabilities"") elif hmr_factor < 2: if dt_max > 0.002: warn(f""{hmr_factor =} and {dt_max =}. For hmr_factor < 2; dt_max should be <= 0.002 ps"") else: if dt_max > 0.002: warn(f""{hmr_factor =} and {dt_max =}. hmr_factor is not been, therefore dt_max should be <= 0.002 ps"") # Initialize inputs on config _global_config[""calculation_type""] = calculation_type _global_config[""scheduler_class""] = scheduler_class _global_config[""inputs""] = {} _global_config[""inputs""][""protein""] = tools.input_helper(arg_name='protein', user_input=protein, default_ff='amber99sb-ildn', optional=False) # TODO check that is a list, tuple or string, iterable is nto enough because the dict is an iterable. Not clear how to check for this _global_config[""inputs""][""ligands""] = [tools.input_helper(arg_name='ligand', user_input=ligand, default_ff=None, default_ff_type='openff', optional=False) for ligand in ligands] _global_config[""inputs""][""cofactor""] = tools.input_helper(arg_name='cofactor', user_input=cofactor, default_ff=None, default_ff_type='openff', optional=True) _global_config[""inputs""][""membrane""] = tools.input_helper(arg_name='membrane', user_input=membrane, default_ff='Slipids_2020', optional=True) _global_config[""host_name""] = host_name _global_config[""host_selection""] = host_selection _global_config[""fix_protein""] = fix_protein _global_config[""cofactor_on_protein""] = cofactor_on_protein _global_config[""hmr_factor""] = hmr_factor _global_config[""custom_ff_path""] = custom_ff_path # TODO, for now I will hard code this section becasue I am modifying the topology with some parameters for the water in preparation.gmx_topology _global_config[""water_model""] = water_model _global_config[""dt_max""] = dt_max _global_config[""out_approach_path""] = os.path.abspath(out_root_folder_path) if job_prefix: _global_config[""job_prefix""] = f""{job_prefix}"" else: _global_config[""job_prefix""] = """" # This will only be needed for developing propose. os.environ['BINDFLOW_DEBUG'] = str(debug) # Generate output folders if not Path(_global_config[""out_approach_path""]).is_dir(): Path(_global_config[""out_approach_path""]).mkdir(exist_ok=True, parents=True) # Prepare Input / Parametrize _global_config[""ligand_names""] = [Path(mol['conf']).stem for mol in _global_config[""inputs""][""ligands""]] _global_config[""num_jobs""] = num_jobs _global_config[""replicas""] = replicas _global_config[""threads""] = threads # Check default samples for mmpbsa simulations if calculation_type == 'mmpbsa': if 'samples' in _global_config: samples = _global_config['samples'] else: _global_config['samples'] = 20 samples = 20 logger.info(f""🏗️ Building file structure for {calculation_type}: {out_root_folder_path}"") if not _global_config[""ligand_names""]: raise ValueError(""No ligands found"") if calculation_type == 'fep': expected_out_paths = int(replicas) * len(_global_config[""ligand_names""]) result_paths = glob.glob(_global_config[""out_approach_path""] + ""/*/*/dG*csv"") elif calculation_type == 'mmpbsa': expected_out_paths = replicas * samples * len(_global_config[""ligand_names""]) result_paths = glob.glob(_global_config[""out_approach_path""] + ""/*/*/complex/mmpbsa/simulation/*/mmxbsa.csv"") # Only if there is something missing if (len(result_paths) != expected_out_paths): job_id = approach_flow(global_config=_global_config, submit=submit) if job_id: logger.info(f""🚀 Submit Job - ID: {job_id}"") else: logger.info(""🛰️ BindFlow tasks are not yet submitted"") else: logger.info(""✅ All gathering CSV files were generated, nothing to do."") if (len(result_paths) > 0): print(f""🗃️ Trying to gather {len(result_paths)} ready results on: {out_root_folder_path}"") if calculation_type == 'fep': gather_results.get_all_fep_dgs(root_folder_path=out_root_folder_path, out_csv=out_root_folder_path/'fep_partial_results.csv') gather_results.get_raw_fep_data(root_folder_path=out_root_folder_path, out_csv=out_root_folder_path/'fep_partial_results_raw.csv') elif calculation_type == 'mmpbsa': full_df = gather_results.get_raw_mmxbsa_dgs(root_folder_path=out_root_folder_path, out_csv=out_root_folder_path/'mmxbsa_partial_results_raw.csv') gather_results.get_all_mmxbsa_dgs(full_df=full_df, columns_to_process=None, out_csv=out_root_folder_path/'mmxbsa_partial_results.csv') ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/__init__.py",".py","117","6","from pathlib import Path from bindflow._version import __version__ pkg_root_path = Path(__file__).resolve().parent ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/cli.py",".py","9144","251","#!/usr/bin/env python3 import argparse import logging import os from bindflow import __version__ loggers = [logging.getLogger(name) for name in logging.root.manager.loggerDict] for logger in loggers: logger.setLevel(logging.NOTSET) def dag_maker(input_path, out_name): """"""Useful for DEBUG"""""" from bindflow.utils import tools cwd = os.getcwd() os.chdir(input_path) tools.run(f""snakemake --dag | dot -Tpng -o {out_name}.png"", interactive=True) os.chdir(cwd) def fep_check_results(out_root_folder_path, out_csv_summary, out_csv_raw): from bindflow.free_energy import gather_results df_summary = gather_results.get_all_fep_dgs(root_folder_path=out_root_folder_path) if len(df_summary): df_summary = df_summary.sort_values(by='MBAR').reset_index() if out_csv_summary: df_summary.to_csv(out_csv_summary) print(df_summary) if out_csv_raw: df_raw = gather_results.get_raw_fep_data(root_folder_path=out_root_folder_path) if len(df_raw): df_raw.to_csv(out_csv_raw) else: print(""🫣"") def mmxbsa_check_results(out_root_folder_path, out_csv_summary, out_csv_raw): from bindflow.free_energy import gather_results full_df = gather_results.get_raw_mmxbsa_dgs( root_folder_path=out_root_folder_path, out_csv=out_csv_raw ) df_summary = gather_results.get_all_mmxbsa_dgs( full_df=full_df, columns_to_process=None, out_csv=out_csv_summary ) if len(df_summary): print(df_summary) else: print(""🫣"") def clean(out_root_folder_path): import subprocess import signal import shutil from pathlib import Path print(""🧹 Initiating lab cleanup sequence..."") # ---------- Step 1: Kill Snakemake processes ---------- try: result = subprocess.run( [""ps"", ""aux""], capture_output=True, text=True, check=True ) lines = result.stdout.splitlines() # Filter out lines with ""snakemake"" but not ""grep"" matching = [line for line in lines if ""snakemake"" in line and ""grep"" not in line] # Extract PIDs (second column) pids = [int(line.split()[1]) for line in matching] if pids: print(""🧹🐍 Snakes on the compute node! Initiating containment..."") for pid in pids: os.kill(pid, signal.SIGKILL) print(""✅ Free of snakes!"") else: print(""✅ No Snakemake found slithering around."") except subprocess.CalledProcessError: print(""Failed to run 'ps aux'. Is this a Unix-like system?"") except IndexError: print(""Unexpected output format from 'ps'."") except ValueError: print(""Failed to parse PID."") except ProcessLookupError: print(""Process no longer exists."") except PermissionError: print(""Permission denied when trying to kill a process."") except Exception as e: print(""❌ Snake scan failed. Something went wrong:"", e) # ---------- Step 2: Cancel SLURM jobs ---------- # Check if 'squeue' is available on the system if shutil.which(""squeue""): print(""🧹👨‍🔬 Scanning the SLURM queue..."") # Build and run the squeue command command = 'squeue --noheader -u $USER --format=""%i""' process = subprocess.Popen( command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, executable='/bin/bash' ) output, _ = process.communicate() # Decode and filter non-empty job IDs job_ids = [jid.strip() for jid in output.decode().split('\n') if jid.strip()] if job_ids: print(""🧹🧪⚠️ Found SLURM jobs. Everything will be cancelled."") cancel_command = ""scancel "" + "" "".join(job_ids) subprocess.run(cancel_command, shell=True, executable='/bin/bash') print(""✅ Lab bench cleared! SLURM jobs canceled."") else: print(""✅ No active experiments — lab bench is clear."") else: print(""❌ 'squeue' not found — SLURM job cleanup skipped."") # Deleting temporal directories # ---------- Step 3: Delete workflow folders ---------- slurm_logs = Path(out_root_folder_path) / ""slurm_logs"" snakemake = Path(out_root_folder_path) / "".snakemake"" if snakemake.exists() and snakemake.is_dir(): try: shutil.rmtree(snakemake) print(f""🧽 Removed '{snakemake}' — workflow residue eliminated."") except Exception as e: print(f""❌ Failed to remove '{snakemake}':"", e) else: print(f""✅ No '{snakemake.name}' directory found — already clean."") if slurm_logs.exists() and slurm_logs.is_dir(): for item in slurm_logs.iterdir(): item.unlink() print(f""🧽 Removed '{slurm_logs}' content — workflow residue eliminated."") else: print(f""✅ No '{slurm_logs.name}' directory found — already clean."") print(""🧼✨ Lab cleanup complete — your workspace is spotless!"") def main(): parser = argparse.ArgumentParser() parser.add_argument( '-v', '--version', action='version', version=f""✨ BindFlow: {__version__}"") subparsers = parser.add_subparsers(required=True, dest=""command"") dag = subparsers.add_parser('dag', help=""🏗️ Build the DAG of the workflow"", description=""🏗️ Build the DAG of the workflow"") dag.add_argument( '-i', dest='input_path', help='Where should the dag command should be executed. The path where the main Snakemake file is located', type=str, default='.') dag.add_argument( '-o', dest='out_name', help='Name of the output image. The suffix `.png` will be added at the end', default='dag', type=str) dag.set_defaults(func=lambda args: dag_maker(input_path=args.input_path, out_name=args.out_name)) fep_check = subparsers.add_parser( 'check_fep', help=""🔎 Check for completion of an FEP workflow"", description=""🔎 Check for completion of an FEP workflow"") fep_check.add_argument( dest='out_root_folder_path', help='fep directory (`out_root_folder_path` kwarg of :func:`bindflow.runners.calculate`)', type=str) fep_check.add_argument( '-os', '--out_csv_summary', help=""The path to output the summary csv file, by default None"", dest='out_csv_summary', nargs=argparse.OPTIONAL, default=None, type=str) fep_check.add_argument( '-or', '--out_csv_raw', help=""The path to output the raw csv file, by default None"", dest='out_csv_raw', nargs=argparse.OPTIONAL, default=None, type=str) fep_check.set_defaults( func=lambda args: fep_check_results( out_root_folder_path=args.out_root_folder_path, out_csv_summary=args.out_csv_summary, out_csv_raw=args.out_csv_raw)) mmxbsa_check = subparsers.add_parser( 'check_mmxbsa', help=""🔎 Check for completion of an MM(PB/GB)SA workflow"", description=""🔎 Check for completion of an MM(PB/GB)SA workflow"") mmxbsa_check.add_argument( dest='out_root_folder_path', help='MM(P/B)BSA directory (`out_root_folder_path` kwarg of :func:`bindflow.runners.calculate`)', type=str) mmxbsa_check.add_argument( '-os', '--out_csv_summary', help=""The path to output the summary csv file, by default None"", dest='out_csv_summary', nargs=argparse.OPTIONAL, default=None, type=str) mmxbsa_check.add_argument( '-or', '--out_csv_raw', help=""The path to output the raw csv file, by default None"", dest='out_csv_raw', nargs=argparse.OPTIONAL, default=None, type=str) mmxbsa_check.set_defaults( func=lambda args: mmxbsa_check_results( out_root_folder_path=args.out_root_folder_path, out_csv_summary=args.out_csv_summary, out_csv_raw=args.out_csv_raw)) cleaner = subparsers.add_parser( 'clean', help=""🧹 Clean the running directory for restart"", description=""🧹 Clean the running directory for restart. It will:\n"" "" 1 - ⚠️ Kill ALL snakemake process running\n"" "" 2 - ⚠️ Cancel ALL running jobs of an Slurm queue\n"" "" 3 - Delete the .snakemake directory and the content of slurm_logs\n"", formatter_class=argparse.RawDescriptionHelpFormatter) cleaner.add_argument( dest='out_root_folder_path', help='MM(P/B)BSA / FEP directory (`out_root_folder_path` kwarg of :func:`bindflow.runners.calculate`)', type=str) cleaner.set_defaults(func=lambda args: clean(out_root_folder_path=args.out_root_folder_path)) args = parser.parse_args() args.func(args) if __name__ == ""__main__"": pass ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/home.py",".py","1215","53","#!/usr/bin/env python3 # -*- coding: utf-8 -*- import bindflow from pathlib import Path import sys import inspect import platform def home(dataDir=None, libDir=False) -> Path: """"""Return the pathname of the bindflow root directory (or a data subdirectory). Parameters ---------- dataDir : str If not None, return the path to a specific data directory libDir : bool If True, return path to the lib directory Returns ------- dir : pathlib.Path The directory Example ------- .. ipython:: python from bindflow.home import home print(home()) print(home(dataDir=""gmx_ff"")) print(home(dataDir=""gmx_ff"")/""amber99sb-star-ildn.ff.tar.gz"") """""" homeDir = Path(inspect.getfile(bindflow)).parent try: if sys._MEIPASS: homeDir = Path(sys._MEIPASS) except Exception: pass if dataDir: return homeDir/f""data/{dataDir}"" elif libDir: libdir = homeDir/f""lib{platform.system()}"" if not libdir.exists(): raise FileNotFoundError(""Could not find libs."") return libdir else: return homeDir if __name__ == ""__main__"": pass ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/utils/tools.py",".py","35411","919","#!/usr/bin/env python import copy import os import re import subprocess import tempfile from math import sqrt from pathlib import Path from typing import Iterable, List, Optional, Tuple, Union from parmed import Structure from parmed.gromacs import GromacsGroFile, GromacsTopologyFile PathLike = Union[os.PathLike, str, bytes] # Because of how snakemake handles environmental variables that # are used by GROMACS (https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html) # We have to hard code the unset of some of them # TODO, check the implications of such modifications. I hope that only affects the specific rule where GROMACS is called HARD_CODE_DEPENDENCIES = [ 'unset OMP_NUM_THREADS', 'unset GOTO_NUM_THREADS', 'unset OPENBLAS_NUM_THREADS', 'unset MKL_NUM_THREADS', 'unset VECLIB_MAXIMUM_THREADS', 'unset NUMEXPR_NUM_THREADS', ] class DotDict: """"""A simple implementation of dot-access dict"""""" def __init__(self, **kwargs): for key, value in kwargs.items(): if isinstance(value, dict): self.__dict__[key] = DotDict(**value) else: self.__dict__[key] = value def __repr__(self) -> str: return str(self.__dict__) def to_dict(self): return self.__dict__ def run(command: str, shell: bool = True, executable: str = '/bin/bash', interactive: bool = False, stdin_command: Union[None, str] = None) -> subprocess.CompletedProcess: """"""A simple wrapper around subprocess.Popen/subprocess.run Parameters ---------- command : str The command line to be executed shell : bool, optional Create a shell section, by default True executable : str, optional what executable to use, pass `sys.executable` to check yours, by default '/bin/bash' interactive : bool, optional To interact with the command, by default False. If True, you can access stdout and stderr of the returned process. stdin_command : Union[None, str], optional Command to pipe to the main command, by default None. Returns ------- subprocess.CompletedProcess The process Raises ------ RuntimeError In case that the command fails, the error is raised in a nice way """""" if interactive: process = subprocess.run(command, shell=shell, executable=executable) returncode = process.returncode if returncode != 0: raise RuntimeError(f'Command {command} returned non-zero exit status {returncode}') else: if stdin_command: stdin_process = subprocess.Popen(stdin_command, shell=shell, executable=executable, stdout=subprocess.PIPE, text=True) process = subprocess.run(command, shell=shell, executable=executable, stdin=stdin_process.stdout, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True) else: process = subprocess.run(command, shell=shell, executable=executable, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True) returncode = process.returncode if returncode != 0: print(f'Command {command} returned non-zero exit status {returncode}') raise RuntimeError(process.stderr) return process def gmx_command(load_dependencies: List[str] = None, interactive: bool = False, stdout_file: PathLike = None, stdin_command: Union[None, str] = None): """"""Lazy wrapper of gmx commands Parameters ---------- load_dependencies : List[str] It is used in case some previous loading steps are needed; e.g: ['source /groups/CBG/opt/spack-0.18.1/shared.bash', 'module load sandybridge/gromacs/2022.4'] interactive : bool In case, and interactive section is desired, by default False stdout_file : bool If provided, it will append to the command ` >& {stdout_file}`, by default None stdin_command : Union[None, str], optional Command to pipe to the main command, by default None. A typical function will be: Example ------- .. ipython:: python from bindflow.utils import tools @tools.gmx_command() def mdrun(**kwargs): ... The important parts are: #. The name of the function must be the name of the gmx command, for example mdrun, grompp, etc. #. You must return the local variables of the function #. The names of the keywords are exactly the same name as got it by the respective function. #. For flags, a boolean will be provided as value, for example v = True, if you want to be verbose. Some GROMACS functions need the user inputs (E.g. pdb2gmx, trjconv, make_ndx). For those cases we can use interactive mode or pipe the input as echo to the gmx command, for example: .. code-block:: bash echo 'System' | gmx trjconv -s prod.tpr -f prod.xtc -o whole.xtc -pbc whole To achieve this with gmx_command, we can: .. code-block:: python @gmx_command(stdin_command=""echo 'System'"") def trjconv(**kwargs): ... trjconv(s='prod.tpr', f='prod.xtc', o='whole.xtc', pbc='whole') It is important to remark that every time that `trjconv` is executed, the output of the echo command will be passed. To change this you have to redefine the function. .. code-block:: python @gmx_command(stdin_command=""echo 'Protein'"") def trjconv(**kwargs): ... trjconv(s='prod.tpr', f='prod.xtc', o='whole.xtc', pbc='whole') """""" def decorator(gmx_function: object): def wrapper(**kwargs): if load_dependencies: cmd = "" && "".join(load_dependencies) cmd += "" && "" else: cmd = '' cmd += f""gmx {gmx_function.__name__}"" for key in kwargs: value = kwargs[key] if value: if isinstance(value, bool): if value: cmd += f"" -{key}"" else: cmd += f"" -{key} {value}"" if stdout_file: cmd += f"" >& {stdout_file}"" if interactive: raise RuntimeError(""stdout_file argument is not compatible with interactive flag"") if interactive: return run(cmd, interactive=True) else: if stdin_command: return run(cmd, stdin_command=stdin_command) else: return run(cmd) return wrapper return decorator def readParmEDMolecule(top_file: PathLike, gro_file: PathLike, check_box:bool = False) -> Structure: """"""Read a gro and top GROMACS file and return a topology Structure Parameters ---------- top_file : PathLike Path of the top file gro_file : PathLike Path of the gro file check_box : bool If True and sum(gmx_gro.box[:3]) == 0, gmx_gro.box[:3] = [10, 10, 10] Returns ------- Structure Structure with topologies, coordinates and box information """""" gmx_top = GromacsTopologyFile(str(top_file)) gmx_gro = GromacsGroFile.parse(str(gro_file), skip_bonds=True) # Despite top_file might have different chains # defined as different molecules, it looks like # this is interpreted by parmed as a continuation # of the chain when the gro of this system is # written, the current residue numeration is not # respect and a continues numeration is set # this makes that in the topology you may have # two chains but in the gro you have a continue chain. # This means that post-processing of the gro file # is needed in case of multiple chains and the residue # numeration is important for the analysis # Add positions if sum(gmx_gro.box[:3]) == 0 and check_box: # Place holder in case no box info on the reader file # THIS MAY CAUSE ISSUES WHEN IS COMBINED WITH THE LIGAND # I AM NOT SURE, MAYBE IT IS NT A PROBLEM AS THE COORDINATES # DO NOT CHANGE. gmx_gro.box[:3] = [10, 10, 10] gmx_top.positions = gmx_gro.positions # Needed because .prmtop contains box info gmx_top.box = gmx_gro.box return gmx_top def gmx_runner(mdp: PathLike, topology: PathLike, structure: PathLike, checkpoint: PathLike = None, index: PathLike = None, nthreads: int = 12, load_dependencies: List[str] = None, run_dir: PathLike = '.', **mdrun_extra): """"""This function create the tpr file based on the input provided And run the simulation. Note: During the tpr creation maxwarn = 2 (TODO: remove it in the future) The following commands will be executed by default: gmx grompp -f {mdp} -c {structure} -r {structure} -p {topology} -o {mdp-name}.tpr -maxwarn 2 gmx mdrun -nt 12 -deffnm {mdp-name} ``mdrun`` will update the command based on ``mdrun_extra``. You can also suppress the use of ``nt`` and/or ``deffnm`` passing them as ``False`` and construct your own mdrun command. E.g. gmx_runner(mdp='emin.mdp', topology='ligand.top', structure='ligand.gro', deffnm=False, cpi=True, s='emin.tpr') The last will give (): gmx mdrun -nt 12 -cpi -s emin.tpr -o emin2 Parameters ---------- mdp : str The path to the MDP file. The name of the file will be used for the tpr and for the files generated during mdrun. topology : PathLike GMX topology file structure : PathLike The PDB, GRO, etc structure of the system checkpoint : PathLike Full precision trajectory: trr cpt tng, by default None> if given will be used on grompp with the flag `-t {checkpoint}` index : PathLike A GMX index to be used on grompp, by default None nthreads : int, optional Number of threads to run, by default 12 load_dependencies : List[str], optional It is used in case some previous loading steps are needed; e.g: ['source /groups/CBG/opt/spack-0.18.1/shared.bash', 'module load sandybridge/gromacs/2022.4'], by default None run_dir : PathLike, optional Where the simulation should run (write files). If it does not exist will be created, by default '.' **mdrun_extra : any Any valid keyword for mdrun. Flags are passing as boolean. E.g: cpi = True. There is not check of right keywords, for wrong keywords an error will be raised at GROMACS level """""" # Create run directory on demand run_dir = Path(run_dir) run_dir.mkdir(exist_ok=True, parents=True) name = Path(mdp).stem @gmx_command(load_dependencies=HARD_CODE_DEPENDENCIES + load_dependencies) def grompp(**kwargs): ... @gmx_command(load_dependencies=HARD_CODE_DEPENDENCIES + load_dependencies, stdout_file=f""{name}.lis"") def mdrun(**kwargs): ... cwd = os.getcwd() os.chdir(run_dir) grompp_extra = {} if checkpoint: grompp_extra['t'] = checkpoint if index: grompp_extra['n'] = index # TODO, I do not like to use the maxwarn keyword hardcoded. grompp(f=f""{mdp}"", c=structure, r=structure, p=topology, o=f""{name}.tpr"", maxwarn=2, **grompp_extra) mdrun_kwargs = { # TODO DEBUG # ""ntomp"": nthreads, ""nt"": nthreads, # TODO: this flag is deprecate in new GROMACS versions and in 2024 is not longer available # This means that I have to build the mdrun command at rule level. ""deffnm"": name, } if mdrun_extra: mdrun_kwargs.update(mdrun_extra) mdrun(**mdrun_kwargs) os.chdir(cwd) def center_xtc(tpr: PathLike, xtc: PathLike, run_dir: PathLike, host_name: str = 'Protein', load_dependencies: List[str] = None) -> PathLike: """"""Center an xtc file Parameters ---------- tpr : PathLike Binary GROMACS topology xtc : PathLike Trajectory file run_dir : PathLike Directory to run and save the center trajectory host_name : str, optional Name of the host/receptor, by default 'Protein' load_dependencies : List[str], optional It is used in case some previous loading steps are needed; e.g: ['source /groups/CBG/opt/spack-0.18.1/shared.bash', 'module load sandybridge/gromacs/2022.4'], by default None Returns ------- PathLike The path of the center trajectory: {run_dir}/center.xtc """""" dependencies = HARD_CODE_DEPENDENCIES + [""export GMX_MAXBACKUP=-1""] if load_dependencies: if isinstance(load_dependencies, List): dependencies += load_dependencies else: raise ValueError(f""load_dependencies must be a List. Provided: {load_dependencies}"") run_dir = Path(run_dir) run_dir.mkdir(exist_ok=True, parents=True) @gmx_command(load_dependencies=dependencies, stdin_command=""echo 'System'"") def trjconv(**kwargs): ... trjconv(s=tpr, f=xtc, o=run_dir/""whole.xtc"", pbc=""whole"") trjconv(s=tpr, f=run_dir/""whole.xtc"", o=run_dir/""nojump.xtc"", pbc=""nojump"") @gmx_command(load_dependencies=dependencies, stdin_command=f""echo '{host_name} System'"") def trjconv(**kwargs): ... trjconv(s=tpr, f=run_dir/""nojump.xtc"", o=run_dir/""center.xtc"", pbc=""mol"", center=True, ur=""compact"") # Clean (run_dir/""whole.xtc"").unlink() (run_dir/""nojump.xtc"").unlink() return f""{run_dir}/center.xtc"" def paths_exist(paths: List, raise_error: bool = False, out: Union[str, None] = None) -> None: """"""Check that the paths exist Parameters ---------- paths : List A list of paths raise_error : bool, optional If True will raise a RuntimeError when any path doe not exist, by default False out : Union[str, None], optional In case that all files exist and out is st to some file; the existence of this file could be used as a check that all paths exist (useful for sanekemake), by default None Raises ------ RuntimeError In case some path does not exist and rasie_error = True """""" check = True for path in paths: if not Path(path).exists(): check = False msg = f""Missing path/file: {path}"" if raise_error: raise RuntimeError(msg) else: print(msg) if out and check: open(out, ""w"").close() def list_if_dir(path: PathLike = '.') -> List[Path]: return [p for p in Path(path).iterdir() if p.is_dir()] def list_if_file(path: PathLike = '.', ext: str = None) -> List[Path]: """"""Dir all the files in path Parameters ---------- path : PathLike, optional Path to look for the file, by default '.' ext : str, optional The extension of the file, for example: "".py"", "".sh"", "".txt"", by default None Returns ------- List[Path] The list of file names """""" files = [p for p in Path(path).iterdir() if p.is_file()] if ext: files = [file for file in files if file.suffix == ext] return files def is_file_inside_directory(directory_path, file_path): # Convert paths to Path objects directory_path = Path(directory_path).resolve() file_path = Path(file_path).resolve() # Check if the file path starts with the directory path # print(file_path.parts) return file_path.parts[:len(directory_path.parts)] == directory_path.parts def find_xtc(root_path: PathLike, exclude_suffixes: List[str] = None) -> List[PathLike]: """"""Find all the files with the extension .xtc that does not have any parent directory with any exclude_suffixes. If the name if the xtc file has as suffix some of the ones specified in excluded_suffixes, it will also discarded as well. Parameters ---------- root_path : PathLike Root path to look for XTC files exclude_suffixes : List[str], optional list of suffixes to exclude from wither parent directories or the XTC files themself , by default None Returns ------- List[PathLike] LIst of XTC file paths """""" xtc_files = Path(root_path).resolve().rglob('*.xtc') if exclude_suffixes: exclude_suffixes = tuple(exclude_suffixes) xtc_files_filtered = [] for xtc_file in xtc_files: components = [xtc_file] + list(xtc_file.parents) # any parent directories or the file itself has any of exclude_suffixes test = any([True if str(component).endswith(exclude_suffixes) else False for component in components]) if not test: xtc_files_filtered.append(xtc_file) return xtc_files_filtered else: return xtc_files def archive(root_path: PathLike, exclude_suffixes: List[str] = None, name: str = 'archive', compress_type: str = 'gz', remove_dirs: bool = False, out_check_file: bool = True): """"""Recursively archive root_path. Directories and/or files with any suffixes from exclude_suffixes are ignored . It creates a tar file with the XTC files (without compress) and a main_project.tar.{compress_type} with the rest of directories. Compression will only be applied to those files included in main_project.tar.{compress_type}. In-house benchmark showed a compress rate close to for a fep campaign 1.8 using gz compression (data taken from MCL1). 139 GB to 77 GB .. warning:: It may be that the function fail because the directory is too large, in this case you must split the directory, this was the case for the p38 campaign (https://github.com/openforcefield/protein-ligand-benchmark) with 3 replicas BE AWARE OF THE IMPLICATION TO DELETE A SIMULATION DIRECTORY with the option ``remove_dirs = True`` In-house benchmark showed: +-------+-------+-------+ | | Time | Space | +=======+=======+=======+ | bz2 | x s | x MB | +-------+-------+-------+ | gz | x s | x MB | +-------+-------+-------+ | xz | x s | x MB | +-------+-------+-------+ Parameters ---------- root_path : PathLike The root path for which all the dirs will be compressed exclude_suffixes : List[PathLike], optional List of suffix to exclude for compression either directories or files. The endswith method will be applied Use case example could be: [.snakemake, .log, .edr, .lis, .err]. In this case the directory .snakemake will be ignored and all the files with the specified extensions. name : str, optional Output name of the archive file, by default 'archive' compress_type : str, optional Type of compression to use, tar, gz, bz2 and xz are possible, by default 'gz' remove_dirs : bool, optional Remove compressed root_path, by default False out_check_file : bool, optional If the archive worked as expected, a file {name}_safe_remove.check will be written, by default True Raises ------ FileNotFoundError If root_path does not exist ValueError Incorrect compress_type ValueError If the provided name lays on root_path, this is not expected. """""" import shutil import tarfile # Ensure the provided path exists root_path = Path(root_path) if not root_path.exists(): raise FileNotFoundError(f""Directory '{root_path}' does not exist."") # Define the name of the compressed file compress_type = compress_type.lower() valid_tar_exts = ['tar', 'gz', 'bz2', 'xz'] if compress_type not in valid_tar_exts: raise ValueError(f""Unsupported compression type ({compress_type}). Use: {' '.join(valid_tar_exts)}."") if is_file_inside_directory(root_path, f""{name}.tar""): raise ValueError(f""Invalid {name=}. It lays in {root_path=}"") # Convert to list if exclude_suffixes: exclude_suffixes = list(set(exclude_suffixes)) else: exclude_suffixes = [] # Find and create a separate archive for XTC files xtc_files = find_xtc(root_path=root_path, exclude_suffixes=exclude_suffixes) with tarfile.open(f""{name}.tar"", 'w:tar') as project_archive: if xtc_files: for xtc_file in xtc_files: xtc_file_path = root_path/xtc_file print(f""Adding XTC: {xtc_file}"") project_archive.add(xtc_file_path, arcname=xtc_file) with tempfile.TemporaryDirectory(prefix='.main_archive', dir='.') as tmpdir: # Create the compressed main_archive arcname = 'main_project.tar' if compress_type != 'tar': arcname += f"".{compress_type}"" # For the main archive always exclude XTC files internal_excluded_ext = tuple(set(exclude_suffixes + ['.xtc'])) with tarfile.open(os.path.join(tmpdir, arcname), f'w:{compress_type}') as main_archive: for root, _, files in os.walk(root_path): for file in files: if not file.endswith(internal_excluded_ext): file_path = os.path.relpath(os.path.join(root, file), root_path) main_archive.add(os.path.join(root, file), arcname=file_path) print(f""Adding: {arcname}"") project_archive.add(os.path.join(tmpdir, arcname), arcname=arcname) if out_check_file: with open(f""{name}_safe_remove.check"", ""w"") as f: f.write('All files were successfully archived!') # Optionally remove the source directories if remove_dirs: # TODO Check that f""{name}.tar"" does not lay in root_dir print(""Cleaning after compression:"") print(f""Removing: {root_path}"") shutil.rmtree(root_path) def _filter_helper(TarInfo: str, suffix: Tuple[str], prefix: Tuple[str] = ('main_project.tar')): if suffix: if TarInfo.name.endswith(suffix): return TarInfo else: if prefix: if TarInfo.name.startswith(prefix): return TarInfo else: return None return None return TarInfo def unarchive(archive_file: PathLike, target_path: PathLike, only_with_suffix: Union[None, List[str]] = None, prefix: Tuple[str] = ('main_project.tar')): """"""It unarchive a project archived by the function :func:`bindflow.utils.tools.archive` Parameters ---------- archive_file : PathLike Archived project target_path : PathLike Out path to unarchive only_with_suffix : Union[None, List[str]] Only extract those files that present the suffix """""" import tarfile # Ensure the target directory exists target_path = Path(target_path).resolve() target_path.mkdir(exist_ok=True, parents=True) # Convert to list if only_with_suffix: # Addint the main_project.tar only_with_suffix = tuple(only_with_suffix) else: only_with_suffix = tuple() # Create a temporary directory for extracting the main compressed archive with tempfile.TemporaryDirectory(prefix='.unarchive_main', dir='.') as tmpdir: # Extract the XTC archive first with tarfile.open(archive_file, 'r') as archive: for member in archive.getmembers(): member = _filter_helper(member, only_with_suffix, prefix=prefix) if member: print(f""Decompressing: {member.name}"") if member.name.startswith('main_project.tar'): compress_type = member.name.split('.')[-1] main_archive_path = os.path.join(tmpdir, member.name) # TODO # This step is extremely painful, at some point you have # twice the size of the original archive file # The solution is to have separately for xtc and main project, but then we have two files # not soe ""archive"", but either we solve the clean archive, or improve the unarchive. archive.extract(member, tmpdir) with tarfile.open(main_archive_path, f'r:{compress_type}') as main_archive: for main_member in main_archive.getmembers(): main_member = _filter_helper(main_member, only_with_suffix, prefix=prefix) if main_member: print(f""Decompressing: {main_member.name}"") main_archive.extract(main_member, target_path) else: archive.extract(member, target_path) def recursive_update_dict(original_dict: dict, update_dict: dict) -> None: for key, value in update_dict.items(): if isinstance(value, dict) and key in original_dict and isinstance(original_dict[key], dict): recursive_update_dict(original_dict[key], value) else: original_dict[key] = value def config_validator(global_config: dict) -> List: """"""It checks for the validity of the global config. This dictionary is used for :func:`bindflow.runners.calculate` Parameters ---------- global_config : dict The configuration of the BindFlow workflow Returns ------- List[bool,str] result[0], True if pass all the checks. False otherwise. result[1], Extra information. """""" # Checking cluster if 'cluster' not in global_config: global_config['cluster'] = { 'options': { 'calculation': None } } print(""No \""cluster\"" definition. Setting cluster/options/calculation = None"") if 'options' not in global_config['cluster']: global_config['cluster'] = { 'options': { 'calculation': None } } print(""No \""cluster/options\"" definition. Setting cluster/options/calculation = None"") if 'calculation' not in global_config['cluster']['options']: global_config['cluster'] = { 'options': { 'calculation': None } } print(""No \""cluster/options/calculation\"" definition. Setting cluster/options/calculation = None"") # Setting up default extra mdrun and job dependencies in case it was not provided if ""extra_directives"" in global_config: if ""dependencies"" not in global_config[""extra_directives""]: global_config[""extra_directives""][""dependencies""] = [] if ""mdrun"" not in global_config[""extra_directives""]: global_config[""extra_directives""][""mdrun""] = { 'ligand': {}, 'complex': {}, 'all': {} } else: global_config[""extra_directives""] = { ""dependencies"": [], ""mdrun"": { 'ligand': {}, 'complex': {}, 'all': {} }, } valid_mdrun = [""ligand"", ""complex"", ""all""] # In case that 'extra_directives/mdrun/key' was not defined for key in valid_mdrun: if key not in global_config[""extra_directives""][""mdrun""]: global_config[""extra_directives""][""mdrun""][key] = {} # Check that mdrun is valid valid_mdrun = [""ligand"", ""complex"", ""all""] for key in global_config[""extra_directives""][""mdrun""]: if key not in valid_mdrun: return False, f""extra_directives/mdrun/{key} is not valid, you must select one of valid mdrun options {valid_mdrun}"" # Here we use as base keywords the one defined in all # And then, for ligand and complex, update those based on th user input # In other words, ligand and complex will use the all definition updated by their own keywords. if key != 'all': key_all = global_config[""extra_directives""][""mdrun""]['all'].copy() key_all.update(global_config[""extra_directives""][""mdrun""][key]) global_config[""extra_directives""][""mdrun""][key] = key_all # Always allow continuation in case the user did not defined if ""cpi"" not in global_config[""extra_directives""][""mdrun""][key]: global_config[""extra_directives""][""mdrun""][key]['cpi'] = True # After the update keywords, keep all is not needed any more del global_config[""extra_directives""][""mdrun""]['all'] return True, ""Cluster configuration is valid"" def input_helper(arg_name: str, user_input: Union[PathLike, dict, None], default_ff: Union[PathLike, str], default_ff_type: Union[str, None] = None, optional: bool = False) -> dict: """"""This helper function is called inside bindflow.runners.calculate to check for the inputs: protein, ligands, membrane and cofactor Parameters ---------- arg_name : str The name of the part of the system. It is just used for to print information in case of error user_input : Union[PathLike, dict, None] The user input provided default_ff : Union[PathLike, str] A code of the force field. Internally it will be check if [default_ff].ff exist as a directory. This allow a much bigger flexibility on the use of different force fields that do not come with the GROMACS distribution by default default_ff_type : Union[PathLike, str] This is used for the small molecules. It must be openff, gaff or espaloma (case insensitive). If it is provided, default_ff will NOT be used and set to None. During the building of the system, it will be converted internally as: * openff -> openff_unconstrained-2.0.0.offxml * gaff -> gaff-2.11 * espaloma -> espaloma-0.3.1 optional : bool, optional if the arguments under analysis is optional or not, by default False Returns ------- dict A dictionary with keywords: conf[configuration file], top[GROMACS topology file], ff:code[force field code], path[absolute path in case the directory exists] Raises ------ ValueError if user_input is None but optional is False FileNotFoundError The configuration file is not found even when some path was provided ValueError In case conf is not provided when user_input is a dict and optional is False FileNotFoundError The configuration file is not found when user_input is suppose to be a path """""" valid_ff_types = ['openff', 'gaff', 'espaloma'] if default_ff_type: default_ff_type = str(default_ff_type).lower() if default_ff_type not in valid_ff_types: raise ValueError(f""{default_ff_type =} is not valid. Choose from {valid_ff_types}"") if not user_input: if optional: return None else: raise ValueError(f""{arg_name =} was set with {user_input =} but {optional =}"") else: internal_dict = { 'conf': None, # This must be a single file topology with all the force field information # without positional restraint definition for the heavy atoms, thi will be generated internally. 'top': None, 'ff': { 'code': default_ff, } } if default_ff_type: internal_dict['ff']['type'] = default_ff_type internal_dict['ff']['code'] = None if isinstance(user_input, dict): recursive_update_dict(internal_dict, user_input) # Convert to absolute paths if internal_dict['conf']: if not Path(internal_dict['conf']).exists(): raise FileNotFoundError(f""{internal_dict['conf'] = } is not accessible."") internal_dict['conf'] = os.path.abspath(internal_dict['conf']) # Needed the string for JSON else: if not optional: raise ValueError(f'conf must be provided on the `{arg_name}` entry when a dictionary is used') if internal_dict['top']: if not Path(internal_dict['top']).exists(): raise FileNotFoundError(f""{internal_dict['top'] = } is not accessible."") internal_dict['top'] = os.path.abspath(internal_dict['top']) # Needed the string for JSON # set to None unused variables: if internal_dict['conf'] and internal_dict['top']: internal_dict['ff']['code'] = None if 'type' in internal_dict['ff']: internal_dict['ff']['type'] = None # This is the case that only a path was provided else: if not Path(user_input).exists(): raise FileNotFoundError(f""On {arg_name} entry; {user_input = } is not accessible"") internal_dict['conf'] = os.path.abspath(user_input) # Needed the string for JSON return copy.deepcopy(internal_dict) def natsort(iterable: List) -> Iterable: """"""Natural sort of an iterable Parameters ---------- iterable : List Some iterable Example ------- .. ipython:: python from bindflow.utils import tools my_list = ['1', '2', 3, '4', '11', 5, 'A', '0', 13, '6'] try: print(sorted(my_list)) except TypeError: print(""We need to convert to string but still is not what we are expecting"") print(sorted(map(str, my_list))) print(tools.natsort(my_list)) Returns ------- Iterable The natural sorted iterable """""" def conversion(element): return int(element) if element.isdigit() else element.lower() return sorted(iterable, key=lambda k: [conversion(c) for c in re.split('([0-9]+)', str(k))]) def sum_uncertainty_propagation( errors: Iterable[float], coefficients: Optional[Iterable[float]] = None, ) -> float: """""" Compute the combined uncertainty using standard uncertainty propagation rules for a sum of terms with optional scaling coefficients. The formula applied is: sigma_total = sqrt( Σ (c_i * sigma_i)^2 ) where: - sigma_i is the uncertainty (error) of the i-th term - sigma_i is the coefficient (default = 1 for all terms) Parameters ---------- errors : Sequence[float] A list or sequence of uncertainty values (standard deviations). coefficients : Optional[Iterable[float]], default=None Coefficients corresponding to each error term. If not provided, all coefficients are assumed to be 1. Returns ------- float The propagated uncertainty. Raises ------ ValueError If the length of `coefficients` does not match the length of `errors`. Examples -------- >>> sum_uncertainty_propagation([0.1, 0.2, 0.15]) 0.2692582403567252 >>> sum_uncertainty_propagation([0.1, 0.2, 0.15], coefficients=[2, 1, 0.5]) 0.3301517104052358 """""" if coefficients is None: coefficients = [1.0] * len(errors) else: coefficients = list(coefficients) if len(coefficients) != len(errors): raise ValueError(""`coefficients` must have the same length as `errors`."") return sqrt(sum((c * e) ** 2 for c, e in zip(coefficients, errors))) ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/utils/cluster.py",".py","3772","113","#!/usr/bin/env python3 # -*- coding: utf-8 -*- # https://slurm.schedmd.com/sbatch.html _SBATCH_KEYWORDS = { 'A': 'account', 'account': 'account', 'acctg-freq': 'acctg-freq', 'a': 'array', 'array': 'array', 'batch': 'batch', 'bb': 'bb', 'bbf': 'bbf', 'b': 'begin', 'begin': 'begin', 'D': 'chdir', 'chdir': 'chdir', 'cluster-constraint': 'cluster-constraint', 'M': 'clusters', 'clusters': 'clusters', 'comment': 'comment', 'C': 'constraint', 'constraint': 'constraint', 'container': 'container', 'contiguous': 'contiguous', 'S': 'core-spec', 'core-spec': 'core-spec', 'cores-per-socket': 'cores-per-socket', 'cpu-freq': 'cpu-freq', 'cpus-per-gpu': 'cpus-per-gpu', 'c': 'cpus-per-task', 'cpus-per-task': 'cpus-per-task', 'deadline': 'deadline', 'delay-boot': 'delay-boot', 'd': 'dependency', 'dependency': 'dependency', 'm': 'distribution', 'distribution': 'distribution', 'e': 'error', 'error': 'error', 'x': 'exclude', 'exclude': 'exclude', 'exclusive': 'exclusive', 'export': 'export', 'export-file': 'export-file', 'B': 'extra-node-info', 'extra-node-info': 'extra-node-info', 'get-user-env': 'get-user-env', 'gid': 'gid', 'gpu-bind': 'gpu-bind', 'gpu-freq': 'gpu-freq', 'G': 'gpus', 'gpus': 'gpus', 'gpus-per-node': 'gpus-per-node', 'gpus-per-socket': 'gpus-per-socket', 'gpus-per-task': 'gpus-per-task', 'gres': 'gres', 'gres-flags': 'gres-flags', 'h': 'help', 'help': 'help', 'hint': 'hint', 'H': 'hold', 'hold': 'hold', 'ignore-pbs': 'ignore-pbs', 'i': 'input', 'input': 'input', 'J': 'job-name', 'job-name': 'job-name', 'kill-on-invalid-dep': 'kill-on-invalid-dep', 'L': 'licenses', 'licenses': 'licenses', 'mail-type': 'mail-type', 'mail-user': 'mail-user', 'mcs-label': 'mcs-label', 'mem': 'mem', 'mem-bind': 'mem-bind', 'mem-per-cpu': 'mem-per-cpu', 'mem-per-gpu': 'mem-per-gpu', 'mincpus': 'mincpus', 'network': 'network', 'nice': 'nice', 'k': 'no-kill', 'no-kill': 'no-kill', 'no-requeue': 'no-requeue', 'F': 'nodefile', 'nodefile': 'nodefile', 'w': 'nodelist', 'nodelist': 'nodelist', 'N': 'nodes', 'nodes': 'nodes', 'n': 'ntasks', 'ntasks': 'ntasks', 'ntasks-per-core': 'ntasks-per-core', 'ntasks-per-gpu': 'ntasks-per-gpu', 'ntasks-per-node': 'ntasks-per-node', 'ntasks-per-socket': 'ntasks-per-socket', 'open-mode': 'open-mode', 'o': 'output', 'output': 'output', 'O': 'overcommit', 'overcommit': 'overcommit', 's': 'oversubscribe', 'oversubscribe': 'oversubscribe', 'parsable': 'parsable', 'p': 'partition', 'partition': 'partition', 'power': 'power', 'priority': 'priority', 'profile': 'profile', 'propagate': 'propagate', 'q': 'qos', 'qos': 'qos', 'Q': 'quiet', 'quiet': 'quiet', 'reboot': 'reboot', 'requeue': 'requeue', 'reservation': 'reservation', 'signal': 'signal', 'sockets-per-node': 'sockets-per-node', 'spread-job': 'spread-job', 'switches': 'switches', 'test-only': 'test-only', 'thread-spec': 'thread-spec', 'threads-per-core': 'threads-per-core', # Acceptable time formats include ""minutes"", ""minutes:seconds"", ""hours:minutes:seconds"", ""days-hours"", # ""days-hours:minutes"" and ""days-hours:minutes:seconds"". 't': 'time', 'time': 'time', 'tmp': 'tmp', 'uid': 'uid', 'usage': 'usage', 'use-min-nodes': 'use-min-nodes', 'v': 'verbose', 'verbose': 'verbose', 'V': 'version', 'version': 'version', 'W': 'wait', 'wait': 'wait', 'wait-all-nodes': 'wait-all-nodes', 'wckey': 'wckey', 'wrap': 'wrap', } if __name__ == '__main__': pass ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/mdp/mdp.py",".py","9153","245","import json from pathlib import Path from bindflow.utils.tools import List, PathLike, list_if_file _MDP_PARAM_DEFAULT = { ""integrator"": ""steep"", ""emtol"": ""1000.0"", ""nsteps"": ""5000"", ""nstlist"": ""10"", ""cutoff-scheme"": ""Verlet"", ""rlist"": ""1.0"", ""vdwtype"": ""Cut-off"", ""vdw-modifier"": ""Potential-shift-Verlet"", ""rvdw-switch"": ""0"", ""rvdw"": ""1.0"", ""coulombtype"": ""pme"", ""rcoulomb"": ""1.0"", ""epsilon-r"": ""1"", ""epsilon-rf"": ""1"", ""constraints"": ""h-bonds"", ""constraint-algorithm"": ""LINCS"" } class MDP: """"""Base class to work with MDP files """""" def __init__(self, **kwargs): self.parameters = dict() self._set_default_parameters() self.set_parameters(**kwargs) def _set_default_parameters(self): # Add any default parameters here self.parameters = _MDP_PARAM_DEFAULT def set_parameters(self, **kwargs): kwargs = {key.replace('_', '-'): value for key, value in kwargs.items()} self.parameters.update(kwargs) def from_file(self, template_filename, clean_current_parameters=True): with open(template_filename, 'r') as f: lines = f.readlines() if clean_current_parameters: # Clean all defined parameters self.parameters = {} for line in lines: if line.startswith(';') or line.startswith('#'): continue tokens = line.strip().split('=', 1) if len(tokens) != 2: continue parameter_name = tokens[0].strip().replace('_', '-') parameter_value = tokens[1].strip() self.parameters[parameter_name] = parameter_value return self def to_string(self): s = '' for parameter_name, parameter_value in self.parameters.items(): s += f'{parameter_name:<40} = {parameter_value}\n' return s def write(self, filename: str): with open(filename, 'w') as f: f.write(self.to_string()) def __repr__(self): return f""{self.__class__.__name__}({json.dumps(self.parameters, indent=4)})"" class StepMDP(MDP): """"""This subclass will inherit from :class:`bindflow.mdp.mdp.MDP` It is meant to be used in combination with the templates that can be access from ``bindflow.mdp.templates.TemplatePath``. This class define the method ``set_new_step``. One time initialized, the instance could be used to access other steps on the step_path Parameters ---------- MDP : :class:`bindflow.mdp.mdp.MDP` base MDP class """""" def __init__(self, step: str = None, step_path: PathLike = None, **kwargs): """"""Constructor. It is assume a tree directory as: .. code-block:: text . ├── emin.mdp ├── npt.mdp ├── npt-norest.mpd ├── nvt.mdp └── prod.mdp Parameters ---------- step : str, optional the step, basically the name of the mdp file on templates, by default None step_path : PathLike, optional where to look for the mdp, by default None Example ------- .. ipython:: python from bindflow.mdp import mdp from bindflow.mdp.templates import TemplatePath from pathlib import Path my_mdp = mdp.StepMDP(step='00_min', step_path=Path(TemplatePath.ligand.fep)/'coul') my_mdp.set_parameters(**{""init-lambda-state"": ""0"", ""coul-lambdas"": ""0 0.5 1""}) print(my_mdp) my_mdp.set_new_step(step='01_nvt') print(my_mdp.to_string()) """""" super().__init__(**kwargs) self.step = step self.step_path = Path(step_path) if self.step: self.__from_archive() def set_new_step(self, step): self.__from_archive(explicit_step=step) return self def __from_archive(self, explicit_step: str = None): if explicit_step: self.step = explicit_step valid_steps = [step.stem for step in list_if_file(self.step_path, ext='.mdp')] if self.step not in valid_steps: raise ValueError(f""name = {self.step} is not a valid step mdp, must be one of: {valid_steps}"") self.from_file(self.step_path/f""{self.step}.mdp"") def make_fep_dir_structure(sim_dir: PathLike, template_dir: PathLike, lambda_values: List[float], lambda_type: str, sys_type: str, dt_max: float, mdp_extra_kwargs: dict = None): """"""This function is meant to be used on ``ligand_fep_setup`` and ``complex_fet_setup`` rules. It will create the structure of the simulation directory: ``{sim_dir}/simulation/{lambda_type}.{i}/{step}/{step}.mdp`` Where: * i: init-lambda-state, * step: the name of the simulation to carry on Parameters ---------- sim_dir : PathLike Where the simulation suppose to run template_dir : PathLike This is the directory that storage the mdp templates: bindflow.mdp.templates.TemplatePath.ligand.fep or bindlfow.mdp.templates.TemplatePath.complex.fep lambda_values : List[float] This is a the list of lambda values to be used inside the mdp on the entrance {lambda_type}-lambdas lambda_type : str Must be one of the following strings ""vdw"", ""coul"", ""bonded"" (the last is for restraints) sys_type : str Must one of the following strings ""ligand"" or ""complex"". This is used in order to turn on the bonded lambdas for the complex simulations mdp_extra_kwargs : dict The MDP options for the fep calculations on every step. This dictionary must have the structure: .. code-block:: text { 'vdw':{ 'step1': , 'step2': , ... } 'coul':{ 'step1': , 'step2': , ... 'bonded':{ 'step1': , 'step2': , ... } } Raises ------ ValueError In case of an invalid ``lambda_type`` ValueError In case of an invalid ``sys_type`` """""" sim_dir = Path(sim_dir) template_dir = Path(template_dir) valid_lambda_types = [""vdw"", ""coul"", ""bonded""] valid_sys_types = ['ligand', 'complex'] if lambda_type not in valid_lambda_types: raise ValueError(f""Non valid lambda_type = {lambda_type}. Must be one of {valid_lambda_types}"") if sys_type not in valid_sys_types: raise ValueError(f""Non valid sys_type = {sys_type}. Must be one of {valid_sys_types}"") # Take from the source of the package what are the input MDP files input_mdp = [step.name for step in list_if_file(template_dir/f""{lambda_type}"", ext='.mdp')] # Create the lambda string lambda_range_str = "" "".join(map(str, lambda_values)) # Create MDP template for fep calculations mdp_template = StepMDP(step_path=template_dir/lambda_type) for mdp_file in input_mdp: step = Path(mdp_file).stem # Update MDP step mdp_template.set_new_step(step) # Check dt and set dt_max if needed, this will be overwrite by the parameters provided in the mdp section of the config if 'dt' in mdp_template.parameters: # Avoid min step, it assumes that the rest of the mdp templates steps have dt defined. if float(mdp_template.parameters['dt'].split(';')[0]) > dt_max: mdp_template.set_parameters(dt=dt_max) # Set, if any, the user MDP options if mdp_extra_kwargs: try: # TODO sanity check on the passed mdp options mdp_template.set_parameters(**mdp_extra_kwargs[lambda_type][step]) except KeyError: pass # Update lambdas mdp_template.set_parameters(**{f""{lambda_type}-lambdas"": lambda_range_str}) # Set to 1 all the bonded-lambdas in case of vdw and coul for the complex if sys_type.lower() == 'complex' and lambda_type in ['vdw', 'coul']: mdp_template.set_parameters(**{""bonded-lambdas"": "" "".join(map(str, len(lambda_values)*[1]))}) for i in range(len(lambda_values)): # Create simulation/state/step directory (sim_dir/f""simulation/{lambda_type}.{i}/{step}"").mkdir(exist_ok=True, parents=True) # Update init-lambda-state mdp_template.set_parameters(**{""init-lambda-state"": i}) # Write MDP to the proper location mdp_template.write(sim_dir/f""simulation/{lambda_type}.{i}/{step}/{step}.mdp"") def get_number_of_frames(input_mdp): loaded_mdp_params = MDP().from_file(input_mdp).parameters return -(int(loaded_mdp_params['nsteps'].split(';')[0]) // -int(loaded_mdp_params['nstxout-compressed'].split(';')[0])) # ceiling to the next int if __name__ == ""__main__"": pass ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/mdp/__init__.py",".py","0","0","","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/mdp/_path_handler.py",".py","773","27","from pathlib import Path from bindflow.utils import tools root_path = Path(__file__).resolve().parent __PathDir__ = { 'complex': { 'membrane': { 'equi': root_path/'templates/complex/membrane/equi', 'fep': root_path/'templates/complex/membrane/fep', 'mmpbsa': root_path/'templates/complex/membrane/mmpbsa', }, 'soluble': { 'equi': root_path/'templates/complex/soluble/equi', 'fep': root_path/'templates/complex/soluble/fep', 'mmpbsa': root_path/'templates/complex/soluble/mmpbsa', }, }, 'ligand': { 'equi': root_path/'templates/ligand/equi', 'fep': root_path/'templates/ligand/fep', } } _TemplatePath = tools.DotDict(**__PathDir__) ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/mdp/templates/__init__.py",".py","68","1","from bindflow.mdp._path_handler import _TemplatePath as TemplatePath","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/orchestration/flow_builder.py",".py","10021","240","import json import os import tarfile from pathlib import Path from typing import Union import numpy as np from bindflow import rules PathLike = Union[os.PathLike, str, bytes] def update_nwindows_config(config: dict) -> dict: """"""A simple function to update the config file for the entrance nwindows Parameters ---------- config : dict The configuration file with or without the nwindows keyword. In case it is present, must be in the shape of: .. code-block:: python 'nwindows': { 'ligand': { 'vdw': [11], 'coul': [11], }, 'complex': { 'vdw': [21], 'coul': [11], 'bonded': [11] }, } Returns ------- dict The updated config """""" nwindows_default = { 'ligand': { 'vdw': 11, 'coul': 11, }, 'complex': { 'vdw': 21, 'coul': 11, 'bonded': 11, }, } if 'nwindows' in config: nwindows = config['nwindows'] for key in ['ligand', 'complex']: if key in nwindows: nwindows_default[key].update(nwindows[key]) config['nwindows'] = nwindows_default return config def generate_approach_snake_file(out_file_path: str, conf_file_path: str, calculation_type: str) -> None: """"""Used to generate the main Snakefile Parameters ---------- out_file_path : str Path to write the Snakefile conf_file_path : str Path of the yml workflow configuration file. calculation_type : str Either mmpbsa or fep. """""" # Sanity check valid_calculation_type = ['mmpbsa', 'fep'] if calculation_type not in valid_calculation_type: raise ValueError(f""{calculation_type} is an invalid calculation_type, choose from {valid_calculation_type}"") file_str = ""# Load Config:\n""\ f""configfile: \'{conf_file_path}\'\n""\ ""from pathlib import Path\n\n""\ ""# Start Flow\n""\ f""include: \'{rules.super_flow}/Snakefile\'\n\n""\ ""# Specify targets and dependencies\n""\ ""rule RuleThemAll:\n"" if calculation_type == 'fep': file_str += "" input: Path(config[\""out_approach_path\""])/\""fep_results.csv\"""" elif calculation_type == 'mmpbsa': file_str += "" input: Path(config[\""out_approach_path\""])/\""mmxbsa_results.csv\"""" with open(out_file_path, 'w') as out: out.write(file_str) def approach_flow(global_config: dict, submit: bool = False) -> str: """"""It controls the rest of the workflows that make the actual calculations. It will only hang and wait till the rest subprocess finish. In case that cluster/options/job is defined in global_config, those options will be used to create the proper cluster submit script, if not cluster/option/calculation will be used instead Parameters ---------- global_config : dict The global configuration. It should contain: out_approach_path[PathLike], inputs[dict[dict]], water_model[str], host_name[str], host_selection[str] (no needed for mmpbsa), cofactor_on_protein[bool], extra_directives[dict], dt_max[float] ligand_names[list[str]], replicas[float], threads[int], samples[int] (no needed for fep) hmr_factor[float, None], custom_ff_path[str, None], cluster/type[str], cluster/options/calculation[dict] num_max_thread: int, The maximum number of threads to be used on each simulation. mdrun: dict: A dict of mdrun keywords to add to gmx mdrun, flag must be passed with boolean values. E.g {'cpi': True} extra_dependencies: A list of dependencies that must be run before gmx mdrun. Useful to launch modules as spack or conda. num_jobs: int: Maximum number of jobs to run in parallel cluster/options/job[dict]. The last is optional and will override cluster/options/calculation[dict] during submit submit : bool, optional Submit to the workload manager, by default False Returns ------- str Some identification of the submitted job. It will depend on how the submit method of the corresponded Schedular (:class:`bindflow.orchestration.generate_scheduler.Scheduler`) was implemented """""" out_path = Path(global_config[""out_approach_path""]) snake_path = out_path/""Snakefile"" approach_conf_path = out_path/""snake_conf.json"" approach_config = { ""calculation_type"": global_config[""calculation_type""], ""out_approach_path"": str(global_config[""out_approach_path""]), ""inputs"": global_config[""inputs""], ""water_model"": global_config[""water_model""], ""host_name"": global_config[""host_name""], ""fix_protein"": global_config[""fix_protein""], ""cofactor_on_protein"": global_config[""cofactor_on_protein""], ""ligand_names"": global_config[""ligand_names""], ""replicas"": global_config[""replicas""], ""hmr_factor"": global_config[""hmr_factor""], ""custom_ff_path"": global_config[""custom_ff_path""], 'threads': global_config['threads'], 'extra_directives': global_config['extra_directives'], 'retries': 3, 'dt_max': global_config['dt_max'], # With this implementation the user can select the number of windows setting them up on the global configuration. } if global_config[""calculation_type""] == 'fep': # Update number of windows if needed and create the lambda-schedule global_config = update_nwindows_config(global_config) approach_config['lambdas'] = { 'ligand': { 'vdw': list(np.round(np.linspace(0, 1, global_config['nwindows']['ligand']['vdw']), 2)), 'coul': list(np.round(np.linspace(0, 1, global_config['nwindows']['ligand']['coul']), 2)), }, 'complex': { 'vdw': list(np.round(np.linspace(0, 1, global_config['nwindows']['complex']['vdw']), 2)), 'coul': list(np.round(np.linspace(0, 1, global_config['nwindows']['complex']['coul']), 2)), 'bonded': list(np.round(np.linspace(0, 1, global_config['nwindows']['complex']['bonded']), 2)), }, } approach_config[""host_selection""] = global_config[""host_selection""] elif global_config[""calculation_type""] == 'mmpbsa': approach_config[""samples""] = global_config[""samples""] if ""mmpbsa"" in global_config.keys(): approach_config[""mmpbsa""] = global_config[""mmpbsa""] # Specify the complex type if global_config[""inputs""][""membrane""]: approach_config[""complex_type""] = 'membrane' else: approach_config[""complex_type""] = 'soluble' # Add extra mdp options if provided try: approach_config['mdp'] = global_config['mdp'] except KeyError: pass # Just to save the prefix if global_config[""job_prefix""]: approach_config[""job_prefix""] = global_config[""job_prefix""] for ligand_definition in global_config[""inputs""][""ligands""]: input_ligand_path = Path(ligand_definition['conf']) ligand_name = input_ligand_path.stem out_ligand_path = Path(global_config[""out_approach_path""])/ligand_name # Make directories on demand out_ligand_path.mkdir(exist_ok=True, parents=True) out_ligand_input_path = out_ligand_path/""input"" out_ligand_input_path.mkdir(exist_ok=True, parents=True) (out_ligand_input_path/""complex"").mkdir(exist_ok=True, parents=True) (out_ligand_input_path/""ligand"").mkdir(exist_ok=True, parents=True) # Archive original files with tarfile.open(out_ligand_input_path/'orig_in.tar.gz', ""w:gz"") as tar: tar.add(input_ligand_path, arcname=input_ligand_path.name) tar.add(global_config[""inputs""][""protein""][""conf""], arcname=Path(global_config[""inputs""][""protein""][""conf""]).name) if global_config[""inputs""][""cofactor""]: tar.add(global_config[""inputs""][""cofactor""][""conf""], arcname=Path(global_config[""inputs""][""cofactor""][""conf""]).name) if global_config[""inputs""][""membrane""]: tar.add(global_config[""inputs""][""membrane""][""conf""], arcname=Path(global_config[""inputs""][""membrane""][""conf""]).name) # Build the replicas for num_replica in range(1, global_config[""replicas""] + 1): out_replica_path = out_ligand_path/str(num_replica) out_replica_path.mkdir(exist_ok=True, parents=True) with open(approach_conf_path, ""w"") as out_IO: json.dump(approach_config, out_IO, indent=4) generate_approach_snake_file(out_file_path=snake_path, conf_file_path=approach_conf_path, calculation_type=global_config[""calculation_type""]) scheduler_class = global_config['scheduler_class'] scheduler = scheduler_class( # by default, run with the main cluster options # only if global_config[""cluster""][""options""][""job""] is defined it will change during submit cluster_config=global_config[""cluster""][""options""][""calculation""], out_dir=out_path, prefix_name=f""{global_config['job_prefix']}"", snake_executor_file='job.sh') scheduler.build_snakemake(jobs=global_config[""num_jobs""]) # Check for extra definitions if 'job' in global_config[""cluster""][""options""]: job_cluster_config = global_config[""cluster""][""options""][""job""] else: job_cluster_config = None # if global_config[""cluster""][""options""][""job""] changes during submit the cluster options # Execute the pipeline in out_approach_path cwd = os.getcwd() os.chdir(global_config[""out_approach_path""]) job_id = scheduler.submit(only_build=not submit, new_cluster_config=job_cluster_config, job_prefix=global_config[""job_prefix""]) os.chdir(cwd) return job_id ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/orchestration/generate_scheduler.py",".py","18711","445","import json import os from abc import ABC, abstractmethod from pathlib import Path from bindflow.utils import tools from bindflow.utils.cluster import _SBATCH_KEYWORDS from bindflow.utils.tools import PathLike class Scheduler(ABC): """"""Abstract Base Class to build an Schedular Class variables --------------- submit_command : str The command used for your scheduler to launch jobs cancel_command : str Command used to cancel jobs shebang : str Used to build script and detect properly the environment E.g: ``#!/bin/bash``, ``#!/bin/sh``, ... This will be used to make the ``snake_executor_file`` executable. """""" # Default class variables submit_command = None cancel_command = None shebang = None job_keyword = None def __init__(self, cluster_config: dict, out_dir: PathLike = '.', prefix_name: str = '', snake_executor_file: str = None) -> None: """"""Constructor of the class Parameters ---------- cluster_config : dict All the necessary information for the specific schedular out_dir : PathLike, optional Where all files will be exported and executed, by default '.' prefix_name : str, optional A prefix append to the jobs names for easy identification, by default '' snake_executor_file : str, optional The name/path of the file that will be used for execution of the workflow, by default None """""" self.cluster_config = cluster_config self.out_dir = Path(out_dir).resolve() self.prefix_name = prefix_name if self.prefix_name: self.prefix_name += '.' if snake_executor_file: self.snake_executor_file = self.out_dir/snake_executor_file else: self.snake_executor_file = snake_executor_file self.__cluster_validation__() @abstractmethod def __cluster_validation__(self): """"""Each scheduler should validate if the necessary options, as partition, CPUs, etc are in cluster_config. """""" ... @abstractmethod def build_snakemake(self, jobs: int): """"""Function to create the snakemake command Parameters ---------- jobs : int Number of snakemake jobs. Passed to the flag `--jobs` """""" ... @abstractmethod def submit(self, only_build: bool, new_cluster_config: dict, job_prefix: str): """"""Command to update and execute the snake_executor_file. Check the example implementations: - :meth:`bindflow.orchestration.generate_scheduler.SlurmScheduler.submit` - :meth:`bindflow.orchestration.generate_scheduler.FrontEnd.submit` Parameters ---------- only_build : bool, optional Only create the file to submit but it will not be executed, by default False new_cluster_config and job_prefix: Extra keyword arguments specific to the schedular. This makes it compatible with the current submission of :func:`bindflow.orchestration.flow_builder.approach_flow` """""" def __get_full_data(self) -> dict: """"""Get the data of the class Returns ------- dict Information of the class """""" data = { ""submit_command"": self.__class__.submit_command, ""cancel_command"": self.__class__.cancel_command, ""shebang"": self.__class__.shebang, ""job_keyword"": self.__class__.job_keyword, } data.update(self.__dict__) return data def to_json(self, out_file: str = ""cluster.json""): """"""Method to write all the attributes of the BaseCluster class to a JSON file Parameters ---------- out_file : str, optional Name of the output JSON file, by default ""cluster.config"". """""" with open(out_file, 'w') as f: json.dump(self.__get_full_data(), f, indent=4) def __repr__(self): return f""{self.__class__.__name__}(\n{json.dumps(self.__get_full_data(), indent=5)}\n)"" class SlurmScheduler(Scheduler): # Override class variables submit_command = ""sbatch"" cancel_command = ""scancel"" shebang = ""#!/bin/bash"" job_keyword = ""#SBATCH"" def __init__(self, cluster_config: dict, out_dir: PathLike = '.', prefix_name: str = '', snake_executor_file: str = None) -> None: super().__init__(cluster_config=cluster_config, out_dir=out_dir, prefix_name=prefix_name, snake_executor_file=snake_executor_file) self.__update_internal_sbatch_values__() def __cluster_validation__(self): self.cluster_config = slurm_validation(self.cluster_config) def __update_internal_sbatch_values__(self): """"""This will update self.cluster_config keywords: ntasks, cpus-per-task, job-name, output and error for better interaction with snakemake rules. """""" # Make log directory on demand cluster_log_path = (self.out_dir/'slurm_logs').resolve() cluster_log_path.mkdir(exist_ok=True, parents=True) # Make a copy of the user defined cluster configuration self._user_cluster_config = self.cluster_config.copy() # Update with internal values # threads, rule and jobid are identified and accessible during snakemake execution self.cluster_config.update( { # Always use the threads defined on the rules # Need to define in this way so MPI process detect slots properly. ""ntasks"": ""{threads}"", ""cpus-per-task"": ""1"", # Clear naming ""job-name"": f""{self.prefix_name}{{rule}}.{{jobid}}"", ""output"": cluster_log_path/f""{self.prefix_name}{{rule}}.{{jobid}}.out"", ""error"": cluster_log_path/f""{self.prefix_name}{{rule}}.{{jobid}}.err"", } ) def build_snakemake(self, jobs: int = 100000, latency_wait: int = 360, verbose: bool = False, debug_dag: bool = False, rerun_incomplete: bool = True, keep_incomplete: bool = True, keep_going: bool = True) -> str: """"""Build the snakemake command TODO Consider to put it in the parent class Parameters ---------- jobs : int, optional Use at most N CPU cluster/cloud jobs in parallel. For local execution this is an alias for --cores. Note: Set to 'unlimited' in case, this does not play a role. For cluster this is just a limitation. It is advise to provided a big number in order to do not wait for finishing of the jobs rather that launch all in the queue, by default 100000 latency_wait : int, optional Wait given seconds if an output file of a job is not present after the job finished. This helps if your filesystem suffers from latency, by default 120 verbose : bool, optional Print debugging output, by default False debug_dag : bool, optional Print candidate and selected jobs (including their wildcards) while inferring DAG. This can help to debug unexpected DAG topology or errors, by default False rerun_incomplete : bool, optional Re-run all jobs the output of which is recognized as incomplete, by default True keep_incomplete : bool, optional TODO !!! This could let to undesired effects but it is needed for GROMACS continuation Do not remove incomplete output files by failed jobs, by default True. keep_going : bool, optional Go on with independent jobs if a job fails, by default True Returns ------- str The snakemake command string. It also will set self._snakemake_str_cmd to the command string value """""" # TODO, For DEBUG Only if 'BINDFLOW_DEBUG' in os.environ: if os.environ['BINDFLOW_DEBUG'] == 'True': verbose = True debug_dag = True keep_going = False command = f""snakemake --jobs {jobs} --latency-wait {latency_wait} --cluster-cancel {self.cancel_command} "" if verbose: command += ""--verbose "" if debug_dag: command += ""--debug-dag "" if rerun_incomplete: command += ""--rerun-incomplete "" if keep_incomplete: command += ""--keep-incomplete "" if keep_going: command += ""--keep-going "" # Construct the cluster configuration command += f""--cluster '{self.submit_command}"" # Here is the only possible difference, maybe it could be creates an # abstract method that return cluster_config to a string representation valid to execute the jobs for key in self.cluster_config: command += f"" --{key}={self.cluster_config[key]}"" command += ""'"" # Just save the command in the class self._snakemake_str_cmd = command if self.snake_executor_file: with open(self.out_dir/self.snake_executor_file, 'w') as f: f.write(command) return command def submit(self, only_build: bool = False, new_cluster_config: dict = None, job_prefix: str = """") -> str: """"""Submit to the cluster the snake_executor_file Parameters ---------- only_build : bool, optional Only create the file to submit to the cluster but it will not be executed, by default False new_cluster_config : dict, optional New definition of the cluster. It could be useful to run the snakemake command with different resources as the one used on the workflow. For example, if the cluster has two partition deflt and long with 2 and 5 days as maximum time, we could run in the long partition the snakemake job and only ask for 1 CPU and in deflt the computational expensive calculations. If nothing is provided, cluster_config (passed during initialization) will be used, by default None job_prefix : bool, optional It will be added as {job_prefix}.RuleThemAll , by default False Returns ------- str The output of the submit command or None. Raises ------ RuntimeError If snake_executor_file is not present. You must declare it during initialization """""" # If extra_cluster_config, modify self.snake_executor_file # Validate # TODO: Maybe is a good idea, instead of use the whole new_cluster_config, update the current self._user_cluster_config # and then validate with slurm_validation if new_cluster_config: cluster_to_work = slurm_validation(new_cluster_config) else: cluster_to_work = self._user_cluster_config # Update some configurations: # Make log directory on demand cluster_log_path = (self.out_dir/'slurm_logs').resolve() cluster_log_path.mkdir(exist_ok=True, parents=True) cluster_to_work.update({ # Clear naming ""job-name"": f""{job_prefix}.RuleThemAll"", ""output"": cluster_log_path/f""{job_prefix}.RuleThemAll.out"", ""error"": cluster_log_path/f""{job_prefix}.RuleThemAll.err"", }) # Create the sbatch section of the script sbatch_section = f""{self.shebang}\n"" for key in cluster_to_work: sbatch_section += f""{self.job_keyword} --{key}={cluster_to_work[key]}\n"" if self.snake_executor_file: # Update snake_executor_file with open(self.snake_executor_file, 'w') as sef: sef.write(sbatch_section + self._snakemake_str_cmd) if not only_build: # Submit to the cluster process = tools.run(f""{self.submit_command} {self.snake_executor_file}"") return process.stdout else: raise RuntimeError(""'snake_executor_file' attribute is not present on the current instance. Consider to call build_snakemake first"") def slurm_validation(cluster_config: dict) -> dict: """"""Validate the provided user slurm keywords Parameters ---------- cluster_config : dict A dictionary with key[SBATCH keyword]: value[SBATCH value] Returns ------- dict Corrected dictionary. Keywords like: c or p are translated to cpu-per-task and partition respectively. Raises ------ ValueError Invalid Slurm keywords ValueError It was not provided necessary Slurm keywords """""" # Translate scheduler_directives translated_cluster_config = {} for key in cluster_config: if key not in _SBATCH_KEYWORDS: raise ValueError(f""{key} is not a valid SLURM string key"") # Check for SBATCH flags (setting by using a boolean as value) if isinstance(cluster_config[key], bool): if cluster_config[key]: # Just set the flag translated_cluster_config[_SBATCH_KEYWORDS[key]] = """" else: translated_cluster_config[_SBATCH_KEYWORDS[key]] = cluster_config[key] # Check for important missing cluster definitions # TODO, check for other kwargs if 'partition' not in translated_cluster_config: raise ValueError(""cluster_config does not have a valid SLURM definition for partition, consider to include 'p' or 'partition'"") return translated_cluster_config class FrontEnd(Scheduler): # Override class variables submit_command = ""bash"" shebang = ""#!/bin/bash"" # TODO build a class to execute the workflow in a frontend-like environment, E.g LAPTOP. def __init__(self, cluster_config: None = None, out_dir: PathLike = '.', prefix_name: str = '', snake_executor_file: str = None) -> None: super().__init__(cluster_config=cluster_config, out_dir=out_dir, prefix_name=prefix_name, snake_executor_file=snake_executor_file) def __cluster_validation__(self): ... def build_snakemake(self, jobs: int = 12, latency_wait: int = 360, verbose: bool = False, debug_dag: bool = False, rerun_incomplete: bool = True, keep_incomplete: bool = True, keep_going: bool = True) -> str: """"""Build the snakemake command TODO Consider to put it in the parent class Parameters ---------- jobs : int, optional Use at most N CPU cluster/cloud jobs in parallel. For local execution this is an alias for --cores. Note: Set to 'unlimited' in case, this does not play a role. For cluster this is just a limitation. It is advise to provided a big number in order to do not wait for finishing of the jobs rather that launch all in the queue, by default 100000 latency_wait : int, optional Wait given seconds if an output file of a job is not present after the job finished. This helps if your filesystem suffers from latency, by default 120 verbose : bool, optional Print debugging output, by default False debug_dag : bool, optional Print candidate and selected jobs (including their wildcards) while inferring DAG. This can help to debug unexpected DAG topology or errors, by default False rerun_incomplete : bool, optional Re-run all jobs the output of which is recognized as incomplete, by default True keep_incomplete : bool, optional TODO !!! This could let to undesired effects but it is needed for GROMACS continuation Do not remove incomplete output files by failed jobs, by default True. keep_going : bool, optional Go on with independent jobs if a job fails, by default True Returns ------- str The snakemake command string. It also will set self._snakemake_str_cmd to the command string value """""" # TODO, For DEBUG Only if 'BINDFLOW_DEBUG' in os.environ: if os.environ['BINDFLOW_DEBUG'] == 'True': verbose = True debug_dag = True keep_going = False command = f""snakemake --jobs {jobs} --latency-wait {latency_wait} "" if verbose: command += ""--verbose "" if debug_dag: command += ""--debug-dag "" if rerun_incomplete: command += ""--rerun-incomplete "" if keep_incomplete: command += ""--keep-incomplete "" if keep_going: command += ""--keep-going "" # Just save the command in the class self._snakemake_str_cmd = command if self.snake_executor_file: with open(self.out_dir/self.snake_executor_file, 'w') as f: f.write(command) return command def submit(self, only_build: bool = False, new_cluster_config=None, job_prefix=None) -> str: """"""Submit to the workstation the snake_executor_file Parameters ---------- only_build : bool, optional Only create the file to submit to the Frontend but it will not be executed, by default False new_cluster_config and job_prefix : Are only added for compatibility and readability. This allows the current signature used on: :func:`bindflow.orchestration.flow_builder.approach_flow` during submission In reality it will not be used at all for this class Returns ------- str The output of the submit command or None. Raises ------ RuntimeError If snake_executor_file is not present. You must declare it during initialization """""" # Create the sbatch section of the script bash_section = f""{self.shebang}\n"" if self.snake_executor_file: # Update snake_executor_file with open(self.snake_executor_file, 'w') as sef: sef.write(bash_section + self._snakemake_str_cmd) if not only_build: # Submit to the Frontend tools.run(f""{self.submit_command} {self.snake_executor_file}"", interactive=True) else: raise RuntimeError(""'snake_executor_file' attribute is not present on the current instance. Consider to call build_snakemake first"") if __name__ == ""__main__"": pass ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/orchestration/__init__.py",".py","0","0","","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/preparation/boresch.py",".py","2273","65",""""""" define restraints for ligand in protein during the uncoupling. """""" import MDAnalysis as mda from MDRestraintsGenerator import restraints, search from bindflow.utils.tools import PathLike def gen_restraint(topology: PathLike, trajectory: PathLike, ligand_selection: str = 'resname LIG and not name H*', host_selection: str = 'protein and name CA', temperature: float = 298.15, outpath: PathLike = './'): """"""It will generate the Boresch restraints. It use MDAnalysis and MDRestraintsGenerator. It defines restraints for ligand in protein during the uncoupling. Parameters ---------- topology : PathLike Path to the topology (binary) file. E.g: TPR, PRM7 trajectory : PathLike Path to the trajectory file. E.g: XTC, NC, TRJ ligand_selection : str, optional MDAnalysis selection to define the ligand, by default 'resname LIG and not name H*' host_selection : str, optional MDAnalysis selection to define the host (receptor), by default 'protein and name CA' temperature : float simulation temperature [298.15] outpath : PathLike, optional Where the output files will be written out, by default './' """""" u = mda.Universe(topology, trajectory) # exclude H* named atoms ligand_atoms = search.find_ligand_atoms(u, l_selection=ligand_selection, p_align=host_selection) # find protein atoms atom_set = [] for l_atoms in ligand_atoms: psearch = search.FindHostAtoms(u, l_atoms[0], p_selection=host_selection) psearch.run(verbose=True) atom_set.extend([(l_atoms, p) for p in psearch.host_atoms]) # Create the boresch finder analysis object boresch = restraints.FindBoreschRestraint(u, atom_set) boresch.run(verbose=True) # boresch.restraint.plot(path=args.outpath) #this is not necessary and might lead to qt errors. (can be turned on if needed) boresch.restraint.write(path=outpath) dG = boresch.restraint.standard_state(temperature=temperature) with open(f'{outpath}/dG_off.dat', 'w') as writer: writer.write(f'{dG}') if __name__ == ""__main__"": pass ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/preparation/__init__.py",".py","0","0","","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/preparation/solvent.py",".py","29753","767","#!/usr/bin/env python import logging import os import shutil import tempfile from pathlib import Path from typing import Iterable, List, Tuple, Union import yaml from parmed import Structure from bindflow.home import home from bindflow.utils import tools logger = logging.getLogger(__name__) def get_atom_types(top: tools.PathLike) -> dict: """""" Return the atomtypes section as a dict with key atom type and values the corresponded line. Include statements are not take it into account. """""" atom_types = {} with open(top, 'r') as f: lines = f.readlines() section_found = False for line in lines: if line.startswith('[ atomtypes ]'): section_found = True continue if section_found: if line.startswith(';'): continue elif (not line.strip() or line.startswith('[')) and not line.startswith('[ atomtypes ]'): section_found = False continue fields = line.split() if len(fields) >= 6: atom_type = fields[0] atom_types[atom_type] = line return atom_types def get_molecule_names(input_topology: tools.PathLike, section: str = 'molecules') -> list: """"""It gets the molecule names specified inside input_topology Parameters ---------- input_topology : tools.PathLike The path of the input topology section : str The section to extract names from: molecules or moleculetype Returns ------- list A list of the molecules presented in the topology """""" if section not in ['molecules', 'moleculetype']: raise ValueError(f""section must be 'molecules', 'moleculetype. {section} was provided."") with open(input_topology, 'r') as f: lines = f.readlines() molecules = [] i = 0 while i < len(lines): if section in lines[i]: i += 1 while (""["" not in lines[i]): if not lines[i].startswith(';'): split_line = lines[i].split() if len(split_line) == 2: molecules.append(split_line[0]) i += 1 if i >= len(lines): break i += 1 return molecules def add_posres_section(input_topology: tools.PathLike, molecules: Iterable[str], out_file: tools.PathLike = None): """"""This will add to the original topology file the corresponded POSRES section to the provided molecules: Examples of added lines: #ifdef POSRES #include ""posres_{molecule}.itp"" #endif Parameters ---------- input_topology : PathLike The path of the input topology molecules : Iterable[str] The list of name of the molecules for which the topology section will be added out_file : PathLike, optional The path to output the modified topology file, by default None. Which means that it will modify inplace input_topology. """""" with open(input_topology, ""r"") as f: top_lines = f.readlines() # This is just to be as close as possible to the result of pdb2gmx add_sol_internally = False if 'SOL' not in molecules: molecules.append('SOL') add_sol_internally = True look_out_flag = False out_lines = [] for line in top_lines: if not line.startswith(""[ molecules ]""): for molecule in molecules: if molecule in line and "" 3\n"" in line: look_out_flag = True mol_name = line.split()[0] if look_out_flag and ('[ moleculetype ]' in line or '[ system ]' in line): if mol_name == 'SOL' and add_sol_internally: out_lines.append(""\n#ifdef POSRES_WATER\n"") out_lines.append(""; Position restraint for each water oxygen\n"") out_lines.append(""[ position_restraints ]\n"") out_lines.append(""; i funct fcx fcy fcz\n"") out_lines.append("" 1 1 1000 1000 1000\n"") out_lines.append(""#endif\n\n"") else: out_lines.append(""\n#ifdef POSRES\n"") out_lines.append(f'#include ""posres_{mol_name}.itp""\n') out_lines.append(""#endif\n\n"") look_out_flag = False out_lines.append(line) if not out_file: out_file = input_topology with open(out_file, ""w"") as w: w.write("""".join(out_lines)) def make_posres(input_topology: tools.PathLike, molecules: Iterable[str], out_dir: tools.PathLike, f_xyz: tuple = (2500, 2500, 2500)): """"""Make a position restraint file out of input_topology for all the molecules specified on molecules. Taking only the heavy atoms into account Parameters ---------- input_topology : PathLike The path of the input topology molecules : Iterable[str] The list of name of the molecules for which the posres file will be created out_dir : PathLike The path where the posres files will be written f_xyz : tuple The x, y, z components of the restraint force to be used. It could be a float number of a string to be then defined on the mdp file, by default (2500, 2500, 2500) """""" for molecule in molecules: atom_flag = False with open(input_topology, ""r"") as f: top_lines = f.readlines() posres_filename = f""posres_{molecule}.itp"" with open(Path(out_dir)/posres_filename, ""w"") as posres_file: posres_file.write(""[ position_restraints ]\n"") for i, _ in enumerate(top_lines): if f""{molecule} "" in (top_lines[i]) and "" 3\n"" in (top_lines[i]): j = i + 1 while j < len(top_lines): if '[ atoms ]' in top_lines[j]: j += 1 # skip this line atom_flag = True if top_lines[j].startswith('['): # A new section was reached break if atom_flag: if not top_lines[j].startswith(""\n"") and not top_lines[j].startswith("";"") and not top_lines[j].startswith(""#""): # Check if heavy atom based on the mass. In case of use of HMR, for that reason 3 if float(top_lines[j].split()[7]) > 3: posres_str = f""{top_lines[j].split()[0]} 1 {f_xyz[0]} {f_xyz[1]} {f_xyz[2]}\n"" posres_file.write(posres_str) j += 1 break # Add posre sections to the topology add_posres_section(input_topology=input_topology, molecules=molecules, out_file=None) def _tip3p_settles_to_constraints(top: tools.PathLike, molecule: str, out_top: Union[tools.PathLike, None] = None) -> None: """"""Temporal solution to TODO (put the GitHub Issue). Basically it will change the settles entrance of `molecule` by: ; https://gromacs.bioexcel.eu/t/how-to-treat-specific-water-molecules-as-ligand/3470/9 '[ constraints ]' ; ai aj funct length 1 2 1 0.09572 1 3 1 0.09572 2 3 1 0.15139 Warning ------- This is only useful for replacing the settle section of a tip3p-like molecule. This function its just a workaround and will probably bve removed on the future Parameters ---------- top : tools.PathLike The GMX topology file molecule : str Name of the molecule where to look for the [ settles ] section out_top : Union[tools.PathLike, None], optional Path for a output topology, by default None which means that top will be modify in place. """""" constraints_section = ""; https://gromacs.bioexcel.eu/t/how-to-treat-specific-water-molecules-as-ligand/3470/9\n""\ ""[ constraints ]\n""\ ""; ai aj funct length\n""\ ""1 2 1 0.09572\n""\ ""1 3 1 0.09572\n""\ ""2 3 1 0.15139\n\n"" with open(top, 'r') as f: lines = f.readlines() idx_begins, idx_ends = None, None section_found = False i = 0 while not lines[i].startswith('[ molecules ]') and i < len(lines): if molecule in lines[i] and "" 3\n"" in lines[i]: j = i while not lines[j].startswith('[ moleculetype ]') and j < len(lines): if lines[j].startswith('[ settles ]'): section_found = True idx_begins = j j += 1 if section_found and lines[j].startswith(('[', '#')): idx_ends = j break j += 1 break i += 1 if not out_top: out_top = top with open(out_top, 'w') as f: f.write("""".join(lines[:idx_begins]) + constraints_section + """".join(lines[idx_ends:])) class Solvate: def __init__(self, water_model_code: str, builder_dir: tools.PathLike = '.solvate', load_dependencies: List[str] = None) -> None: """"""Class to solvate GMX systems. Force fields were extracted from `GMX topologies `__. Remember to cite properly the main references if you use any of the water models in your work. Available water models: * amber: * amber/spc * amber/spce * amber/tip3p * amber/tip4p * amber/tip4pew * amber/tip5p * charmm * charmm/spc * charmm/spce * charmm/tip3p * charmm/tips3p * charmm/tip4p * charmm/tip5p * oplsaa * oplsaa/spc * oplsaa/spce * oplsaa/tip3p * oplsaa/tip4p * oplsaa/tip4pew * oplsaa/tip5p * oplsaa/tip5pe Parameters ---------- water_model_code : str Water model code in the form: ""{force field family}/{water model}"" builder_dir : tools.PathLik, optional Where the temporal files will be written. load_dependencies : List[str], optional It is used in case some previous loading steps are needed for GROMACS commands; e.g: ['source /groups/CBG/opt/spack-0.18.1/shared.bash', 'module load sandybridge/gromacs/2022.4'], by default None Raises ------ ValueError Invalid force field family ValueError Invalid water model for the selected force field """""" self.load_dependencies = load_dependencies self.builder_dir = Path(builder_dir).resolve() self.builder_dir.mkdir(exist_ok=True, parents=True) # Make directory to save topologies after solvation. # This will be cleaned out and created every time the class is called (at the beginning) # to avoid mismatch.ch between files generated on different calls self.solvated_dir = self.builder_dir/'solvated_sys' with open(Path(home(dataDir='gmx_water_models'))/'water_models.yml', 'r') as f: self.water_models_data = yaml.safe_load(f) # Check validity of input code force_field_family, water_model = water_model_code.split('/') if force_field_family not in self.water_models_data: raise ValueError(f""Invalid force field family: {force_field_family}. Choose from {self.water_models_data.keys()}"") elif water_model not in self.water_models_data[force_field_family]: raise ValueError(f""Invalid water model ({water_model}) for {force_field_family}."" f""Choose from {self.water_models_data[force_field_family].keys()}"") self.force_field_family = force_field_family self.water_model = water_model self.water_itp, self.ions_itp, self.ffnonbonded_itp, self.water_gro = self._get_gmx_water_model() self.cwd = os.getcwd() if load_dependencies: if isinstance(load_dependencies, List): self.load_dependencies = tools.HARD_CODE_DEPENDENCIES + [""export GMX_MAXBACKUP=-1""] + load_dependencies else: raise ValueError(f""load_dependencies must be a List. Provided: {load_dependencies}"") def _get_gmx_water_model(self) -> Tuple[tools.PathLike]: """""" Retrieve water model files Returns ------- Tuple[PathLike] A tuple with the absolute path of (in this order): * water itp file * ions itp file * water (configuration) gro file * atom type itp definition """""" # Extract water and ions topologies ff_dir = Path(home(dataDir='gmx_water_models')) water_itp = (ff_dir/str(self.force_field_family)/f""{self.water_model}.itp"").resolve() ions_itp = (ff_dir/str(self.force_field_family)/""ions.itp"").resolve() ffnonbonded_itp = (ff_dir/str(self.force_field_family)/""ffnonbonded.itp"").resolve() water_gro = (ff_dir/""configurations""/self.water_models_data[self.force_field_family][self.water_model]).resolve() return water_itp, ions_itp, ffnonbonded_itp, water_gro def _include_all_atom_types(self, top: tools.PathLike) -> None: """"""Add all the atom types of the corresponded force field family They will be added to the first [ atomtypes ] section on the file top. Parameters ---------- top : top: tools.PathLike Topology file to be modified. """""" with open(top, 'r') as f: lines = f.readlines() idx_begins, idx_ends = None, None section_found = False for i, line in enumerate(lines): if line.startswith('[ atomtypes ]'): idx_begins = i + 1 section_found = True continue if section_found: if line.startswith('['): idx_ends = i break # Add missing atom_types for solvation # Extra atom_types will be removed when parmed write the structure if idx_begins is not None and idx_ends is not None: atom_types = get_atom_types(top) for atom_type_name, atom_type_info in get_atom_types(self.ffnonbonded_itp).items(): if atom_type_name not in atom_types: atom_types[atom_type_name] = atom_type_info with open(top, 'w') as f: f.write("""".join(lines[:idx_begins] + list(atom_types.values()) + [""\n\n""] + lines[idx_ends:])) def _include_water_ions_params(self, top: tools.PathLike) -> None: """"""It add include statements to the corresponded water and ion itp files Parameters ---------- top : tools.PathLike The topology file """""" include_statements = [ f""#include \""{self.water_itp}\""\n"", f""#include \""{self.ions_itp}\""\n"", ] with open(top, 'r') as f: lines = f.readlines() for idx, line in enumerate(lines): if line.startswith('[ system ]'): break with open(top, 'w') as f: f.write("""".join(lines[:idx] + include_statements + lines[idx:])) def _add_water_and_ions( self, gro: tools.PathLike, top: tools.PathLike, bt: str = ""triclinic"", box: list[float] = None, angles: list[float] = None, d: float = None, c: bool = False, pname: str = ""NA"", nname: str = ""CL"", ion_conc: float = 150E-3, rmin: float = 1.0) -> None: """"""Make box, solvate and add ions to the system Parameters ---------- gro : tools.PathLike The configuration file. top: tools.PathLike The GMX's topology file. bt : str, optional Box type for -box and -d: triclinic, cubic, dodecahedron, octahedron, by default triclinic box : str, optional Box vector lengths (a,b,c) in nm (remember that PDB are in Angstroms), by default None. Which means that gmx editconf will use (0 0 0) angles : Iterable[float], optional This is the angles between the components of the vector in DEGREES. It is important that the provided vector has the correct units, by default None. For membrane systems (90,90,60) is advisable. d : float, optional Distance between the solute and the box, by default None. Which means that gmx editconf will use 0 c : bool, optional Center molecule in box (implied by -box and -d), by default False pname : str, optional Name of the positive ion, by default NA nname : str, optional Name of the negative ion, by default CL ion_conc : float, optional Ion concentration used during neutralization of the system, by default 150E-3 rmin : float, optional Minimum distance between ions and non-solvent, by default 1.0 out_dir : PathLike, optional Where the files will be written: solvated.gro, solvated.top, by default '.' """""" # We can change directory because all the path used are already converted to absolute paths os.chdir(self.solvated_dir) editconf_kwargs = dict( f=gro, o=gro, bt=bt ) if box: editconf_kwargs['box'] = ' '.join([str(i) for i in box]) if angles: editconf_kwargs['angles'] = ' '.join([str(i) for i in angles]) if d: editconf_kwargs['d'] = d if c: editconf_kwargs['c'] = True # First write an mdp file. with open(""ions.mdp"", ""w"") as file: file.write(""; Neighbor searching\n"" ""cutoff-scheme = Verlet\n"" ""rlist = 1.1\n"" ""pbc = xyz\n"" ""verlet-buffer-tolerance = -1\n"" ""\n; Electrostatics\n"" ""coulombtype = cut-off\n"" ""\n; VdW\n"" ""rvdw = 1.0\n"") # It is failing becasue There is not define the atom type for the water molecules # Define GMX functions @tools.gmx_command(load_dependencies=self.load_dependencies) def editconf(**kwargs): ... @tools.gmx_command(load_dependencies=self.load_dependencies) def solvate(**kwargs): ... @tools.gmx_command(load_dependencies=self.load_dependencies) def grompp(**kwargs): ... @tools.gmx_command(load_dependencies=self.load_dependencies, stdin_command=""echo \""SOL\"""") def genion(**kwargs): ... # Execute the GMX functions editconf(**editconf_kwargs) solvate(cp=gro, p=top, cs=self.water_gro, o=gro) grompp(f=""ions.mdp"", c=gro, p=top, o=""ions.tpr"") genion(s=""ions.tpr"", p=top, o=gro, neutral=True, pname=pname, nname=nname, rmin=rmin, conc=ion_conc) # Just to clean the topology. In this way only the used atom types are written. # And the include statements are removed # It builds a monolithic topology struc = tools.readParmEDMolecule(top_file=top, gro_file=gro) struc.save(str(top), overwrite=True) struc.save(str(gro), overwrite=True) # Change back to cwd os.chdir(self.cwd) def clean(self, directory: Union[None, tools.PathLike] = None) -> None: """"""Used to delete self.builder_dir or directory if provided Danger ------ Use it wisely (when directory is provided), you may ended up deleting your computer :-) Parameters ---------- directory : Union[None, tools.PathLike], optional Directory to delete, by default None """""" os.chdir(self.cwd) if directory: dir2delete = directory else: dir2delete = self.builder_dir try: shutil.rmtree(dir2delete) except FileNotFoundError: pass def __enter__(self): return self def __exit__(self, exception_type, exception_value, exception_traceback): self.clean() def __call__( self, structure: Structure, bt: str = ""triclinic"", box: list[float] = None, angles: list[float] = None, d: float = None, c: bool = False, pname: str = ""NA"", nname: str = ""CL"", ion_conc: float = 150E-3, rmin: float = 1.0, exclusion_list: list = None, out_dir: tools.PathLike = '.', out_name: str = 'solvated', f_xyz: tuple = (2500, 2500, 2500), settles_to_constraints_on: Union[tools.PathLike, str] = None) -> None: if exclusion_list is None: exclusion_list = [""SOL"", ""NA"", ""CL""] # ""MG"", ""ZN""] # Clean any possible generated files during previous calls out_dir = Path(out_dir) self.clean(self.solvated_dir) self.solvated_dir.mkdir(exist_ok=True, parents=True) out_dir.mkdir(exist_ok=True, parents=True) # Set out files init_top = self.solvated_dir/'init.top' init_gro = self.solvated_dir/'init.gro' # Write the top and gro file of the structure structure.save(str(init_top), overwrite=True) structure.save(str(init_gro), overwrite=True) # Add ion and water section to the topology self._include_water_ions_params(init_top) # Include all the atom types of the force field self._include_all_atom_types(init_top) # Solvate add ions and clean the topology self._add_water_and_ions( gro=init_gro, top=init_top, bt=bt, box=box, angles=angles, d=d, c=c, pname=pname, nname=nname, ion_conc=ion_conc, rmin=rmin) # Add position restraint section to topology molecules = list(set(get_molecule_names(init_top)) - set(exclusion_list)) # Here I have to move the files to the final directory with its specified names make_posres( input_topology=init_top, molecules=molecules, out_dir=out_dir, f_xyz=f_xyz ) # Fix conversion for constraints to settles on water-like molecules if settles_to_constraints_on: _tip3p_settles_to_constraints(top=init_top, molecule=settles_to_constraints_on, out_top=None) shutil.copy(init_top, out_dir/f'{out_name}.top') shutil.copy(init_gro, out_dir/f'{out_name}.gro') def index_for_membrane_system( configuration_file: tools.PathLike, ndxout: tools.PathLike = ""index.ndx"", ligand_name: str = ""LIG"", host_name: str = ""Protein"", cofactor_name: str = None, cofactor_on_protein: bool = True, load_dependencies: List[str] = None): """"""Make the index file for membrane systems with SOLU, MEMB and SOLV. It uses gmx make_ndx and select internally. One examples selection that can be created with ligand_name = LIG; cofactor_name = COF and cofactor_on_protein = True is: #. ""RECEPTOR"" group {host_name}; #. ""LIGAND"" resname {ligand_name}; #. ""SOLU"" group {host_name} or resname {ligand_name} or resname COF; #. ""MEMB"" ((group System and ! group Water_and_ions) and ! group {host_name}) and ! (resname {ligand_name}) and ! (resname COF); #. ""SOLV"" group Water_and_ions; Parameters ---------- configuration_file : PathLike PDB or GRO file of the system. ndxout : PathLike Path to output the index file. ligand_name : str The residue name for the ligand in the configuration file, by default ""LIG"". host_name : str The group name for the host in the configuration file, by default ""Protein"". cofactor_name : str The residue name for the cofactor in the configuration file, bt default None cofactor_on_protein : bool It only works if cofactor_name is provided. If True, the cofactor will be part of the protein and the lignad if False will be part of the solvent and ions, bt default True load_dependencies : List[str], optional It is used in case some previous loading steps are needed for GROMACS commands; e.g: ['source /groups/CBG/opt/spack-0.18.1/shared.bash', 'module load sandybridge/gromacs/2022.4'], by default None """""" tmpopt = tempfile.NamedTemporaryFile(suffix='.opt') tmpndx = tempfile.NamedTemporaryFile(suffix='.ndx') # Nice use of gmx select, see the use of the parenthesis sele_RECEPTOR = f""\""RECEPTOR\"" group {host_name}"" sele_LIGAND = f""\""LIGAND\"" resname {ligand_name}"" sele_MEMB = f""\""MEMB\"" ((group System and ! group Water_and_ions) and ! group {host_name}) and ! (resname {ligand_name})"" sele_SOLU = f""\""SOLU\"" group {host_name} or resname {ligand_name}"" sele_SOLV = ""\""SOLV\"" group Water_and_ions"" if cofactor_name: sele_MEMB += f"" and ! (resname {cofactor_name})"" if cofactor_on_protein: sele_SOLU += f"" or resname {cofactor_name}"" else: sele_SOLV += f"" or resname {cofactor_name}"" logger.info(""Groups in the index.ndx file:"") logger.info(f""\t{sele_RECEPTOR}"") logger.info(f""\t{sele_LIGAND}"") logger.info(f""\t{sele_SOLU}"") logger.info(f""\t{sele_MEMB}"") logger.info(f""\t{sele_SOLV}"") sele_RECEPTOR += "";\n"" sele_LIGAND += "";\n"" sele_SOLU += "";\n"" sele_MEMB += "";\n"" sele_SOLV += "";\n"" with open(tmpopt.name, ""w"") as opt: opt.write(sele_RECEPTOR + sele_LIGAND + sele_SOLU + sele_MEMB + sele_SOLV) @tools.gmx_command(load_dependencies=load_dependencies, stdin_command=""echo \""q\"""") def make_ndx(**kwargs): ... @tools.gmx_command(load_dependencies=load_dependencies) def select(**kwargs): ... make_ndx(f=configuration_file, o=tmpndx.name) select(s=configuration_file, sf=tmpopt.name, n=tmpndx.name, on=ndxout) # tools.run(f"""""" # export GMX_MAXBACKUP=-1 # echo ""q"" | gmx make_ndx -f {configuration_file} -o {tmpndx.name} # gmx select -s {configuration_file} -sf {tmpopt.name} -n {tmpndx.name} -on {ndxout} # """""") # deleting the line _f0_t0.000 in the file with open(ndxout, ""r"") as index: data = index.read() data = data.replace(""_f0_t0.000"", """") with open(ndxout, ""w"") as index: index.write(data) tmpopt.close() tmpndx.close() def index_for_soluble_system( configuration_file: tools.PathLike, ndxout: tools.PathLike = ""index.ndx"", ligand_name: str = ""LIG"", host_name: str = ""Protein"", load_dependencies: List[str] = None): """"""Make the index file for soluble system. This is only needed in case MMPBSA calculation; #. ""RECEPTOR"" group {host_name}; #. ""LIGAND"" resname {ligand_name}; Parameters ---------- configuration_file : PathLike PDB or GRO file of the system. ndxout : PathLike Path to output the index file. ligand_name : str The residue name for the ligand in the configuration file, by default ""LIG"". host_name : str The group name for the host in the configuration file, by default ""Protein"". load_dependencies : List[str], optional It is used in case some previous loading steps are needed for GROMACS commands; e.g: ['source /groups/CBG/opt/spack-0.18.1/shared.bash', 'module load sandybridge/gromacs/2022.4'], by default None """""" tmpopt = tempfile.NamedTemporaryFile(suffix='.opt') tmpndx = tempfile.NamedTemporaryFile(suffix='.ndx') sele_RECEPTOR = f""\""RECEPTOR\"" group {host_name}"" sele_LIGAND = f""\""LIGAND\"" resname {ligand_name}"" logger.info(""Groups in the index.ndx file:"") logger.info(f""\t{sele_RECEPTOR}"") logger.info(f""\t{sele_LIGAND}"") sele_RECEPTOR += "";\n"" sele_LIGAND += "";\n"" with open(tmpopt.name, ""w"") as opt: opt.write(sele_RECEPTOR + sele_LIGAND) @tools.gmx_command(load_dependencies=load_dependencies, stdin_command=""echo \""q\"""") def make_ndx(**kwargs): ... @tools.gmx_command(load_dependencies=load_dependencies) def select(**kwargs): ... make_ndx(f=configuration_file, o=tmpndx.name) select(s=configuration_file, sf=tmpopt.name, n=tmpndx.name, on=ndxout) # tools.run(f"""""" # export GMX_MAXBACKUP=-1 # echo ""q"" | gmx make_ndx -f {configuration_file} -o {tmpndx.name} # gmx select -s {configuration_file} -sf {tmpopt.name} -n {tmpndx.name} -on {ndxout} # """""") # deleting the line _f0_t0.000 in the file with open(ndxout, ""r"") as index: data = index.read() data = data.replace(""_f0_t0.000"", """") with open(ndxout, ""w"") as index: index.write(data) tmpopt.close() tmpndx.close() if __name__ == '__main__': pass ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/preparation/system_builder.py",".py","32407","716","#!/usr/bin/env python import copy import logging import os import shutil import tarfile import warnings from itertools import chain from pathlib import Path from typing import List, Union from parmed.structure import Structure from parmed.tools.actions import HMassRepartition from toff import Parameterize from bindflow.home import home from bindflow.preparation import solvent from bindflow.utils import tools from bindflow.utils.tools import PathLike, recursive_update_dict, run # from pdbfixer import PDBFixer logger = logging.getLogger(__name__) def get_gmx_ff(ff_code: str, out_dir: PathLike = '.') -> PathLike: """"""Get GROMACS Force Field Parameters ---------- ff_code : PathLike The identification of the gromacs force field. For now only: Slipids_2020 and amber99sb-star-ildn are supported. out_dir : PathLike, optional Where the file will be decompress, by default '.' """""" out_dir = Path(out_dir).resolve() supported_ff = [ 'Slipids_2020', 'amber99sb-star-ildn', ] if ff_code not in supported_ff: raise ValueError(f""ff_code = {ff_code} is not valid. Chose between: {supported_ff}"") else: fname = home(dataDir='gmx_ff')/f'{ff_code}.ff.tar.gz' tar = tarfile.open(fname, ""r:gz"") tar.extractall(out_dir) tar.close() return out_dir/f'{ff_code}.ff' def system_combiner(**md_elements): """"""This function simply sum up all the elements provided as keyword arguments. Returns ------- object any Python object with the method sum implemented. In case elements that evaluate as False in Python will not be taken into account: E.g. False, 0, '', None Raises ------ RuntimeError In case all the elements evaluate as False """""" if any(md_elements.values()): # md_system = sum(element for element in md_elements.values() if element) # it does not work with sum # Use copy to avoid inplace modifications for element in md_elements: if md_elements[element]: try: md_system += copy.copy(md_elements[element]) except NameError: md_system = copy.copy(md_elements[element]) else: raise RuntimeError(f""\t* system_combiner failed with the inputs: {md_elements}"") logger.info(f"" The system was constructed as follows: {' + '.join([key for key in md_elements if md_elements[key]])}"") return md_system def make_bindflow_dir(out_dir: PathLike, ligand_dir: PathLike, sys_dir: PathLike): """"""A copy and paste function to create the structure of the BindFlow directory Parameters ---------- out_dir : PathLike Where the complex and the ligand systems will be created ligand_dir : PathLike Origin of the ligand inputs configuration and topologies files sys_dir : PathLike Origin of the complex inputs configuration and topologies files """""" out_dir = Path(out_dir) ligand_dir = Path(ligand_dir) sys_dir = Path(sys_dir) complex_out = out_dir/""complex"" ligand_out = out_dir/""ligand"" complex_out.mkdir(exist_ok=True, parents=True) ligand_out.mkdir(exist_ok=True, parents=True) for itp_ndx_file in chain(ligand_dir.rglob(""*.itp""), ligand_dir.rglob(""*.ndx"")): shutil.copy(src=itp_ndx_file, dst=ligand_out) shutil.copyfile(src=ligand_dir/""solvated.gro"", dst=ligand_out/""ligand.gro"") shutil.copyfile(src=ligand_dir/""solvated.top"", dst=ligand_out/""ligand.top"") for itp_ndx_file in chain(sys_dir.rglob(""*.itp""), sys_dir.rglob(""*.ndx"")): shutil.copy(src=itp_ndx_file, dst=complex_out) shutil.copyfile(src=sys_dir/""solvated.gro"", dst=complex_out/""complex.gro"") # The last one in be copy, this will be used in the snake rule shutil.copyfile(src=sys_dir/""solvated.top"", dst=complex_out/""complex.top"") class CRYST1: """"""https://www.wwpdb.org/documentation/file-format-content/format33/sect8.html#CRYST1 """""" def __init__(self, line: str = None): """"""The constructor Parameters ---------- line : str, optional a line to process, by default None """""" if line: self.a = float(line[6:15]) # Real(9.3) a a (Angstroms). self.b = float(line[15:24]) # Real(9.3) b b (Angstroms). self.c = float(line[24:33]) # Real(9.3) c c (Angstroms). self.alpha = float(line[33:40]) # Real(7.2) alpha alpha (degrees). self.beta = float(line[40:47]) # Real(7.2) beta beta (degrees). self.gamma = float(line[47:54]) # Real(7.2) gamma gamma (degrees). self.sGroup = line[55:66] # LString sGroup Space group. try: self.z = int(line[66:70]) # Integer z Z value. except ValueError: self.z = """" self.__is_init = True else: self.__is_init = False def from_pdb(self, file: PathLike): """"""Initialize the class from a pdb file Parameters ---------- file : PathLike The PDB file """""" with open(file, 'r') as f: for line in f.readlines(): if line.startswith('CRYST1'): self.__init__(line) self.__is_init = True break if not self.__is_init: warnings.warn('from_pdb was not able to initialize {self.__class__.__name__}') def __getitem__(self, key): return self.__dict__[key] def string(self): string_repr = ""CRYST1%9.3f%9.3f%9.3f%7.2f%7.2f%7.2f%-12s%4s\n"" %\ (self.a, self.b, self.c, self.alpha, self.beta, self.gamma, self.sGroup, self.z) return string_repr def __repr__(self): return self.string() class MakeInputs: """"""This class is used for building the systems for a BindFlow calculation. It will create the necessary topology and configuration files, as well the correct directory trees. """""" def __init__(self, protein: dict = None, host_name: str = ""Protein"", membrane: dict = None, cofactor: dict = None, cofactor_on_protein: bool = True, water_model: str = 'amber/tip3p', custom_ff_path: Union[None, PathLike] = None, hmr_factor: Union[float, None] = None, fix_protein: bool = True, builder_dir: PathLike = 'builder', load_dependencies: List[str] = None): """"""Constructor Parameters ---------- protein : dict, optional This is a dictionary with the following information for the protein: * conf -> The path of the protein PDB/GRO file [mandatory] * top -> GROMACS topology [optional], by default None. Should be a single file topology with all the force field information and without the position restraint included. However, in case, you need to use an include statement such as: include ""./charmm36-jul2022.ff/forcefield.itp"" You must change the statement to the absolute path: include ""{prefix of the absolute path}/charmm36-jul2022.ff/forcefield.itp"" And copy the charmm36-jul2022.ff to custom_ff_path and set this parameter accordingly. If not you may get some errors about files not founded. The force field directory must end with the suffix "".ff"". * ff * code -> GMX force field code [optional], by default amber99sb-ildn You can use your custom force field, but custom_ff_path must be provided host_name : str The group name for the host in the configuration file, by default ""Protein"" membrane : dict, optional This is a dictionary with the following information for the membrane: * conf -> The path of the membrane PDB file [mandatory]. If provided, the PDB must have a correct definition of the CRYST1. This information will be used for the solvation step. The membrane must be already correctly placed around the protein. Servers like CHARM-GUI can be used on this step. * top -> GROMACS topology [optional], by default None. Should be a single file topology with all the force field information and without the position restraint included. However, in case, you need to use an include statement such as: include ""./amber-lipids14.ff/forcefield.itp"" You must change the statement to the absolute path: include ""{prefix of the absolute path}/amber-lipids14.ff/forcefield.itp"" And copy theamber-lipids14.ff to custom_ff_path and set this parameter accordingly. If not You may get some errors about files not founded. The force field directory must end with the suffix "".ff"". * ff * code -> GMX force field code [optional], by default Slipids_2020 You can use yoru custom force field, but custom_ff_path must be provided cofactor : dict, optional This is a dictionary with the following information for the cofactor: * conf -> The path of the small molecule file [mandatory] * top -> GROMACS topology [optional]. Must be a single file topology with all the force field information and without the position restraint included, by default None * ff: * type -> openff, gaff or espaloma * code -> force field code [optional], by default depending on type * openff -> openff_unconstrained-2.0.0.offxml * gaff -> gaff-2.11 * espaloma -> espaloma-0.3.1 With this parameter you can access different small molecule force fields * is_water -> If presents and set to True; it is assumed that this is a water system and that will change the settles section (if any) to tip3p-like triangular constraints. This is needed for compatibility with GROMACS. Check here: https://gromacs.bioexcel.eu/t/how-to-treat-specific-water-molecules-as-ligand/3470/9 cofactor_on_protein : bool It is used during the index generation for membrane systems. It only works if cofactor_mol is provided. If True, the cofactor will be part of the protein and the ligand if False will be part of the solvent and ions. This is used mainly for the thermostat. By default True hmr_factor : float, optional The Hydrogen Mass Factor to use, by default None .. warning:: For provided topologies if hmr_factor is set, it will pass any way. So for topology files with already HMR, this should be None. And all the topologies should be provided protein, cofactors, membrane, ligands with the HMR already done water_model : str, optional The water force field to use, by default amber/tip3p. if you would likle to use the flexible definition of the CHARMM TIP3P you must define FLEXIBLE and CHARMM_TIP3P in the define statement of the mdp file custom_ff_path : Union[None, PathLike], optional All the custom force field must be in this directory. The class will set: os.environ[""GMXLIB""] = os.path.abspath(custom_ff_path) fix_protein : bool, optional If True, `pdbfixer` will be applied with flags `--add-atoms=all --replace-nonstandard` and `gmx editconf` will the `-ignh` flag. This is needed to avoid possible issues when processing the structure through GROMACS. To kept an specific protonation state is advised to input the full definition of the protein (.top, .gro) or a PDB with the atom-naming (mainly H-naming) consistent with your selected force field. This should be used for protein mainly, by default True builder_dir : PathLike, optional Where all the building files. After completion you can safely remove calling the method clean, by default builder load_dependencies : List[str], optional It is used in case some previous loading steps are needed for GROMACS commands; e.g: ['source /groups/CBG/opt/spack-0.18.1/shared.bash', 'module load sandybridge/gromacs/2022.4'], by default None """""" self.protein = protein self.host_name = host_name self.membrane = membrane self.cofactor = cofactor self.cofactor_on_protein = cofactor_on_protein self.hmr_factor = hmr_factor self.water_model = water_model self.fix_protein = fix_protein self.load_dependencies = load_dependencies self.wd = Path(builder_dir).resolve() self.wd.mkdir(exist_ok=True, parents=True) self.__self_was_called = False # Setting environmental variable for user custom force field: if custom_ff_path: self.custom_ff_path = Path(custom_ff_path).resolve() os.environ[""GMXLIB""] = str(self.custom_ff_path) else: self.custom_ff_path = None # Initialize vectors and angles based on the information of the PDB only if a membrane system if self.membrane: cryst_info = CRYST1() cryst_info.from_pdb(self.membrane['conf']) self.vectors = (cryst_info.a/10, cryst_info.b/10, cryst_info.c/10) # Must convert form Angstrom to nm self.angles = (cryst_info.alpha, cryst_info.beta, cryst_info.gamma) logger.info(f""This is a membrane system. Crystal information was taken from the configuration of: "" f""{self.membrane} and it will be used for solvating the system as a GROMACS triclinic box: \n\t{cryst_info}"") else: self.vectors, self.angles = None, None self.cwd = os.getcwd() def small_mol_process(self, mol_definition: dict, name: str = ""MOL"", safe_naming_prefix: str = None): """"""Get parameters for small molecules: ligands, cofactors, ... Parameters ---------- mol_definition : dict This is a dictionary with: * conf -> The path of the small molecule MOL/SDF file [mandatory]. In case that top is provided, this must be a .gro, a ValueError will be raised if it is not the case the molecule will not get its parameters. * top -> GROMACS topology [optional]. Must be a single file topology with all the force field information and without the position restraint included, by default None * ff: * type -> openff, gaff or espaloma * code -> force field code [optional], by default depending on type * openff -> openff_unconstrained-2.0.0.offxml * gaff -> gaff-2.11 * espaloma -> espaloma-0.3.1 name : str, optional Name to give, by default ""MOL"" safe_naming_prefix : str, optional This is used to be sure that there will not happen any naming conflict in hte topologies, by default None name and safe_naming_prefix will only be used if top is not provided in mol_definition. Returns ------- object The BioSimSpace system """""" force_field_code_default = { 'openff': 'openff_unconstrained-2.0.0.offxml', 'gaff': 'gaff-2.11', 'espaloma': 'espaloma-0.3.1' } dict_to_work = { 'top': None, 'ff': { 'type': 'openff', 'code': None, } } if mol_definition: recursive_update_dict(dict_to_work, mol_definition) # Only apply string operations if it is a string if isinstance(dict_to_work['ff']['type'], str): dict_to_work['ff']['type'] = str(dict_to_work['ff']['type']).lower() if dict_to_work['ff']['type'] not in force_field_code_default and not dict_to_work['top']: raise ValueError(f""Molecule {dict_to_work} has non valid type for the force field. Choose from {force_field_code_default.keys()}."") # Plug back the default option in case that the user defined None for the code but type was provided correctly # type = None, 0, '' will evaluated as False if not dict_to_work['ff']['code'] and dict_to_work['ff']['type']: dict_to_work['ff']['code'] = force_field_code_default[dict_to_work['ff']['type']] else: raise ValueError(f""Molecule {mol_definition} has a wrong definition."") if dict_to_work['conf']: if dict_to_work['top']: logger.info(f""Using supplied: {dict_to_work['top']} for {dict_to_work['conf']}"") else: logger.info(f""Getting {dict_to_work['ff']['code']} (type = {dict_to_work['ff']['type']}) parameters for: {dict_to_work['conf']}"") else: raise ValueError(f""Molecule {mol_definition} has a wrong configuration"") # Set flag to False by default provided_top_flag = False if dict_to_work['top']: top_file = Path(dict_to_work['top']).resolve() # In case the user provided a top, set the flag to True provided_top_flag = True if Path(dict_to_work['conf']).suffix == '.gro': gro_file = Path(dict_to_work['conf']).resolve() else: raise ValueError(""For safety reasons, if top is provided for small molecule; "" f""the gro file must be provided. Provided: {dict_to_work['conf']}."") else: parameterizer = Parameterize( force_field_code=dict_to_work['ff']['code'], force_field_type=dict_to_work['ff']['type'], ext_types=['top', 'gro'], hmr_factor=self.hmr_factor, overwrite=True, safe_naming_prefix=safe_naming_prefix, out_dir=self.wd, ) # Actually you can pass to parameterize Chem.rdchem.Mol, *.inchi, *.smi, *.mol, *.mol2, *.sdf parameterizer(input_mol=dict_to_work['conf'], mol_resi_name=name) top_file = self.wd/f""{name}.top"" gro_file = self.wd/f""{name}.gro"" parmed_system = tools.readParmEDMolecule(top_file=top_file, gro_file=gro_file) if provided_top_flag and self.hmr_factor: HMassRepartition(parmed_system, self.hmr_factor).execute() return parmed_system def gmx_process(self, mol_definition: dict, is_membrane: bool = False) -> Structure: """"""Used to process the compatibles biomolecules. By default it will use amber99sb-ildn (protein, DNA, ..) Slipids_2020 (membrane). However, these setups are overwritten by the definitions on `mol_definition` Parameters ---------- mol_definition : dict This dictionary with the self.protein or self.membrane. See the constructor-method's documentation for more information in its definition. is_membrane : bool, optional If True, Slipids_2020 will be set as internal default instead of amber99sb-ildn, by default False Returns ------- Structure A parameterize Structure object """""" check_box = False # Setting default parameters dict_to_work = { 'top': None, 'ff': { 'code': 'Slipids_2020' if is_membrane else 'amber99sb-ildn', } } if mol_definition: recursive_update_dict(dict_to_work, mol_definition) else: return None if dict_to_work['conf']: dict_to_work['conf'] = Path(dict_to_work['conf']).resolve() name, ext = dict_to_work['conf'].stem, dict_to_work['conf'].suffix if dict_to_work['top']: # Convert to absolute paths dict_to_work['top'] = Path(dict_to_work['top']).resolve() logger.info(f""Using supplied: {dict_to_work['top']} for {dict_to_work['conf']}"") else: logger.info(f""Getting {dict_to_work['ff']['code']} parameters for: {dict_to_work['conf']}"") else: return None gro_out = self.wd/f'{name}.gro' top_out = self.wd/f'{name}.top' posre_out = self.wd/f'{name}_posre.itp' if is_membrane: if dict_to_work['ff']['code'] == 'Slipids_2020': # Retrieve internal Slipids_2020 only if the user did not provided this force field if self.custom_ff_path: if 'Slipids_2020' not in list(self.custom_ff_path.iterdir()): get_gmx_ff('Slipids_2020', out_dir=self.wd) else: get_gmx_ff('Slipids_2020', out_dir=self.wd) # TODO Something strange is going on with the posre files. Those are not been used, however, the include statement should be in the topology # and becasue I call fix_topology on __call__ the include section of the position # restraint should be duplicated but it is not the case, not sure why os.chdir(self.wd) if dict_to_work['top']: shutil.copy(dict_to_work['top'], top_out) if ext == '.pdb': # This is needed as PDB have a tendency to do not have the box informaiton (CRYST1) # In such case, problems during solvation happens at parmed level when writing. # pdb2gmx adds by defualt some box info (most outer else) # GRO files ussully have non-zero boxes check_box = True @tools.gmx_command(load_dependencies=self.load_dependencies) def editconf(**kwargs): ... # If the PDB does not have CRYST1, it will generated as vecotr 0 0 0 on the gro file editconf(f=dict_to_work['conf'], o=gro_out) elif ext == '.gro': shutil.copy(dict_to_work['conf'], gro_out) else: raise ValueError(f""Extension of {dict_to_work['conf']} must be .gro or .pdb"") else: @tools.gmx_command(load_dependencies=self.load_dependencies) def pdb2gmx(**kwargs): ... if is_membrane: pdb2gmx(f=dict_to_work['conf'], ff=dict_to_work['ff']['code'], water=""none"", o=gro_out, p=top_out, i=posre_out) else: if self.fix_protein: logger.info(f""fix_protein = {self.fix_protein}; therefore pdbfixer will be used \ with flags --add-atoms=all --replace-nonstandard and pdb2gmx with -ignh.\ The protonation of your protien may have changed!"") env_prefix = os.environ[""CONDA_PREFIX""] fixed_pdb = self.wd/f""{name}_fixed.pdb"" run(f""{env_prefix}/bin/pdbfixer {dict_to_work['conf']} --output={fixed_pdb} --add-atoms=all --replace-nonstandard"") pdb2gmx(f=fixed_pdb, merge=""all"", ff=dict_to_work['ff']['code'], water=""none"", o=gro_out, p=top_out, i=posre_out, ignh=True) else: pdb2gmx(f=dict_to_work['conf'], merge=""all"", ff=dict_to_work['ff']['code'], water=""none"", o=gro_out, p=top_out, i=posre_out) os.chdir(self.cwd) # TODO and readParmEDMolecule fails with amber99sb-start-ildn system = tools.readParmEDMolecule(top_file=top_out, gro_file=gro_out, check_box=check_box) if self.hmr_factor: HMassRepartition(system, self.hmr_factor).execute() system.write(str(self.wd/f'{name}_final.top')) return system def make_system(self, ligand_definition: dict): """"""Create self.sys_ligand, self.sys_cofactor, self.sys_protein, self.sys_membrane and self.md_system (the combination of the available components). In case that the class was already called, it will be assumed that self.sys_cofactor, self.sys_protein, self.sys_membrane ere already calculated, only self.sys_ligand will be updated as well self.md_system Parameters ---------- ligand_definition : dict This is a dictionary with. Its definition is the same as mol_definition of the methods self.small_mol_process. """""" logger.info(""Processing system components"") self.sys_ligand = self.small_mol_process( mol_definition=ligand_definition, name=""LIG"", safe_naming_prefix='x') # Only if the class has not yet called the full build will be carry out. if self.__self_was_called: logger.info(""Reusing components from cache"") else: if self.cofactor: self.sys_cofactor = self.small_mol_process( mol_definition=self.cofactor, name=""COF"", safe_naming_prefix='z') else: self.sys_cofactor = None self.sys_protein = self.gmx_process(mol_definition=self.protein) self.sys_membrane = self.gmx_process(mol_definition=self.membrane, is_membrane=True) logger.info(""Merging Components"") # Cofactor at the end in case is a water molecule, not complains from GROMACS after solvation self.md_system = system_combiner(protein=self.sys_protein, membrane=self.sys_membrane, ligand=self.sys_ligand, cofactor=self.sys_cofactor) def clean(self): """"""Small cleaner, the intermediate steps saved on builder_dir will be deleted """""" os.chdir(self.cwd) try: shutil.rmtree(self.wd) except FileNotFoundError: pass def __enter__(self): return self def __exit__(self, exception_type, exception_value, exception_traceback): self.clean() def __call__(self, ligand_definition: Union[dict, PathLike], out_dir: str = 'fep'): """"""The call implementation. It identify if it is needed to build all the components of the systems, In case that the class was already called, it will assume that all the components of the system, with the exception of the ligand, were already builded. This is useful to call the class on several ligands that share the same components: protein, membrane and cofactor Parameters ---------- ligand_definition : Union[dict, PathLike] In case of dictionary, it should have: * conf -> The path of the small molecule MOL/SDF file [mandatory]. In case that top is provided, this must be a .gro, a ValueError will be raised if it is not the case the molecule will not get its parameters. * top -> GROMACS topology [optional]. Must be a single file topology with all the force field information and without the position restraint included, by default None * ff: * type -> openff, gaff or espaloma * code -> force field code [optional], by default depending on type * openff -> openff_unconstrained-2.0.0.offxml * gaff -> gaff-2.11 * espaloma -> espaloma-0.3.1 With this parameter you can access different small molecule force fields In case of PathLike: * The path of the small MOL/SDF molecule file out_dir : str, optional Where you would like to export the generated files, by default 'fep' """""" logger.info(39*""-"") if not isinstance(ligand_definition, dict): ligand_definition = { 'conf': ligand_definition } logger.info(f""Processing ligand: {ligand_definition['conf']}"") # Update (on multiple calls) or just create the out_dir (first call) self.out_dir = Path(out_dir) self.out_dir.mkdir(exist_ok=True, parents=True) # Construct MD system: self.make_system(ligand_definition) system_dir = self.wd/'system' ligand_dir = self.wd/'ligand' logger.info(f""Solvating with {self.water_model}:"") if self.membrane: # TODO: this is the easiest way to implement the position restraints changing the restraints # during different steps. However, we are not using different restraints for different molecules # what might be needed for some systems. That will take some coding in order to identify the molecules f_xyz_complex = 3*['POSRES_DYNAMIC'] else: f_xyz_complex = 3*[2500] with solvent.Solvate(self.water_model, builder_dir=self.wd/'.solvating') as SolObj: logger.info(f""Ligand in: {ligand_dir}"") SolObj(structure=self.sys_ligand, bt='octahedron', d=1.5, out_dir=ligand_dir, out_name='solvated', f_xyz=3*[2500]) logger.info(f""Complex in: {system_dir}"") settles_to_constraints_on = None if self.cofactor: if 'is_water' in self.cofactor: if self.cofactor['is_water']: warnings.warn(f'Provided cofactor {self.cofactor} was labeled as water (is_water = True). ' 'So, its settles section (if any), will be changed to tip3p-like triangular constraints. ' 'Check here for more information: ' 'https://gromacs.bioexcel.eu/t/how-to-treat-specific-water-molecules-as-ligand/3470/9') settles_to_constraints_on = 'COF' if self.membrane: SolObj(structure=self.md_system, bt='triclinic', box=self.vectors, angles=self.angles, out_dir=system_dir, out_name='solvated', f_xyz=f_xyz_complex, settles_to_constraints_on=settles_to_constraints_on) else: SolObj(structure=self.md_system, bt='octahedron', d=1.5, out_dir=system_dir, out_name='solvated', f_xyz=f_xyz_complex, settles_to_constraints_on=settles_to_constraints_on) # Make index file in case of membrane systems if self.membrane: solvent.index_for_membrane_system( configuration_file=system_dir/""solvated.gro"", ndxout=system_dir/""index.ndx"", ligand_name=""LIG"", host_name=self.host_name, cofactor_name='COF' if self.cofactor else None, cofactor_on_protein=self.cofactor_on_protein, load_dependencies=self.load_dependencies ) else: # This index file is only needed in case of MMPBSA (system_dir/""index.ndx"").touch(exist_ok=True) solvent.index_for_soluble_system( configuration_file=system_dir/""solvated.gro"", ndxout=system_dir/""index.ndx"", ligand_name=""LIG"", host_name=self.host_name, load_dependencies=self.load_dependencies ) # Construct BindFlow system: logger.info(f""Final build of BindFlow directory on: {self.out_dir}"") make_bindflow_dir(out_dir=self.out_dir, ligand_dir=ligand_dir, sys_dir=system_dir) # Change state self.__self_was_called = True logger.info(""--------- Building Completed ----------\n"") ############################################################################################# if __name__ == ""__main__"": pass ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/rules/__init__.py",".py","173","9","from pathlib import Path root_path = Path(__file__).resolve().parent # Path of Snakefile equi = root_path/'equi' fep = root_path/'fep' super_flow = root_path/'super_flow' ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/mmpbsa_in/__init__.py",".py","0","0","","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/mmpbsa_in/input_loader.py",".py","4189","101","import copy import os from typing import Union import importlib_resources from GMXMMPBSA.input_parser import InputFile from GMXMMPBSA.input_parser import input_file as _InternalInputFile PathLike = Union[os.PathLike, str, bytes] _bindflow_template_resources = importlib_resources.files(""bindflow"") class GMXMMPBSAInputMaker: """"""Class to handle gmx_MMPBSA input files Example ------- .. ipython:: python import sys input_file = GMXMMPBSAInputMaker(pb={""ipb"": 123}, general={""sys_name"": ""abc""}) # In real example, just provided the file path input_file.write(sys.stdout) """""" def __init__(self, **kwargs): """"""Here we check the type of calculation to perform based on the provided kwargs. If no kwargs was provided a default Poison-Boltzmann (pb) calculation is performed based on the internal BindFlow templates. If you would like to perform a General Boltzmann (gb) calculation you must provided the keyword gb={}. You can specify parameters inside the dictionary or leave it empty and the internal default BindFlow parameters will be used. See that if the values of each passed keyword is not a dictionary, a ValueError will be raised. E.g. gb=True is an invalid keyword. """""" for key, value in kwargs.items(): if not isinstance(value, dict): raise ValueError(f""{key} = {value} is an invalid keyword. The value must be a dictionary"") self.__mmpbsa_in_opts = kwargs self.__do_gb = True if ""gb"" in self.__mmpbsa_in_opts.keys() else False # Do pb by default self.__do_pb = True if ""pb"" in self.__mmpbsa_in_opts.keys() or not self.__do_gb else False self.__template = self.__load_from_template() self.__update_user_specific_fields() def __load_from_template(self) -> InputFile: """"""Loading internal BindFLow templates on demand. Returns ------- InputFile An instance of `GMXMMPBSA.input_parser.InputFile` with the namelist initiated internally by GMXMMPBSA. """""" input_copy = copy.deepcopy(_InternalInputFile) if self.__do_pb and self.__do_gb: template_path = _bindflow_template_resources.joinpath(""mmpbsa_in/templates"", ""pb_gb.in"") input_copy.Parse(template_path) return input_copy elif self.__do_pb: template_path = _bindflow_template_resources.joinpath(""mmpbsa_in/templates"", ""pb.in"") input_copy.Parse(template_path) return input_copy elif self.__do_gb: template_path = _bindflow_template_resources.joinpath(""mmpbsa_in/templates"", ""gb.in"") input_copy.Parse(template_path) return input_copy def __update_user_specific_fields(self) -> None: """"""Helper function to pass user defined parameters passed during initialization of the class Raises ------ ValueError In case of invalid parameter """""" if self.__mmpbsa_in_opts: for key in self.__mmpbsa_in_opts.keys(): if self.__mmpbsa_in_opts[key] is None or self.__mmpbsa_in_opts[key] is True: continue for parameter in self.__mmpbsa_in_opts[key].keys(): if parameter in self.__template.namelists[key].variables.keys(): self.__template.namelists[key].variables[parameter].SetValue(self.__mmpbsa_in_opts[key][parameter]) else: raise ValueError(f""The parameter {key}/{parameter} for the MMPBSA/MMGBSA calculation is unknown. "" ""Check this list https://valdes-tresanco-ms.github.io/gmx_MMPBSA/dev/input_file/ "" ""for possible input options."") def write(self, out_path: PathLike): outputs = [""general""] if self.__do_gb: outputs.append(""gb"") if self.__do_pb: outputs.append(""pb"") self.__template.print_contents(out_path, outputs) if __name__ == ""__main__"": pass ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/free_energy/__init__.py",".py","0","0","","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/free_energy/mmxbsa_analysis.py",".py","33966","549","from pathlib import Path import GMXMMPBSA.API import pandas as pd def convert_format_flatten(df, ligand_name, replica, sample): res = { ""name"": [ligand_name], ""replica"": [int(replica)], ""sample"": [int(sample)], ""dg_c2_pb"": df[""dg_c2_pb""], ""dg_c2_gb"": df[""dg_c2_gb""], ""dg_ie_pb"": df[""dg_ie_pb""], ""dg_ie_gb"": df[""dg_ie_gb""], ""dg_qh_pb"": df[""dg_qh_pb""], ""dg_qh_gb"": df[""dg_qh_gb""], ""dg_en_pb"": df[""dg_en_pb""], ""dg_en_gb"": df[""dg_en_gb""], ""c2_pb"": df[""c2_pb""], ""c2_gb"": df[""c2_gb""], ""ie_pb"": df[""ie_pb""], ""ie_gb"": df[""ie_gb""], ""qh"": df[""qh""], ""gb_energy_complex_bond"": df[""gb_energy_complex_bond""], ""gb_energy_complex_angle"": df[""gb_energy_complex_angle""], ""gb_energy_complex_dihed"": df[""gb_energy_complex_dihed""], ""gb_energy_complex_vdwaals"": df[""gb_energy_complex_vdwaals""], ""gb_energy_complex_eel"": df[""gb_energy_complex_eel""], ""gb_energy_complex_14vdw"": df[""gb_energy_complex_14vdw""], ""gb_energy_complex_14eel"": df[""gb_energy_complex_14eel""], ""gb_energy_complex_egb"": df[""gb_energy_complex_egb""], ""gb_energy_complex_esurf"": df[""gb_energy_complex_esurf""], ""gb_energy_complex_ggas"": df[""gb_energy_complex_ggas""], ""gb_energy_complex_gsolv"": df[""gb_energy_complex_gsolv""], ""gb_energy_complex_total"": df[""gb_energy_complex_total""], ""gb_energy_receptor_bond"": df[""gb_energy_receptor_bond""], ""gb_energy_receptor_angle"": df[""gb_energy_receptor_angle""], ""gb_energy_receptor_dihed"": df[""gb_energy_receptor_dihed""], ""gb_energy_receptor_vdwaals"": df[""gb_energy_receptor_vdwaals""], ""gb_energy_receptor_eel"": df[""gb_energy_receptor_eel""], ""gb_energy_receptor_14vdw"": df[""gb_energy_receptor_14vdw""], ""gb_energy_receptor_14eel"": df[""gb_energy_receptor_14eel""], ""gb_energy_receptor_egb"": df[""gb_energy_receptor_egb""], ""gb_energy_receptor_esurf"": df[""gb_energy_receptor_esurf""], ""gb_energy_receptor_ggas"": df[""gb_energy_receptor_ggas""], ""gb_energy_receptor_gsolv"": df[""gb_energy_receptor_gsolv""], ""gb_energy_receptor_total"": df[""gb_energy_receptor_total""], ""gb_energy_ligand_bond"": df[""gb_energy_ligand_bond""], ""gb_energy_ligand_angle"": df[""gb_energy_ligand_angle""], ""gb_energy_ligand_dihed"": df[""gb_energy_ligand_dihed""], ""gb_energy_ligand_vdwaals"": df[""gb_energy_ligand_vdwaals""], ""gb_energy_ligand_eel"": df[""gb_energy_ligand_eel""], ""gb_energy_ligand_14vdw"": df[""gb_energy_ligand_14vdw""], ""gb_energy_ligand_14eel"": df[""gb_energy_ligand_14eel""], ""gb_energy_ligand_egb"": df[""gb_energy_ligand_egb""], ""gb_energy_ligand_esurf"": df[""gb_energy_ligand_esurf""], ""gb_energy_ligand_ggas"": df[""gb_energy_ligand_ggas""], ""gb_energy_ligand_gsolv"": df[""gb_energy_ligand_gsolv""], ""gb_energy_ligand_total"": df[""gb_energy_ligand_total""], ""gb_energy_delta_bond"": df[""gb_energy_delta_bond""], ""gb_energy_delta_angle"": df[""gb_energy_delta_angle""], ""gb_energy_delta_dihed"": df[""gb_energy_delta_dihed""], ""gb_energy_delta_vdwaals"": df[""gb_energy_delta_vdwaals""], ""gb_energy_delta_eel"": df[""gb_energy_delta_eel""], ""gb_energy_delta_14vdw"": df[""gb_energy_delta_14vdw""], ""gb_energy_delta_14eel"": df[""gb_energy_delta_14eel""], ""gb_energy_delta_egb"": df[""gb_energy_delta_egb""], ""gb_energy_delta_esurf"": df[""gb_energy_delta_esurf""], ""gb_energy_delta_ggas"": df[""gb_energy_delta_ggas""], ""gb_energy_delta_gsolv"": df[""gb_energy_delta_gsolv""], ""gb_energy_delta_total"": df[""gb_energy_delta_total""], ""pb_energy_complex_bond"": df[""pb_energy_complex_bond""], ""pb_energy_complex_angle"": df[""pb_energy_complex_angle""], ""pb_energy_complex_dihed"": df[""pb_energy_complex_dihed""], ""pb_energy_complex_vdwaals"": df[""pb_energy_complex_vdwaals""], ""pb_energy_complex_eel"": df[""pb_energy_complex_eel""], ""pb_energy_complex_14vdw"": df[""pb_energy_complex_14vdw""], ""pb_energy_complex_14eel"": df[""pb_energy_complex_14eel""], ""pb_energy_complex_epb"": df[""pb_energy_complex_epb""], ""pb_energy_complex_enpolar"": df[""pb_energy_complex_enpolar""], ""pb_energy_complex_edisper"": df[""pb_energy_complex_edisper""], ""pb_energy_complex_ggas"": df[""pb_energy_complex_ggas""], ""pb_energy_complex_gsolv"": df[""pb_energy_complex_gsolv""], ""pb_energy_complex_total"": df[""pb_energy_complex_total""], ""pb_energy_receptor_bond"": df[""pb_energy_receptor_bond""], ""pb_energy_receptor_angle"": df[""pb_energy_receptor_angle""], ""pb_energy_receptor_dihed"": df[""pb_energy_receptor_dihed""], ""pb_energy_receptor_vdwaals"": df[""pb_energy_receptor_vdwaals""], ""pb_energy_receptor_eel"": df[""pb_energy_receptor_eel""], ""pb_energy_receptor_14vdw"": df[""pb_energy_receptor_14vdw""], ""pb_energy_receptor_14eel"": df[""pb_energy_receptor_14eel""], ""pb_energy_receptor_epb"": df[""pb_energy_receptor_epb""], ""pb_energy_receptor_enpolar"": df[""pb_energy_receptor_enpolar""], ""pb_energy_receptor_edisper"": df[""pb_energy_receptor_edisper""], ""pb_energy_receptor_ggas"": df[""pb_energy_receptor_ggas""], ""pb_energy_receptor_gsolv"": df[""pb_energy_receptor_gsolv""], ""pb_energy_receptor_total"": df[""pb_energy_receptor_total""], ""pb_energy_ligand_bond"": df[""pb_energy_ligand_bond""], ""pb_energy_ligand_angle"": df[""pb_energy_ligand_angle""], ""pb_energy_ligand_dihed"": df[""pb_energy_ligand_dihed""], ""pb_energy_ligand_vdwaals"": df[""pb_energy_ligand_vdwaals""], ""pb_energy_ligand_eel"": df[""pb_energy_ligand_eel""], ""pb_energy_ligand_14vdw"": df[""pb_energy_ligand_14vdw""], ""pb_energy_ligand_14eel"": df[""pb_energy_ligand_14eel""], ""pb_energy_ligand_epb"": df[""pb_energy_ligand_epb""], ""pb_energy_ligand_enpolar"": df[""pb_energy_ligand_enpolar""], ""pb_energy_ligand_edisper"": df[""pb_energy_ligand_edisper""], ""pb_energy_ligand_ggas"": df[""pb_energy_ligand_ggas""], ""pb_energy_ligand_gsolv"": df[""pb_energy_ligand_gsolv""], ""pb_energy_ligand_total"": df[""pb_energy_ligand_total""], ""pb_energy_delta_bond"": df[""pb_energy_delta_bond""], ""pb_energy_delta_angle"": df[""pb_energy_delta_angle""], ""pb_energy_delta_dihed"": df[""pb_energy_delta_dihed""], ""pb_energy_delta_vdwaals"": df[""pb_energy_delta_vdwaals""], ""pb_energy_delta_eel"": df[""pb_energy_delta_eel""], ""pb_energy_delta_14vdw"": df[""pb_energy_delta_14vdw""], ""pb_energy_delta_14eel"": df[""pb_energy_delta_14eel""], ""pb_energy_delta_epb"": df[""pb_energy_delta_epb""], ""pb_energy_delta_enpolar"": df[""pb_energy_delta_enpolar""], ""pb_energy_delta_edisper"": df[""pb_energy_delta_edisper""], ""pb_energy_delta_ggas"": df[""pb_energy_delta_ggas""], ""pb_energy_delta_gsolv"": df[""pb_energy_delta_gsolv""], ""pb_energy_delta_total"": df[""pb_energy_delta_total""], } return pd.DataFrame.from_dict(res) class GmxMmxbsaDataRetriever: def __init__(self, binary_api_file): """"""This class extracts the data generated from the GMX_MMPBSA program. Note that this class requires the binary data file generated after setting the keep_files=0 or keep_files=1 parameter (keep_files=2 does not generate the required file)"""""" self.gmx_api = GMXMMPBSA.API.MMPBSA_API() self.gmx_api.setting_time() self.gmx_api.load_file(binary_api_file) self.__extract_entropies() self.__extract_energies() self.__extract_others() def __extract_entropies(self): if ""c2"" in self.gmx_api.data[""normal""].keys(): if ""pb"" in self.gmx_api.data[""normal""][""c2""].keys(): self.c2_pb = self.gmx_api.data[""normal""][""c2""][""pb""][""c2data""] else: self.c2_pb = None if ""gb"" in self.gmx_api.data[""normal""][""c2""].keys(): self.c2_gb = self.gmx_api.data[""normal""][""c2""][""gb""][""c2data""] else: self.c2_gb = None else: self.c2_pb = None self.c2_gb = None if ""ie"" in self.gmx_api.data[""normal""].keys(): if ""pb"" in self.gmx_api.data[""normal""][""ie""].keys(): self.ie_pb = float(self.gmx_api.data[""normal""][""ie""][""pb""][""iedata""].mean()) else: self.ie_pb = None if ""gb"" in self.gmx_api.data[""normal""][""ie""].keys(): self.ie_gb = float(self.gmx_api.data[""normal""][""ie""][""gb""][""iedata""].mean()) else: self.ie_gb = None else: self.ie_pb = None self.ie_gb = None if ""qh"" in self.gmx_api.data[""normal""].keys(): self.qh = self.gmx_api.data[""normal""][""qh""][""delta""][""TOTAL""] else: self.qh = None return self.c2_pb, self.c2_gb, self.ie_pb, self.ie_gb, self.qh def __extract_energies(self): if ""pb"" in self.gmx_api.data[""normal""].keys(): self.pb_en = self.gmx_api.data[""normal""][""pb""][""delta""][""TOTAL""] else: self.pb_en = None if ""gb"" in self.gmx_api.data[""normal""].keys(): self.gb_en = self.gmx_api.data[""normal""][""gb""][""delta""][""TOTAL""] else: self.gb_en = None return self.pb_en, self.gb_en def __extract_others(self): if ""gb"" in self.gmx_api.data[""normal""].keys(): self.gb_energy_complex_bond = float(self.gmx_api.data[""normal""][""gb""][""complex""][""BOND""].mean()) self.gb_energy_complex_angle = float(self.gmx_api.data[""normal""][""gb""][""complex""][""ANGLE""].mean()) self.gb_energy_complex_dihed = float(self.gmx_api.data[""normal""][""gb""][""complex""][""DIHED""].mean()) self.gb_energy_complex_vdwaals = float(self.gmx_api.data[""normal""][""gb""][""complex""][""VDWAALS""].mean()) self.gb_energy_complex_eel = float(self.gmx_api.data[""normal""][""gb""][""complex""][""EEL""].mean()) self.gb_energy_complex_14vdw = float(self.gmx_api.data[""normal""][""gb""][""complex""][""1-4 VDW""].mean()) self.gb_energy_complex_14eel = float(self.gmx_api.data[""normal""][""gb""][""complex""][""1-4 EEL""].mean()) self.gb_energy_complex_egb = float(self.gmx_api.data[""normal""][""gb""][""complex""][""EGB""].mean()) self.gb_energy_complex_esurf = float(self.gmx_api.data[""normal""][""gb""][""complex""][""ESURF""].mean()) self.gb_energy_complex_ggas = float(self.gmx_api.data[""normal""][""gb""][""complex""][""GGAS""].mean()) self.gb_energy_complex_gsolv = float(self.gmx_api.data[""normal""][""gb""][""complex""][""GSOLV""].mean()) self.gb_energy_complex_total = float(self.gmx_api.data[""normal""][""gb""][""complex""][""TOTAL""].mean()) self.gb_energy_receptor_bond = float(self.gmx_api.data[""normal""][""gb""][""receptor""][""BOND""].mean()) self.gb_energy_receptor_angle = float(self.gmx_api.data[""normal""][""gb""][""receptor""][""ANGLE""].mean()) self.gb_energy_receptor_dihed = float(self.gmx_api.data[""normal""][""gb""][""receptor""][""DIHED""].mean()) self.gb_energy_receptor_vdwaals = float(self.gmx_api.data[""normal""][""gb""][""receptor""][""VDWAALS""].mean()) self.gb_energy_receptor_eel = float(self.gmx_api.data[""normal""][""gb""][""receptor""][""EEL""].mean()) self.gb_energy_receptor_14vdw = float(self.gmx_api.data[""normal""][""gb""][""receptor""][""1-4 VDW""].mean()) self.gb_energy_receptor_14eel = float(self.gmx_api.data[""normal""][""gb""][""receptor""][""1-4 EEL""].mean()) self.gb_energy_receptor_egb = float(self.gmx_api.data[""normal""][""gb""][""receptor""][""EGB""].mean()) self.gb_energy_receptor_esurf = float(self.gmx_api.data[""normal""][""gb""][""receptor""][""ESURF""].mean()) self.gb_energy_receptor_ggas = float(self.gmx_api.data[""normal""][""gb""][""receptor""][""GGAS""].mean()) self.gb_energy_receptor_gsolv = float(self.gmx_api.data[""normal""][""gb""][""receptor""][""GSOLV""].mean()) self.gb_energy_receptor_total = float(self.gmx_api.data[""normal""][""gb""][""receptor""][""TOTAL""].mean()) self.gb_energy_ligand_bond = float(self.gmx_api.data[""normal""][""gb""][""ligand""][""BOND""].mean()) self.gb_energy_ligand_angle = float(self.gmx_api.data[""normal""][""gb""][""ligand""][""ANGLE""].mean()) self.gb_energy_ligand_dihed = float(self.gmx_api.data[""normal""][""gb""][""ligand""][""DIHED""].mean()) self.gb_energy_ligand_vdwaals = float(self.gmx_api.data[""normal""][""gb""][""ligand""][""VDWAALS""].mean()) self.gb_energy_ligand_eel = float(self.gmx_api.data[""normal""][""gb""][""ligand""][""EEL""].mean()) self.gb_energy_ligand_14vdw = float(self.gmx_api.data[""normal""][""gb""][""ligand""][""1-4 VDW""].mean()) self.gb_energy_ligand_14eel = float(self.gmx_api.data[""normal""][""gb""][""ligand""][""1-4 EEL""].mean()) self.gb_energy_ligand_egb = float(self.gmx_api.data[""normal""][""gb""][""ligand""][""EGB""].mean()) self.gb_energy_ligand_esurf = float(self.gmx_api.data[""normal""][""gb""][""ligand""][""ESURF""].mean()) self.gb_energy_ligand_ggas = float(self.gmx_api.data[""normal""][""gb""][""ligand""][""GGAS""].mean()) self.gb_energy_ligand_gsolv = float(self.gmx_api.data[""normal""][""gb""][""ligand""][""GSOLV""].mean()) self.gb_energy_ligand_total = float(self.gmx_api.data[""normal""][""gb""][""ligand""][""TOTAL""].mean()) self.gb_energy_delta_bond = float(self.gmx_api.data[""normal""][""gb""][""delta""][""BOND""].mean()) self.gb_energy_delta_angle = float(self.gmx_api.data[""normal""][""gb""][""delta""][""ANGLE""].mean()) self.gb_energy_delta_dihed = float(self.gmx_api.data[""normal""][""gb""][""delta""][""DIHED""].mean()) self.gb_energy_delta_vdwaals = float(self.gmx_api.data[""normal""][""gb""][""delta""][""VDWAALS""].mean()) self.gb_energy_delta_eel = float(self.gmx_api.data[""normal""][""gb""][""delta""][""EEL""].mean()) self.gb_energy_delta_14vdw = float(self.gmx_api.data[""normal""][""gb""][""delta""][""1-4 VDW""].mean()) self.gb_energy_delta_14eel = float(self.gmx_api.data[""normal""][""gb""][""delta""][""1-4 EEL""].mean()) self.gb_energy_delta_egb = float(self.gmx_api.data[""normal""][""gb""][""delta""][""EGB""].mean()) self.gb_energy_delta_esurf = float(self.gmx_api.data[""normal""][""gb""][""delta""][""ESURF""].mean()) self.gb_energy_delta_ggas = float(self.gmx_api.data[""normal""][""gb""][""delta""][""GGAS""].mean()) self.gb_energy_delta_gsolv = float(self.gmx_api.data[""normal""][""gb""][""delta""][""GSOLV""].mean()) self.gb_energy_delta_total = float(self.gmx_api.data[""normal""][""gb""][""delta""][""TOTAL""].mean()) else: self.gb_energy_complex_bond = None self.gb_energy_complex_angle = None self.gb_energy_complex_dihed = None self.gb_energy_complex_vdwaals = None self.gb_energy_complex_eel = None self.gb_energy_complex_14vdw = None self.gb_energy_complex_14eel = None self.gb_energy_complex_egb = None self.gb_energy_complex_esurf = None self.gb_energy_complex_ggas = None self.gb_energy_complex_gsolv = None self.gb_energy_complex_total = None self.gb_energy_receptor_bond = None self.gb_energy_receptor_angle = None self.gb_energy_receptor_dihed = None self.gb_energy_receptor_vdwaals = None self.gb_energy_receptor_eel = None self.gb_energy_receptor_14vdw = None self.gb_energy_receptor_14eel = None self.gb_energy_receptor_egb = None self.gb_energy_receptor_esurf = None self.gb_energy_receptor_ggas = None self.gb_energy_receptor_gsolv = None self.gb_energy_receptor_total = None self.gb_energy_ligand_bond = None self.gb_energy_ligand_angle = None self.gb_energy_ligand_dihed = None self.gb_energy_ligand_vdwaals = None self.gb_energy_ligand_eel = None self.gb_energy_ligand_14vdw = None self.gb_energy_ligand_14eel = None self.gb_energy_ligand_egb = None self.gb_energy_ligand_esurf = None self.gb_energy_ligand_ggas = None self.gb_energy_ligand_gsolv = None self.gb_energy_ligand_total = None self.gb_energy_delta_bond = None self.gb_energy_delta_angle = None self.gb_energy_delta_dihed = None self.gb_energy_delta_vdwaals = None self.gb_energy_delta_eel = None self.gb_energy_delta_14vdw = None self.gb_energy_delta_14eel = None self.gb_energy_delta_egb = None self.gb_energy_delta_esurf = None self.gb_energy_delta_ggas = None self.gb_energy_delta_gsolv = None self.gb_energy_delta_total = None if ""pb"" in self.gmx_api.data[""normal""].keys(): self.pb_energy_complex_bond = float(self.gmx_api.data[""normal""][""pb""][""complex""][""BOND""].mean()) self.pb_energy_complex_angle = float(self.gmx_api.data[""normal""][""pb""][""complex""][""ANGLE""].mean()) self.pb_energy_complex_dihed = float(self.gmx_api.data[""normal""][""pb""][""complex""][""DIHED""].mean()) self.pb_energy_complex_vdwaals = float(self.gmx_api.data[""normal""][""pb""][""complex""][""VDWAALS""].mean()) self.pb_energy_complex_eel = float(self.gmx_api.data[""normal""][""pb""][""complex""][""EEL""].mean()) self.pb_energy_complex_14vdw = float(self.gmx_api.data[""normal""][""pb""][""complex""][""1-4 VDW""].mean()) self.pb_energy_complex_14eel = float(self.gmx_api.data[""normal""][""pb""][""complex""][""1-4 EEL""].mean()) self.pb_energy_complex_epb = float(self.gmx_api.data[""normal""][""pb""][""complex""][""EPB""].mean()) self.pb_energy_complex_enpolar = float(self.gmx_api.data[""normal""][""pb""][""complex""][""ENPOLAR""].mean()) self.pb_energy_complex_edisper = float(self.gmx_api.data[""normal""][""pb""][""complex""][""EDISPER""].mean()) self.pb_energy_complex_ggas = float(self.gmx_api.data[""normal""][""pb""][""complex""][""GGAS""].mean()) self.pb_energy_complex_gsolv = float(self.gmx_api.data[""normal""][""pb""][""complex""][""GSOLV""].mean()) self.pb_energy_complex_total = float(self.gmx_api.data[""normal""][""pb""][""complex""][""TOTAL""].mean()) self.pb_energy_receptor_bond = float(self.gmx_api.data[""normal""][""pb""][""receptor""][""BOND""].mean()) self.pb_energy_receptor_angle = float(self.gmx_api.data[""normal""][""pb""][""receptor""][""ANGLE""].mean()) self.pb_energy_receptor_dihed = float(self.gmx_api.data[""normal""][""pb""][""receptor""][""DIHED""].mean()) self.pb_energy_receptor_vdwaals = float(self.gmx_api.data[""normal""][""pb""][""receptor""][""VDWAALS""].mean()) self.pb_energy_receptor_eel = float(self.gmx_api.data[""normal""][""pb""][""receptor""][""EEL""].mean()) self.pb_energy_receptor_14vdw = float(self.gmx_api.data[""normal""][""pb""][""receptor""][""1-4 VDW""].mean()) self.pb_energy_receptor_14eel = float(self.gmx_api.data[""normal""][""pb""][""receptor""][""1-4 EEL""].mean()) self.pb_energy_receptor_epb = float(self.gmx_api.data[""normal""][""pb""][""receptor""][""EPB""].mean()) self.pb_energy_receptor_enpolar = float(self.gmx_api.data[""normal""][""pb""][""receptor""][""ENPOLAR""].mean()) self.pb_energy_receptor_edisper = float(self.gmx_api.data[""normal""][""pb""][""receptor""][""EDISPER""].mean()) self.pb_energy_receptor_ggas = float(self.gmx_api.data[""normal""][""pb""][""receptor""][""GGAS""].mean()) self.pb_energy_receptor_gsolv = float(self.gmx_api.data[""normal""][""pb""][""receptor""][""GSOLV""].mean()) self.pb_energy_receptor_total = float(self.gmx_api.data[""normal""][""pb""][""receptor""][""TOTAL""].mean()) self.pb_energy_ligand_bond = float(self.gmx_api.data[""normal""][""pb""][""ligand""][""BOND""].mean()) self.pb_energy_ligand_angle = float(self.gmx_api.data[""normal""][""pb""][""ligand""][""ANGLE""].mean()) self.pb_energy_ligand_dihed = float(self.gmx_api.data[""normal""][""pb""][""ligand""][""DIHED""].mean()) self.pb_energy_ligand_vdwaals = float(self.gmx_api.data[""normal""][""pb""][""ligand""][""VDWAALS""].mean()) self.pb_energy_ligand_eel = float(self.gmx_api.data[""normal""][""pb""][""ligand""][""EEL""].mean()) self.pb_energy_ligand_14vdw = float(self.gmx_api.data[""normal""][""pb""][""ligand""][""1-4 VDW""].mean()) self.pb_energy_ligand_14eel = float(self.gmx_api.data[""normal""][""pb""][""ligand""][""1-4 EEL""].mean()) self.pb_energy_ligand_epb = float(self.gmx_api.data[""normal""][""pb""][""ligand""][""EPB""].mean()) self.pb_energy_ligand_enpolar = float(self.gmx_api.data[""normal""][""pb""][""ligand""][""ENPOLAR""].mean()) self.pb_energy_ligand_edisper = float(self.gmx_api.data[""normal""][""pb""][""ligand""][""EDISPER""].mean()) self.pb_energy_ligand_ggas = float(self.gmx_api.data[""normal""][""pb""][""ligand""][""GGAS""].mean()) self.pb_energy_ligand_gsolv = float(self.gmx_api.data[""normal""][""pb""][""ligand""][""GSOLV""].mean()) self.pb_energy_ligand_total = float(self.gmx_api.data[""normal""][""pb""][""ligand""][""TOTAL""].mean()) self.pb_energy_delta_bond = float(self.gmx_api.data[""normal""][""pb""][""delta""][""BOND""].mean()) self.pb_energy_delta_angle = float(self.gmx_api.data[""normal""][""pb""][""delta""][""ANGLE""].mean()) self.pb_energy_delta_dihed = float(self.gmx_api.data[""normal""][""pb""][""delta""][""DIHED""].mean()) self.pb_energy_delta_vdwaals = float(self.gmx_api.data[""normal""][""pb""][""delta""][""VDWAALS""].mean()) self.pb_energy_delta_eel = float(self.gmx_api.data[""normal""][""pb""][""delta""][""EEL""].mean()) self.pb_energy_delta_14vdw = float(self.gmx_api.data[""normal""][""pb""][""delta""][""1-4 VDW""].mean()) self.pb_energy_delta_14eel = float(self.gmx_api.data[""normal""][""pb""][""delta""][""1-4 EEL""].mean()) self.pb_energy_delta_epb = float(self.gmx_api.data[""normal""][""pb""][""delta""][""EPB""].mean()) self.pb_energy_delta_enpolar = float(self.gmx_api.data[""normal""][""pb""][""delta""][""ENPOLAR""].mean()) self.pb_energy_delta_edisper = float(self.gmx_api.data[""normal""][""pb""][""delta""][""EDISPER""].mean()) self.pb_energy_delta_ggas = float(self.gmx_api.data[""normal""][""pb""][""delta""][""GGAS""].mean()) self.pb_energy_delta_gsolv = float(self.gmx_api.data[""normal""][""pb""][""delta""][""GSOLV""].mean()) self.pb_energy_delta_total = float(self.gmx_api.data[""normal""][""pb""][""delta""][""TOTAL""].mean()) else: self.pb_energy_complex_bond = None self.pb_energy_complex_angle = None self.pb_energy_complex_dihed = None self.pb_energy_complex_vdwaals = None self.pb_energy_complex_eel = None self.pb_energy_complex_14vdw = None self.pb_energy_complex_14eel = None self.pb_energy_complex_epb = None self.pb_energy_complex_enpolar = None self.pb_energy_complex_edisper = None self.pb_energy_complex_ggas = None self.pb_energy_complex_gsolv = None self.pb_energy_complex_total = None self.pb_energy_receptor_bond = None self.pb_energy_receptor_angle = None self.pb_energy_receptor_dihed = None self.pb_energy_receptor_vdwaals = None self.pb_energy_receptor_eel = None self.pb_energy_receptor_14vdw = None self.pb_energy_receptor_14eel = None self.pb_energy_receptor_epb = None self.pb_energy_receptor_enpolar = None self.pb_energy_receptor_edisper = None self.pb_energy_receptor_ggas = None self.pb_energy_receptor_gsolv = None self.pb_energy_receptor_total = None self.pb_energy_ligand_bond = None self.pb_energy_ligand_angle = None self.pb_energy_ligand_dihed = None self.pb_energy_ligand_vdwaals = None self.pb_energy_ligand_eel = None self.pb_energy_ligand_14vdw = None self.pb_energy_ligand_14eel = None self.pb_energy_ligand_epb = None self.pb_energy_ligand_enpolar = None self.pb_energy_ligand_edisper = None self.pb_energy_ligand_ggas = None self.pb_energy_ligand_gsolv = None self.pb_energy_ligand_total = None self.pb_energy_delta_bond = None self.pb_energy_delta_angle = None self.pb_energy_delta_dihed = None self.pb_energy_delta_vdwaals = None self.pb_energy_delta_eel = None self.pb_energy_delta_14vdw = None self.pb_energy_delta_14eel = None self.pb_energy_delta_epb = None self.pb_energy_delta_enpolar = None self.pb_energy_delta_edisper = None self.pb_energy_delta_ggas = None self.pb_energy_delta_gsolv = None self.pb_energy_delta_total = None def store_dg(self, output_file, run_dir): # storing pb energies of each frame pd.DataFrame(self.pb_en, columns=[""delta_g_pb""]).to_csv(Path(run_dir)/""pb_energy_frames.csv"", index=False) # storing gb energies of each frame pd.DataFrame(self.gb_en, columns=[""delta_g_gb""]).to_csv(Path(run_dir)/""gb_energy_frames.csv"", index=False) delta_g_dict = { ""dg_c2_pb"": [self.pb_en.mean() + self.c2_pb if (self.pb_en is not None and self.c2_pb is not None) else None], ""dg_c2_gb"": [self.gb_en.mean() + self.c2_gb if (self.gb_en is not None and self.c2_gb is not None) else None], ""dg_ie_pb"": [self.pb_en.mean() + self.ie_pb if (self.pb_en is not None and self.ie_pb is not None) else None], ""dg_ie_gb"": [self.gb_en.mean() + self.ie_gb if (self.gb_en is not None and self.ie_gb is not None) else None], ""dg_qh_pb"": [self.pb_en.mean() + self.qh if (self.pb_en is not None and self.qh is not None) else None], ""dg_qh_gb"": [self.gb_en.mean() + self.qh if (self.gb_en is not None and self.qh is not None) else None], ""dg_en_pb"": [self.pb_en.mean() if self.pb_en is not None else None], ""dg_en_gb"": [self.gb_en.mean() if self.gb_en is not None else None], ""c2_pb"": [self.c2_pb if self.c2_pb is not None else None], ""c2_gb"": [self.c2_gb if self.c2_gb is not None else None], ""ie_pb"": [self.ie_pb if self.ie_pb is not None else None], ""ie_gb"": [self.ie_gb if self.ie_gb is not None else None], ""qh"": [self.qh if self.qh is not None else None], ""gb_energy_complex_bond"": self.gb_energy_complex_bond, ""gb_energy_complex_angle"": self.gb_energy_complex_angle, ""gb_energy_complex_dihed"": self.gb_energy_complex_dihed, ""gb_energy_complex_vdwaals"": self.gb_energy_complex_vdwaals, ""gb_energy_complex_eel"": self.gb_energy_complex_eel, ""gb_energy_complex_14vdw"": self.gb_energy_complex_14vdw, ""gb_energy_complex_14eel"": self.gb_energy_complex_14eel, ""gb_energy_complex_egb"": self.gb_energy_complex_egb, ""gb_energy_complex_esurf"": self.gb_energy_complex_esurf, ""gb_energy_complex_ggas"": self.gb_energy_complex_ggas, ""gb_energy_complex_gsolv"": self.gb_energy_complex_gsolv, ""gb_energy_complex_total"": self.gb_energy_complex_total, ""gb_energy_receptor_bond"": self.gb_energy_receptor_bond, ""gb_energy_receptor_angle"": self.gb_energy_receptor_angle, ""gb_energy_receptor_dihed"": self.gb_energy_receptor_dihed, ""gb_energy_receptor_vdwaals"": self.gb_energy_receptor_vdwaals, ""gb_energy_receptor_eel"": self.gb_energy_receptor_eel, ""gb_energy_receptor_14vdw"": self.gb_energy_receptor_14vdw, ""gb_energy_receptor_14eel"": self.gb_energy_receptor_14eel, ""gb_energy_receptor_egb"": self.gb_energy_receptor_egb, ""gb_energy_receptor_esurf"": self.gb_energy_receptor_esurf, ""gb_energy_receptor_ggas"": self.gb_energy_receptor_ggas, ""gb_energy_receptor_gsolv"": self.gb_energy_receptor_gsolv, ""gb_energy_receptor_total"": self.gb_energy_receptor_total, ""gb_energy_ligand_bond"": self.gb_energy_ligand_bond, ""gb_energy_ligand_angle"": self.gb_energy_ligand_angle, ""gb_energy_ligand_dihed"": self.gb_energy_ligand_dihed, ""gb_energy_ligand_vdwaals"": self.gb_energy_ligand_vdwaals, ""gb_energy_ligand_eel"": self.gb_energy_ligand_eel, ""gb_energy_ligand_14vdw"": self.gb_energy_ligand_14vdw, ""gb_energy_ligand_14eel"": self.gb_energy_ligand_14eel, ""gb_energy_ligand_egb"": self.gb_energy_ligand_egb, ""gb_energy_ligand_esurf"": self.gb_energy_ligand_esurf, ""gb_energy_ligand_ggas"": self.gb_energy_ligand_ggas, ""gb_energy_ligand_gsolv"": self.gb_energy_ligand_gsolv, ""gb_energy_ligand_total"": self.gb_energy_ligand_total, ""gb_energy_delta_bond"": self.gb_energy_delta_bond, ""gb_energy_delta_angle"": self.gb_energy_delta_angle, ""gb_energy_delta_dihed"": self.gb_energy_delta_dihed, ""gb_energy_delta_vdwaals"": self.gb_energy_delta_vdwaals, ""gb_energy_delta_eel"": self.gb_energy_delta_eel, ""gb_energy_delta_14vdw"": self.gb_energy_delta_14vdw, ""gb_energy_delta_14eel"": self.gb_energy_delta_14eel, ""gb_energy_delta_egb"": self.gb_energy_delta_egb, ""gb_energy_delta_esurf"": self.gb_energy_delta_esurf, ""gb_energy_delta_ggas"": self.gb_energy_delta_ggas, ""gb_energy_delta_gsolv"": self.gb_energy_delta_gsolv, ""gb_energy_delta_total"": self.gb_energy_delta_total, ""pb_energy_complex_bond"": self.pb_energy_complex_bond, ""pb_energy_complex_angle"": self.pb_energy_complex_angle, ""pb_energy_complex_dihed"": self.pb_energy_complex_dihed, ""pb_energy_complex_vdwaals"": self.pb_energy_complex_vdwaals, ""pb_energy_complex_eel"": self.pb_energy_complex_eel, ""pb_energy_complex_14vdw"": self.pb_energy_complex_14vdw, ""pb_energy_complex_14eel"": self.pb_energy_complex_14eel, ""pb_energy_complex_epb"": self.pb_energy_complex_epb, ""pb_energy_complex_enpolar"": self.pb_energy_complex_enpolar, ""pb_energy_complex_edisper"": self.pb_energy_complex_edisper, ""pb_energy_complex_ggas"": self.pb_energy_complex_ggas, ""pb_energy_complex_gsolv"": self.pb_energy_complex_gsolv, ""pb_energy_complex_total"": self.pb_energy_complex_total, ""pb_energy_receptor_bond"": self.pb_energy_receptor_bond, ""pb_energy_receptor_angle"": self.pb_energy_receptor_angle, ""pb_energy_receptor_dihed"": self.pb_energy_receptor_dihed, ""pb_energy_receptor_vdwaals"": self.pb_energy_receptor_vdwaals, ""pb_energy_receptor_eel"": self.pb_energy_receptor_eel, ""pb_energy_receptor_14vdw"": self.pb_energy_receptor_14vdw, ""pb_energy_receptor_14eel"": self.pb_energy_receptor_14eel, ""pb_energy_receptor_epb"": self.pb_energy_receptor_epb, ""pb_energy_receptor_enpolar"": self.pb_energy_receptor_enpolar, ""pb_energy_receptor_edisper"": self.pb_energy_receptor_edisper, ""pb_energy_receptor_ggas"": self.pb_energy_receptor_ggas, ""pb_energy_receptor_gsolv"": self.pb_energy_receptor_gsolv, ""pb_energy_receptor_total"": self.pb_energy_receptor_total, ""pb_energy_ligand_bond"": self.pb_energy_ligand_bond, ""pb_energy_ligand_angle"": self.pb_energy_ligand_angle, ""pb_energy_ligand_dihed"": self.pb_energy_ligand_dihed, ""pb_energy_ligand_vdwaals"": self.pb_energy_ligand_vdwaals, ""pb_energy_ligand_eel"": self.pb_energy_ligand_eel, ""pb_energy_ligand_14vdw"": self.pb_energy_ligand_14vdw, ""pb_energy_ligand_14eel"": self.pb_energy_ligand_14eel, ""pb_energy_ligand_epb"": self.pb_energy_ligand_epb, ""pb_energy_ligand_enpolar"": self.pb_energy_ligand_enpolar, ""pb_energy_ligand_edisper"": self.pb_energy_ligand_edisper, ""pb_energy_ligand_ggas"": self.pb_energy_ligand_ggas, ""pb_energy_ligand_gsolv"": self.pb_energy_ligand_gsolv, ""pb_energy_ligand_total"": self.pb_energy_ligand_total, ""pb_energy_delta_bond"": self.pb_energy_delta_bond, ""pb_energy_delta_angle"": self.pb_energy_delta_angle, ""pb_energy_delta_dihed"": self.pb_energy_delta_dihed, ""pb_energy_delta_vdwaals"": self.pb_energy_delta_vdwaals, ""pb_energy_delta_eel"": self.pb_energy_delta_eel, ""pb_energy_delta_14vdw"": self.pb_energy_delta_14vdw, ""pb_energy_delta_14eel"": self.pb_energy_delta_14eel, ""pb_energy_delta_epb"": self.pb_energy_delta_epb, ""pb_energy_delta_enpolar"": self.pb_energy_delta_enpolar, ""pb_energy_delta_edisper"": self.pb_energy_delta_edisper, ""pb_energy_delta_ggas"": self.pb_energy_delta_ggas, ""pb_energy_delta_gsolv"": self.pb_energy_delta_gsolv, ""pb_energy_delta_total"": self.pb_energy_delta_total, } pd.DataFrame.from_dict(delta_g_dict).to_csv(output_file, index=False) ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/free_energy/fep_analysis.py",".py","12699","287","import json import math from pathlib import Path import warnings import numpy as np import pandas as pd from alchemlyb import concat from alchemlyb.estimators import MBAR, TI from alchemlyb.parsing.gmx import extract_dHdl, extract_u_nk # from alchemlyb.visualisation import plot_convergence # from alchemlyb.convergence import forward_backward_convergence from alchemlyb.postprocessors import units from alchemlyb.preprocessing import slicing, statistical_inefficiency from bindflow.utils.tools import PathLike, sum_uncertainty_propagation def run_alchemlyb(xvgs: list, lower: int = None, upper: int = None, min_samples: int = 500, temperature: float = 298.15, convergency_plots_prefix: str = None) -> dict: """""" Function to get MBAR and TI estimates using alchemlyb from an input set of xvgs Parameters ---------- xvgs : list of str list of filenames for input xvg files. This list must be sorted based on the lambda values. For example. If we have coul and vdw and three lambda points; the list must be: either: [coul1, coul2, coul3, vdw1, vdw2, vdw3] or [vdw1, vdw2, vdw3, coul1, coul2, coul3] TODO: We can sort the input files too. I am also not sure that that is needed. Maybe alchemlyb does the sort internally. overlap_path : str path to write overlap matrix (if None, no matrix will be written) [None] lower : int starting time to sample dhdl xvgs from [None] upper : int inclusive end time to sample dhdl xvgs from [None] min_samples : int minimum number of samples to analyze, if statistical inefficiency returns fewer samples than this, then min_samples will be picked instead [500] temperature : float simulation temperature [298.15] convergency_plots_prefix : str If gives, it will plot the convergency to {convergency_plots_prefix}convergence_TI.pdf and {convergency_plots_prefix}convergence_MBAR.pdf, by default None Returns ------- deltaG : dict deltaG = { 'MBAR': { 'value': , 'error': }, 'TI': { 'value': , 'error': }, } two entry dictionary containing the MBAR and TI free energy and associated variance error estimate in kcal/mol """""" # Check how many independent samples do we have in our data. sub_steps = [] for xvg in xvgs: extracted_dHdls = extract_dHdl(xvg, T=temperature) df = slicing(extracted_dHdls, lower=lower, upper=upper) df_ineff = statistical_inefficiency(df, series=df.iloc[:, 0]) if len(df_ineff) != 0: ineff_step = math.ceil(len(df) / len(df_ineff)) else: ineff_step = 1 wmsg = f""statistical_inefficiency does not give data. This usually means that the sampling is too poor.\n {xvg = }"" warnings.warn(wmsg) # Check the lag of the step to fulfill the minimum number of samples step_cutoff = int(len(df) / min_samples) if step_cutoff == 0: step_cutoff = 1 wmsg = f""The number of raw data point ({len(df)}) is less than {min_samples =}. ""\ f""This usually means that the sampling is too poor\n {xvg = }"" warnings.warn(wmsg) # Select the proper step lag if ineff_step <= step_cutoff: sub_steps.append(ineff_step) else: sub_steps.append(int(step_cutoff)) print(f""number of samples per window: {[int(len(df) / sub_step) for sub_step in sub_steps]}"") dhdls_data = [slicing(extract_dHdl(xvg, T=temperature), lower=lower, upper=upper, step=step) for xvg, step in zip(xvgs, sub_steps)] u_nks_data = [slicing(extract_u_nk(xvg, T=temperature), lower=lower, upper=upper, step=step) for xvg, step in zip(xvgs, sub_steps)] # Get estimations mbar = MBAR(maximum_iterations=1000000).fit(concat(u_nks_data)) ti = TI().fit(concat(dhdls_data)) # TODO And print some images that show some convergence related factors # Convert values and errors to kcal/mol, and access the free energy difference between the states at lambda 0.0 and 1.0 deltaG = { 'MBAR': { 'value': units.to_kcalmol(mbar.delta_f_).iloc[0, -1], 'error': units.to_kcalmol(mbar.d_delta_f_).iloc[0, -1] }, 'TI': { 'value': units.to_kcalmol(ti.delta_f_).iloc[0, -1], 'error': units.to_kcalmol(ti.d_delta_f_).iloc[0, -1] } } # # Evaluate convergency # # TODO: On MBAR I am getting LLVM ERROR: pthread_create failed: Resource temporarily unavailable Aborted # # And I can not capture this error # if convergency_plots_prefix: # try: # ax = plot_convergence(forward_backward_convergence(dhdls_data, 'TI')) # ax.figure.savefig(f'{convergency_plots_prefix}convergence_TI.pdf') # # ax = plot_convergence(forward_backward_convergence(u_nks_data, 'MBAR')) # # ax.figure.savefig(f'{convergency_plots_prefix}convergence_MBAR.pdf') # except Exception as e: # print(f""Not possible to evaluate convergency on: {xvgs}\n. Exception {e} was got it"") return deltaG # Used on complex(ligand)_fep_ana.smk def get_dG_contributions( boresch_data: PathLike = None, out_json_path: PathLike = 'dg_contributions.json', lower: int = None, upper: int = None, min_samples: int = 500, temperature: float = 298.15, convergency_plots_prefix: str = None, **kwargs): """"""It calculate and gather the vdw, coul and bonded (in case of a complex) dG' contributions. It also adds the analytical correction due to the ligand restraints. Parameters ---------- boresch_data : PathLike, optional File with the boresch analytical corrections, by default None out_csv_path : PathLike, optional Path to output the results, by default 'dg_contributions.csv'. It is going to have as columns: [MBAR, TI, boresch] and as index: [value, error]. lower : int, optional Upper time to slice, by default None upper : int, optional Upper time to slice to (inclusive), by default None min_samples : int, optional Minimum number of samples to use, by default 500 temperature : float, optional Temperature of the simulation, by default 298.15 convergency_plots_prefix : str If gives, it will plot the convergency to {convergency_plots_prefix}{}_convergence_TI.pdf and {convergency_plots_prefix}{}_convergence_MBAR.pdf, by default None **kwargs : optional Only vdw = , coul = and bonded = are valid extra keywords. Those are the path to the xvg files of the corresponded lambda type. # TODO: They should be order form lambda 0 to 1??. it is safe to do it. Raises ------ ValueError Invalid kwargs. Only valid: vdw, could and bonded ValueError The value of the kwargs is not a list FileNotFoundError If some xvg files are not found. """""" # Check validity of keywords: valid_kwargs = ['vdw', 'coul', 'bonded'] for key in kwargs: if key not in valid_kwargs: raise ValueError(f""The provided extra keyword '{key}' is not valid. Choose from: {valid_kwargs}"") elif not isinstance(kwargs[key], list): raise ValueError(f""The provided extra keyword '{key}' is valid. But its value '{kwargs[key]}' is not an integer"") system_results = dict() # For each lambda_type get each its xvg in a sorted manner. for lambda_type in kwargs: for xvg_file in kwargs[lambda_type]: # Check that all xvg files exist if not Path(xvg_file).is_file(): raise FileNotFoundError(f""Provided xvg file: {xvg_file} for lambda_type = {lambda_type} "") if convergency_plots_prefix: convergency_plots_prefix_to_use = f""{convergency_plots_prefix}{lambda_type}_"" else: convergency_plots_prefix_to_use = None print(f'Analyzing {lambda_type =}') dG = run_alchemlyb(xvgs=kwargs[lambda_type], lower=lower, upper=upper, min_samples=min_samples, temperature=temperature, convergency_plots_prefix=convergency_plots_prefix_to_use) ddG_estimator = abs(dG['MBAR']['value'] - dG['TI']['value']) if ddG_estimator > 0.5: wmsg = (f'|dG_MBAR - dG_TI| = {ddG_estimator} > 0.5 kcal/mol for {lambda_type}') warnings.warn(wmsg) system_results[lambda_type] = dG # include boresch correction if boresch_data: system_results['boresch'] = float(np.loadtxt(boresch_data)) # Write the data with open(out_json_path, 'w') as out: json.dump(system_results, out, indent=4) # TODO, check what is going on here calculate_FEP_ligand_dG def get_dg_cycle(ligand_contributions: PathLike = 'dg_ligand_contributions.json', complex_contributions: PathLike = 'dg_complex_contributions.json', out_csv: PathLike = 'dG_results.csv'): # Create new dict containing the results and calculate complete process: with open(ligand_contributions, 'r') as lc: ligand_dict = json.load(lc) with open(complex_contributions, 'r') as cc: complex_dict = json.load(cc) # TODO: I made a small test with reverse True or False in the during sort of xvgs and I am always getting the same value, # So that means that the order should not be a problem, the lambda values are guessing from the xvg file itself # The cycle is based on 10.1038/s42004-022-00721-4 # And all the mdp are build in such a way that the last state is at lambda 1 and the first one at 0 # The only exception is with the bonded # These bonded are based on the boresch restraints and works based on the [ intermolecular_interactions ] # Here 1 means restraints turned on and 0 off. because of that the thermodynamic cycle goes from: # ligand+restraint(bonded) in the complex [lambda = 1] --> ligand in the complex [lambda = 0] # And becasue what we are getting is [lambda = 1] - [lambda = 0] we must use the opposite sign # Also for this on the could and vdw bonded-lambda is set to [1]*number of states # TODO: maybe is a good idea to add it with the opposite sign on the previous steps anyways # ligand_dict[""boresch""] # https://github.com/IAlibay/MDRestraintsGenerator/blob/fa97e5f7032e40327d9d9520091ea5c194aebb86/MDRestraintsGenerator/datatypes.py#L993 # Is the energy to release the restraint, so, we have to subtract, because on the cycle we are activating that restraint # the equation used in: MDRestraintsGenerator.MDRestraintsGenerator.datatypes.BoreschRestraint._analytical_energy # Is the same exposed on: https://chemrxiv.org/engage/chemrxiv/article-details/63cb0e401fb2a897c6dafbd8 # For compatibility try: boresch_off = complex_dict[""boresch""] except KeyError: boresch_off = ligand_dict[""boresch""] dG_MBAR_value = ligand_dict[""coul""][""MBAR""][""value""] + ligand_dict[""vdw""][""MBAR""][""value""] - boresch_off + \ complex_dict[""vdw""][""MBAR""][""value""] + complex_dict[""coul""][""MBAR""][""value""] - complex_dict[""bonded""][""MBAR""][""value""] dG_MBAR_std_dev = sum_uncertainty_propagation( [ ligand_dict[""coul""][""MBAR""][""error""], ligand_dict[""vdw""][""MBAR""][""error""], complex_dict[""vdw""][""MBAR""][""error""], complex_dict[""coul""][""MBAR""][""error""], complex_dict[""bonded""][""MBAR""][""error""] ] ) dG_TI_value = ligand_dict[""coul""][""TI""][""value""] + ligand_dict[""vdw""][""TI""][""value""] - boresch_off + \ complex_dict[""vdw""][""TI""][""value""] + complex_dict[""coul""][""TI""][""value""] - complex_dict[""bonded""][""TI""][""value""] dG_TI_std_dev = sum_uncertainty_propagation( [ ligand_dict[""coul""][""TI""][""error""], ligand_dict[""vdw""][""TI""][""error""], complex_dict[""vdw""][""TI""][""error""], complex_dict[""coul""][""TI""][""error""], complex_dict[""bonded""][""TI""][""error""] ] ) deltaG = { 'MBAR': { 'value': dG_MBAR_value, 'std_dev': dG_MBAR_std_dev }, 'TI': { 'value': dG_TI_value, 'std_dev': dG_TI_std_dev } } pd.DataFrame(deltaG).to_csv(out_csv) if __name__ == ""__main__"": pass ","Python" "Biophysics","ale94mleon/BindFlow","src/bindflow/free_energy/gather_results.py",".py","12286","290","import glob import json import os from pathlib import Path from typing import List, Union import numpy as np import pandas as pd from bindflow.utils.tools import PathLike, sum_uncertainty_propagation def get_fep_stats(replica_paths: List[PathLike]) -> dict: """"""Takes all the replica path and extract free energy statistics Parameters ---------- replica_paths : List[PathLike] A list with all the replica paths Returns ------- dict A dictionary with keywords: #. : the average value of the estimator #. _sem: Standard error of the mean #. _uncertainty_propagation: Propagate the uncertainties after the average. This use the estimated uncertainties from alchemlyb (Check :func:`bindflow.free_energy.fep_analysis.run_alchemlyb`) #. _num_replicas: The number of replicas employed. """""" # Get for each estimator the corresponded values and standard deviations estimator_result = dict() for replica_path in replica_paths: df = pd.read_csv(replica_path, index_col=0) for estimator in df.columns: if estimator in estimator_result: estimator_result[estimator].append((df.loc['value', estimator], df.loc['std_dev', estimator])) else: estimator_result[estimator] = [(df.loc['value', estimator], df.loc['std_dev', estimator])] # Build the final result final_result = dict() for estimator in estimator_result: mean_value = np.mean([value_error[0] for value_error in estimator_result[estimator]]) mean_std_dev = sum_uncertainty_propagation( errors=[value_error[1] for value_error in estimator_result[estimator]], coefficients=len(estimator_result[estimator]) * [1/len(estimator_result[estimator])] ) # Save results final_result[estimator] = mean_value final_result[f""{estimator}_sem""] = pd.Series([value_error[0] for value_error in estimator_result[estimator]]).sem(ddof=1) final_result[f""{estimator}_uncertainty_propagation""] = mean_std_dev final_result[f""{estimator}_num_replicas""] = len(estimator_result[estimator]) return final_result def get_all_fep_dgs(root_folder_path: PathLike, out_csv: PathLike = None) -> pd.DataFrame: """"""Get the independent FEP results and gather them. Average and standard error of the mean are reported. Parameters ---------- root_folder_path : PathLike Where the simulation run. Inside it should be the files: root_folder_path + ""/*/*/dG_results.csv"". This directory is the same specified on :func:`bindflow.runnner.calculate` through the keyword `out_root_folder_path` out_csv : PathLike, optional If given a pandas.DataFrame will be written as csv file, by default None Returns ------- pd.DataFrame All gather results. If there are not dG_results.csv; It will return an empty DataFrame """""" # Get all dG_results.csv files root_folder_path = str(root_folder_path) dg_files_dir = dict() for dg_file in glob.glob(root_folder_path + ""/*/*/dG_results.csv""): dg_file = os.path.normpath(dg_file) ligand_name = dg_file.split(os.path.sep)[-3] if ligand_name in dg_files_dir: dg_files_dir[ligand_name].append(dg_file) else: dg_files_dir[ligand_name] = [dg_file] gathered_results = [] if dg_files_dir: for ligand in dg_files_dir: statistics = get_fep_stats(dg_files_dir[ligand]) statistics['ligand'] = ligand gathered_results.append(statistics) gathered_results = pd.DataFrame(gathered_results) # Put the column 'ligand' at the beginning columns = ['ligand'] + [col for col in gathered_results.columns if col != 'ligand'] gathered_results = gathered_results[columns] # Safe data on request if out_csv: gathered_results.to_csv(out_csv) return gathered_results else: print(f""There is not dG_results.csv yet on {root_folder_path}/*/*"") return pd.DataFrame() def get_raw_fep_data(root_folder_path: PathLike, out_csv: PathLike = None) -> pd.DataFrame: """"""Generate raw dat for an FEP calculation using BindFlow Parameters ---------- root_folder_path : PathLike Where the simulation run. Inside it should be the files: root_folder_path + ""/*/*/complex/fep/ana/dg_complex_contributions.json"". This directory is the same specified on :func:`bindflow.runners.calculate` through the keyword `out_root_folder_path` out_csv : PathLike, optional If given a pandas.DataFrame will be written as csv file, by default None Returns ------- pd.DataFrame Raw FEP data, all the contributions for all ligand/replicas """""" sample_data = [] root_folder_path = Path(root_folder_path).resolve() for item1 in root_folder_path.iterdir(): if item1.is_dir(): ligand = item1.stem for item2 in item1.iterdir(): if item2.is_dir(): replica = item2.stem complex_json = item2/""complex/fep/ana/dg_complex_contributions.json"" ligand_json = item2/""ligand/fep/ana/dg_ligand_contributions.json"" if complex_json.is_file() and ligand_json.is_file(): with open(complex_json, 'r') as cj: complex_data = json.load(cj) with open(ligand_json, 'r') as lj: ligand_data = json.load(lj) sample_data.append( [ ligand, replica, complex_data['vdw']['MBAR']['value'], complex_data['coul']['MBAR']['value'], complex_data['bonded']['MBAR']['value'], ligand_data['vdw']['MBAR']['value'], ligand_data['coul']['MBAR']['value'], complex_data['vdw']['TI']['value'], complex_data['coul']['TI']['value'], complex_data['bonded']['TI']['value'], ligand_data['vdw']['TI']['value'], ligand_data['coul']['TI']['value'], complex_data['boresch'], complex_data['vdw']['MBAR']['error'], complex_data['coul']['MBAR']['error'], complex_data['bonded']['MBAR']['error'], ligand_data['vdw']['MBAR']['error'], ligand_data['coul']['MBAR']['error'], complex_data['vdw']['TI']['error'], complex_data['coul']['TI']['error'], complex_data['bonded']['TI']['error'], ligand_data['vdw']['TI']['error'], ligand_data['coul']['TI']['error'], ] ) df = pd.DataFrame( sample_data, columns=[ 'ligand', 'replica', 'mbar_complex_vdw_value', 'mbar_complex_coul_value', 'mbar_complex_bonded_value', 'mbar_ligand_vdw_value', 'mbar_ligand_coul_value', 'ti_complex_vdw_value', 'ti_complex_coul_value', 'ti_complex_bonded_value', 'ti_ligand_vdw_value', 'ti_ligand_coul_value', 'boresch', 'mbar_complex_vdw_error', 'mbar_complex_coul_error', 'mbar_complex_bonded_error', 'mbar_ligand_vdw_error', 'mbar_ligand_coul_error', 'ti_complex_vdw_error', 'ti_complex_coul_error', 'ti_complex_bonded_error', 'ti_ligand_vdw_error', 'ti_ligand_coul_error', ] ) if out_csv: df.to_csv(out_csv) return df def get_all_mmxbsa_dgs(full_df: pd.DataFrame, columns_to_process: Union[None, List[str]] = None, out_csv: PathLike = None) -> pd.DataFrame: """"""Get the independent MM(P/G)BSA free energy results and gather them. Average and standard error of the mean are across all replicas and samples for each ligand are reported Parameters ---------- full_df : pd.DataFrame, DataFrame generated by :func:`bindflow.free_energy.gather_results.get_raw_mmxbsa_dgs` columns_to_process : Union[None, List[str]], optional The columns of full_df to process, by default None which means that the following will be used: ""dg_c2_pb"", ""dg_c2_gb"", ""dg_ie_pb"", ""dg_ie_gb"", ""dg_qh_pb"", ""dg_qh_gb"", ""dg_en_pb"", ""dg_en_gb"", ""c2_pb"", ""c2_gb"", ""ie_pb"", ""ie_gb"", ""qh"" out_csv : PathLike, optional If given a pandas.DataFrame will be written as csv file, by default None Returns ------- pd.DataFrame All gather results. In case there are not dG_results.csv. It will return an empty DataFrame """""" if len(full_df): if columns_to_process is None: columns_to_process = [ ""dg_c2_pb"", ""dg_c2_gb"", ""dg_ie_pb"", ""dg_ie_gb"", ""dg_qh_pb"", ""dg_qh_gb"", ""dg_en_pb"", ""dg_en_gb"", ""c2_pb"", ""c2_gb"", ""ie_pb"", ""ie_gb"", ""qh"" ] # # Convert replica and sample column to integers # full_df['sample'] = full_df['sample'].astype(int) # Group by 'name' and calculate mean and SEM grouped = full_df.groupby('name') mean_df = grouped[columns_to_process].mean().reset_index() sem_df = grouped[columns_to_process].sem().reset_index() # Count unique replicas replica_counts = grouped['replica'].nunique().reset_index(name='num_replicas') # Calculate total samples total_samples = grouped['sample'].count().reset_index(name='total_samples') # Merge the results final_df = mean_df.merge(sem_df, on='name', suffixes=('_mean', '_sem')) final_df = final_df.merge(replica_counts, on='name') final_df = final_df.merge(total_samples, on='name') if out_csv: final_df.to_csv(out_csv, index=False) return final_df else: return pd.DataFrame() def get_raw_mmxbsa_dgs(root_folder_path: PathLike, out_csv: PathLike = None) -> pd.DataFrame: """"""Main function to retrieve MM(P/G)BSA simulation data generated through BindFlow Parameters ---------- root_folder_path : PathLike Where the simulation run. Inside it should be the files: root_folder_path + ""/*/*/complex/mmpbsa/simulation/*/mmxbsa.csv"". This directory is the same specified on :func:`bindflow.run_mmpbsa.calculate_mmpbsa` through the keyword `out_root_folder_path` out_csv : PathLike, optional If given, a pandas.DataFrame will be written as csv file with the raw data, by default None Returns ------- pd.DataFrame Raw MM(P/G)BSA data """""" from bindflow.free_energy import mmxbsa_analysis root_folder_path = str(root_folder_path) collected_dfs = [] collected_files = glob.glob(root_folder_path + ""/*/*/complex/mmpbsa/simulation/*/mmxbsa.csv"") if len(collected_files) == 0: print(f""There is not mmxbsa.csv yet on {root_folder_path}/*/*/complex/mmpbsa/simulation/*/mmxbsa.csv"") return pd.DataFrame() for inp_file in collected_files: # collecting all of the mmxbsa.csv files string_data = inp_file.removeprefix(root_folder_path).split(""/"") ligand_name, replica, sample = string_data[1], string_data[2], string_data[6].removeprefix(""rep."") collected_dfs.append(mmxbsa_analysis.convert_format_flatten(pd.read_csv(inp_file), ligand_name, replica, sample)) full_df = pd.concat(collected_dfs, ignore_index=True) if out_csv: full_df.to_csv(out_csv, index=False) return full_df if __name__ == '__main__': pass ","Python" "Biophysics","ale94mleon/BindFlow","examples/CyclophilinD/executor-fep.py",".py","1424","55","#!/usr/bin/env python3 import yaml import glob from bindflow.runners import calculate from bindflow.orchestration.generate_scheduler import SlurmScheduler calculation_type = 'fep' force_fields = { ""openff_unconstrained-2.0.0"": { ""type"": ""openff"", ""code"": ""openff_unconstrained-2.0.0.offxml"", }, ""espaloma-0.3.1"": { ""type"": ""espaloma"", ""code"": ""espaloma-0.3.1"", }, ""gaff-2.11"": { ""type"": ""gaff"", ""code"": ""gaff-2.11"", }, } ligand_files = glob.glob(""inputs/ligands/*.sdf"") with open(f""config-{calculation_type}.yml"", ""r"") as c: global_config = yaml.safe_load(c) for ff_id, info in force_fields.items(): ligands = [] for ligand_file in ligand_files: ligands.append({ 'conf': ligand_file, 'ff': { 'type': info[""type""], 'code': info[""code""] } }) calculate( calculation_type=calculation_type, protein='inputs/receptor_protein.pdb', ligands=ligands, water_model='amber/tip3p', hmr_factor=2.5, out_root_folder_path=f""{calculation_type}/{ff_id}"", threads=10, # Configure it based on your cluster num_jobs=100000, replicas=3, scheduler_class=SlurmScheduler, debug=False, job_prefix=f'cycloD.{ff_id}', submit=False, global_config=global_config) ","Python" "Biophysics","ale94mleon/BindFlow","examples/CyclophilinD/executor-mmpbsa.py",".py","1486","57","#!/usr/bin/env python3 import yaml import glob from bindflow.runners import calculate from bindflow.orchestration.generate_scheduler import SlurmScheduler calculation_type = 'mmpbsa' # For benchmark several force fields may be tested # But for production consider to use only one force_fields = { ""openff_unconstrained-2.0.0"": { ""type"": ""openff"", ""code"": ""openff_unconstrained-2.0.0.offxml"", }, ""espaloma-0.3.1"": { ""type"": ""espaloma"", ""code"": ""espaloma-0.3.1"", }, ""gaff-2.11"": { ""type"": ""gaff"", ""code"": ""gaff-2.11"", }, } ligand_files = glob.glob(""inputs/ligands/*.sdf"") with open(f""config-{calculation_type}.yml"", ""r"") as c: global_config = yaml.safe_load(c) for ff_id, info in force_fields.items(): ligands = [] for ligand_file in ligand_files: ligands.append({ 'conf': ligand_file, 'ff': { 'type': info[""type""], 'code': info[""code""] } }) calculate( calculation_type=calculation_type, protein='inputs/receptor_protein.pdb', ligands=ligands, water_model='amber/tip3p', hmr_factor=2.5, out_root_folder_path=f""{calculation_type}/{ff_id}"", threads=10, num_jobs=100000, replicas=3, scheduler_class=SlurmScheduler, debug=False, job_prefix=f'cycloD.{ff_id}', submit=False, global_config=global_config) ","Python" "Biophysics","ale94mleon/BindFlow","examples/A2A/executor-fep.py",".py","1710","65","#!/usr/bin/env python3 import yaml import glob from bindflow.runners import calculate from bindflow.orchestration.generate_scheduler import SlurmScheduler calculation_type = 'fep' force_fields = { ""openff_unconstrained-2.0.0"": { ""type"": ""openff"", ""code"": ""openff_unconstrained-2.0.0.offxml"", }, ""espaloma-0.3.1"": { ""type"": ""espaloma"", ""code"": ""espaloma-0.3.1"", }, ""gaff-2.11"": { ""type"": ""gaff"", ""code"": ""gaff-2.11"", }, } ligand_files = glob.glob(""inputs/sdf_split/*.mol"") with open(f""config-{calculation_type}.yml"", ""r"") as c: global_config = yaml.safe_load(c) for ff_id, info in force_fields.items(): ligands = [] for ligand_file in ligand_files: ligands.append({ 'conf': ligand_file, 'ff': { 'type': info[""type""], 'code': info[""code""] } }) calculate( calculation_type=calculation_type, protein={ 'conf': 'inputs/protein-amber14-all/protein.gro', 'top': 'inputs/protein-amber14-all/protein.top', }, ligands=ligands, membrane='inputs/membrane.pdb', cofactor={ 'conf': 'inputs/cofactor.gro', 'top': 'inputs/cofactor.top', 'is_water': False, }, cofactor_on_protein=True, water_model='amber/tip3p', hmr_factor=2.5, out_root_folder_path=f""{calculation_type}/{ff_id}"", threads=10, num_jobs=100000, replicas=3, scheduler_class=SlurmScheduler, debug=False, job_prefix=f'a2a.{ff_id}', submit=False, global_config=global_config) ","Python" "Biophysics","ale94mleon/BindFlow","examples/A2A/executor-mmpbsa.py",".py","1713","65","#!/usr/bin/env python3 import yaml import glob from bindflow.runners import calculate from bindflow.orchestration.generate_scheduler import SlurmScheduler calculation_type = 'mmpbsa' force_fields = { ""openff_unconstrained-2.0.0"": { ""type"": ""openff"", ""code"": ""openff_unconstrained-2.0.0.offxml"", }, ""espaloma-0.3.1"": { ""type"": ""espaloma"", ""code"": ""espaloma-0.3.1"", }, ""gaff-2.11"": { ""type"": ""gaff"", ""code"": ""gaff-2.11"", }, } ligand_files = glob.glob(""inputs/sdf_split/*.mol"") with open(f""config-{calculation_type}.yml"", ""r"") as c: global_config = yaml.safe_load(c) for ff_id, info in force_fields.items(): ligands = [] for ligand_file in ligand_files: ligands.append({ 'conf': ligand_file, 'ff': { 'type': info[""type""], 'code': info[""code""] } }) calculate( calculation_type=calculation_type, protein={ 'conf': 'inputs/protein-amber14-all/protein.gro', 'top': 'inputs/protein-amber14-all/protein.top', }, ligands=ligands, membrane='inputs/membrane.pdb', cofactor={ 'conf': 'inputs/cofactor.gro', 'top': 'inputs/cofactor.top', 'is_water': False, }, cofactor_on_protein=True, water_model='amber/tip3p', hmr_factor=2.5, out_root_folder_path=f""{calculation_type}/{ff_id}"", threads=10, num_jobs=100000, replicas=3, scheduler_class=SlurmScheduler, debug=False, job_prefix=f'a2a.{ff_id}', submit=False, global_config=global_config) ","Python" "Biophysics","ale94mleon/BindFlow","examples/A2A/make_ndx.py",".py","4472","115","from pathlib import Path from glob import glob from bindflow.utils import tools from typing import List import tempfile import logging logger = logging.getLogger(__name__) def index_for_membrane_system( configuration_file: tools.PathLike, ndxout: tools.PathLike = ""index.ndx"", ligand_name: str = ""LIG"", host_name: str = ""Protein"", host_name_for_mmpbsa: str = ""Protein"", cofactor_name: str = None, cofactor_on_protein: bool = True, load_dependencies: List[str] = None): """"""Make the index file for membrane systems with SOLU, MEMB and SOLV. It uses gmx make_ndx and select internally. One examples selection that can be created with ligand_name = LIG; cofactor_name = COF and cofactor_on_protein = True is: #. ""RECEPTOR"" group {host_name_for_mmpbsa}; #. ""LIGAND"" resname {ligand_name}; #. ""SOLU"" group {host_name} or resname {ligand_name} or resname COF; #. ""MEMB"" ((group System and ! group Water_and_ions) and ! group {host_name}) and ! (resname {ligand_name}) and ! (resname COF); #. ""SOLV"" group Water_and_ions; Parameters ---------- configuration_file : PathLike PDB or GRO file of the system. ndxout : PathLike Path to output the index file. ligand_name : str The residue name for the ligand in the configuration file, by default ""LIG"". host_name : str The group name for the host in the configuration file, by default ""Protein"". cofactor_name : str The residue name for the cofactor in the configuration file, bt default None cofactor_on_protein : bool It only works if cofactor_name is provided. If True, the cofactor will be part of the protein and the lignad if False will be part of the solvent and ions, bt default True load_dependencies : List[str], optional It is used in case some previous loading steps are needed for GROMACS commands; e.g: ['source /groups/CBG/opt/spack-0.18.1/shared.bash', 'module load sandybridge/gromacs/2022.4'], by default None """""" tmpopt = tempfile.NamedTemporaryFile(suffix='.opt') tmpndx = tempfile.NamedTemporaryFile(suffix='.ndx') # Nice use of gmx select, see the use of the parenthesis sele_RECEPTOR = f""\""RECEPTOR\"" group {host_name_for_mmpbsa}"" sele_LIGAND = f""\""LIGAND\"" resname {ligand_name}"" sele_MEMB = f""\""MEMB\"" ((group System and ! group Water_and_ions) and ! group {host_name}) and ! (resname {ligand_name})"" sele_SOLU = f""\""SOLU\"" group {host_name} or resname {ligand_name}"" sele_SOLV = ""\""SOLV\"" group Water_and_ions"" if cofactor_name: sele_MEMB += f"" and ! (resname {cofactor_name})"" if cofactor_on_protein: sele_SOLU += f"" or resname {cofactor_name}"" else: sele_SOLV += f"" or resname {cofactor_name}"" logger.info(""Groups in the index.ndx file:"") logger.info(f""\t{sele_RECEPTOR}"") logger.info(f""\t{sele_LIGAND}"") logger.info(f""\t{sele_SOLU}"") logger.info(f""\t{sele_MEMB}"") logger.info(f""\t{sele_SOLV}"") sele_RECEPTOR += "";\n"" sele_LIGAND += "";\n"" sele_SOLU += "";\n"" sele_MEMB += "";\n"" sele_SOLV += "";\n"" with open(tmpopt.name, ""w"") as opt: opt.write(sele_RECEPTOR + sele_LIGAND + sele_SOLU + sele_MEMB + sele_SOLV) @tools.gmx_command(load_dependencies=load_dependencies, stdin_command=""echo \""q\"""") def make_ndx(**kwargs): ... @tools.gmx_command(load_dependencies=load_dependencies) def select(**kwargs): ... make_ndx(f=configuration_file, o=tmpndx.name) select(s=configuration_file, sf=tmpopt.name, n=tmpndx.name, on=ndxout) # deleting the line _f0_t0.000 in the file with open(ndxout, ""r"") as index: data = index.read() data = data.replace(""_f0_t0.000"", """") with open(ndxout, ""w"") as index: index.write(data) tmpopt.close() tmpndx.close() index_files = glob('mmpbsa/*/*/input/complex/index.ndx') for index_file in index_files: index_file = Path(index_file) parent_dir = index_file.parent print(index_file) index_for_membrane_system( configuration_file=parent_dir/'complex.gro', ndxout=index_file, ligand_name='LIG', host_name='Protein', host_name_for_mmpbsa='Protein or resname COF', load_dependencies=['export GMX_MAXBACKUP=-1'], cofactor_name='COF', cofactor_on_protein=True, ) ","Python" "Biophysics","ale94mleon/BindFlow","examples/SAMPL6-OA/executor-fep.py",".py","1427","55","#!/usr/bin/env python3 import yaml import glob from bindflow.runners import calculate from bindflow.orchestration.generate_scheduler import SlurmScheduler calculation_type = 'fep' force_fields = { ""espaloma-0.3.1"": { ""type"": ""espaloma"", ""code"": ""espaloma-0.3.1"" }, } ligand_files = glob.glob(""inputs/guests/*.sdf"") with open(f""config-{calculation_type}.yml"", ""r"") as c: global_config = yaml.safe_load(c) for ff_id, info in force_fields.items(): ligands = [] for ligand_file in ligand_files: ligands.append({ 'conf': ligand_file, 'ff': { 'type': info[""type""], 'code': info[""code""] } }) calculate( calculation_type=calculation_type, protein={ 'conf': 'inputs/host/espaloma-0.3.1/OA.gro', 'top': 'inputs/host/espaloma-0.3.1/OA.top', }, ligands=ligands, out_root_folder_path=f""{calculation_type}2/{ff_id}"", cofactor=None, cofactor_on_protein=True, host_name='HOST', host_selection='resname HOST', membrane=None, water_model='amber/tip3p', hmr_factor=2.5, threads=10, num_jobs=100000, replicas=5, submit=False, debug=False, job_prefix=f'sampl6-oa.{ff_id}', scheduler_class=SlurmScheduler, global_config=global_config) ","Python" "Biophysics","ale94mleon/BindFlow","examples/SAMPL6-OA/executor-mmpbsa.py",".py","1430","55","#!/usr/bin/env python3 import yaml import glob from bindflow.runners import calculate from bindflow.orchestration.generate_scheduler import SlurmScheduler calculation_type = 'mmpbsa' force_fields = { ""espaloma-0.3.1"": { ""type"": ""espaloma"", ""code"": ""espaloma-0.3.1"" }, } ligand_files = glob.glob(""inputs/guests/*.sdf"") with open(f""config-{calculation_type}.yml"", ""r"") as c: global_config = yaml.safe_load(c) for ff_id, info in force_fields.items(): ligands = [] for ligand_file in ligand_files: ligands.append({ 'conf': ligand_file, 'ff': { 'type': info[""type""], 'code': info[""code""] } }) calculate( calculation_type=calculation_type, protein={ 'conf': 'inputs/host/espaloma-0.3.1/OA.gro', 'top': 'inputs/host/espaloma-0.3.1/OA.top', }, ligands=ligands, out_root_folder_path=f""{calculation_type}2/{ff_id}"", cofactor=None, cofactor_on_protein=True, host_name='HOST', host_selection='resname HOST', membrane=None, water_model='amber/tip3p', hmr_factor=2.5, threads=10, num_jobs=100000, replicas=3, submit=False, debug=False, job_prefix=f'sampl6-oa.{ff_id}', scheduler_class=SlurmScheduler, global_config=global_config) ","Python" "Biophysics","ale94mleon/BindFlow","docs/conf.py",".py","4516","141","# Configuration file for the Sphinx documentation builder. # # This file only contains a selection of the most common options. For a full # list see the documentation: # https://www.sphinx-doc.org/en/master/usage/configuration.html # -- Path setup -------------------------------------------------------------- # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. # import os import sys sys.path.insert(0, os.path.abspath('.')) sys.path.insert(0, os.path.abspath('./source/')) sys.path.insert(0, os.path.abspath('./notebooks/')) from datetime import datetime # -- Project information ----------------------------------------------------- project = 'BindFlow' copyright = f""2022-{datetime.now().year}, Alejandro Martínez León"" author = 'Alejandro Martínez León' # # The full version, including alpha/beta/rc tags # release = '0.0.1-beta5' # -- General configuration --------------------------------------------------- github_doc_root = 'https://github.com/ale94mleon/bindflow/tree/main/docs' # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. extensions = [ ""sphinx.ext.autodoc"", ""sphinx.ext.intersphinx"", ""sphinx.ext.mathjax"", ""sphinx.ext.viewcode"", ""sphinx.ext.napoleon"", ""sphinx.ext.autosectionlabel"", ""IPython.sphinxext.ipython_console_highlighting"", ""IPython.sphinxext.ipython_directive"", ""myst_nb"", ""sphinx_design"", ""sphinx_inline_tabs"", ""sphinx_copybutton"", ""sphinxcontrib.mermaid"", ] myst_enable_extensions = [ ""colon_fence"", ] nb_execution_allow_errors = False nb_execution_raise_on_error = True # nb_execution_timeout = -1 # Do not execute the notebooks, they take too much time nb_execution_mode = 'off' myst_heading_anchors = 6 mathjax_path = 'https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-AMS-MML_HTMLorMML' autosectionlabel_prefix_document = True napoleon_google_docstring = True # copybutton copybutton_exclude = "".linenos, .gp"" # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. # This pattern also affects html_static_path and html_extra_path. exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store'] source_suffix = { "".rst"": ""restructuredtext"", "".md"": ""myst-nb"", "".ipynb"": ""myst-nb"", "".myst"": ""myst-nb"", } # -- Options for HTML output ------------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. # html_theme = ""sphinx_book_theme"" pygments_style = ""sphinx"" html_theme_options = { ""repository_url"": ""https://github.com/ale94mleon/bindflow/"", ""path_to_docs"": ""docs"", ""use_source_button"": True, ""use_download_button"": True, ""use_repository_button"": True, ""use_issues_button"": True, ""launch_buttons"": {""colab_url"": ""https://colab.research.google.com""}, ""icon_links"": [ { ""name"": ""GitHub"", ""url"": ""https://github.com/ale94mleon/bindflow/"", ""icon"": ""fa-brands fa-square-github"", ""type"": ""fontawesome"", } ], } html_logo = ""source/_static/BindFlow-logo.svg"" # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named ""default.css"" will overwrite the builtin ""default.css"". html_static_path = [""source/_static""] html_css_files = [ ""custom.css"", ] html_js_files = [ ""custom.js"", ""https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/highlight.min.js"", ""https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/languages/yaml.min.js"", ] # -- Mock heavy or optional dependencies to avoid import errors -- autodoc_mock_imports = [ ""pandas"", ""toff"", ""parmed"" ] intersphinx_mapping = {'Python': ('https://docs.python.org/3/', None), 'numpy': ('https://numpy.org/doc/stable/', None), 'rdkit': ('https://www.rdkit.org/docs/', None), 'pandas': ('https://pandas.pydata.org/docs/', None), } ","Python" "Biophysics","ale94mleon/BindFlow","docs/source/faq.md",".md","8756","219","# ❓FAQ ````{dropdown} Atom X in residue Y was not found in rtp entry Y with x atoms while sorting atoms :color: info :animate: fade-in-slide-down BindFlow uses [PDBFixer](https://github.com/openmm/pdbfixer) for the standardization of PDB files. However, [PDBFixer](https://github.com/openmm/pdbfixer) is not bulletproof. For such cases where [pdb2gmx](https://manual.gromacs.org/current/onlinehelp/gmx-pdb2gmx.html) fails with the generated PDB file from PDBFixer; the user may fix the PDB by hand. Another strategy is give to BindFlow the TOP and GRO files instead of the plain PDB file. ### Example ```bash wget https://raw.githubusercontent.com/openforcefield/protein-ligand-benchmark/main/data/mcl1/01_protein/crd/protein.pdb ``` The following code will fail ```python from bindflow.preparation.system_builder import MakeInputs ligands = [ ""lig_63.mol"", ] protein = { 'conf': 'protein.pdb', } builder = MakeInputs( protein=protein, water_model='amber/tip3p', hmr_factor=2.5, builder_dir=""builder"") builder(ligand_definition=ligands[0], out_dir='test_test') ``` The error is going to be: ``` ------------------------------------------------------- Program: gmx pdb2gmx, version 2023.3-dev-20231019-5e5ea27-local Source file: src/gromacs/gmxpreprocess/pdb2gmx.cpp (line 870) Fatal error: Atom C in residue NME 322 was not found in rtp entry NME with 6 atoms while sorting atoms. . For more information and tips for troubleshooting, please check the GROMACS website at http://www.gromacs.org/Documentation/Errors ------------------------------------------------------- ``` #### Getting TOP and GRO files and changing protein definition ```python import parmed import os from pathlib import Path from openmm import app pdb_prot_file = Path(""inputs/protein/protein.pdb"") # Any force field in # https://github.com/openmm/openmm/tree/master/wrappers/python/openmm/app/data # can be selected protein_force_field = 'amber14-all' forcefield = app.ForceField(f'{protein_force_field}.xml', 'tip3p.xml') dirname = pdb_prot_file.parent filename = pdb_prot_file.stem out_dir = dirname / f""protein-{protein_force_field}"" Path(out_dir).mkdir(exist_ok=True) print(out_dir) pdb_obj = app.PDBFile(str(pdb_prot_file)) openmm_topology = pdb_obj.topology # Create an OpenMM System from an OpenMM Topology object system = forcefield.createSystem(pdb_obj.topology) struct = parmed.openmm.load_topology(pdb_obj.topology, system=system, xyz=pdb_obj.positions) for file_type in [out_dir / f'{filename}.gro', out_dir / f'{filename}.top']: struct.save(str(file_type), overwrite=True) ``` And then use the GRO and TOP files: ```python protein = { 'conf': 'inputs/protein/protein-amber14-all/protein.gro', 'top': 'inputs/protein/protein-amber14-all/protein.top', } ``` ```` ````{dropdown} Intramolecular Interactions: To Couple or Not to Couple :color: info :animate: fade-in-slide-down The thermodynamic cycle employed by BindFlow involves the parameter `couple-intramol = yes`, indicating that the intramolecular interactions of the ligand change alongside the λ parameter. For instance, upon removing Coulomb and van der Waals interactions in the water box, the ligand ceases to interact with the solvent while also disengaging from self-interactions via non-bonded interactions. This configuration proves advantageous for larger molecules wherein intramolecular interactions may occur over considerable distances. Otherwise, distant regions of the molecule would overly interact via explicit pair interactions, leading to artificially strong bonding, which could bias the resulting free energy. Although `couple-intramol = yes` is primarily beneficial for large molecules, BindFlow sets the default value to `yes` due to the uncertainty of the molecules being processed. Consequently, the energy contributions term `{complex, ligand}_{coul, vdw}` no longer solely denotes the change in free energy for the coupling/decoupling of `{coul, vdw}` interactions of the ligand in the `{protein, solvent}` environment. It encompasses the free energy difference for coupling/decoupling these interactions in the `{protein, solvent}` environment plus the free energy variation when the ligand's intramolecular interaction (`{coul, vdw}`) is also coupled/decoupled. This explains some big values that are usually obtained for the `coul` contribution whcih is mainly formed by the intramolecular contribution BindFlow uses the same λ-schedule for the simulations of the ligand in the water solvent and in the binding pocket of the protein (same simulation time and same λ-values). This means that the contribution of coupling/decoupling the ligand intramolecular interaction is the same but with the opposite sign for each contribution (either `coul` or `vdw`). This helps us to recover some useful information from the energetic contributions. the following sums will cancel out the ligand intramolecular contribution - {math}`\text{complex_vdw} + \text{ligand_vdw} = \text{vdw_contrib}` -> estimation of the van der Waal contribution to the binding - {math}`\text{complex_coul} + \text{ligand_coul} = \text{coul_contrib}` -> estimation of the Coulomb contribution to the binding Then the equation of the cycle: ```{math} \Delta G = \text{ligand_coul} + \text{ligand_vdw} - \text{boresch} + \text{complex_vdw} + \text{complex_coul} - \text{bonded} ``` We can rewrite it as: ```{math} \Delta G = \text{vdw_contrib} + \text{coul_contrib} - \text{boresch} - \text{bonded} ``` ## Where to run the main job? If you use `submit = True` for the functions {py:func}`bindflow.runners.calculate`. One job will be launched to the cluster with the only aim of launching the Snakemake jobs to the cluster and waiting till the completion of the entire workflow. This is inefficient: actively allocated resources in the cluster that are not been used. A workaround in case a frontend is available is to set `submit = False` and then on the `approach` directory do: ```bash conda activate BindFlow cd nohup nice -19 ./job.sh > RuleThemAll.out 2>&1 & ``` Now, even if you close your terminal, the process will continue running in the background because of the use of `nohup`. This process is mainly idle, but by using `nice -19`, we lower its priority, so it does not interfere with any main processes running on your front end. You can also use other persistent terminals like [screen](https://www.gnu.org/software/screen/manual/screen.html) or [byobu](https://www.byobu.org/). ```` ````{dropdown} Error on fep_ana_get_dg_complex_contributions :color: info :animate: fade-in-slide-down Check {ref}`debugging-bindflow-runs` runs section. If, in the `.err` file under `slurm_logs`, you find an error such as: ```{error} Duplicate time values found; it's generally advised to use slicing on DataFrames with unique time values for each row. Use `force=True` to ignore this error. ``` This usually means that BindFlow was restarted and the GROMACS simulation did not handle the restart correctly. ### Step 1 — Identify the problematic window From the error log, determine which `ligand` and `replica` failed. For example, assume the error points to ligand3 and replica 1 ### Step 2 — Detect duplicate time values in XVG files or corrupted XVG files ```python import numpy as np from glob import glob root_path = ""fep/openff_unconstrained-2.0.0/ligand3/1/complex/fep/simulation/"" for xvg in glob(root_path+""/*/prod/prod.xvg""): try: data = np.loadtxt(xvg, comments=[""#"", ""@""])[:, 0] except ValueError: print(xvg) uniques, counts = np.unique(data, return_counts=True) duplicates = uniques[counts > 1] if len(duplicates) > 0: print(xvg, duplicates) ``` Suppose this identifies: ```bash fep/openff_unconstrained-2.0.0/ligand3/1/complex/fep/simulation/vdw.0/prod/prod.xvg ``` ### Step 3 — Clean the problematic window Delete all files in that window **except prod.mdp**: ```bash find fep/openff_unconstrained-2.0.0/ligand3/1/complex/fep/simulation/vdw.0/prod -maxdepth 1 ! -name 'prod.mdp' -type f -delete ``` ### Step 4 — Reset and rerun 1. Clean the working directory: ```bash bindflow clean fep/openff_unconstrained-2.0.0 ``` 2. Rerun the pipeline. The affected window (e.g., vdw.0) will be repeated. ### TL;DR ```{mermaid} flowchart TD A[Error detected in slurm_logs .err file] --> B[Identify ligand and replica from error log] B --> C[Run Python script to scan XVG files] C --> D{Duplicates or corrupted found?} D -- Yes --> E[Delete all files except prod.mdp in problematic window] E --> F[Run 'bindflow clean'] F --> G[Rerun pipeline] D -- No --> H[Check main BindFlow log for other causes] ``` ```` ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/CHANGELOG.md",".md","259","6","# 🗒️ Changelog All notable changes to this project will be documented in this file. The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/installation.md",".md","7841","230","# 💿 Installation ## Installing micromamba We highly recommend the latest version of [micromamba](https://mamba.readthedocs.io/en/latest/installation/micromamba-installation.html) for the conda environment creation and a fresh environment (as it will be demonstrated here). This is going to ease the resolution of dependencies. See the [Official Micromamba Installation Instructions](https://mamba.readthedocs.io/en/latest/installation/micromamba-installation.html). [Mamba](https://mamba.readthedocs.io/en/latest/index.html) may also be used. ## Building the environment We would like to work in a more relaxed environment, but we have encountered challenging situations. For now, we **highly** recommend the pinned environment (although the relaxed one is provided for reference). ```{raw} html
Select environment style:
Features:
Generated environment.yml: 
Select options above...
⬇️ Download environment.yml
``` ````{note} We observed that conda must be configured with `channel_priority: flexible` instead of `strict`. You may get the following error after the environment is created: ```text ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behavior is the source of the following dependency conflicts. tensorflow 2.17.0 requires ml-dtypes<0.5.0,>=0.3.1, but you have ml-dtypes 0.5.4 which is incompatible. ``` You can **safely** ignore it. This is may happen in MacOS when Espaloma is selected. The issue arieses because the chain dependency: `Espaloma > DLG > TensorFlow > ml-dtypes`. We are currently working to get rid of this ""error"". ```` ```python micromamba env create -f environment.yml --channel-priority flexible -y micromamba activate BindFlow ``` ## Final optional pip dependency and BindFlow installation `````{tab} With MM(P/G)BSA capabilities ````{tab} Production mode ```bash micromamba activate BindFlow python -m pip install bindflow --no-deps python -m pip install -U git+https://github.com/Valdes-Tresanco-MS/gmx_MMPBSA.git@27929e02067bc2321286809818d778a77a872010 --no-deps ``` ```` ````{tab} Developer mode ```bash micromamba activate BindFlow git clone --depth 1 git@github.com:ale94mleon/BindFlow.git cd BindFlow python -m pip install -e . --no-deps python -m pip install -U git+https://github.com/Valdes-Tresanco-MS/gmx_MMPBSA.git@27929e02067bc2321286809818d778a77a872010 --no-deps ``` ```` ```{note} Currently, we are using the `gmx_MMPBSA` commit [27929e0](https://github.com/Valdes-Tresanco-MS/gmx_MMPBSA/commit/27929e02067bc2321286809818d778a77a872010). This commit has been tested and provides flexibility in selecting the Python version. ``` ````` `````{tab} Without MM(P/G)BSA capabilities ````{tab} Production mode ```bash micromamba activate BindFlow python -m pip install bindflow --no-deps ``` ```` ````{tab} Developer mode ```bash micromamba activate BindFlow git clone --depth 1 git@github.com:ale94mleon/BindFlow.git cd BindFlow python -m pip install -e . --no-deps ``` ```` ````` ## GROMACS [GROMACS](https://www.gromacs.org/) can be installed in various ways depending on your computer architecture. It is essential to ensure a proper installation that fits your resources. BindFlow relies on GROMACS as its molecular dynamics engine, so it is crucial to have GROMACS installed and ready to use. Here, we will demonstrate how to build GROMACS from Source (courtesy of [Maciej Wójcik](https://biophys.uni-saarland.de/author/maciej-wojcik/)). If this method does not work, consult the [GROMACS Installation Guide](https://manual.gromacs.org/current/install-guide/index.html) for more information. ```{important} At the moment we support GROMACS versions in the range [2022, 2026); BindFlow throws a clean error at the very beginning of the execution of {py:func}`bindflow.runners.calculate` if otherwise. ``` ````{tab} Linux 🐧 ```bash VERSION=""2022.6"" TARGET_LOCATION=""gromacs/${VERSION}"" SOURCE=""https://gitlab.com/gromacs/gromacs.git"" SOURCE_REF=""v${VERSION}"" mkdir -p ${TARGET_LOCATION} git clone --depth 1 --branch ${SOURCE_REF} ""${SOURCE}"" ""${TARGET_LOCATION}-src"" cmake -DGMX_GPU=""CUDA"" -DCMAKE_C_COMPILER=gcc-13 -DCMAKE_CXX_COMPILER=g++-13 \ -DGMX_BUILD_OWN_FFTW=ON -DCMAKE_INSTALL_PREFIX=""$(pwd)/${TARGET_LOCATION}"" -S ""${TARGET_LOCATION}-src"" -B ""${TARGET_LOCATION}-build"" nice -19 cmake --build ""${TARGET_LOCATION}-build"" --target install -j 8 rm -rf ""${TARGET_LOCATION}-build"" rm -rf ""${TARGET_LOCATION}-src"" source ""${TARGET_LOCATION}/bin/GMXRC.bash"" ``` ```` ````{tab} MacOS 🍏 Assuming [brew](https://brew.sh) is installed (a must for Mac developers). ```bash brew install hwloc cmake gcc@13 ``` ```bash VERSION=2022.4 git clone --depth 1 --branch v${VERSION} https://gitlab.com/gromacs/gromacs.git gromacs-src cmake -DGMX_BUILD_OWN_FFTW=ON -DCMAKE_INSTALL_PREFIX=""$(pwd)/gromacs-${VERSION}"" -DGMX_GPU=OpenCL -DGMX_HWLOC=ON -DCMAKE_C_COMPILER=gcc-13 -DCMAKE_CXX_COMPILER=g++-13 -DCMAKE_POLICY_VERSION_MINIMUM=3.5 -B gromacs-build -S gromacs-src cmake --build ""gromacs-build"" --target install -j $(sysctl -n hw.logicalcpu) rm -rf gromacs-build rm -rf gromacs-src source gromacs-${VERSION}/bin/GMXRC.bash ``` ```{important} To use the GPU, it is needed to set the following environmental variable: ```bash export GMX_GPU_DISABLE_COMPATIBILITY_CHECK=1 ``` Highly discouraged for production! ``` ```` ## Documentation dependencies This online [Sphinx](https://www.sphinx-doc.org/en/master/) documentation can also be built and accessed locally. ````{admonition} requirements_doc.txt :class: tip ``` myst-nb myst-parser sphinx_book_theme sphinx==7.2.6 sphinx_design sphinxcontrib-katex sphinxcontrib-mermaid sphinx-inline-tabs sphinx_copybutton sphinx-autobuild roman ``` ```` ```bash pip install -r requirements_docs.txt ``` ```bash sphinx-autobuild docs public -a ``` Open [http://localhost:8000](http://localhost:8000). The HTML documentation is in the `public` directory. ## Testing installation Finally, it is advised to check if everything is alright. Be patient and go for a coffee ☕, this could take a couple of minutes (~11 min on my Laptop) ⏳. ````{tab} BindFlow is already cloned ```bash cd BindFlow # The path to your local copy of the repository python -m pytest tests ``` ```` ````{tab} BindFlow is not cloned yet ```bash git clone --depth 1 git@github.com:ale94mleon/BindFlow.git cd BindFlow python -m pytest tests ``` ```` `````{admonition} Expected results :class: info ````{tab} Linux 🐧 ```yaml passed: 5 xfailed: 0 ``` ```` ````{tab} MacOS 🍏 ```bash passed: 3 xfailed: 2 # from test/test_small.py ``` ```` ````` ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/about-us.md",".md","873","13","# 😊 About Us ## Project Origins This project began during my Ph.D. studies at [Jochen Hub's Computational Biophysics Group](https://biophys.uni-saarland.de/) at [Saarland University](https://www.uni-saarland.de/en/home.html). It was carried out within the framework of the ITN (Innovative Training Network) [PROTON](https://cordis.europa.eu/project/id/860592). If you are interested in getting in touch or learning more about my work, please visit my [Portfolio](https://alejandro.netlify.app). We would like to acknowledge the project [ABFE_Workflow](https://github.com/bigginlab/ABFE_workflow), which was the starting point of the development of BindFlow. ```{important} This project received funding from [Marie Skłodowska-Curie Actions](https://cordis.europa.eu/project/id/860592). ``` [![parts](_static/parts.png)](https://www.uni-saarland.de/en/home.html)","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/api-reference.md",".md","73","9","# 🛠️ API Reference ```{toctree} :maxdepth: 2 :glob: modules/* ``` ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/citations.md",".md","714","18","# 🖋️ Citation If you use BindFlow in your research, please cite the following paper: ```bibtex @article {leon2025bindflow, author = {Mart{\'i}nez Le{\'o}n, Alejandro and Andersen, Lucas and Hub, Jochen S}, title = {BindFlow: a free, user-friendly pipeline for absolute binding free energy calculations using free energy perturbation or MM(PB/GB)SA}, elocation-id = {2025.09.25.678545}, year = {2025}, doi = {10.1101/2025.09.25.678545}, publisher = {Cold Spring Harbor Laboratory}, URL = {https://www.biorxiv.org/content/early/2025/09/27/2025.09.25.678545}, eprint = {https://www.biorxiv.org/content/early/2025/09/27/2025.09.25.678545.full.pdf}, journal = {bioRxiv} } ``` ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/tutorials.md",".md","5729","118","# 🚀 Tutorials Get started quickly with **ready-to-simulate** examples provided in the [examples](https://github.com/ale94mleon/BindFlow/tree/main/examples) directory of the BindFlow repository. These examples are designed to work out of the box, giving you a hands-on introduction to BindFlow. ## Current examples In the example directory there are three systems: - **A2A**: membrane protein with a Na ion cofactor, - **CyclophilinD**: soluble protein, - **SAMPL6-OA**: non-protein receptor, ideal for testing as is the smallest system. For each system you will find: - Protein and ligands input files in the `inputs` directory, - BindFlow configuration files for: - FEP: `config-fep.yml`, and - MM(PB/GB)SA: `config-mmpbsa.yml`. - BindFlow executor files: `executor-fep.py` and `executor-mmpbsa.py`. Files presented on the examples are those used on the [BindFlow's paper](https://www.biorxiv.org/content/10.1101/2025.09.25.678545v1) Here we will only follow step-by-step the **CyclophilinD** example, the other examples are very similar. ## Tips before starting 1. **Review the examples** - Browse through the example simulations to understand how they are structured. 2. **Adjust configurations** - Update the configuration files to match your cluster resources and environment. This ensures simulations run smoothly. 3. **Reference configuration files** - Several files are provided for illustration in the [config](https://github.com/ale94mleon/BindFlow/tree/main/examples/configs) directory. Use them as a guide to create or customize your own simulation setups. 4. **Run your simulations** - Once configured, execute the examples to see BindFlow in action. For deployment instructions, see the [Deploy guide](./guides/deploy.md). 5. **Troubleshooting** - Check common issues and solutions in the [FAQ](./faq.md). If your problem is not listed, questions on how to use BindFlow, or if you want to give feedback or share ideas and new features, please head to the [BindFlow's discussions](https://github.com/ale94mleon/BindFlow/discussions). ## CylophilinD FEP tutorial ### Hardware To complete this tutorial we need an HPC with SLURM as task manager. This is not strictly needed for BindFlow to run, but it will be easy to be on the same page for the tutorial. ```{admonition} Hardware accessibility :class: info In case you do not have access to an HPC-like computer environment and you are only interesting in see if BindFlow works, consider to use the small SAMPL6-OA system and only a couple of ligands. So the calculations are doable in your workstation. ``` ### Getting ready First we need to install BindFlow in our computer system, for that follow the [Installation instructions](./installation.md). Get the files by cloning the [BindFlow repo](https://github.com/ale94mleon/BindFlow/) ```bash git clone --depth 1 git@github.com:ale94mleon/BindFlow.git cd BindFlow/examples/CyclophilinD ``` #### Exploring and modifying the executor file Explore the directory, check the files and try to understand the logic of `executor-fep.py`. You will see that only a single function is used: {py:func}`bindflow.runners.calculate`. This is the core function you should get familiar for most of the general cases. Therefore, it is **highly recommended** to learn its parameters and options. The documentation of {py:func}`bindflow.runners.calculate` is very extensive, but you will learn how to use BindFlow effectively. Let's modify `executor-fep.py` by: - using only one of the three force fields, - using two replicas, - using only two ligands and, - submitting the main job to the queue system. ```diff 10,17d9 < ""openff_unconstrained-2.0.0"": { < ""type"": ""openff"", < ""code"": ""openff_unconstrained-2.0.0.offxml"", < }, < ""espaloma-0.3.1"": { < ""type"": ""espaloma"", < ""code"": ""espaloma-0.3.1"", < }, 43c35 < ligands=ligands, --- > ligands=ligands[:2], 49c41 < replicas=3, --- > replicas=2, 53c45 < submit=False, --- > submit=True, ``` #### Tuning the config file The provided `config-fep.yml` offers SLURM configurations for the calculation jobs (`cluster:options:calculation`) and for the sentinel job (`cluster:options:job`). The last will only launch jobs and handled the snakemake queue system, but it will not perform heavy calculations, it will be mainly sleeping and waiting. Keywords for these sections are any valid SLURM parameter. You will need to adjust based on your HPC configuration. `extra_directives/dependencies` is a list of commands that will be executed sequentially before any GROMACS command. In the provided example, this section is used to load GROMACS package on our system (for sure different in your case) and avoid GROMACS backup on files (this ensures cleaner working directory during production). You **must** change those sections accordingly to your HPC configuration. #### Run BindFlow run After you tuned your configurations, you can just: ```bash python executor-fep.py ``` #### Checking the run BindFlow offers some basic, but powerful CLI functionalities; check the command `bindflow -h`. You can also check the SLURM queue and the main snakemake log file located at `fep/gaff-2.11/.snakemake/log` to see the completion percent of the pipeline. To debug possible issues, read the [Debugging page](./guides/debugging.md) and the [FAQ](./faq.md). ```{admonition} Friendly reminder :class: info The examples are a great way to get hands-on quickly, but they’re **not a replacement for the full documentation**. For a deeper understanding of BindFlow and its features, we encourage you to explore the documentation--we put a lot of love into it! 😊 ``` ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/modules/data.md",".md","41","4","# Data This is sub-package for testing. ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/modules/mdp.md",".md","123","8","# MDP utilities ```{eval-rst} .. automodule:: bindflow.mdp.mdp :members: :special-members: __init__, __call__ ``` ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/modules/utils.md",".md","119","8","# Tools ```{eval-rst} .. automodule:: bindflow.utils.tools :members: :special-members: __init__, __call__ ``` ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/modules/flow_builder.md",".md","207","10","# Builder helper Some helper functions used during the building of the pipeline ```{eval-rst} .. automodule:: bindflow.orchestration.flow_builder :members: :special-members: __init__, __call__ ``` ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/modules/generate_scheduler.md",".md","297","10","# Scheduler Here is the template class to build your Scheduler based on your needs as well as the already implemented and tested scheduler. ```{eval-rst} .. automodule:: bindflow.orchestration.generate_scheduler :members: :special-members: __init__, __call__, __cluster_validation__ ``` ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/modules/solvent.md",".md","138","8","# Solvation ```{eval-rst} .. autoclass:: bindflow.preparation.solvent.Solvate :members: :special-members: __init__, __call__ ``` ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/modules/system_builder.md",".md","143","8","# System Builder ```{eval-rst} .. automodule:: bindflow.preparation.system_builder :members: :special-members: __init__, __call__ ``` ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/modules/runners.md",".md","216","11","# BindFlow's runners (bindflow-runners)= These are the main functions to execute BindFlow. Learn them well! ```{eval-rst} .. automodule:: bindflow.runners :members: :special-members: __init__, __call__ ``` ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/guides/force-fields.md",".md","18317","604","# Force fields BindFlow provides several out-of-the-box force fields. This section explains how to access them and integrate custom force fields within BindFlow. We mainly focus on the input possibilities for [BindFlow's runner](#bindflow-runners) functions. BindFlow offers a variety of force field options, but as Uncle Ben says, ""With great power comes great responsibility."" Users must choose the appropriate combination of force fields. By default, BindFlow offers a suitable combination. ## Structure inputs Six keywords control the type of force field used for each specific component in the system: 1. `protein`: Definition of the host 2. `membrane`: Definition of the membrane 3. `ligands`: A list of ligand's definitions 4. `cofactor`: Definition of the cofactor 5. `water_model`: Type of GROMACS' water model to use 6. `custom_ff_path`: Path to the custom force field if needed. ## Partial and Full Definitions For a straightforward setup, you can provide the path to the corresponding file(s), which we will call the _partial definition_. However, you also have the option to fine-tune the definition of force fields for each component, referred to as the _full definition_. The quality of the initial structure is critical for accurate results, whether using FEP or MM(PB/GB)SA [Behera et al, 2025](https://pubs.acs.org/doi/10.1021/acs.jcim.5c00947). Proper definitions of tautomeric, isomeric, and protonation states for both proteins and ligands are essential as well the conformation state of the protein-ligand complex. BindFlow does not aim to solve this issue directly, as specialized tools excel in this domain. However, BindFlow offers basic functionality to ""fix"" proteins (e.g., resolving missing atoms or correcting atom naming) using pdbfixer from [OpenMM](https://openmm.org/) and [pdb2gmx](https://manual.gromacs.org/current/onlinehelp/gmx-pdb2gmx.html) from GROMACS. For complex receptors, users are advised to provide fully defined structures (e.g., GRO and TOP files) or preprocessed, compatible PDB files. In the following examples, we will use the runner {py:func}`bindflow.runners.calculate`. ````````{tab} Partial definition ``````{tab} protein The protein will be processed with [amber99sb-ildn](https://ambermd.org/#ff) force field after been fixed (if `fix_protein = True`) with [PDBFixer](https://github.com/openmm/pdbfixer). ```{hint} It is advised to spend some time on the processing of the protein beforehand (better a minute than repeat the whole campaign): 1. Missing atoms 2. Missing loops 3. Terminal capping 4. Protonation state All the above steps are highly system-dependent, and while PDBFixer can handle some minor issues, it is far from perfect. In addition, our use of PDBFixer is very simple. ``` ```python calculate( ... protein=""path/to/protein.{pdb;gro}"", ... ) ``` `````` ``````{tab} membrane The membrane will be processed with [SLipids_2020](http://www.fos.su.se/~sasha/SLipids/Downloads.html). ```{dropdown} Getting the membrane.pdb file :color: info :animate: fade-in-slide-down :icon: rocket For a membrane systems you first need to embed the protein into the membrane. This can easily done with [CHARMM-GUI](https://www.charmm-gui.org). This is a non-exhaustive list of steps for this process: Processing on [CHARMM-GUI](https://www.charmm-gui.org): * ACE and CT3 terminus * pH=7 * Run PPM 2.0 * Hexagonal box * Water thickness: 15 * Length of X and Y: 90 (initial guess) * Only POPC for a simple membrane or any other lipid composition you would like to use * Do not include ions * force field: - AMBER: - Protein: ff14sb - Lipid: SLipids - Water: TIP3P * Input Generation Options: GROMACS Open `gromac/step5_input.gro`. This file has the crystal information which is important during the solvation step in BindFLow. Convert to PDB with `gmx editconf -f step5_input.gro -o temporal.pdb `. The last PDB will also have the crystal info. Split the PDB in POPC and protein. In [PyMOL](https://www.pymol.org): * `select popc, resn POPC` * `select prot, (polymer.protein or resn ACE or resn NME)` 👀 Depending on how you are processing the protein, you might need to change the entry ATOM to HETATM for the CAP groups ACE and NME manually in the PDB file. ``` ```python calculate( ... membrane=""path/to/membrane.pdb"", ... ) ``` `````` ``````{tab} ligands ```python calculate( ... ligands=[ ""path/to/ligand1.{mol;sdf}"", ""path/to/ligand2.{mol;sdf}"", ""path/to/ligand3.{mol;sdf}"", ... ], ... ) ``` `````` ``````{tab} cofactor ```python calculate( ... cofactor=""path/to/cofactor.{mol;sdf}"", ... ) ``` `````` ```````` ````````{tab} Full definition ``````{tab} protein `````{tab} by code ````{tab} on GROMACS distribution You can access all the [GROMACS force fields](https://manual.gromacs.org/current/user-guide/force-fields.html) by their code, they will be pass to [pdb2gmx](https://manual.gromacs.org/documentation/current/onlinehelp/gmx-pdb2gmx.html) through the flag `-ff` after been fixed (if `fix_protein = True`) with [PDBFixer](https://github.com/openmm/pdbfixer). ```{hint} It is advised to spend some time on the processing of the protein beforehand (better a minute than repeat the whole campaign): 1. Missing atoms 2. Missing loops 3. Terminal capping 4. Protonation state All the above steps are highly system-dependent, and while PDBFixer can handle some minor issues, it is far from perfect. In addition, our use of PDBFixer is very simple ``` ```python calculate( ... protein={ ""conf"": ""path/to/protein.{pdb;gro}"", ""ff"":{ ""code"": } }, ... ) ``` ```` ````{tab} external To add even more flexibility, you can use any external force field ported to GROMACS, in this case you just need to copy your `force_field.ff` (e.g. `charmm36-jul2022.ff`) to your desired directory and pass the path of this directory to `custom_ff_path` parameter. If you have more force fields, you can copy all of them in the same directory. BindFlow will internally set the following environmental variable at run time. ```python os.environ[""GMXLIB""] = os.path.abspath(custom_ff_path) ``` ```{warning} See how the force field directory ends in `.ff`; e.g. `charmm36-jul2022.ff`. This is needed. ``` The force field code (e.g. for `charmm36-jul2022.ff`, the code is `charmm36-jul2022`) will be pass to [pdb2gmx](https://manual.gromacs.org/documentation/current/onlinehelp/gmx-pdb2gmx.html) through the flag `-ff` after been fixed (if `fix_protein = True`) with [PDBFixer](https://github.com/openmm/pdbfixer). ```{hint} It is advised to spend some time on the processing of the protein beforehand (better a minute than repeat the whole campaign): 1. Missing atoms 2. Missing loops 3. Terminal capping 4. Protonation state All the above steps are highly system-dependent, and while PDBFixer can handle some minor issues, it is far from perfect. In addition, our use of PDBFixer is very simple ``` ```python calculate( ... protein={ ""conf"": ""path/to/protein.{pdb;gro}"", ""ff"":{ ""code"": } }, custom_ff_path='parent/directory/of/custom.ff' ... ) ``` ```` ````` `````{tab} by top ```{admonition} Be careful :class: danger It is advised to build a single topology file without any `include` statements. If you want to use those include statements, they **MUST BE** absolute paths to their corresponded files. ``` ```python calculate( ... protein={ ""conf"": ""path/to/protein.gro"", ""top"": ""path/to/protein.top"", }, ... ) ``` ````` `````` ``````{tab} membrane In this case a topology must be generated and provided. This topology can also be obtained from CHARMM-GUI. ```{admonition} Be careful :class: danger It is advised to build a single topology file without any `include` statements. If you want to use those include statements, they **MUST BE** absolute paths to their corresponded files. You must always past the PDB despite passing a topology, GRO files are not accepted at the moment. ``` ```{dropdown} Getting the membrane.pdb file :color: info :animate: fade-in-slide-down :icon: rocket For a membrane systems you first need to embed the protein into the membrane. This can easily done with [CHARMM-GUI](https://www.charmm-gui.org). This is a non-exhaustive list of steps for this process: Processing on [CHARMM-GUI](https://www.charmm-gui.org): * ACE and CT3 terminus * pH=7 * Run PPM 2.0 * Hexagonal box * Water thickness: 15 * Length of X and Y: 90 (initial guess) * Only POPC for a simple membrane or any other lipid composition you would like to use * Do not include ions * force field: - AMBER: - Protein: - Lipid: - Water: TIP3P * Input Generation Options: GROMACS Open `gromac/step5_input.gro`. This file has the crystal information which is important during the solvation step in BindFLow. Convert to PDB with `gmx editconf -f step5_input.gro -o temporal.pdb `. The last PDB will also have the crystal info. Split the PDB in POPC and protein. In [PyMOL](https://www.pymol.org): * `select popc, resn POPC` * `select prot, (polymer.protein or resn ACE or resn NME)` 👀 Depending on how you are processing the protein, you might need to change the entry ATOM to HETATM for the CAP groups. You may also need to manually split the topology into protein and membrane. ``` ```python calculate( ... membrane={ ""conf"": ""path/to/membrane.pdb"", ""top"": ""path/to/membrane.top"", } ... ) ``` `````` ``````{tab} ligands `````{tab} openff Any force field from [OpenFF](https://openforcefield.org/force-fields/force-fields/) can be acceded by setting its name as `code` (see that the `.offxml` extension is kept). If `code` is not provided, the default force field for `type = ""openff""` is `openff_unconstrained-2.0.0.offxml`. ```python ligand_files = [ ""path/to/ligand1.{mol;sdf}"", ""path/to/ligand2.{mol;sdf}"", ""path/to/ligand3.{mol;sdf}"", ... ] ligands = [] for ligand_file in ligand_files: ligands.append({ ""conf"": ligand_file, ""ff"":{ ""type"": ""openff"", ""code"": ""openff_unconstrained-2.0.0.offxml"" } }) calculate( ... ligands=ligands, ... ) ``` ````` `````{tab} espaloma It is recommended to use `espaloma >= 0.3.1`. If `code` is not provided, the default force field for `type = ""espaloma""` is `espaloma-0.3.1`. ```python ligand_files = [ ""path/to/ligand1.{mol;sdf}"", ""path/to/ligand2.{mol;sdf}"", ""path/to/ligand3.{mol;sdf}"", ... ] ligands = [] for ligand_file in ligand_files: ligands.append({ ""conf"": ligand_file, ""ff"":{ ""type"": ""espaloma"", ""code"": ""espaloma-0.3.1"" } }) calculate( ... ligands=ligands, ... ) ``` ````` `````{tab} gaff If `code` is not provided, the default force field for `type = ""gaff""` is `gaff-2.11`. ```python ligand_files = [ ""path/to/ligand1.{mol;sdf}"", ""path/to/ligand2.{mol;sdf}"", ""path/to/ligand3.{mol;sdf}"", ... ] ligands = [] for ligand_file in ligand_files: ligands.append({ ""conf"": ligand_file, ""ff"":{ ""type"": ""gaff"", ""code"": ""gaff-2.11"" } }) calculate( ... ligands=ligands, ... ) ``` ````` `````{tab} custom force field ```{admonition} Be careful :class: danger It is advised to build a single topology file without any `include` statements. If you want to use those include statements, they **MUST BE** absolute paths to their corresponded files. ``` ```python ligands = [ { ""conf"": ""path/to/ligand1.gro"", ""top"": ""path/to/ligand1.top"" }, { ""conf"": ""path/to/ligand2.gro"", ""top"": ""path/to/ligand2.top"" }, { ""conf"": ""path/to/ligand3.gro"", ""top"": ""path/to/ligand3.top"" }, ... ] calculate( ... ligands=ligands, ... ) ``` ````` `````` ``````{tab} cofactor `````{tab} openff Any force field from [OpenFF](https://openforcefield.org/force-fields/force-fields/) can be acceded by setting its name as `code` (see that the `.offxml` extension is kept). If `code` is not provided, the default force field for `type = ""openff""` is `openff_unconstrained-2.0.0.offxml`. ```python calculate( ... cofactor={ ""conf"": ""path/to/cofactor.{mol;sdf}"", ""ff"":{ ""type"": ""openff"", ""code"": ""openff_unconstrained-2.0.0.offxml"" } }, ... ) ``` ````` `````{tab} espaloma It is recommended to use `espaloma >= 0.3.1`. If `code` is not provided, the default force field for `type = ""espaloma""` is `espaloma-0.3.1`. ```python calculate( ... cofactor={ ""conf"": ""path/to/cofactor.{mol;sdf}"", ""ff"":{ ""type"": ""espaloma"", ""code"": ""espaloma-0.3.1"" } }, ... ) ``` ````` `````{tab} gaff If `code` is not provided, the default force field for `type = ""gaff""` is `gaff-2.11`. ```python calculate( ... cofactor={ ""conf"": ""path/to/cofactor.{mol;sdf}"", ""ff"":{ ""type"": ""gaff"", ""code"": ""gaff-2.11"" } }, ... ) ``` ````` `````{tab} custom force field ````{tab} non-water ```{admonition} Be careful :class: danger It is advised to build a single topology file without any `include` statements. If you want to use those include statements, they **MUST BE** absolute paths to their corresponded files. ``` ```python calculate( ... cofactor={ ""conf"": ""path/to/cofactor.gro"", ""top"": ""path/to/cofactor.top"", }, ... ) ``` ```` ````{tab} water-like ```{admonition} Be careful :class: danger It is advised to build a single topology file without any `include` statements. If you want to use those include statements, they **MUST BE** absolute paths to their corresponded files. In the case that the cofactor(s) is (are) water-like molecule(s), this should be specified by the keyword `is_water = True`. In this case, a special treatment is done in BindFlow internally. Here, its settles section (if any) will be changed to TIP3P-like triangular constraints. Check the discussion [How to treat specific water molecules as ligand?](https://gromacs.bioexcel.eu/t/how-to-treat-specific-water-molecules-as-ligand/3470/9). Note that this is only possible for TIP3P-like water molecules at the moment. ``` ```python calculate( ... cofactor={ ""conf"": ""path/to/cofactor.gro"", ""top"": ""path/to/cofactor.top"", ""is_water"": True, }, ... ) ``` ```` ````` `````` ```````` ## Water models BindFlow comes with (at present 07.2024) all water models distributed with GROMACS. They are set by the keyword: `water_model`. E.g.: ```python calculate( ... water_model=""amber/tip3p"" ... ) ``` The structure of the string is `force_field_family/water_model`; `amber/tip3p` is the default. All configuration and topology files are sourced from GROMACS force fields, available at [GROMACS GitLab - share/top](https://gitlab.com/gromacs/gromacs/-/tree/main/share/top?ref_type=heads). These files contain topologies and configurations for water models and ions within three force field families: AMBER, CHARMM, and OPLS-AA. ```{note} It is assumed that inside the same family, the non-bonded interactions (for water models and ions) are the same (`epsilon` and `sigma` parameters), which is true for the force fields presented in the GROMACS distribution. ``` The `ffnonbonded.itp` for each family was taken from: * AMBER: amber99sb-ildn * CHARMM: charmm27 * OPLS-AA: oplsaa These `ffnonbonded.itp` files were modified to retain only the `[ atomtypes ]` section, including only atom types related to the water models and ions. This modification prevents potential conflicts with atom-type definitions from user-provided force fields. The available force fields and their corresponding configuration files are: ```yaml amber: spc: spc216.gro spce: spc216.gro tip3p: spc216.gro tip4p: tip4p.gro tip4pew: tip4p.gro tip5p: tip5p.gro charmm: spc: spc216.gro spce: spc216.gro tip3p: spc216.gro tip4p: tip4p.gro tip5p: tip5p.gro tips3p: spc216.gro oplsaa: spc: spc216.gro spce: spc216.gro tip3p: spc216.gro tip4p: tip4p.gro tip4pew: tip4p.gro tip5p: tip5p.gro tip5pe: tip5p.gro ``` ## MDP options modification based on the force field. AMBER and CHARMM36-like force fields example Some Molecular Dynamic Parameters (MDP) are usually, rather than interchangeable options, parts of each force field derivation and parametrization. So, we should always use those parameters during our simulations. A typical example are AMBER and CHARMM36-like force fields: ````{tab} AMBER-like force fields BindFlow use this parameter by default. So, you do not need to modify them. ```yaml constraints: all-bonds cutoff-scheme: Verlet vdwtype: cutoff vdw-modifier: Potential-Shift-Verlet rlist: 1.2 rvdw: 1.0 coulombtype: PME rcoulomb: 1.0 DispCorr: EnerPres ``` ```` ````{tab} CHARMM36-like force fields In this case you should pass to to all the steps these parameters. BindFlow works with AMBER-like force fields by default. In the [GROMACS' docs](https://manual.gromacs.org/current/user-guide/force-fields.html) says: ```yaml constraints: h-bonds cutoff-scheme: Verlet vdwtype: cutoff vdw-modifier: force-switch rlist: 1.2 rvdw: 1.2 rvdw-switch: 1.0 coulombtype: PME rcoulomb: 1.2 DispCorr: no ``` Note that dispersion correction should be applied in the case of lipid monolayers, but not bilayers. Please also note that the switching distance is a matter of some debate in lipid bilayer simulations, and it is dependent to some extent on the nature of the lipid. Some studies have found that an 0.8-1.0 nm switch is appropriate, others argue 0.8-1.2 nm is best, and yet others stand by 1.0-1.2 nm. The user is cautioned to thoroughly investigate the force field literature for their chosen lipid(s) before beginning a simulation! ```` ## Final note Remember to cite properly the main references if you use any of the force fields in your work. ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/guides/debugging.md",".md","811","18","(debugging-bindflow-runs)= # Debugging BindFlow runs To troubleshoot a BindFlow run: 1. Check the main log file - Located in the `.snakemake` directory of the running simulation. - Search for the keyword error. - Note the rule name and job ID associated with the failure. 2. If running on an HPC system - Go to the `slurm_logs` directory. - Find the corresponding `.err` and/or `.out` files using the rule name and job ID. - Review their contents — in most cases this will clearly indicate what went wrong and which steps were involved. 3. If the issue remains unclear - Return to the main log file and locate the reported working directory. - Explore that directory for more detailed logs. - For GROMACS simulations, check for `.log` and `.lis` files in the specified directory. ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/guides/customizing.md",".md","14288","577","# Customizing the Workflow BindFlow is highly customizable. In this section, we will discuss the options accessible through the `global_config` keyword of the [BindFlow's runners](#bindflow-runners). The `global_config` is a nested Python dictionary. A useful tip is to write this dictionary in YAML format, which is essentially a ""human-readable dictionary."" Here, we will go through each section of this YAML file: ````{dropdown} config.yml :color: info :animate: fade-in-slide-down :icon: rocket ```yaml cluster: options: # Depending on the Scheduler calculation: job: # Optional extra_directives: # Optional dependencies: - mdrun: ligand: complex: all: samples: # Optional nwindows: # Optional ligand: vdw: coul: complex: vdw: coul: bonded: < mmpbsa: # Optional mdp: # Optional ligand: equi: : fep: vdw: : coul: : complex: equi: : fep: vdw: : coul: : bonded: : mmpbsa: prod: ``` ```` ```{important} The options provided on this configuration have higher priority to those ones passed as keywords to the runner function. For example: * Pass to the runner `dt_max=0.003` and specify for an specific simulation `dt=0.004` (see [MDP section](#mdp-optional)) * Pass to the runner `threads=12` and specify for `mdrun` the flag `-nt 10` (see [mdrun section](#mdrun-optional)) ``` ## `cluster` This section specifies the computational resources required by the selected scheduler (see the [BindFlow’s deploy](#bindflow-deploy) section). It allows you to control the allocated resources for two types of jobs: 1. **Main Job (`job`):** This job primarily waits and launches other jobs. 2. **Calculation Jobs (`calculation`):** These jobs perform the actual calculations. The `job` section is optional; if it is not defined, the main job will use the same resources specified in the mandatory `calculation` section. `````{dropdown} Example of cluster section :color: info :animate: fade-in-slide-down :icon: rocket ````{tab} FrontEnd ```yaml cluster: options: calculation: None ``` ```` ````{tab} SLURM ```yaml cluster: options: calculation: partition: uds-hub time: ""2-00:00:00"" gpus: 1 mem: '4G' constraint: Ryzen_3975WX job: partition: uds-hub time: ""2-00:00:00"" mem: '1G' cpus-per-task: 2 ``` ```` ````` ## `extra_directives` (optional) ### `dependencies` (optional) This is a list of executable commands that should be run before any `gmx` command. These commands inject the necessary dependencies to ensure the proper execution of the `gmx` command. ````{dropdown} Example of dependencies section :color: info :animate: fade-in-slide-down :icon: rocket ```yaml extra_directives: dependencies: - source /groups/CBG/opt/spack-0.18.1/shared.bash - module load gromacs/2022.4 - module load nvidia/latest - export GMX_MAXBACKUP=-1 ``` ```` ### `mdrun` (optional) The user can customize the `gmx mdrun` command. By default, the command `gmx mdrun -nt {threads} -deffnm {simulation_step_name}` is built. You can adjust the `mdrun` options for the ligand, complex, or both simultaneously using the keywords `ligand`, `complex`, and `all`, respectively. ``````{dropdown} Examples of mdrun section :color: info :animate: fade-in-slide-down :icon: rocket `````{tab} gmx mdrun [...] -cpi -stepout 5000 -v Example of full command: ```bash gmx mdrun -nt 12 -deffnm 01_nvt -cpi -stepout 5000 -v ``` ````{tab} Configuration acting only on ligand simulations ```yaml extra_directives: mdrun: ligand: cpi: True stepout: 5000 v: True ``` ```` ````{tab} Configuration acting only on complex simulations ```yaml extra_directives: mdrun: complex: cpi: True stepout: 5000 v: True ``` ```` ````{tab} Configuration acting on both ligand and complex simulations (1) ```yaml extra_directives: mdrun: all: cpi: True stepout: 5000 v: True ``` ```` ````{tab} Configuration acting on both ligand and complex simulations (2) ```{tip} Note that the options for the ligand and complex are independent, meaning that you can set different options for the ligand and complex simulations. ``` ```yaml extra_directives: mdrun: ligand: cpi: True stepout: 5000 v: True complex: cpi: True stepout: 5000 v: True ``` ```` ````` `````{tab} gmx mdrun [...] -ntmpi 1 Example of full command ```bash gmx mdrun -nt 12 -deffnm 01_nvt -ntmpi 1 ``` ````{tab} Configuration acting only on ligand simulations ```yaml extra_directives: mdrun: ligand: ntmpi: 1 ``` ```` ````{tab} Configuration acting only on complex simulations ```yaml extra_directives: mdrun: complex: ntmpi: 1 ``` ```` ````{tab} Configuration acting on both ligand and complex simulations (1) ```yaml extra_directives: mdrun: all: ntmpi: 1 ``` ```` ````{tab} Configuration acting on both ligand and complex simulations (2) ```{tip} Note that the options for the ligand and complex are independent, meaning that you can set different options for the ligand and complex simulations. ``` ```yaml extra_directives: mdrun: ligand: ntmpi: 1 complex: ntmpi: 1 ``` ```` ````` `````` ## `nwindows` (optional) Number of windows for each step of the perturbation simulations for both the ligand in the solvent and the (membrane) protein-ligand complex. The following is the thermodynamic cycle followed in BindFlow: ```{mermaid} graph TB no_interacted_lig_in_prot(Non Interacted Restrained Ligand) no_coul_lig_in_prot(Restrained Ligand without Coulomb) lig_in_prot(Restrained Interacted Ligand) free_lig_in_prot(Free Fully Interacted Ligand) free_lig_in_water(Free Fully Interacted Ligand) free_no_coul_lig_in_water(Free Ligand without Coulomb) free_no_interacted_lig_in_water(Free Non Interacted Ligand) no_interacted_lig_in_water(Non Interacted Restrained Ligand) subgraph In the Protein Pocket - 'protein' direction BT no_interacted_lig_in_prot -- Activate van der Waal - 'vdw' --> no_coul_lig_in_prot -- Activate Coulomb - 'coul' --> lig_in_prot -- Remove Restraints - 'bonded' --> free_lig_in_prot end subgraph In Water - 'ligand' direction TB free_lig_in_water -- Remove Coulomb - 'coul' --> free_no_coul_lig_in_water -- Remove van der Waal - 'vdw' --> free_no_interacted_lig_in_water -- Activate Restraints --> no_interacted_lig_in_water end free_lig_in_water -- dG_binding --> free_lig_in_prot no_interacted_lig_in_water -- dG = 0 --> no_interacted_lig_in_prot ``` ````{dropdown} Example of nwindows section :color: info :animate: fade-in-slide-down :icon: rocket These are the default options used internally by BindFlow ```yaml nwindows: ligand: vdw: 11 coul: 11 complex: vdw: 21 coul: 11 bonded: 11 ``` ```` ## `mmpbsa` (optional) This section is used to set the MM(PB/GB)SA calculations. These parameters are passed to [gmx_MMPBSA](https://valdes-tresanco-ms.github.io/gmx_MMPBSA/dev/) package through the `.in` file. ````{dropdown} Example of mmpbsa section :color: info :animate: fade-in-slide-down :icon: rocket In this example, the C2, QH, and IE methods are used to estimate entropy, while the PB and GB methods are applied to calculate the polar component of the solvation free energy. For your application, we recommend benchmarking all possible combinations on a small subset of your data to determine the most suitable methods. Once identified, you can streamline your workflow by using a single method (either PB or GB) for solvation free energy calculations and a single method for entropy estimation. In certain cases, especially within the same family of compounds and a common receptor where relative comparisons are the primary goal, entropy calculations may not be necessary. Omitting them can significantly improve the efficiency of your production workflow. ```yaml mmpbsa: general: c2_entropy: 1 qh_entropy: 1 interaction_entropy: 1 pb: {} # enable MMPBSA computation gb: {} # enable MMGBSA computation ``` ```` ## `mdp` (optional) This section is used to control all Molecular Dynamic Parameters for every single simulation `````{dropdown} Example of mdp section :color: info :animate: fade-in-slide-down :icon: rocket Here we are only changing the `nsteps` parameter of some of the involved steps. ````{tab} Equilibration ```yaml mdp: ligand: equi: 01_nvt: nsteps: 25 prod: nsteps: 250 complex: equi: 04_npt: nsteps: 25 prod: nsteps: 250 ``` ```` ````{tab} FEP ```yaml mdp: ligand: fep: vdw: 01_nvt: nsteps: 25 prod: nsteps: 250 coul: 01_nvt: nsteps: 25 prod: nsteps: 250 complex: equi: fep: vdw: 02_npt: nsteps: 25 03_npt_norest: nsteps: 25 prod: nsteps: 250 coul: 02_npt: nsteps: 25 03_npt_norest: nsteps: 25 prod: nsteps: 250 bonded: 02_npt: nsteps: 25 03_npt_norest: nsteps: 25 prod: nsteps: 250 ``` ```` ````{tab} MM(PB/GB)SA ```yaml mdp: complex: mmpbsa: prod: nsteps: 400 ``` ```` ````` You can explore what are the steps involved in your calculation: ````{tab} Equilibration steps for membrane protein-ligand system ```python from bindflow.utils.tools import list_if_file from bindflow.mdp._path_handler import _TemplatePath print(list_if_file(_TemplatePath.complex.membrane.equi)) ``` ```` ````{tab} FEP steps for soluble protein-ligand system ```python from bindflow.utils.tools import list_if_file from bindflow.mdp._path_handler import _TemplatePath print(list_if_file(_TemplatePath.complex.soluble.fep)) ``` ```` ````{tab} MM(PB/GB)SA step for membrane protein-ligand system ```python from bindflow.utils.tools import list_if_file from bindflow.mdp._path_handler import _TemplatePath print(list_if_file(_TemplatePath.complex.membrane.mmpbsa)) ``` ```` ````{tab} Equilibration steps for the ligand in water ```python from bindflow.utils.tools import list_if_file from bindflow.mdp._path_handler import _TemplatePath print(list_if_file(_TemplatePath.ligand.equi)) ``` ```` You can also take a look a the default parameters of the step. In the following example, you can print the parameters for the `prod` step of the membrane protein-ligand complex equilibration phase in the MDP format. ```python from bindflow.mdp._path_handler import _TemplatePath from bindflow.mdp.mdp import MDP print(MDP().from_file(_TemplatePath.complex.membrane.equi + ""/prod.mdp"").to_string()) ``` ## Suggested options for MM(PB/GB)SA calculations The default MDP options are optimized for FEP calculations. However, for MM(PB/GB)SA calculations, we recommend using a less resource-intensive scheme. This approach has been shown to be effective, as demonstrated in the main BindFlow publication. `````{dropdown} Suggested mmpbsa scheme :color: info :animate: fade-in-slide-down :icon: rocket Note that we are collecting 20 samples (`samples: 20`), and in the `mdp/complex/prod` step, exactly 20 frames are output (`nsteps / nstxout-compressed`) on each XTC file. This configuration ensures the final workflow requires minimal storage, as its size primarily depends on the XTC files. Additionally, note that a high amount of memory is allocated for the execution of calculations (`cluster/options/mem = 10GB`). This is necessary because [gmx_MMPBSA](https://valdes-tresanco-ms.github.io/gmx_MMPBSA/dev/) is memory-intensive, as it uses MPI to process frames in parallel. As a general rule, allocate at least 1 GB of memory per thread specified in the `{py:func}`bindflow.runners.calculate` function. ````{tab} Soluble protein-ligand system ```yaml cluster: options: calculation: mem: 10G samples: 20 mdp: complex: equi: 00_min: nsteps: 100000 01_nvt: dt: 0.002 nsteps: 5000 02_nvt: dt: 0.003 nsteps: 5000 03_npt: dt: 0.003 nsteps: 7500 04_npt: dt: 0.004 nsteps: 30000 prod: dt: 0.004 nsteps: 237500 nstxout-compressed: 11875 mmpbsa: prod: dt: 0.004 nsteps: 25000 nstxout-compressed: 1250 mmpbsa: general: c2_entropy: 1 gb: {} ``` ```` ````{tab} Membrane protein-ligand system ```yaml cluster: options: calculation: mem: 10G samples: 20 mdp: complex: equi: 00_min: nsteps: 100000 01_nvt: dt: 0.001 nsteps: 5000 02_nvt: dt: 0.001 nsteps: 5000 03_npt: dt: 0.001 nsteps: 5000 04_npt: dt: 0.002 nsteps: 7500 05_npt: dt: 0.002 nsteps: 7500 06_npt: dt: 0.003 nsteps: 15000 prod: dt: 0.004 nsteps: 237500 nstxout-compressed: 11875 mmpbsa: prod: dt: 0.004 nsteps: 25000 nstxout-compressed: 1250 mmpbsa: general: c2_entropy: 1 gb: {} ``` ```` ````` ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/guides/index.md",".md","106","12","# 📚 Guides ```{toctree} :maxdepth: 2 force-fields deploy customizing debugging performance/index ``` ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/guides/deploy.md",".md","5076","91","# BindFlow's deploy (bindflow-deploy)= As with any other Snakemake workflow, BindFlow can be deployed in a variety of environments, the only thing to change is how we call the [snakemake command](https://snakemake.readthedocs.io/en/stable/executing/cli.html). At the `approach` directory, you can: `````{admonition} Execution options :class: tip ````{tab} FrontEnd ```bash snakemake --jobs 12 --latency-wait 360 --rerun-incomplete --keep-incomplete --keep-going ``` All jobs will run on the current frontend. This setup is practical for testing and, in some cases, for processing a small set of ligands during MM(PB/GB)SA calculations. To optimize the use of your frontend resources, you need to configure the `threads` (specified as a keyword to the runner) and `--jobs` (the maximum number of concurrent tasks) settings appropriately. In Snakemake terminology, `--jobs` represents the maximum number of CPUs available to run the workflow. For example, if you set `threads = 4` and your frontend has 12 CPUs, this configuration means that for rules requiring the threads definition, you can run a maximum of 3 concurrent instances of those rules. ```` ````{tab} SLURM ```bash snakemake --jobs 100000 --latency-wait 360 --cluster-cancel scancel --rerun-incomplete --keep-incomplete --keep-going --cluster 'sbatch --partition=uds-hub --time=2-00:00:00 --gpus=1 --gres=gpu:1 --mem=4G --cpus-per-task={threads} --job-name=test.{rule}.{jobid} --output=approach/slurm_logs/test.{rule}.{jobid}.out --error=approach/slurm_logs/test.{rule}.{jobid}.err' ``` All jobs will be launched using the `sbatch` command. Note that the only differences with the frontend executions are `--cluster-cancel scancel` and `--cluster (...)`. The first defines the command used in the cluster to cancel jobs, and the second defines how to interact with the cluster. The number of jobs can be typically a big number, but there are some clusters that set a maximum number of job to be lunch, so you can lay with this number. In this case, `--jobs` represents how many concurrent jobs can be run in parallel. This includes all jobs added to the queue, regardless of their status (RUNNING, PENDING, CANCELING, CONFIGURING, etc.). Resource allocation is handled by [SLURM](https://slurm.schedmd.com/documentation.html). ```` ````` Similar commands are generated in the `job.sh` script in the `approach` directory when the scheduler classes {py:class}`bindflow.orchestration.generate_scheduler.FrontEnd` or {py:class}`bindflow.orchestration.generate_scheduler.SlurmScheduler` is passed to any of the [BindFlow's runners](#bindflow-runners). However, users can adapt the command based on their needs and available resources either manually (not too great 🤨) or by using the Abstract Base Class {py:class}`bindflow.orchestration.generate_scheduler.Scheduler` as a template. You can consult the source code of any of the previous schedulers to get an idea of how to implement your own. A rough estimation of the maximum level of parallelization for the computationally intense task (those that run the GROMACS simulations) is: * **Equilibration:** `number of ligands` X `replicas` * **FEP:** `total number of lambda points` X `number of ligands` X `replicas` * **MM(PB/GB)SA:** `samples` X `number of ligands` X `replicas` These estimates only represent the parallelization at the job level. Each of these jobs is also parallelized at the GMX level, where GPU acceleration can be utilized, just like any typical GROMACS simulation (and this is even cooler 😎). ## Running workflow partially In some cases, it may be convenient to run the workflow up to a specific point and resume it at a later time. Snakemake provides several options to achieve this. ````{tab} until The `--until` option allows you to execute the workflow up to and including a specific rule. This is particularly useful when you want to stop at an intermediate step and resume the remaining workflow later, possibly on different hardware or computational resources. For example, to stop the workflow after the `mmxbsa_sample_prod` rule finish: ```bash snakemake (...) --until mmxbsa_sample_prod (...) ``` ```` ````{tab} target-jobs Another approach is to specify target jobs by providing the rule name and the associated wildcards. This allows you to execute the dependencies of a specific job and its instances. For example: ```bash snakemake (...) --target-jobs run_gmx_mmpbsa:ligand_name=ligand1,replica=3,sample=2 (...) ``` The above command will execute all dependent rules for `run_gmx_mmpbsa` and specifically the instances of `run_gmx_mmpbsa` with the following wildcards: ```yaml ligand_name: ligand1 replica: 3 sample: 2 ``` ```` ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/guides/performance/index.md",".md","22707","455","# Performance estimation To estimate the execution time of our pipeline, we computed the total time required to complete all tasks from the directed acyclic graph (DAG) representation of the workflow. Each task correspond to a simulation step, with dependencies defining execution order. The detailed results are presented in the following chapters. As a rule of thumb, you can estimate the total number of days required using: `````{tab} FEP ```{math} :label: fep_estimation \frac{(\lambda + 1) \times R \times L \times T}{24 \times C} ``` - {math}`\lambda=` total number of lambda points for the complex simulations; + 1 for the initial equilibration phase (non-FEP) - {math}`R=` number of replicas - {math}`L=` number of ligands - {math}`C=` number of available compute nodes - {math}`T=` average time (in hours) to complete one FEP production simulation This formula provides a lower bound for the execution time. In practice, you should account for an additional ± 1 days to accommodate for the remaining tasks, scheduling overheads and runtime variations. Nevertheless, this estimation is usually reliable, as the total time is dominated by the FEP complex simulations. The value of {math}`T` can be determined either from preliminary test runs or by monitoring ongoing simulations ````{dropdown} Example Calculation :color: info :animate: fade-in-slide-down :icon: plus-circle Suppose you plan to run the following: - {math}`\lambda = 43` (default) - {math}`R = 3` (default) - {math}`L = 100` - {math}`C = 100` - {math}`T = 1` Plugging into Eq. {eq}`fep_estimation`: ```{math} \frac{(43+1) \times 3 \times 100}{100} \times \frac{1}{24} = 5.5 \pm 1 \,\text{days} ``` ```` ````` `````{tab} MMMGBSA ```{math} :label: mmgbsa_estimation \frac{(T_E + S \times T_S) \times R \times L}{24 \times C} ``` - {math}`S=` number of samples - {math}`R=` number of replicas - {math}`L=` number of ligands - {math}`C=` number of available compute nodes - {math}`T_E=` average time (in hours) to complete the production equilibration simulation - {math}`T_S=` average time (in hours) to complete the sample simulation This formula provides a lower bound for the execution time. In practice, you should account for an additional ± 0.2 days to accommodate for the remaining tasks, scheduling overheads and runtime variations. Nevertheless, this estimation is usually reliable, as the total time is dominated by the production MD steps. The value of {math}`T_E` and {math}`T_S` can be determined either from preliminary test runs or by monitoring ongoing simulations ````{dropdown} Example Calculation :color: info :animate: fade-in-slide-down :icon: plus-circle Suppose you plan to run the following: - {math}`S = 20` (default) - {math}`R = 3` (default) - {math}`L = 100` - {math}`C = 100` - {math}`T_E = 0.1` - {math}`T_S = 0.01` Plugging into Eq. {eq}`mmgbsa_estimation`: ```{math} \frac{(0.1 + 20 \times 0.01) \times 3 \times 100}{24 \times 100} = 0.04 \pm 0.2 \,\text{days} ``` ```` ````` ## Methodology followed for the estimation of ligand completion time ``````{dropdown} Method :color: info :animate: fade-in-slide-down :icon: gear Task durations were determined based on the estimated GROMACS performance, obtained from a short simulation of the equilibrated structure on an isolated computing node. To avoid startup overhead and performance instability (e.g., due to load balancing), performance counters were restarted after 2000 steps. For non-GROMACS tasks and queuing delays, empirical durations were assigned based on prior experience. The scheduling algorithm assigns tasks to a fixed number of available computing nodes, considering both task dependencies and a queuing delay to simulate node reconfiguration time. Task execution follows a topological order, ensuring dependency constraints are met. The execution time was computed using a priority queue-based scheduling approach [Abhishek et al. 2022](https://link.springer.com/chapter/10.1007/978-981-19-3575-6_33), which minimizes idle time and optimizes resource utilization, similar to standard schedulers such as SLURM [Yoo et al. 2003](https://link.springer.com/chapter/10.1007/10968987_3). In our performance analysis, we evaluated the pipeline’s execution time across varying numbers of ligands and computing nodes. Specifically, we considered ligand counts ranging from 10 to 1000, in increments of 10, and computing nodes ranging from 10 to 200, also in increments of 10. This analysis provides an estimate of the pipeline runtime and scalability under idealized conditions and BindFlow parameters used in this study, serving as a reference for the expected computational cost. The initial time needed for Snakemake to resolve the Direct Acyclic Graph (DAG) was not included although it may be relevant as the number of ligands increases. GROMACS performance was calculated for several systems listed in the next section. All the scripts to reproduce these results are on [GitHub](https://github.com/ale94mleon/bindflow/tree/main/docs/source/guides/performance/scripts). ### Running details ````{dropdown} mdrun command :color: info :animate: fade-in-slide-down :icon: rocket ```bash gmx mdrun -stepout 5000 -resetstep 20000 -nsteps 30000 -v -nt 10 -pin on -pinoffset 0 -pinstride 1 -gpu_id 0 -deffnm prod ``` ```` `````{dropdown} Employed MDP :color: info :animate: fade-in-slide-down :icon: book ````{tab} Complex. All systems (soluble proteins) except A2A ```ini integrator = sd ; stochastic leap-frog integrator nsteps = 2500000 ; 4 * 2 500 000 fs = 10 000 ps = 10 ns dt = 0.004 ; 4 fs comm-mode = Linear ; remove center of mass translation nstcomm = 50 ; frequency for center of mass motion removal ;---------------------------------------------------- ; OUTPUT CONTROL ;---------------------------------------------------- nstxout = 0 ; don't save coordinates to .trr nstvout = 0 ; don't save velocities to .trr nstfout = 0 ; don't save forces to .trr nstxout-compressed = 0 ; xtc compressed trajectory output every 1000 steps (2 ps) compressed-x-precision = 0 ; precision with which to write to the compressed trajectory file nstlog = 0 ; update log file every 2 ps nstenergy = 1000 ; save energies every 2 ps nstcalcenergy = 50 ; calculate energies every 200 fs ;---------------------------------------------------- ; BONDS ;---------------------------------------------------- constraint_algorithm = lincs ; holonomic constraints constraints = all-bonds ; all bonds are constrained (HMR) lincs_iter = 1 ; accuracy of LINCS (1 is default) lincs_order = 6 ; also related to accuracy (4 is default) lincs-warnangle = 30 ; maximum angle that a bond can rotate before LINCS will complain (30 is default) continuation = yes ;---------------------------------------------------- ; NEIGHBOR SEARCHING ;---------------------------------------------------- cutoff-scheme = Verlet ns-type = grid ; search neighboring grid cells nstlist = 10 ; 20 fs (default is 10) rlist = 1.2 ; short-range neighborlist cutoff (in nm) pbc = xyz ; 3D PBC ;---------------------------------------------------- ; ELECTROSTATICS ;---------------------------------------------------- coulombtype = PME ; Particle Mesh Ewald for long-range electrostatics rcoulomb = 1.0 ; short-range electrostatic cutoff (in nm) ewald_geometry = 3d ; Ewald sum is performed in all three dimensions pme-order = 4 ; interpolation order for PME (default is 4) fourierspacing = 0.10 ; grid spacing for FFT ewald-rtol = 1e-6 ; relative strength of the Ewald-shifted direct potential at rcoulomb ;---------------------------------------------------- ; VDW ;---------------------------------------------------- vdwtype = Cut-off rvdw = 1.0 ; short-range van der Waals cutoff (in nm) DispCorr = EnerPres ; Apply long range dispersion corrections for Energy and Pres verlet-buffer-tolerance = 0.005 vdw-modifier = Potential-shift-Verlet ;---------------------------------------------------- ; TEMPERATURE & PRESSURE COUPL ;---------------------------------------------------- tc-grps = System tau-t = 2.0 ref-t = 298.15 pcoupl = Parrinello-Rahman pcoupltype = isotropic ; uniform scaling of box vectors tau-p = 2.0 ; time constant (ps) ref-p = 1.01325 ; reference pressure (bar) compressibility = 4.5e-05 ; isothermal compressibility of water (bar^-1) ;---------------------------------------------------- ; VELOCITY GENERATION ;---------------------------------------------------- gen_vel = no ; Velocity generation is off (if gen_vel is 'yes', continuation should be 'no') gen-seed = -1 ; Use random seed gen-temp = 298.15 ; FREE ENERGY ;---------------------------------------------------- free-energy = yes couple-moltype = LIG couple-lambda0 = vdw couple-lambda1 = vdw-q sc-alpha = 0.5 sc-power = 1 sc-sigma = 0.3 ``` ```` ````{tab} Complex. A2A system (membrane protein) ```ini integrator = sd ; stochastic leap-frog integrator nsteps = 2500000 ; 4 * 2 500 000 fs = 10 000 ps = 10 ns dt = 0.004 ; 4 fs comm-mode = Linear ; remove center of mass translation nstcomm = 50 ; frequency for center of mass motion removal ;---------------------------------------------------- ; OUTPUT CONTROL ;---------------------------------------------------- nstxout = 0 ; don't save coordinates to .trr nstvout = 0 ; don't save velocities to .trr nstfout = 0 ; don't save forces to .trr nstxout-compressed = 0 ; xtc compressed trajectory output every 1000 steps (2 ps) compressed-x-precision = 0 ; precision with which to write to the compressed trajectory file nstlog = 0 ; update log file every 2 ps nstenergy = 1000 ; save energies every 2 ps nstcalcenergy = 50 ; calculate energies every 200 fs ;---------------------------------------------------- ; BONDS ;---------------------------------------------------- constraint_algorithm = lincs ; holonomic constraints constraints = all-bonds ; all bonds are constrained (HMR) lincs_iter = 1 ; accuracy of LINCS (1 is default) lincs_order = 6 ; also related to accuracy (4 is default) lincs-warnangle = 30 ; maximum angle that a bond can rotate before LINCS will complain (30 is default) continuation = yes ;---------------------------------------------------- ; NEIGHBOR SEARCHING ;---------------------------------------------------- cutoff-scheme = Verlet ns-type = grid ; search neighboring grid cells nstlist = 10 ; 20 fs (default is 10) rlist = 1.2 ; short-range neighborlist cutoff (in nm) pbc = xyz ; 3D PBC ;---------------------------------------------------- ; ELECTROSTATICS ;---------------------------------------------------- coulombtype = PME ; Particle Mesh Ewald for long-range electrostatics rcoulomb = 1.0 ; short-range electrostatic cutoff (in nm) ewald_geometry = 3d ; Ewald sum is performed in all three dimensions pme-order = 4 ; interpolation order for PME (default is 4) fourierspacing = 0.10 ; grid spacing for FFT ewald-rtol = 1e-6 ; relative strength of the Ewald-shifted direct potential at rcoulomb ;---------------------------------------------------- ; VDW ;---------------------------------------------------- vdwtype = Cut-off rvdw = 1.0 ; short-range van der Waals cutoff (in nm) DispCorr = EnerPres ; Apply long range dispersion corrections for Energy and Pres verlet-buffer-tolerance = 0.005 vdw-modifier = Potential-shift-Verlet ;---------------------------------------------------- ; TEMPERATURE & PRESSURE COUPL ;---------------------------------------------------- tc_grps = SOLU MEMB SOLV tau_t = 2.0 2.0 2.0 ref_t = 298.15 298.15 298.15 pcoupl = c-rescale pcoupltype = semiisotropic tau_p = 2.0 ; time constant (ps) ref_p = 1.01325 1.01325 ; reference pressure (bar) compressibility = 4.5e-5 4.5e-5 ; isothermal compressibility of water (bar^-1) ;---------------------------------------------------- ; VELOCITY GENERATION ;---------------------------------------------------- gen_vel = no ; Velocity generation is off (if gen_vel is 'yes', continuation should be 'no') gen-seed = -1 ; Use random seed gen-temp = 298.15 ; FREE ENERGY ;---------------------------------------------------- free-energy = yes couple-moltype = LIG couple-lambda0 = vdw couple-lambda1 = vdw-q sc-alpha = 0.5 sc-power = 1 sc-sigma = 0.3 init-lambda-state = 5 coul-lambdas = 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 nstdhdl = 100 dhdl-print-energy = total calc-lambda-neighbors = -1 separate-dhdl-file = yes couple-intramol = yes ``` ```` ````{tab} Ligand ```ini integrator = sd ; stochastic leap-frog integrator nsteps = 2500000 ; 4 * 2 500 000 fs = 10 000 ps = 10 ns dt = 0.004 ; 4 fs comm-mode = Linear ; remove center of mass translation nstcomm = 50 ; frequency for center of mass motion removal ;---------------------------------------------------- ; OUTPUT CONTROL ;---------------------------------------------------- nstxout = 0 ; don't save coordinates to .trr nstvout = 0 ; don't save velocities to .trr nstfout = 0 ; don't save forces to .trr nstxout-compressed = 0 ; xtc compressed trajectory output every 1000 steps (2 ps) compressed-x-precision = 0 ; precision with which to write to the compressed trajectory file nstlog = 0 ; update log file every 2 ps nstenergy = 1000 ; save energies every 2 ps nstcalcenergy = 50 ; calculate energies every 200 fs ;---------------------------------------------------- ; BONDS ;---------------------------------------------------- constraint_algorithm = lincs ; holonomic constraints constraints = all-bonds ; all bonds are constrained (HMR) lincs_iter = 1 ; accuracy of LINCS (1 is default) lincs_order = 6 ; also related to accuracy (4 is default) lincs-warnangle = 30 ; maximum angle that a bond can rotate before LINCS will complain (30 is default) continuation = yes ;---------------------------------------------------- ; NEIGHBOR SEARCHING ;---------------------------------------------------- cutoff-scheme = Verlet ns-type = grid ; search neighboring grid cells nstlist = 10 ; 20 fs (default is 10) rlist = 1.2 ; short-range neighborlist cutoff (in nm) pbc = xyz ; 3D PBC ;---------------------------------------------------- ; ELECTROSTATICS ;---------------------------------------------------- coulombtype = PME ; Particle Mesh Ewald for long-range electrostatics rcoulomb = 1.0 ; short-range electrostatic cutoff (in nm) ewald_geometry = 3d ; Ewald sum is performed in all three dimensions pme-order = 4 ; interpolation order for PME (default is 4) fourierspacing = 0.10 ; grid spacing for FFT ewald-rtol = 1e-6 ; relative strength of the Ewald-shifted direct potential at rcoulomb ;---------------------------------------------------- ; VDW ;---------------------------------------------------- vdwtype = Cut-off rvdw = 1.0 ; short-range van der Waals cutoff (in nm) DispCorr = EnerPres ; Apply long range dispersion corrections for Energy and Pres verlet-buffer-tolerance = 0.005 vdw-modifier = Potential-shift-Verlet ;---------------------------------------------------- ; TEMPERATURE & PRESSURE COUPL ;---------------------------------------------------- tc-grps = System tau-t = 2.0 ref-t = 298.15 pcoupl = Parrinello-Rahman pcoupltype = isotropic ; uniform scaling of box vectors tau-p = 2.0 ; time constant (ps) ref-p = 1.01325 ; reference pressure (bar) compressibility = 4.5e-05 ; isothermal compressibility of water (bar^-1) ;---------------------------------------------------- ; VELOCITY GENERATION ;---------------------------------------------------- gen_vel = no ; Velocity generation is off (if gen_vel is 'yes', continuation should be 'no') gen-seed = -1 ; Use random seed gen-temp = 298.15 ; FREE ENERGY ;---------------------------------------------------- free-energy = yes couple-moltype = LIG couple-lambda0 = vdw-q couple-lambda1 = vdw sc-alpha = 0.5 sc-power = 1 sc-sigma = 0.3 init-lambda-state = 5 coul-lambdas = 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 nstdhdl = 100 dhdl-print-energy = total calc-lambda-neighbors = -1 separate-dhdl-file = yes couple-intramol = yes ``` ```` ````` `````` ## GROMACS benchmark Reported values are in ns/day (first row of next figure). The node was isolated (SLURM keyword: `exclusive=True`) for the calculation removing the possibility of sharing resources across process. Each job used 10 CPUs and 1 GPU. ```{figure} scripts/fep-mmxbsa-cluster-bench.svg :alt: Example plot :width: 80% :name: fep-mmxbsa-cluster-bench BinFlow computational performance. (First row) shows the GROMACS performance in ns/day for (left) ligand simulations and (right) protien--ligand complex simulations. (Second row) BindFlow completion time as a function of the number of ligands and computers for (left) FEP and (right) MMGBSA in the thrombin system with RTX A6000/Ryzen Threadripper PRO 3975WX hardware. MMGBSA is approximatly x75 times faster than FEP. ``` | Hardware ID | GPU | CPU | |-------------|-------------------|-------------------------------| | 1 | RTX 4070 Ti SUPER | EPYC 7443 | | 2 | RTX 4000 Ada | Xeon E-2136 CPU | | 3 | RTX A4000 | Ryzen Threadripper PRO 3975WX | | 4 | RTX A4000 | Xeon E-2136 CPU | | 5 | GTX 1070 Ti | Xeon CPU E5-2630 v4 | | 6 | GTX 1070 | Xeon CPU E5-2630 v4 | | 7 | RTX A6000 | Ryzen Threadripper PRO 3975WX | ## Pipeline completion time To estimate the completion time, we selected the thrombin system, which achieved a mid-range performance of 270 ns/day for the protein--ligand complex using an Nvidia RTX A4000 GPU and 10 CPU cores of and Ryzen Threadripper PRO 3975WX (second row of previous fgure). The following figure illustrates the average completion time per ligand as a function of the number of computers (or computing nodes). MMGBSA was approximately 75 times faster than FEP, completing each ligand in under 0.10 hours on average with just 10 computing nodes, demonstrating its computational efficiency. While FEP was more resource-intensive, it scaled efficiently with the number of available computing nodes, achieving an average ligand completion time below the hour with 60 nodes and just 0.29 hours with 200 nodes on the described architecture. ```{figure} scripts/fep-mmxbsa-avg-time-per-lig.svg :alt: Example plot :width: 80% :name: fep-mmxbsa-avg-time-per-lig Computational performance and scalability of BindFlow on the Thrombin system. (Upper panel): Estimated average ligand completion time under ideal conditions. Standard deviation is reported (very small). (Lower panel): Estimated rate of ligand completion time between FEP and MMGBSA. Error bars were calculated after uncertainty propagation. ``` For instance, with **200** nodes running for a week, up to **580** or **39,965** binding free energy calculations could be theoretically performed at FEP or MMGBSA levels, respectively. These estimates assume **ideal conditions** and should be interpreted as preliminary projections of BindFlow’s computational cost. ## Disk use BindFlow aims to minimize the disk usage during FEP and MM(PB/GB)SA calculations. In addition, after finishing the simulations, BindFlow provides post-processing archiving and unarchiving functionalities to reduce the required medium-term storage. As a numerical example, for the P38 system that comprised 86376 atoms, calculations with 29 ligands (triplicated calculations) required 320 GB disk space for FEP and 40 GB for MMGBSA during runtime, respectively. By excluding log files (`.snakemake` directory and `*.log` and `*.err` files) and irrelevant GROMACS files (`.edr`, `mdout.mdp` and `*.tpr`) during archive and compressing all non-trajectory files, the disk space was reduced to 137 GB for FEP and 19 GB for MMGBSA. However, owing to BindFlow full automation, to reproduce the simulations, only the BindFlow version, input structures, run script, and configuration file are required; involving typically only few megabytes for long-term archive. ```{figure} scripts/fep-mmxbsa-simu-size.svg :alt: Example plot :width: 80% :name: fep-mmxbsa-simu-size Disk space used by BindFlow for all simulation sets of this study. Top: for FEP. Bottom: for MM(PB/GB)SA. Red bars: disk space used during simulations. Blue bars: after compression of raw simulation data. Yielding compression factors of 2.6 and 2.3 for FEP and MM(PB/GB)SA, respectively. ``` ","Markdown" "Biophysics","ale94mleon/BindFlow","docs/source/guides/performance/scripts/dag-performance.ipynb",".ipynb","10904","304","{ ""cells"": [ { ""cell_type"": ""code"", ""execution_count"": 1, ""metadata"": {}, ""outputs"": [], ""source"": [ ""from dag_perf_utility import *\n"", ""import pandas as pd\n"", ""import numpy as np\n"", ""import seaborn as sn"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""This estimation of the performance include:\n"", ""\n"", ""- Dynamic allocation\n"", ""- Waiting time between the queue of jobs\n"", ""- Estimation of the minimization, boresch restraint estimation and gmx_MMPBSA steps"" ] }, { ""cell_type"": ""code"", ""execution_count"": 2, ""metadata"": {}, ""outputs"": [], ""source"": [ ""\n"", ""# thrombin, hardware 3\n"", ""# This performance is on:\n"", ""# AMD Ryzen Threadripper PRO 3975WX 32-Cores: 10 / NVIDIA RTX A4000: 1\n"", ""performance_ligand = 806 # ns/day with a dt = 0.004 ps\n"", ""performance_complex = 270 # ns/day with a dt = 0.004 ps\n"", ""suffix = \""_thrombin_amd-ryzen_nvidia-rtxa4000\""\n"", ""SCALE = False\n"", ""complex_type = 'soluble'\n"", ""\n"", ""\n"", ""\n"", ""# I have to scale down the performance based on:\n"", ""if SCALE:\n"", "" # https://technical.city/en/video/Tesla-T4-vs-RTX-A4000\n"", "" performance_RTX_A4000 = 48.31\n"", "" performance_Tesla_T4 = 26.69\n"", "" scaling_factor = performance_Tesla_T4 / performance_RTX_A4000\n"", ""\n"", "" performance_ligand *=scaling_factor\n"", "" performance_complex *=scaling_factor\n"", ""\n"", ""\n"", ""\n"", ""\n"", ""# The correction factor is to estimate the computation time properly taking into account the\n"", ""# integration time step. Calcualted performance are for 0.004 ps\n"", ""# For a step with 0.002 ps, it will take double of that time.\n"", ""\n"", ""\n"", ""# Lets assume that the steps on min and boresch can be approximated as\n"", ""# a production step that takes 0.1, 0.5 and 1 ns\n"", ""extra_steps = {\n"", "" \""min_ligand\"": 0.1 * 0.004,\n"", "" \""min_complex\"": 0.5 * 0.004,\n"", "" \""boresch\"": 1 * 0.004,\n"", "" \""gmx_mmpbsa\"": 1 * 0.004,\n"", ""}\n"", ""\n"", ""simulation_time = { # ns\n"", "" \""fep\"": {\n"", "" \""ligand\"": {\n"", "" \""equi\"": [extra_steps['min_ligand'], 1 * (0.004/0.002), 1.05 * (0.004/0.003), 1, 5],\n"", "" \""perturbation\"": [[extra_steps['min_ligand'], 0.01 * (0.004/0.002), 0.1, 0.5, 10]] * 23\n"", "" },\n"", "" \""complex\"": {\n"", "" \""soluble\"": {\n"", "" \""equi\"": [extra_steps['min_complex'], 1 * (0.004/0.002), 1.05 * (0.004/0.003), 1.00005 * (0.004/0.003), 5, 10, extra_steps['boresch']],\n"", "" \""perturbation\"": [[extra_steps['min_complex'], 0.01 * (0.004/0.003), 0.1, 0.5, 10]] * 44\n"", "" },\n"", "" \""membrane\"": {\n"", "" \""equi\"": [extra_steps['min_complex'], 0.125 * (0.004/0.001), 0.125 * (0.004/0.001), 0.125 * (0.004/0.001), 0.5 * (0.004/0.002), 0.5 * (0.004/0.002), 0.5 * (0.004/0.002), 10, extra_steps['boresch']],\n"", "" \""perturbation\"": [[extra_steps['min_complex'], 0.01 * (0.004/0.002), 0.1, 0.5, 10]] * 44\n"", "" },\n"", "" }\n"", "" },\n"", "" \""mmgbsa\"": {\n"", "" \""complex\"": {\n"", "" \""soluble\"": {\n"", "" \""equi\"": [extra_steps['min_complex'], 10/1000 * (0.004/0.002), 15/1000 * (0.004/0.003), 22.5/1000 * (0.004/0.003), 60/1000, 950/1000, extra_steps['gmx_mmpbsa']], # Here I had the time in ps, the factor 1000 is to convert to ns\n"", "" },\n"", "" \""membrane\"": {\n"", "" \""equi\"": [extra_steps['min_complex'], 5/1000 * (0.004/0.001), 5/1000 * (0.004/0.001), 5/1000 * (0.004/0.001), 15/1000 * (0.004/0.002), 15/1000 * (0.004/0.002), 45/1000 * (0.004/0.002), 950/1000, extra_steps['gmx_mmpbsa']],\n"", "" },\n"", "" },\n"", "" \""samples\"": [100/1000] * 20\n"", "" }\n"", ""}"" ] }, { ""cell_type"": ""code"", ""execution_count"": 3, ""metadata"": {}, ""outputs"": [], ""source"": [ ""import matplotlib.pyplot as plt\n"", ""from concurrent.futures import ProcessPoolExecutor, as_completed\n"", ""from tqdm import tqdm\n"", ""\n"", ""EXECUTE = True\n"", ""\n"", ""# Parameters\n"", ""num_ligands = [1] + list(range(10, 1010, 10))\n"", ""num_computers = [1] + list(range(10, 210, 10))"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""# FEP"" ] }, { ""cell_type"": ""code"", ""execution_count"": 4, ""metadata"": {}, ""outputs"": [ { ""name"": ""stderr"", ""output_type"": ""stream"", ""text"": [ ""Computing Makespan: 100%|███████████████████████████████████████| 2121/2121 [06:20<00:00, 5.57it/s]"" ] }, { ""name"": ""stdout"", ""output_type"": ""stream"", ""text"": [ ""Results saved to 'makespan_data_fep_thrombin_amd-ryzen_nvidia-rtxa4000.dfpkl'\n"" ] }, { ""name"": ""stderr"", ""output_type"": ""stream"", ""text"": [ ""\n"" ] } ], ""source"": [ ""if EXECUTE:\n"", "" # Initialize results array\n"", "" makespan_data = np.zeros((len(num_ligands), len(num_computers)))\n"", ""\n"", "" # Initialize tqdm progress bar\n"", "" progress_bar = tqdm(total=len(num_ligands) * len(num_computers), desc=\""Computing Makespan\"", ncols=100)\n"", ""\n"", "" # List to hold futures\n"", "" futures = []\n"", ""\n"", "" # Function to update the progress bar\n"", "" def update_progress(future):\n"", "" progress_bar.update(1)\n"", ""\n"", "" # Parallelize using ProcessPoolExecutor\n"", "" with ProcessPoolExecutor() as executor:\n"", "" for _, ligs in enumerate(num_ligands):\n"", "" for _, comps in enumerate(num_computers):\n"", "" future = executor.submit(\n"", "" compute_makespan_fep,\n"", "" ligs, comps,\n"", "" performance_ligand,\n"", "" performance_complex,\n"", "" simulation_time[\""fep\""][\""ligand\""][\""equi\""],\n"", "" simulation_time[\""fep\""][\""ligand\""][\""perturbation\""],\n"", "" simulation_time[\""fep\""][\""complex\""][complex_type][\""equi\""],\n"", "" simulation_time[\""fep\""][\""complex\""][complex_type][\""perturbation\""],\n"", "" configure_node_wait_queue_time=60/3600)\n"", "" future.add_done_callback(update_progress)\n"", "" futures.append(future)\n"", "" \n"", "" # Wait for all futures to finish\n"", "" for future in as_completed(futures):\n"", "" ligs, comps, makespan = future.result()\n"", "" # Map results to the makespan_data array\n"", "" i = num_ligands.index(ligs)\n"", "" j = num_computers.index(comps)\n"", "" makespan_data[i, j] = makespan\n"", ""\n"", "" # Finalize the progress bar\n"", "" progress_bar.close()\n"", "" df = pd.DataFrame(makespan_data, columns=num_computers, index=num_ligands)\n"", "" # Save the results using joblib (you can save any object here)\n"", "" pd.to_pickle(df, f'makespan_data_fep{suffix}.dfpkl')\n"", "" print(f\""Results saved to 'makespan_data_fep{suffix}.dfpkl'\"")"" ] }, { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""# MMGBSA"" ] }, { ""cell_type"": ""code"", ""execution_count"": 5, ""metadata"": {}, ""outputs"": [ { ""name"": ""stderr"", ""output_type"": ""stream"", ""text"": [ ""Computing Makespan: 100%|██████████████████████████████████████| 2121/2121 [00:13<00:00, 157.28it/s]"" ] }, { ""name"": ""stdout"", ""output_type"": ""stream"", ""text"": [ ""Results saved to 'makespan_data_mmgbsa_thrombin_amd-ryzen_nvidia-rtxa4000.dfpkl'\n"" ] }, { ""name"": ""stderr"", ""output_type"": ""stream"", ""text"": [ ""\n"" ] } ], ""source"": [ ""if EXECUTE:\n"", "" # Initialize results array\n"", "" makespan_data = np.zeros((len(num_ligands), len(num_computers)))\n"", ""\n"", "" # Initialize tqdm progress bar\n"", "" progress_bar = tqdm(total=len(num_ligands) * len(num_computers), desc=\""Computing Makespan\"", ncols=100)\n"", ""\n"", "" # List to hold futures\n"", "" futures = []\n"", ""\n"", "" # Function to update the progress bar\n"", "" def update_progress(future):\n"", "" progress_bar.update(1)\n"", ""\n"", "" # Parallelize using ProcessPoolExecutor\n"", "" with ProcessPoolExecutor() as executor:\n"", "" for i, ligs in enumerate(num_ligands):\n"", "" for j, comps in enumerate(num_computers):\n"", "" future = executor.submit(\n"", "" compute_makespan_mmgbsa,\n"", "" ligs, comps,\n"", "" performance_complex,\n"", "" simulation_time[\""mmgbsa\""][\""complex\""][\""soluble\""][\""equi\""],\n"", "" simulation_time[\""mmgbsa\""][\""samples\""],\n"", "" configure_node_wait_queue_time=60/3600)\n"", "" future.add_done_callback(update_progress)\n"", "" futures.append(future)\n"", "" \n"", "" # Wait for all futures to finish\n"", "" for future in as_completed(futures):\n"", "" ligs, comps, makespan = future.result()\n"", "" # Map results to the makespan_data array\n"", "" i = num_ligands.index(ligs)\n"", "" j = num_computers.index(comps)\n"", "" makespan_data[i, j] = makespan\n"", ""\n"", "" # Finalize the progress bar\n"", "" progress_bar.close()\n"", ""\n"", "" # Save the results using joblib (you can save any object here)\n"", "" df = pd.DataFrame(makespan_data, columns=num_computers, index=num_ligands)\n"", "" pd.to_pickle(df, f'makespan_data_mmgbsa{suffix}.dfpkl')\n"", "" print(f\""Results saved to 'makespan_data_mmgbsa{suffix}.dfpkl'\"")"" ] } ], ""metadata"": { ""kernelspec"": { ""display_name"": ""plbenchmark"", ""language"": ""python"", ""name"": ""python3"" }, ""language_info"": { ""codemirror_mode"": { ""name"": ""ipython"", ""version"": 3 }, ""file_extension"": "".py"", ""mimetype"": ""text/x-python"", ""name"": ""python"", ""nbconvert_exporter"": ""python"", ""pygments_lexer"": ""ipython3"", ""version"": ""3.11.13"" } }, ""nbformat"": 4, ""nbformat_minor"": 2 } ","Unknown" "Biophysics","ale94mleon/BindFlow","docs/source/guides/performance/scripts/dag_perf_utility.py",".py","9011","207","import networkx as nx import heapq def calculate_makespan(tasks, dependencies, num_computers, configure_node_wait_queue_time=60/3600): """""" Calculate the makespan of a DAG given task times and dependencies. Args: tasks (dict): Task times (e.g., {'A': 3, 'B': 2}). dependencies (list of tuples): Edges representing dependencies (e.g., [('A', 'B'), ('B', 'C')]). num_computers (int): Number of available computers. configure_node_wait_queue_time (float): How much time does it take to have the node ready for the next job; by default 60 seconds. It must be converted to hours Returns: int: Total completion time (makespan). dict: Task schedule with start and end times. """""" # Step 1: Build the DAG dag = nx.DiGraph() dag.add_nodes_from(tasks.keys()) dag.add_edges_from(dependencies) # Step 2: Topological Sort try: top_order = list(nx.topological_sort(dag)) except nx.NetworkXUnfeasible: raise ValueError(""The graph contains a cycle!"") # Step 3: Schedule Tasks on Computers available_computers = [(0, i) for i in range(num_computers)] # (next_available_time, computer_id) heapq.heapify(available_computers) task_schedule = {} end_times = {node: 0 for node in dag.nodes} # End times for all tasks current_time = 0 for node in top_order: # Determine earliest start time based on dependencies predecessors = list(dag.predecessors(node)) earliest_start = max([end_times[p] for p in predecessors], default=0) # Wait for the earliest available computer next_available_time, computer_id = heapq.heappop(available_computers) start_time = max(earliest_start, next_available_time) # It is also added configure_node_wait_queue_time to simulate # the latency of the node when releasing and catching the new job end_time = start_time + tasks[node] + configure_node_wait_queue_time # Schedule the task task_schedule[node] = { 'computer': computer_id, 'start': start_time, 'end': end_time } # Update end time and computer availability end_times[node] = end_time heapq.heappush(available_computers, (end_time, computer_id)) current_time = max(current_time, end_time) return current_time, task_schedule def build_dag_from_fep_simulation(num_ligands, performance_ligand, performance_complex, equi_sim_time_ligand, fep_sim_time_ligand, equi_sim_time_complex, fep_sim_time_complex): """""" Build a DAG for multiple ligands, each with its own simulation tasks. Args: num_ligands (int): Number of ligands. performance_ligand (float): Performance (ns/day) for ligand tasks. performance_complex (float): Performance (ns/day) for complex tasks. equi_sim_time_ligand (list of float): Equilibration times (ns) for ligand. fep_sim_time_ligand (list of of list of float): FEP times (ns) for ligand. equi_sim_time_complex (list of float): Equilibration times (ns) for complex. fep_sim_time_complex (list of list of float): FEP times (ns) for complex. Returns: dict: Tasks with their durations (in hours). list: Dependencies between tasks. """""" tasks = {} dependencies = [] # Convert performance from ns/day to ns/hour performance_complex = performance_complex / 24 performance_ligand = performance_ligand / 24 for ligand_idx in range(1, num_ligands + 1): ligand_prefix = f""lig{ligand_idx}"" # Process ligand equilibration for i, sim_time in enumerate(equi_sim_time_ligand, start=1): task_name = f""{ligand_prefix}_equi_lig{i}"" task_duration = sim_time / performance_ligand # Convert ns to days tasks[task_name] = task_duration if i > 1: dependencies.append((f""{ligand_prefix}_equi_lig{i-1}"", task_name)) # Process ligand FEP for i, sim_times in enumerate(fep_sim_time_ligand, start=1): for j, sim_time in enumerate(sim_times, start=1): task_name = f""{ligand_prefix}_fep_lig{i}_step{j}"" task_duration = sim_time / performance_ligand # Convert ns to days tasks[task_name] = task_duration if j == 1: dependencies.append((f""{ligand_prefix}_equi_lig{len(equi_sim_time_ligand)}"", task_name)) else: dependencies.append((f""{ligand_prefix}_fep_lig{i}_step{j-1}"", task_name)) # Process complex equilibration for i, sim_time in enumerate(equi_sim_time_complex, start=1): task_name = f""{ligand_prefix}_equi_comp{i}"" task_duration = sim_time / performance_complex # Convert ns to hours tasks[task_name] = task_duration if i > 1: dependencies.append((f""{ligand_prefix}_equi_comp{i-1}"", task_name)) # Process complex FEP for i, sim_time in enumerate(fep_sim_time_complex, start=1): for j, sim_time in enumerate(sim_times, start=1): task_name = f""{ligand_prefix}_fep_comp{i}_step{j}"" task_duration = sim_time / performance_complex # Convert ns to hours tasks[task_name] = task_duration if j == 1: dependencies.append((f""{ligand_prefix}_equi_comp{len(equi_sim_time_complex)}"", task_name)) else: dependencies.append((f""{ligand_prefix}_fep_comp{i}_step{j-1}"", task_name)) return tasks, dependencies def build_dag_from_mmgbsa_simulation(num_ligands, performance_complex, equi_sim_time_complex, mmgbsa_sim_time_complex): """""" Build a DAG for multiple ligands, each with its own simulation tasks. Args: num_ligands (int): Number of ligands. performance_complex (float): Performance (ns/day) for complex tasks. fep_sim_time_ligand (list of float): FEP times (ns) for ligand. equi_sim_time_complex (list of float): Equilibration times (ns) for complex. mmgbsa_sim_time_complex (list of float): FEP times (ns) for complex. Returns: dict: Tasks with their durations (in hours). list: Dependencies between tasks. """""" tasks = {} dependencies = [] # Convert performance from ns/day to ns/hour performance_complex = performance_complex / 24 for ligand_idx in range(1, num_ligands + 1): ligand_prefix = f""lig{ligand_idx}"" # Process complex equilibration for i, sim_time in enumerate(equi_sim_time_complex, start=1): task_name = f""{ligand_prefix}_equi_comp{i}"" task_duration = sim_time / performance_complex # Convert ns to hours tasks[task_name] = task_duration if i > 1: dependencies.append((f""{ligand_prefix}_equi_comp{i-1}"", task_name)) # Process complex FEP for i, sim_time in enumerate(mmgbsa_sim_time_complex, start=1): task_name = f""{ligand_prefix}_sample_comp{i}"" task_duration = sim_time / performance_complex # Convert ns to hours tasks[task_name] = task_duration dependencies.append((f""{ligand_prefix}_equi_comp{len(equi_sim_time_complex)}"", task_name)) return tasks, dependencies # Function to calculate makespan for a given number of ligands and computers for fep def compute_makespan_fep(ligs, comps, performance_ligand, performance_complex, equi_sim_time_ligand, fep_sim_time_ligand, equi_sim_time_complex, fep_sim_time_complex, configure_node_wait_queue_time): tasks, dependencies = build_dag_from_fep_simulation( ligs, performance_ligand, performance_complex, equi_sim_time_ligand, fep_sim_time_ligand, equi_sim_time_complex, fep_sim_time_complex) makespan, _ = calculate_makespan(tasks, dependencies, comps, configure_node_wait_queue_time=configure_node_wait_queue_time) return ligs, comps, makespan # Function to calculate makespan for a given number of ligands and computers for mmgbsa def compute_makespan_mmgbsa(ligs, comps, performance_complex, equi_sim_time_complex, mmgbsa_sim_time_complex, configure_node_wait_queue_time): tasks, dependencies = build_dag_from_mmgbsa_simulation( ligs, performance_complex, equi_sim_time_complex, mmgbsa_sim_time_complex) makespan, _ = calculate_makespan(tasks, dependencies, comps, configure_node_wait_queue_time=configure_node_wait_queue_time) return ligs, comps, makespan","Python" "Biophysics","ale94mleon/BindFlow","docs/source/guides/performance/scripts/fep-mmxbsa-cluster-bench.ipynb",".ipynb","877126","1369","{ ""cells"": [ { ""cell_type"": ""code"", ""execution_count"": 2, ""metadata"": {}, ""outputs"": [ { ""data"": { ""text/html"": [ ""
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system_namesystem_typenum_atomssimu_idequi_time_secondscpugpuperformace_ns_dayhardware_nameSystem
0SAMPL6-OAcomplex9207rtx4070ti10.0AMD EPYC 7443 24-Core ProcessorNVIDIA GeForce RTX 4070 Ti SUPER934.324AMD EPYC 7443 24-Core Processor / NVIDIA GeFor...SAMPL6-OA\\n(9207)
1SAMPL6-OAcomplex9207rtx400013.0Intel(R) Xeon(R) E-2136 CPU @ 3.30GHzNVIDIA RTX 4000 Ada Generation894.667Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA...SAMPL6-OA\\n(9207)
2SAMPL6-OAcomplex9207rtxa40009.0Intel(R) Xeon(R) E-2136 CPU @ 3.30GHzNVIDIA RTX A4000932.075Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA...SAMPL6-OA\\n(9207)
3SAMPL6-OAligand3630rtx4070ti5.0AMD EPYC 7443 24-Core ProcessorNVIDIA GeForce RTX 4070 Ti SUPER1246.916AMD EPYC 7443 24-Core Processor / NVIDIA GeFor...SAMPL6-OA\\n(3630)
5SAMPL6-OAligand3630rtx40004.0Intel(R) Xeon(R) E-2136 CPU @ 3.30GHzNVIDIA RTX 4000 Ada Generation1312.631Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA...SAMPL6-OA\\n(3630)
.................................
43p38complex86364gpu:RTX1070Ti:1245.0Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHzNVIDIA GeForce GTX 1070 Ti67.924Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NV...p38\\n(86364)
44p38complex86364gpu:RTX1070:1204.0Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHzNVIDIA GeForce GTX 107062.827Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NV...p38\\n(86364)
45p38ligand6802gpu:A4000:110.0AMD Ryzen Threadripper PRO 3975WX 32-CoresNVIDIA RTX A4000870.327AMD Ryzen Threadripper PRO 3975WX 32-Cores / N...p38\\n(6802)
46p38ligand6802gpu:RTX1070Ti:121.0Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHzNVIDIA GeForce GTX 1070 Ti501.999Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NV...p38\\n(6802)
47p38ligand6802gpu:RTX1070:123.0Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHzNVIDIA GeForce GTX 1070491.267Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NV...p38\\n(6802)
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96 rows × 10 columns

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"" ], ""text/plain"": [ "" system_name system_type num_atoms simu_id equi_time_seconds \\\n"", ""0 SAMPL6-OA complex 9207 rtx4070ti 10.0 \n"", ""1 SAMPL6-OA complex 9207 rtx4000 13.0 \n"", ""2 SAMPL6-OA complex 9207 rtxa4000 9.0 \n"", ""3 SAMPL6-OA ligand 3630 rtx4070ti 5.0 \n"", ""5 SAMPL6-OA ligand 3630 rtx4000 4.0 \n"", "".. ... ... ... ... ... \n"", ""43 p38 complex 86364 gpu:RTX1070Ti:1 245.0 \n"", ""44 p38 complex 86364 gpu:RTX1070:1 204.0 \n"", ""45 p38 ligand 6802 gpu:A4000:1 10.0 \n"", ""46 p38 ligand 6802 gpu:RTX1070Ti:1 21.0 \n"", ""47 p38 ligand 6802 gpu:RTX1070:1 23.0 \n"", ""\n"", "" cpu \\\n"", ""0 AMD EPYC 7443 24-Core Processor \n"", ""1 Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz \n"", ""2 Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz \n"", ""3 AMD EPYC 7443 24-Core Processor \n"", ""5 Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz \n"", "".. ... \n"", ""43 Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz \n"", ""44 Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz \n"", ""45 AMD Ryzen Threadripper PRO 3975WX 32-Cores \n"", ""46 Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz \n"", ""47 Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz \n"", ""\n"", "" gpu performace_ns_day \\\n"", ""0 NVIDIA GeForce RTX 4070 Ti SUPER 934.324 \n"", ""1 NVIDIA RTX 4000 Ada Generation 894.667 \n"", ""2 NVIDIA RTX A4000 932.075 \n"", ""3 NVIDIA GeForce RTX 4070 Ti SUPER 1246.916 \n"", ""5 NVIDIA RTX 4000 Ada Generation 1312.631 \n"", "".. ... ... \n"", ""43 NVIDIA GeForce GTX 1070 Ti 67.924 \n"", ""44 NVIDIA GeForce GTX 1070 62.827 \n"", ""45 NVIDIA RTX A4000 870.327 \n"", ""46 NVIDIA GeForce GTX 1070 Ti 501.999 \n"", ""47 NVIDIA GeForce GTX 1070 491.267 \n"", ""\n"", "" hardware_name System \n"", ""0 AMD EPYC 7443 24-Core Processor / NVIDIA GeFor... SAMPL6-OA\\n(9207) \n"", ""1 Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA... SAMPL6-OA\\n(9207) \n"", ""2 Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA... SAMPL6-OA\\n(9207) \n"", ""3 AMD EPYC 7443 24-Core Processor / NVIDIA GeFor... SAMPL6-OA\\n(3630) \n"", ""5 Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA... SAMPL6-OA\\n(3630) \n"", "".. ... ... \n"", ""43 Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NV... p38\\n(86364) \n"", ""44 Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NV... p38\\n(86364) \n"", ""45 AMD Ryzen Threadripper PRO 3975WX 32-Cores / N... p38\\n(6802) \n"", ""46 Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NV... p38\\n(6802) \n"", ""47 Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NV... p38\\n(6802) \n"", ""\n"", ""[96 rows x 10 columns]"" ] }, ""execution_count"": 2, ""metadata"": {}, ""output_type"": ""execute_result"" } ], ""source"": [ ""import pandas as pd\n"", ""from pathlib import Path\n"", ""\n"", ""csv_root = Path(\""data\"")\n"", ""full_data = pd.concat([pd.read_csv(csv_root/\""smaug.csv\"", index_col=0), pd.read_csv(csv_root/\""elwe.csv\"", index_col=0)])\n"", ""# full_data.to_csv(\""gather/full.csv\"")\n"", ""full_data['hardware_name'] = full_data['cpu'] + \"" / \"" + full_data['gpu']\n"", ""full_data[\""System\""] = full_data[\""system_name\""]+ \""\\n(\""+full_data['num_atoms'].astype(str)+\"")\""\n"", ""full_data = full_data[full_data['gpu'] != \""NVIDIA RTX A6000\""] # Only one point\n"", ""# full_data['Hardware ID'] = full_data['hardware_name'].factorize()[0] + 1\n"", ""full_data"" ] }, { ""cell_type"": ""code"", ""execution_count"": 3, ""metadata"": {}, ""outputs"": [ { ""name"": ""stdout"", ""output_type"": ""stream"", ""text"": [ ""AMD EPYC 7443 24-Core Processor / NVIDIA GeForce RTX 4070 Ti SUPER\n"", ""Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA RTX 4000 Ada Generation\n"", ""Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA RTX A4000\n"", ""AMD Ryzen Threadripper PRO 3975WX 32-Cores / NVIDIA RTX A4000\n"", ""Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NVIDIA GeForce GTX 1070 Ti\n"", ""Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NVIDIA GeForce GTX 1070\n"", ""SAMPL6-OA\n"", ""(9207)\n"", ""SAMPL6-OA\n"", ""(3630)\n"", ""tyk2\n"", ""(66425)\n"", ""tyk2\n"", ""(5817)\n"", ""mcl1\n"", ""(34827)\n"", ""mcl1\n"", ""(5389)\n"", ""ptp1b\n"", ""(74246)\n"", ""ptp1b\n"", ""(9647)\n"", ""thrombin\n"", ""(49471)\n"", ""thrombin\n"", ""(5980)\n"", ""A2A\n"", ""(84996)\n"", ""A2A\n"", ""(5005)\n"", ""CyclophilinD\n"", ""(31857)\n"", ""CyclophilinD\n"", ""(7304)\n"", ""p38\n"", ""(86364)\n"", ""p38\n"", ""(6802)\n"" ] } ], ""source"": [ ""for item in full_data['hardware_name'].unique():\n"", "" print(item)\n"", ""for item in full_data['System'].unique():\n"", "" print(item)"" ] }, { ""cell_type"": ""code"", ""execution_count"": 4, ""metadata"": {}, ""outputs"": [ { ""data"": { ""text/html"": [ ""
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system_namesystem_typenum_atomssimu_idequi_time_secondscpugpuperformace_ns_dayhardware_nameSystemHardware ID
0SAMPL6-OAcomplex9207rtx4070ti10.0AMD EPYC 7443 24-Core ProcessorNVIDIA GeForce RTX 4070 Ti SUPER934.324AMD EPYC 7443 24-Core Processor / NVIDIA GeFor...SAMPL6-OA\\n(9207)1
1SAMPL6-OAcomplex9207rtx400013.0Intel(R) Xeon(R) E-2136 CPU @ 3.30GHzNVIDIA RTX 4000 Ada Generation894.667Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA...SAMPL6-OA\\n(9207)2
2SAMPL6-OAcomplex9207rtxa40009.0Intel(R) Xeon(R) E-2136 CPU @ 3.30GHzNVIDIA RTX A4000932.075Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA...SAMPL6-OA\\n(9207)4
3SAMPL6-OAligand3630rtx4070ti5.0AMD EPYC 7443 24-Core ProcessorNVIDIA GeForce RTX 4070 Ti SUPER1246.916AMD EPYC 7443 24-Core Processor / NVIDIA GeFor...SAMPL6-OA\\n(3630)1
5SAMPL6-OAligand3630rtx40004.0Intel(R) Xeon(R) E-2136 CPU @ 3.30GHzNVIDIA RTX 4000 Ada Generation1312.631Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA...SAMPL6-OA\\n(3630)2
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43p38complex86364gpu:RTX1070Ti:1245.0Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHzNVIDIA GeForce GTX 1070 Ti67.924Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NV...p38\\n(86364)5
44p38complex86364gpu:RTX1070:1204.0Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHzNVIDIA GeForce GTX 107062.827Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NV...p38\\n(86364)6
45p38ligand6802gpu:A4000:110.0AMD Ryzen Threadripper PRO 3975WX 32-CoresNVIDIA RTX A4000870.327AMD Ryzen Threadripper PRO 3975WX 32-Cores / N...p38\\n(6802)3
46p38ligand6802gpu:RTX1070Ti:121.0Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHzNVIDIA GeForce GTX 1070 Ti501.999Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NV...p38\\n(6802)5
47p38ligand6802gpu:RTX1070:123.0Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHzNVIDIA GeForce GTX 1070491.267Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NV...p38\\n(6802)6
\n"", ""

96 rows × 11 columns

\n"", ""
"" ], ""text/plain"": [ "" system_name system_type num_atoms simu_id equi_time_seconds \\\n"", ""0 SAMPL6-OA complex 9207 rtx4070ti 10.0 \n"", ""1 SAMPL6-OA complex 9207 rtx4000 13.0 \n"", ""2 SAMPL6-OA complex 9207 rtxa4000 9.0 \n"", ""3 SAMPL6-OA ligand 3630 rtx4070ti 5.0 \n"", ""5 SAMPL6-OA ligand 3630 rtx4000 4.0 \n"", "".. ... ... ... ... ... \n"", ""43 p38 complex 86364 gpu:RTX1070Ti:1 245.0 \n"", ""44 p38 complex 86364 gpu:RTX1070:1 204.0 \n"", ""45 p38 ligand 6802 gpu:A4000:1 10.0 \n"", ""46 p38 ligand 6802 gpu:RTX1070Ti:1 21.0 \n"", ""47 p38 ligand 6802 gpu:RTX1070:1 23.0 \n"", ""\n"", "" cpu \\\n"", ""0 AMD EPYC 7443 24-Core Processor \n"", ""1 Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz \n"", ""2 Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz \n"", ""3 AMD EPYC 7443 24-Core Processor \n"", ""5 Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz \n"", "".. ... \n"", ""43 Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz \n"", ""44 Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz \n"", ""45 AMD Ryzen Threadripper PRO 3975WX 32-Cores \n"", ""46 Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz \n"", ""47 Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz \n"", ""\n"", "" gpu performace_ns_day \\\n"", ""0 NVIDIA GeForce RTX 4070 Ti SUPER 934.324 \n"", ""1 NVIDIA RTX 4000 Ada Generation 894.667 \n"", ""2 NVIDIA RTX A4000 932.075 \n"", ""3 NVIDIA GeForce RTX 4070 Ti SUPER 1246.916 \n"", ""5 NVIDIA RTX 4000 Ada Generation 1312.631 \n"", "".. ... ... \n"", ""43 NVIDIA GeForce GTX 1070 Ti 67.924 \n"", ""44 NVIDIA GeForce GTX 1070 62.827 \n"", ""45 NVIDIA RTX A4000 870.327 \n"", ""46 NVIDIA GeForce GTX 1070 Ti 501.999 \n"", ""47 NVIDIA GeForce GTX 1070 491.267 \n"", ""\n"", "" hardware_name System \\\n"", ""0 AMD EPYC 7443 24-Core Processor / NVIDIA GeFor... SAMPL6-OA\\n(9207) \n"", ""1 Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA... SAMPL6-OA\\n(9207) \n"", ""2 Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA... SAMPL6-OA\\n(9207) \n"", ""3 AMD EPYC 7443 24-Core Processor / NVIDIA GeFor... SAMPL6-OA\\n(3630) \n"", ""5 Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA... SAMPL6-OA\\n(3630) \n"", "".. ... ... \n"", ""43 Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NV... p38\\n(86364) \n"", ""44 Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NV... p38\\n(86364) \n"", ""45 AMD Ryzen Threadripper PRO 3975WX 32-Cores / N... p38\\n(6802) \n"", ""46 Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NV... p38\\n(6802) \n"", ""47 Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NV... p38\\n(6802) \n"", ""\n"", "" Hardware ID \n"", ""0 1 \n"", ""1 2 \n"", ""2 4 \n"", ""3 1 \n"", ""5 2 \n"", "".. ... \n"", ""43 5 \n"", ""44 6 \n"", ""45 3 \n"", ""46 5 \n"", ""47 6 \n"", ""\n"", ""[96 rows x 11 columns]"" ] }, ""execution_count"": 4, ""metadata"": {}, ""output_type"": ""execute_result"" } ], ""source"": [ ""# Give an order\n"", ""mapping = {\n"", "" 'AMD EPYC 7443 24-Core Processor / NVIDIA GeForce RTX 4070 Ti SUPER': 1,\n"", "" 'Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA RTX 4000 Ada Generation': 2,\n"", "" 'AMD Ryzen Threadripper PRO 3975WX 32-Cores / NVIDIA RTX A4000': 3,\n"", "" 'Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA RTX A4000': 4,\n"", "" 'Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NVIDIA GeForce GTX 1070 Ti': 5,\n"", "" 'Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NVIDIA GeForce GTX 1070': 6,\n"", "" 'AMD Ryzen Threadripper PRO 3975WX 32-Cores / NVIDIA RTX A6000': 7\n"", ""}\n"", ""\n"", ""full_data['Hardware ID'] = full_data['hardware_name'].map(mapping)\n"", ""full_data"" ] }, { ""cell_type"": ""code"", ""execution_count"": 5, ""metadata"": {}, ""outputs"": [], ""source"": [ ""import seaborn as sns\n"", ""import numpy as np\n"", ""import matplotlib.pyplot as plt\n"", ""import json\n"", ""import matplotlib.pyplot as plt\n"", ""from matplotlib.gridspec import GridSpec\n"", ""import matplotlib.pyplot as plt\n"", ""from matplotlib.patches import Rectangle\n"", ""\n"", ""import matplotlib as mpl\n"", ""plt.rcParams['text.usetex'] = True\n"", ""plt.rcParams['font.family'] = 'serif' # Use Computer Modern fonts\n"", ""plt.rcParams['text.latex.preamble'] = r'\\usepackage{amsmath,amsfonts}'\n"", ""mpl.rcParams['font.size'] = 30"" ] }, { ""cell_type"": ""code"", ""execution_count"": 6, ""metadata"": {}, ""outputs"": [], ""source"": [ ""simu_size_csv_root = Path(\""data\"")\n"", ""\n"", ""def plot_performance(fig, gs):\n"", "" # Define the desired order for the X-axis\n"", "" desired_order_complex = [\n"", "" 'p38\\n(86364)',\n"", "" 'A2A\\n(84996)',\n"", "" 'ptp1b\\n(74246)',\n"", "" 'tyk2\\n(66425)',\n"", "" 'thrombin\\n(49471)',\n"", "" 'mcl1\\n(34827)',\n"", "" 'CyclophilinD\\n(31857)',\n"", "" 'SAMPL6-OA\\n(9207)',\n"", "" ]\n"", "" desired_order_ligand = [\n"", "" 'p38\\n(6802)',\n"", "" 'A2A\\n(5005)',\n"", "" 'ptp1b\\n(9647)',\n"", "" 'tyk2\\n(5817)',\n"", "" 'thrombin\\n(5980)',\n"", "" 'mcl1\\n(5389)',\n"", "" 'CyclophilinD\\n(7304)',\n"", "" 'SAMPL6-OA\\n(3630)'\n"", "" ]\n"", ""\n"", "" # Split into Ligand and Complex\n"", "" ligand_data = full_data[full_data['system_type'] == 'ligand']\n"", "" complex_data = full_data[full_data['system_type'] == 'complex']\n"", ""\n"", "" # Pivot data for heatmap\n"", "" ligand_matrix = ligand_data.pivot_table(index=\""Hardware ID\"", columns=\""System\"", values=\""performace_ns_day\"")\n"", "" complex_matrix = complex_data.pivot_table(index=\""Hardware ID\"", columns=\""System\"", values=\""performace_ns_day\"")\n"", ""\n"", "" ligand_matrix = ligand_matrix.reindex(columns=desired_order_ligand)\n"", "" complex_matrix = complex_matrix.reindex(columns=desired_order_complex)\n"", "" # # Ensure the pivoted data forms matrices (check the structure)\n"", "" # print(\""Ligand Matrix:\\n\"", ligand_matrix)\n"", "" # print(\""Complex Matrix:\\n\"", complex_matrix)\n"", ""\n"", "" # First subplot (top-left)\n"", "" ax1 = fig.add_subplot(gs[0, 0]) # First row, first column\n"", ""\n"", "" # Ligand heatmap\n"", "" sns.heatmap(ligand_matrix, annot=True, fmt=\"".0f\"", cmap=\""viridis\"", cbar=True, ax=ax1)\n"", "" \n"", "" row, col = 2, 4 # Zero-based indexing for matrix coordinates\n"", "" rect = Rectangle((col, row), 1, 1, fill=False, edgecolor='red', linewidth=4) # Create a rectangle\n"", "" ax1.add_patch(rect) # Add the rectangle to the plot\n"", "" \n"", "" # Access the color bar and set its label\n"", "" cbar = ax1.collections[0].colorbar # Access the color bar associated with the heatmap\n"", "" # # Set scientific notation on the color bar\n"", "" # formatter = ScalarFormatter(useMathText=True) # Use scientific notation\n"", "" # formatter.set_scientific(True) # Enable scientific formatting\n"", "" # formatter.set_powerlimits((-2, 2)) # Set limits for scientific notation\n"", "" # cbar.ax.yaxis.set_major_formatter(formatter) # Apply formatter to color bar axis\n"", "" cbar.set_label(\""GMX's performance [ns/day]\"", rotation=270, labelpad=35) # Set label and rotate it\n"", "" # Rotate the x-axis and y-axis tick labels\n"", "" ax1.set_xticklabels(ax1.get_xticklabels(), rotation=45, ha='right', rotation_mode=\""anchor\"", fontsize=27) # Rotate x-axis\n"", "" ax1.set_yticklabels(ax1.get_yticklabels(), rotation=0) # Rotate y-axis (optional)\n"", "" ax1.set_title(\""Ligand\"")\n"", "" # plt.xlabel(\""Systems\"")\n"", "" # plt.ylabel(\""GPU/System\"")\n"", ""\n"", "" # Complex heatmap\n"", "" # Second subplot (top-right)\n"", "" ax2 = fig.add_subplot(gs[0, 1]) # First row, second column\n"", "" sns.heatmap(complex_matrix, annot=True, fmt=\"".0f\"", cmap=\""magma\"", cbar=True, ax=ax2)\n"", "" \n"", "" row, col = 2, 4 # Zero-based indexing for matrix coordinates\n"", "" rect = Rectangle((col, row), 1, 1, fill=False, edgecolor='red', linewidth=4) # Create a rectangle\n"", "" ax2.add_patch(rect) # Add the rectangle to the plot\n"", "" \n"", "" # Access the color bar and set its label\n"", "" cbar = ax2.collections[0].colorbar # Access the color bar associated with the heatmap\n"", "" # # Set scientific notation on the color bar\n"", "" # formatter = ScalarFormatter(useMathText=True) # Use scientific notation\n"", "" # formatter.set_scientific(True) # Enable scientific formatting\n"", "" # formatter.set_powerlimits((-2, 2)) # Set limits for scientific notation\n"", "" # cbar.ax.yaxis.set_major_formatter(formatter) # Apply formatter to color bar axis\n"", "" cbar.set_label(\""GMX's performance [ns/day]\"", rotation=270, labelpad=35) # Set label and rotate it\n"", "" # Rotate the x-axis and y-axis tick labels\n"", "" \n"", "" ax2.set_xticklabels(ax2.get_xticklabels(), rotation=45, ha='right', rotation_mode=\""anchor\"", fontsize=27) # Rotate x-axis\n"", "" ax2.set_yticklabels(ax2.get_yticklabels(), rotation=0) # Rotate y-axis (optional)\n"", "" ax2.set_title(\""Complex\"")\n"", "" # plt.xlabel(\""Number of Atoms\"")\n"", "" # plt.ylabel(\""GPU/System\""\n"", ""\n"", ""\n"", ""def simu_time(fig, gs):\n"", "" suffix = \""_thrombin_amd-ryzen_nvidia-rtxa4000\""\n"", "" # Plotting the heatmap\n"", "" ax1 = fig.add_subplot(gs[1,0]) # Second row, spans all columns\n"", "" makespan_data_fep = pd.read_pickle(f\""makespan_data_fep{suffix}.dfpkl\"")\n"", "" sns.heatmap(makespan_data_fep, norm=plt.Normalize(vmin=0, vmax=720),\n"", "" cmap='twilight', linewidths=0, ax=ax1)\n"", "" cbar = ax1.collections[0].colorbar # Access the color bar associated with the heatmap\n"", "" cbar.set_label('Completion time [hours]', rotation=270, labelpad=35) # Set label and rotate i\n"", "" ax1.set(\n"", "" title='FEP',\n"", "" xlabel='Number of computers',\n"", "" ylabel='Number of ligands',\n"", "" )\n"", "" ax1.invert_yaxis()\n"", "" \n"", "" ax2 = fig.add_subplot(gs[1,1]) # Second row, spans all columns\n"", "" makespan_data_mmgbsa = pd.read_pickle(f\""makespan_data_mmgbsa{suffix}.dfpkl\"")\n"", "" sns.heatmap(makespan_data_mmgbsa, norm=plt.Normalize(vmin=0, vmax=72), cmap='twilight', linewidths=0, ax=ax2)\n"", "" cbar = ax2.collections[0].colorbar # Access the color bar associated with the heatmap\n"", "" cbar.set_label('Completion time [hours]', rotation=270, labelpad=35) # Set label and rotate i\n"", "" ax2.set(\n"", "" title='MMGBSA',\n"", "" xlabel='Number of computers',\n"", "" ylabel='Number of ligands'\n"", "" )\n"", "" ax2.invert_yaxis()\n"", "" mean_speed_off = np.mean(makespan_data_fep / makespan_data_mmgbsa)\n"", "" print(\""Mean of element-wise division:\"", mean_speed_off)\n"", "" \n"", "" ax2.text(\n"", "" 0.70, 0.65, # Coordinates (center of the plot)\n"", "" f'$\\\\times${round(mean_speed_off)}', # Text to display\n"", "" color='black', # Bright gray color\n"", "" # alpha=0.25, # Transparency (0: fully transparent, 1: fully opaque)\n"", "" fontsize=200, # Font size to cover most of the figure\n"", "" ha='center', # Horizontal alignment\n"", "" va='center', # Vertical alignment\n"", "" transform=ax2.transAxes, # Use axis coordinates (0 to 1)\n"", "" # rotation=30 # Optional: Rotate the text\n"", "" )\n"", ""\n"", ""\n"", ""\n"", ""\n"", ""def _simu_time_per_lig_m1(ax, makespan_data, simu_type='FEP'):\n"", "" time_per_lig_mean = makespan_data.div(makespan_data.index, axis=0).mean(axis=0)\n"", "" time_per_lig_std = makespan_data.div(makespan_data.index, axis=0).std(axis=0)\n"", "" # Increase frame thickness\n"", "" for spine in ax.spines.values():\n"", "" spine.set_linewidth(2) # Adjust thickness as needed\n"", ""\n"", "" # Plot with error bars\n"", "" ax.errorbar(\n"", "" time_per_lig_mean.index, # x values\n"", "" time_per_lig_mean.values, # y values\n"", "" yerr=time_per_lig_std.values, # Error bars (standard deviation)\n"", "" fmt='o--',\n"", "" ecolor='#888888',\n"", "" markersize=16,\n"", "" markerfacecolor='#00D1FF',\n"", "" markeredgecolor='#0A0A0A',\n"", "" linewidth=3,\n"", "" alpha=0.8,\n"", "" label=simu_type\n"", "" )\n"", ""\n"", "" # Enhance labels and title\n"", "" ax.set_xlabel('Number of computers', fontweight='bold', labelpad=10)\n"", "" # ax.set_title(simu_type, fontweight='bold', pad=15)\n"", "" # ax.set_title(f'{simu_type}. 10--1000 ligands', fontweight='bold', pad=15)\n"", ""\n"", "" # Adjust tick parameters\n"", "" ax.tick_params(axis='both', which='major')\n"", "" ax.set_xticks([10, 50, 100, 150, 200])\n"", "" \n"", "" if simu_type == \""FEP\"":\n"", "" ax.set_yticks(np.arange(np.floor(time_per_lig_mean.min()), np.ceil(time_per_lig_mean.max()) + 1, 1))\n"", "" else:\n"", "" ax.set_yticks([0, 0.05, 0.1, 0.15, 0.2, 0.25])\n"", "" \n"", "" # Add a grid\n"", "" ax.grid(True, linestyle='--', linewidth=0.5, alpha=0.7)\n"", ""\n"", "" # Add legend\n"", "" ax.legend(frameon=True, framealpha=0.5, edgecolor='gray')\n"", "" ax.tick_params(axis='both', width=2, size=5) # Change tick width and label size\n"", "" # plt.ticklabel_format(axis='y', style='scientific', scilimits=(-1,3))\n"", "" \n"", ""\n"", ""\n"", ""def _simu_time_per_lig_m2(ax, simu_type_makespan_data:dict):\n"", "" \n"", "" ax1 = ax \n"", "" ax2 = ax.twinx()\n"", "" for simu_type, makespan_data in simu_type_makespan_data.items():\n"", "" if simu_type == \""FEP\"":\n"", "" ax_temp = ax1\n"", "" else:\n"", "" ax_temp = ax2\n"", "" time_per_lig_mean = makespan_data.div(makespan_data.index, axis=0).mean(axis=0)\n"", "" time_per_lig_std = makespan_data.div(makespan_data.index, axis=0).std(axis=0)\n"", ""\n"", ""\n"", "" # Plot with error bars\n"", "" ax_temp.errorbar(\n"", "" time_per_lig_mean.index, # x values\n"", "" time_per_lig_mean.values, # y values\n"", "" yerr=time_per_lig_std.values, # Error bars (standard deviation)\n"", "" fmt='o--',\n"", "" ecolor='#888888',\n"", "" markersize=16,\n"", "" markerfacecolor='#00D1FF',\n"", "" markeredgecolor='#0A0A0A',\n"", "" linewidth=3,\n"", "" alpha=0.8,\n"", "" label=simu_type\n"", "" )\n"", ""\n"", "" # if simu_type == \""FEP\"":\n"", "" # ax_temp.set_yticks(np.arange(np.floor(time_per_lig_mean.min()), np.ceil(time_per_lig_mean.max()) + 1, 1))\n"", "" # else:\n"", "" # ax_temp.set_yticks([0, 0.05, 0.1, 0.15, 0.2, 0.25])\n"", "" \n"", "" ax_temp.tick_params(axis='both', which='major')\n"", "" ax_temp.tick_params(axis='both', width=2, size=5) # Change tick width and label size\n"", ""\n"", "" # Increase frame thickness\n"", "" for spine in ax1.spines.values():\n"", "" spine.set_linewidth(2) # Adjust thickness as needed\n"", "" # Enhance labels and title\n"", "" ax1.set_xlabel('Number of computers', fontweight='bold', labelpad=10)\n"", "" # ax.set_title(simu_type, fontweight='bold', pad=15)\n"", "" # ax.set_title(f'{simu_type}. 10--1000 ligands', fontweight='bold', pad=15)\n"", ""\n"", "" # Adjust tick parameters\n"", "" \n"", "" ax1.set_xticks([10, 50, 100, 150, 200])\n"", "" # Add a grid\n"", "" ax1.grid(True, linestyle='--', linewidth=0.5, alpha=0.7)\n"", "" \n"", "" \n"", ""def _simu_time_per_lig_m3(ax, makespan_data_fep, makespan_data_mmgbsa):\n"", "" # Increase frame thickness\n"", "" for spine in ax.spines.values():\n"", "" spine.set_linewidth(2) # Adjust thickness as needed\n"", "" time_per_lig_mean_fep = makespan_data_fep.div(makespan_data_fep.index, axis=0).mean(axis=0)\n"", "" time_per_lig_std_fep = makespan_data_fep.div(makespan_data_fep.index, axis=0).std(axis=0)\n"", ""\n"", "" time_per_lig_mean_mmgbsa = makespan_data_mmgbsa.div(makespan_data_mmgbsa.index, axis=0).mean(axis=0)\n"", "" display(time_per_lig_mean_fep)\n"", "" display(time_per_lig_mean_mmgbsa)\n"", "" time_per_lig_std_mmgbsa = makespan_data_mmgbsa.div(makespan_data_mmgbsa.index, axis=0).std(axis=0)\n"", "" \n"", "" error = (((time_per_lig_mean_fep.values / time_per_lig_mean_mmgbsa.values**2) * time_per_lig_std_mmgbsa.values)**2 + \\\n"", "" (time_per_lig_std_fep.values / time_per_lig_mean_mmgbsa.values)**2)**0.5\n"", ""\n"", "" # Plot with error bars\n"", "" ax.errorbar(\n"", "" time_per_lig_mean_fep.index, # x values\n"", "" time_per_lig_mean_fep.values / time_per_lig_mean_mmgbsa.values, # y values\n"", "" yerr=error,\n"", "" fmt='o--',\n"", "" color='#50225B',\n"", "" ecolor='#888888',\n"", "" markersize=12,\n"", "" markerfacecolor=\""#50225B\"",\n"", "" markeredgecolor='#0A0A0A',\n"", "" linewidth=3,\n"", "" alpha=0.8,\n"", "" label=\""t(FEP)/t(MMGBSA)\""\n"", "" )\n"", ""\n"", "" # Enhance labels and title\n"", "" ax.set_xlabel('Number of computers', fontweight='bold', labelpad=10)\n"", ""\n"", "" # ax.set_yticks([15, 25, 35])\n"", "" # ax.set_ylim((10, 40))\n"", "" # Add a grid\n"", "" ax.grid(True, linestyle='--', linewidth=0.5, alpha=0.7)\n"", "" ax.legend(frameon=True, framealpha=0.5, edgecolor='gray', fontsize=15, loc='upper left')\n"", ""\n"", "" ax.tick_params(axis='both', width=2, size=5) # Change tick width and label size\n"", "" # ax.tick_params(axis='y', labelsize=30)\n"", "" # plt.ticklabel_format(axis='y', style='scientific', scilimits=(-1,3))\n"", ""\n"", ""\n"", ""\n"", ""\n"", ""\n"", ""def simu_time_per_lig(fig, gs, MODE=1, remove_first_row_column=False):\n"", "" \n"", "" suffix = \""_thrombin_amd-ryzen_nvidia-rtxa4000\""\n"", "" makespan_data_fep = pd.read_pickle(f\""makespan_data_fep{suffix}.dfpkl\"")\n"", "" makespan_data_mmgbsa = pd.read_pickle(f\""makespan_data_mmgbsa{suffix}.dfpkl\"")\n"", "" if remove_first_row_column:\n"", "" makespan_data_fep = makespan_data_fep.iloc[1:,1:]\n"", "" makespan_data_mmgbsa = makespan_data_mmgbsa.iloc[1:,1:]\n"", "" if MODE == 1:\n"", "" # Plotting the heatmap\n"", "" ax1 = fig.add_subplot(gs[0,0]) # Second row, spans all columns\n"", "" \n"", "" _simu_time_per_lig_m1(ax1, makespan_data_fep,\""FEP\"")\n"", "" \n"", "" # Plotting the heatmap\n"", "" ax2 = fig.add_subplot(gs[1,0], sharex=ax1) # Second row, spans all columns\n"", "" \n"", "" _simu_time_per_lig_m1(ax2, makespan_data_mmgbsa,\""MMGBSA\"")\n"", "" # Hide x-axis labels on the top plot to avoid redundancy\n"", "" plt.setp(ax1.get_xticklabels(), visible=False)\n"", "" ax1.set_xlabel(\""\"") # Don't need x-axis label on top\n"", "" fig.text(-0.02, 0.5, 'Average time per ligand [hours]', va='center', rotation='vertical')\n"", "" elif MODE == 2:\n"", "" _simu_time_per_lig_m2(gs,\n"", "" {\""FEP\"": pd.read_pickle(makespan_data_fep),\n"", "" \""MMGBSA\"": makespan_data_mmgbsa,}\n"", "" )\n"", "" elif MODE == 3:\n"", "" # Plotting the heatmap\n"", "" ax1 = fig.add_subplot(gs[0,0]) # Second row, spans all columns\n"", "" _simu_time_per_lig_m1(ax1, makespan_data_fep,\""FEP\"")\n"", "" plt.setp(ax1.get_xticklabels(), visible=False)\n"", "" ax1.set_xlabel(\""\"") # Don't need x-axis label on top\n"", "" ax1.set_ylabel('Average ligand\\ncompletion time [h]', fontweight='bold', labelpad=15)\n"", "" \n"", "" # Plotting the heatmap\n"", "" ax2 = fig.add_subplot(gs[1,0], sharex=ax1) # Second row, spans all columns\n"", "" _simu_time_per_lig_m3(ax2, makespan_data_fep, makespan_data_mmgbsa)\n"", "" ax2.set_ylabel('Rate', fontweight='bold', labelpad=15)\n"", "" \n"", "" else:\n"", "" raise ValueError(\""MODE must bew 1 or 2\"")\n"", ""\n"", ""\n"", ""# Desired order for plotting\n"", ""SYSTEM_ORDER = [\""p38\"", \""A2A\"", \""ptp1b\"", \""tyk2\"", \""thrombin\"", \""mcl1\"", \""CyclophilinD\"", \""SAMPL6-OA\""]\n"", ""SYSTEM_NAME = {\n"", "" \""p38\"": \""P38\"", \n"", "" \""A2A\"": \""A2A\"",\n"", "" \""ptp1b\"": \""PTP1B\"",\n"", "" \""tyk2\"": \""TYK2\"",\n"", "" \""thrombin\"": \""Thrombin\"",\n"", "" \""mcl1\"": \""MCL1\"",\n"", "" \""CyclophilinD\"": \""CyclophilinD\"",\n"", "" \""SAMPL6-OA\"": \""SAMPL6-OA\""\n"", ""}\n"", ""\n"", ""def to_latex(string):\n"", "" try:\n"", "" return string.replace(\""_\"", \""\\_\"").replace(\"" \"", \""\\ \"")\n"", "" except:\n"", "" raise Exception(string)\n"", ""\n"", ""\n"", ""def simu_size_fep(ax):\n"", "" # Create a DataFrame\n"", "" df = pd.read_csv(simu_size_csv_root/\""simu-size-fep.csv\"")\n"", ""\n"", ""\n"", "" SYSTEM_ORDER_LATEX = [to_latex(SYSTEM_NAME[s]) for s in SYSTEM_ORDER]\n"", ""\n"", "" df['System_Name'] = pd.Categorical(\n"", "" df['System_Name'].replace(SYSTEM_NAME).map(to_latex), categories=SYSTEM_ORDER_LATEX, ordered=True\n"", "" )\n"", "" df = df.sort_values(\""System_Name\"")\n"", ""\n"", "" # Plot the bottom portion (After compression)\n"", "" bars_after = ax.bar(df[\""System_Name\""], df[\""compressed_GB\""], label=\""Compressed\"", color='skyblue')\n"", ""\n"", "" # Plot the top portion (Before compression minus After compression)\n"", "" bars_diff = ax.bar(\n"", "" df[\""System_Name\""],\n"", "" [before - after for before, after in zip(df[\""non_compressed_GB\""], df[\""compressed_GB\""])],\n"", "" bottom=df[\""compressed_GB\""],\n"", "" label=\""Non-compressed\"",\n"", "" color='lightcoral'\n"", "" )\n"", ""\n"", "" # Add numbers at the top of the bars\n"", "" for bar_after, bar_diff, after, total in zip(bars_after, bars_diff, df[\""compressed_GB\""], df[\""non_compressed_GB\""]):\n"", "" # Add text for the 'After Compression' bars\n"", "" ax.text(bar_after.get_x() + bar_after.get_width() / 2,\n"", "" bar_after.get_height() / 2,\n"", "" f\""{after:.1f}\"",\n"", "" ha='center', va='center', color='gray')\n"", "" \n"", "" # Add text at the top of the stacked bars (Total 'Before Compression')\n"", "" ax.text(bar_diff.get_x() + bar_diff.get_width() / 2,\n"", "" bar_diff.get_height() + bar_diff.get_y(),\n"", "" f\""{total:.1f}\"",\n"", "" ha='center', va='bottom', color='black')\n"", ""\n"", "" # Calculate compression factors for each system\n"", "" df[\""Compression_Factor\""] = df[\""non_compressed_GB\""] / df[\""compressed_GB\""]\n"", ""\n"", "" # Calculate the average compression factor\n"", "" average_compression_factor = df[\""Compression_Factor\""].mean()\n"", ""\n"", "" print(f\""Average compression factor (fep): {average_compression_factor:.2f}\"")\n"", "" ax.set_xticklabels(ax.get_xticklabels(), rotation=90, ha='right', va='center', rotation_mode=\""anchor\"", fontsize=27) # Rotate x-axis\n"", ""\n"", "" ax.text(\n"", "" 0.70, 0.65, # Coordinates (center of the plot)\n"", "" f'$\\\\times${round(average_compression_factor, 1)}', # Text to display\n"", "" color='lightgray', # Bright gray color\n"", "" # alpha=0.25, # Transparency (0: fully transparent, 1: fully opaque)\n"", "" fontsize=150, # Font size to cover most of the figure\n"", "" ha='center', # Horizontal alignment\n"", "" va='center', # Vertical alignment\n"", "" transform=ax.transAxes, # Use axis coordinates (0 to 1)\n"", "" # rotation=30 # Optional: Rotate the text\n"", "" )\n"", ""\n"", "" # Add labels and title\n"", "" ax.set_ylabel(\""Size (GB)\"")\n"", "" # ax.set_xlabel(\""System\"")\n"", "" ax.legend()\n"", ""\n"", ""def simu_size_mmpbsa(ax):\n"", "" # Create a DataFrame\n"", "" df = pd.read_csv(simu_size_csv_root/\""simu-size-mmpbsa.csv\"")\n"", ""\n"", ""\n"", "" SYSTEM_ORDER_LATEX = [to_latex(SYSTEM_NAME[s]) for s in SYSTEM_ORDER]\n"", ""\n"", "" df['System_Name'] = pd.Categorical(\n"", "" df['System_Name'].replace(SYSTEM_NAME).map(to_latex), categories=SYSTEM_ORDER_LATEX, ordered=True\n"", "" )\n"", "" df = df.sort_values(\""System_Name\"")\n"", ""\n"", "" # Plot the bottom portion (After compression)\n"", "" bars_after = ax.bar(df[\""System_Name\""], df[\""compressed_GB\""], label=\""Compressed\"", color='skyblue')\n"", ""\n"", "" # Plot the top portion (Before compression minus After compression)\n"", "" bars_diff = ax.bar(\n"", "" df[\""System_Name\""],\n"", "" [before - after for before, after in zip(df[\""non_compressed_GB\""], df[\""compressed_GB\""])],\n"", "" bottom=df[\""compressed_GB\""],\n"", "" label=\""Non-compressed\"",\n"", "" color='lightcoral'\n"", "" )\n"", ""\n"", "" # Add numbers at the top of the bars\n"", "" for bar_after, bar_diff, after, total in zip(bars_after, bars_diff, df[\""compressed_GB\""], df[\""non_compressed_GB\""]):\n"", "" # Add text for the 'After Compression' bars\n"", "" ax.text(bar_after.get_x() + bar_after.get_width() / 2,\n"", "" bar_after.get_height() / 2,\n"", "" f\""{after:.1f}\"",\n"", "" ha='center', va='center', color='gray')\n"", "" \n"", "" # Add text at the top of the stacked bars (Total 'Before Compression')\n"", "" ax.text(bar_diff.get_x() + bar_diff.get_width() / 2,\n"", "" bar_diff.get_height() + bar_diff.get_y(),\n"", "" f\""{total:.1f}\"",\n"", "" ha='center', va='bottom', color='black')\n"", ""\n"", "" # Calculate compression factors for each system\n"", "" df[\""Compression_Factor\""] = df[\""non_compressed_GB\""] / df[\""compressed_GB\""]\n"", ""\n"", "" # Calculate the average compression factor\n"", "" average_compression_factor = df[\""Compression_Factor\""].mean()\n"", ""\n"", "" print(f\""Average Compression Factor (mmpbsa): {average_compression_factor:.2f}\"")\n"", "" ax.set_xticklabels(ax.get_xticklabels(), rotation=90, ha='right', va='center', rotation_mode=\""anchor\"", fontsize=27) # Rotate x-axis\n"", ""\n"", "" ax.text(\n"", "" 0.70, 0.65, # Coordinates (center of the plot)\n"", "" f'$\\\\times${round(average_compression_factor, 1)}', # Text to display\n"", "" color='lightgray', # Bright gray color\n"", "" # alpha=0.25, # Transparency (0: fully transparent, 1: fully opaque)\n"", "" fontsize=150, # Font size to cover most of the figure\n"", "" ha='center', # Horizontal alignment\n"", "" va='center', # Vertical alignment\n"", "" transform=ax.transAxes, # Use axis coordinates (0 to 1)\n"", "" # rotation=30 # Optional: Rotate the text\n"", "" )\n"", ""\n"", "" # Add labels and title\n"", "" ax.set_ylabel(\""Size (GB)\"")\n"", "" # ax.set_xlabel(\""System\"")\n"", "" ax.legend()\n"" ] }, { ""cell_type"": ""code"", ""execution_count"": 7, ""metadata"": {}, ""outputs"": [ { ""name"": ""stdout"", ""output_type"": ""stream"", ""text"": [ ""Mean of element-wise division: 75.44872040383108\n"", ""{\n"", "" \""AMD EPYC 7443 24-Core Processor / NVIDIA GeForce RTX 4070 Ti SUPER\"": 1,\n"", "" \""Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA RTX 4000 Ada Generation\"": 2,\n"", "" \""AMD Ryzen Threadripper PRO 3975WX 32-Cores / NVIDIA RTX A4000\"": 3,\n"", "" \""Intel(R) Xeon(R) E-2136 CPU @ 3.30GHz / NVIDIA RTX A4000\"": 4,\n"", "" \""Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NVIDIA GeForce GTX 1070 Ti\"": 5,\n"", "" \""Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz / NVIDIA GeForce GTX 1070\"": 6,\n"", "" \""AMD Ryzen Threadripper PRO 3975WX 32-Cores / NVIDIA RTX A6000\"": 7\n"", ""}\n"" ] }, { ""data"": { ""image/png"": 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"" ] }, ""metadata"": {}, ""output_type"": ""display_data"" } ], ""source"": [ ""\n"", ""\n"", ""# Create a figure\n"", ""fig = plt.figure(figsize=(40, 30))\n"", ""\n"", ""# Define a 2x2 GridSpec layout\n"", ""gs = GridSpec(2, 2, figure=fig, height_ratios=[1, 1]) # More height to the last row\n"", ""\n"", ""plot_performance(fig, gs)\n"", ""simu_time(fig, gs)\n"", ""\n"", ""print(json.dumps(mapping, indent=3))\n"", ""\n"", ""# plt.tight_layout(rect=[0, 0, 1, 0.95]) # Adjust layout to fit title\n"", ""plt.show()\n"" ] }, { ""cell_type"": ""code"", ""execution_count"": 8, ""metadata"": {}, ""outputs"": [], ""source"": [ ""fig.savefig('fep-mmxbsa-cluster-bench.svg',\n"", "" bbox_inches=\""tight\"",\n"", "" pad_inches=0.0,\n"", "" transparent=False)"" ] }, { ""cell_type"": ""code"", ""execution_count"": 9, ""metadata"": {}, ""outputs"": [ { ""data"": { ""text/plain"": [ ""10 5.663079\n"", ""20 2.831944\n"", ""30 1.890251\n"", ""40 1.417216\n"", ""50 1.136069\n"", ""60 0.947644\n"", ""70 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"", ""text/plain"": [ ""
"" ] }, ""metadata"": {}, ""output_type"": ""display_data"" } ], ""source"": [ ""# Create a figure\n"", ""fig = plt.figure(figsize=(7.5, 8))\n"", ""\n"", ""# Define a 2x2 GridSpec layout\n"", ""gs = GridSpec(2, 1, figure=fig, height_ratios=[1, 0.3], hspace=0.1) # More height to the last row\n"", ""simu_time_per_lig(fig, gs, MODE=3, remove_first_row_column=True)\n"", ""fig.savefig('fep-mmxbsa-avg-time-per-lig.svg',\n"", "" bbox_inches=\""tight\"",\n"", "" pad_inches=0.0,\n"", "" transparent=False)"" ] }, { ""cell_type"": ""code"", ""execution_count"": 10, ""metadata"": {}, ""outputs"": [ { ""name"": ""stdout"", ""output_type"": ""stream"", ""text"": [ ""Average compression factor (fep): 2.56\n"", ""Average Compression Factor (mmpbsa): 2.30\n"" ] }, { ""name"": ""stderr"", ""output_type"": ""stream"", ""text"": [ ""/var/folders/fl/txtwcjh94vs_gkm_s21h8w7m0000gn/T/ipykernel_24842/299274807.py:390: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.\n"", "" ax.set_xticklabels(ax.get_xticklabels(), rotation=90, ha='right', va='center', rotation_mode=\""anchor\"", fontsize=27) # Rotate x-axis\n"", ""/var/folders/fl/txtwcjh94vs_gkm_s21h8w7m0000gn/T/ipykernel_24842/299274807.py:454: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.\n"", "" ax.set_xticklabels(ax.get_xticklabels(), rotation=90, ha='right', va='center', rotation_mode=\""anchor\"", fontsize=27) # Rotate x-axis\n"", ""/var/folders/fl/txtwcjh94vs_gkm_s21h8w7m0000gn/T/ipykernel_24842/3009324223.py:12: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n"", "" fig.tight_layout()\n"" ] }, { ""data"": { ""image/png"": 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"", ""text/plain"": [ ""
"" ] }, ""metadata"": {}, ""output_type"": ""display_data"" } ], ""source"": [ ""\n"", ""\n"", ""# Create a figure\n"", ""fig = plt.figure(figsize=(10, 20))\n"", ""\n"", ""# Define a 2x2 GridSpec layout\n"", ""gs = GridSpec(2, 1, figure=fig, hspace=0.05)\n"", ""ax1 = fig.add_subplot(gs[0, 0])\n"", ""ax2 = fig.add_subplot(gs[1, 0], sharex=ax1) # <--- share x-axis with ax1\n"", ""\n"", ""simu_size_fep(ax1)\n"", ""ax1.tick_params(axis=\""x\"", which=\""both\"", labelbottom=False)\n"", ""simu_size_mmpbsa(ax2)\n"", ""fig.tight_layout()\n"", ""fig.savefig('fep-mmxbsa-simu-size.svg',\n"", "" bbox_inches=\""tight\"",\n"", "" pad_inches=0.0,\n"", "" transparent=False)"" ] }, { ""cell_type"": ""code"", ""execution_count"": 18, ""metadata"": {}, ""outputs"": [ { ""name"": ""stdout"", ""output_type"": ""stream"", ""text"": [ ""580.4084895427691 39965.744941410834\n"", ""56.6289483319547 0.7243111111111111\n"" ] } ], ""source"": [ ""# def avg_num_lig_on_one_week():\n"", ""suffix = \""_thrombin_amd-ryzen_nvidia-rtxa4000\""\n"", ""makespan_data_fep = pd.read_pickle(f\""makespan_data_fep{suffix}.dfpkl\"").iloc[1:,1:]\n"", ""fep_avg = makespan_data_fep.div(makespan_data_fep.index, axis=0).mean(axis=0)\n"", ""makespan_data_mmgbsa = pd.read_pickle(f\""makespan_data_mmgbsa{suffix}.dfpkl\"").iloc[1:,1:]\n"", ""mmgbsa_avg = makespan_data_mmgbsa.div(makespan_data_mmgbsa.index, axis=0).mean(axis=0)\n"", ""\n"", ""# Number of ligands in a week \n"", ""print(168 /fep_avg.loc[200], 168 /mmgbsa_avg.loc[200])\n"", ""# If the cost is estimated for the use across all GPUs (like running in series in one GPU)\n"", ""print(pd.read_pickle(f\""makespan_data_fep{suffix}.dfpkl\"").iloc[0,0], pd.read_pickle(f\""makespan_data_mmgbsa{suffix}.dfpkl\"").iloc[1:,1:].iloc[0,0])"" ] } ], ""metadata"": { ""kernelspec"": { ""display_name"": ""BindFlow"", ""language"": ""python"", ""name"": ""python3"" }, ""language_info"": { ""codemirror_mode"": { ""name"": ""ipython"", ""version"": 3 }, ""file_extension"": "".py"", ""mimetype"": ""text/x-python"", ""name"": ""python"", ""nbconvert_exporter"": ""python"", ""pygments_lexer"": ""ipython3"", ""version"": ""3.10.18"" } }, ""nbformat"": 4, ""nbformat_minor"": 2 } ","Unknown" "Biophysics","ale94mleon/BindFlow","docs/source/notebooks/mmpbsa.ipynb",".ipynb","362","21","{ ""cells"": [ { ""cell_type"": ""markdown"", ""metadata"": {}, ""source"": [ ""# MM(PB/GB)SA tutorial\n"", ""\n"", ""Here we will demonstrate how to execute a MM(PB/GB)SA calculation on the CyclophilinD system. All the data is on the "" ] } ], ""metadata"": { ""language_info"": { ""name"": ""python"" } }, ""nbformat"": 4, ""nbformat_minor"": 2 } ","Unknown" "Biophysics","ale94mleon/BindFlow","tests/test_small.py",".py","1162","34","#!/usr/bin/env python3 # -*- coding: utf-8 -*- import tempfile import sys import pytest from rdkit import Chem from toff import Parameterize tmp_dir = tempfile.TemporaryDirectory() mol = Chem.MolFromSmiles('CC') @pytest.mark.filterwarnings(""ignore"") def test_Parameterize_openff(): parameterizer = Parameterize(overwrite=True, out_dir=tmp_dir.name, force_field_type='openff', hmr_factor=2.5) parameterizer(input_mol=mol, mol_resi_name='OPE',) @pytest.mark.xfail(sys.platform == ""darwin"", reason=""This test is expected to fail on macOS"") @pytest.mark.filterwarnings(""ignore"") def test_Parameterize_gaff(): parameterizer = Parameterize(overwrite=True, out_dir=tmp_dir.name, force_field_type='gaff') parameterizer(input_mol=mol, mol_resi_name='GAF') @pytest.mark.xfail(sys.platform == ""darwin"", reason=""This test is expected to fail on macOS"") @pytest.mark.filterwarnings(""ignore"") def test_Parameterize_espaloma(): parameterizer = Parameterize(overwrite=True, out_dir=tmp_dir.name, force_field_type='espaloma', force_field_code='espaloma-0.3.1') parameterizer(input_mol=mol, mol_resi_name='ESP') if __name__ == '__main__': pass ","Python" "Biophysics","ale94mleon/BindFlow","tests/test_mmpbsa.py",".py","2410","82","#!/usr/bin/env python3 # -*- coding: utf-8 -*- import pytest @pytest.mark.filterwarnings(""ignore"") def test_mmpbsa(): import tarfile import tempfile # import pytest from multiprocessing import cpu_count from pathlib import Path import yaml from bindflow.home import home from bindflow.orchestration.generate_scheduler import FrontEnd from bindflow.runners import calculate with tempfile.TemporaryDirectory(dir='.', prefix='.test_mmpbsa_') as tmp: home_path = home(dataDir='ci_systems') fname = home_path / 'WP6.tar.gz' tar = tarfile.open(fname, ""r:gz"") tar.extractall(tmp) tar.close() tmp_path = Path(tmp)/""WP6"" ligand_files = list((tmp_path/""guest"").rglob(""*sdf""))[:2] ligands = [] for ligand_file in ligand_files: ligands.append({ 'conf': ligand_file, 'ff': { 'type': 'openff' # 'type': 'espaloma', # 'code': 'espaloma-0.3.1' } }) protein = { 'conf': str(tmp_path / 'host/WP6.gro'), 'top': str(tmp_path / 'host/WP6.top'), 'ff': { 'code': 'espaloma-0.3.1', }, } with open(home_path / ""config-mmpbsa.yml"", ""r"") as c: global_config = yaml.safe_load(c) # TODO # This is needed for MacOS when GROMACS is build wth -DGMX_GPU=OpenCL # This is not needed in the cluster because CUDA is different. global_config['extra_directives']['mdrun']['all']['ntmpi'] = 1 num_jobs = cpu_count() threads = min(4, num_jobs) calculate( calculation_type='mmpbsa', protein=protein, ligands=ligands, membrane=None, cofactor=None, cofactor_on_protein=True, water_model='amber/tip3p', host_name='WP6', hmr_factor=3, dt_max=0.004, threads=threads, num_jobs=num_jobs, replicas=2, scheduler_class=FrontEnd, debug=True, job_prefix='host_guest.test', submit=True, out_root_folder_path=str(tmp_path / ""mmpbsa-frontend""), global_config=global_config) if __name__ == '__main__': pass ","Python" "Biophysics","ale94mleon/BindFlow","tests/test_fep.py",".py","2454","83","#!/usr/bin/env python3 # -*- coding: utf-8 -*- import pytest @pytest.mark.filterwarnings(""ignore"") def test_fep(): import tarfile import tempfile # import pytest from multiprocessing import cpu_count from pathlib import Path import yaml from bindflow.home import home from bindflow.orchestration.generate_scheduler import FrontEnd from bindflow.runners import calculate with tempfile.TemporaryDirectory(dir='.', prefix='.test_fep_') as tmp: home_path = home(dataDir='ci_systems') fname = home(dataDir='ci_systems') / 'WP6.tar.gz' tar = tarfile.open(fname, ""r:gz"") tar.extractall(tmp) tar.close() tmp_path = Path(tmp)/""WP6"" ligand_files = list((tmp_path/""guest"").rglob(""*sdf""))[:2] ligands = [] for ligand_file in ligand_files: ligands.append({ 'conf': ligand_file, 'ff': { 'type': 'openff' # 'type': 'espaloma', # 'code': 'espaloma-0.3.1' } }) protein = { 'conf': str(tmp_path / 'host/WP6.gro'), 'top': str(tmp_path / 'host/WP6.top'), 'ff': { 'code': 'espaloma-0.3.1', }, } with open(home_path / ""config-fep.yml"", ""r"") as c: global_config = yaml.safe_load(c) # TODO # This is needed for MacOS when GROMACS is build wth -DGMX_GPU=OpenCL # This is not needed in the cluster because CUDA is different. global_config['extra_directives']['mdrun']['all']['ntmpi'] = 1 num_jobs = cpu_count() threads = min(4, num_jobs) calculate( calculation_type='fep', protein=protein, ligands=ligands, membrane=None, cofactor=None, cofactor_on_protein=True, water_model='amber/tip3p', host_name='WP6', host_selection='resname WP6', hmr_factor=3, dt_max=0.004, threads=threads, num_jobs=num_jobs, replicas=1, scheduler_class=FrontEnd, job_prefix='host_guest.test', debug=True, out_root_folder_path=str(tmp_path / ""fep-frontend""), submit=True, global_config=global_config) if __name__ == '__main__': pass ","Python" "Biophysics","prescient-design/holo-bench","holo/__init__.py",".py","172","7","from importlib.metadata import PackageNotFoundError, version try: __version__ = version(""holo-bench"") except PackageNotFoundError: __version__ = ""unknown version"" ","Python" "Biophysics","prescient-design/holo-bench","holo/logging/__init__.py",".py","54","2","from ._wandb_setup import flatten_config, wandb_setup ","Python" "Biophysics","prescient-design/holo-bench","holo/logging/_wandb_setup.py",".py","1371","51","from typing import MutableMapping import wandb from omegaconf import DictConfig, OmegaConf import holo def wandb_setup(cfg: DictConfig): """""" Runs `wandb.init` and `wandb.login`. The values in `cfg` are logged to the wandb run. """""" if not hasattr(cfg, ""wandb_host""): cfg[""wandb_host""] = ""https://api.wandb.ai"" if not hasattr(cfg, ""wandb_mode""): cfg[""wandb_mode""] = ""online"" if not hasattr(cfg, ""project_name""): cfg[""project_name""] = ""holo"" if not hasattr(cfg, ""exp_name""): cfg[""exp_name""] = ""default_group"" wandb.login(host=cfg.wandb_host) wandb.init( project=cfg.project_name, mode=cfg.wandb_mode, group=cfg.exp_name, ) cfg[""job_name""] = wandb.run.name cfg[""__version__""] = holo.__version__ log_cfg = flatten_config(OmegaConf.to_container(cfg, resolve=True)) wandb.config.update(log_cfg) def flatten_config(d: DictConfig, parent_key: str = """", sep: str = ""/""): """""" Flatten a nested `DictConfig` object into a flat dictionary for logging. """""" items = [] for k, v in d.items(): new_key = parent_key + sep + k if parent_key else k if isinstance(v, MutableMapping): items.extend(flatten_config(v, new_key, sep=sep).items()) else: items.append((new_key, v)) return dict(items) ","Python" "Biophysics","prescient-design/holo-bench","holo/optim/_discrete_evolution.py",".py","5276","130","from typing import Iterable import torch from torch.optim import Optimizer class DiscreteEvolution(Optimizer): r""""""Implements discrete evolution optimizer."""""" def __init__( self, params: Iterable[torch.nn.Parameter], vocab: Iterable[list[int]], mutation_prob: float = 0.2, recombine_prob: float = 0.5, num_particles: int = 128, survival_quantile: float = 0.5, ): """""" Args: params: Iterable of parameters to optimize or dicts defining parameter groups. vocab: Iterable of lists of integers representing the vocabulary for each parameter group. mutation_prob: Probability of mutating each element of the parameters. recombine_prob: Probability of recombining elements of the parameters. num_particles: Number of particles to maintain for each parameter. survival_quantile: Fraction of particles to keep at each step. """""" if mutation_prob <= 0.0 or mutation_prob >= 1.0: msg = ""Mutation probability must be in (0, 1)."" raise ValueError(msg) if recombine_prob < 0.0 or recombine_prob >= 1.0: msg = ""Recombination probability must be in [0, 1)."" raise ValueError(msg) if num_particles < 1: msg = ""Number of particles must be positive."" raise ValueError(msg) if survival_quantile <= 0.0 or survival_quantile >= 1.0: msg = ""Survival quantile must be in (0, 1)."" raise ValueError(msg) if survival_quantile * num_particles < 2: msg = ""Survival quantile must be large enough to keep at least two particles."" raise ValueError(msg) defaults = dict( mutation_prob=mutation_prob, recombine_prob=recombine_prob, vocab=vocab, ) super(DiscreteEvolution, self).__init__(params, defaults) self._num_particles = num_particles self._survival_quantile = survival_quantile self.particle_loss = None def _init_group(self, group, particle_buffer_list): for p in group[""params""]: state = self.state[p] if ""particles"" not in state: repeat_args = [1] * len(p.data.shape) particles = p.data.clone().repeat(self._num_particles, *repeat_args) particles.requires_grad_(False) state[""particles""] = particles particle_buffer_list.append(particles) else: particle_buffer_list.append(state[""particles""]) def step(self, closure: callable): particle_buffer_list = [] for group in self.param_groups: self._init_group(group, particle_buffer_list) self.particle_loss = closure(particle_buffer_list) # (num_particles,) particle_arg_min = torch.argmin(self.particle_loss) soln_loss = self.particle_loss[particle_arg_min] # update parameters to current best for group in self.param_groups: for p in group[""params""]: state = self.state[p] particles = state[""particles""] p.data = particles[particle_arg_min].clone() # update particles # particle survival threshold determined by quantile threshold = torch.quantile(self.particle_loss, self._survival_quantile) if threshold < float(""inf""): surviving = self.particle_loss <= threshold else: surviving = torch.ones_like(self.particle_loss, dtype=torch.bool) for group in self.param_groups: num_params = len(group[""params""]) count = 0 while count < num_params: particles = particle_buffer_list.pop(0) count += 1 surviving_particles = particles[surviving] num_surviving = surviving_particles.size(0) num_missing = self._num_particles - num_surviving # repopulate missing particles by recombining survivors parent_1 = torch.randint(0, num_surviving, (num_missing,)) parent_2 = torch.randint(0, num_surviving, (num_missing,)) recombine_prob = group[""recombine_prob""] recombine_mask = torch.rand_like(surviving_particles[parent_1]) < recombine_prob replace_particles = torch.where( recombine_mask, surviving_particles[parent_1], surviving_particles[parent_2], ) particles[~surviving] = replace_particles # mutate particles mutation_mask = torch.rand_like(particles) < group[""mutation_prob""] vocab_tensor = torch.tensor(group[""vocab""], device=particles.device) replace_elements = torch.randint( len(vocab_tensor), particles.shape, device=particles.device, dtype=particles.dtype, ) new_particles = torch.where(mutation_mask, replace_elements, particles) particles.copy_(new_particles) return soln_loss ","Python" "Biophysics","prescient-design/holo-bench","holo/optim/__init__.py",".py","84","4","from ._discrete_evolution import DiscreteEvolution __all__ = [""DiscreteEvolution""] ","Python" "Biophysics","prescient-design/holo-bench","holo/test_functions/__init__.py",".py","109","3","# Import lookup-based functions from holo.test_functions.lookup import DHFRLookup, TFBIND8Lookup, TRPBLookup ","Python" "Biophysics","prescient-design/holo-bench","holo/test_functions/lookup/__init__.py",".py","153","6","from ._dhfr import DHFRLookup from ._tfbind8 import TFBIND8Lookup from ._trpb import TRPBLookup __all__ = [""TFBIND8Lookup"", ""TRPBLookup"", ""DHFRLookup""] ","Python" "Biophysics","prescient-design/holo-bench","holo/test_functions/lookup/_abstract_lookup.py",".py","10136","286","""""""Abstract base class for lookup-based benchmark functions."""""" import warnings from typing import Dict, List, Optional, Tuple, Union import numpy as np import torch from botorch.test_functions.synthetic import SyntheticTestFunction class AbstractLookup(SyntheticTestFunction): """""" Abstract base class for lookup-based benchmark functions. This class provides a template and common functionality for creating lookup-based test functions. Subclasses need to implement the _load_data method and define their specific properties (alphabet, dimension, etc.). Attributes: _optimal_value: Optional[float] = None # Will be set after loading the data _optimizers: Optional[List[torch.Tensor]] = None # Optimal solutions num_objectives: int = 1 # Single objective optimization wildtype_sequence: str # The wild-type sequence if known dim: int # The sequence length num_states: int # Number of possible states for each position (alphabet size) alphabet_size: int # Alias for num_states, used in tests """""" _optimal_value: Optional[float] = None _optimizers: Optional[List[torch.Tensor]] = None num_objectives = 1 def __init__( self, dim: int, alphabet: Union[str, List[str]], wildtype_sequence: Optional[str] = None, noise_std: Optional[float] = None, negate: bool = False, device: Optional[torch.device] = None, ) -> None: """"""Initialize the abstract lookup function. Args: dim: The dimension (sequence length). alphabet: The alphabet as a string or list of characters. wildtype_sequence: The wild-type sequence if known. noise_std: Standard deviation of the observation noise. negate: If True, negate the function value. device: The torch device to use. """""" self.dim = dim self.categorical_inds = list(range(dim)) # Set up alphabet and mappings if isinstance(alphabet, str): self.alphabet = list(alphabet) else: self.alphabet = alphabet self.num_states = len(self.alphabet) self.alphabet_size = self.num_states # For test compatibility # Create character to index mappings self.char_to_index = {c: i for i, c in enumerate(self.alphabet)} self.index_to_char = {i: c for i, c in enumerate(self.alphabet)} # Set wildtype sequence if provided if wildtype_sequence: self.wildtype_sequence = wildtype_sequence # Define bounds for parameters bounds = [(0.0, float(self.num_states - 1)) for _ in range(self.dim)] super().__init__( noise_std=noise_std, negate=negate, bounds=bounds, ) # Set device self._device = device or torch.device(""cpu"") # Load dataset self._lookup_dict, self._sorted_scores, self._sorted_seqs = self._load_data() # Find optimal value and optimizers self._optimal_value = float(max(self._lookup_dict.values())) self._optimizers = [ self._seq_to_tensor(seq) for seq, score in self._lookup_dict.items() if score == self._optimal_value ] def _load_data(self) -> Tuple[Dict[str, float], np.ndarray, List[str]]: """"""Load the dataset. This method must be implemented by subclasses to load their specific datasets. Returns: A tuple containing: - lookup_dict: Dictionary mapping sequence strings to fitness scores - sorted_scores: Array of scores sorted in descending order - sorted_seqs: List of sequences sorted by descending score """""" raise NotImplementedError(""Subclasses must implement this method."") def _seq_to_tensor(self, seq: str) -> torch.Tensor: """"""Convert a sequence string to a tensor of indices. Args: seq: Sequence string using the defined alphabet Returns: Tensor of alphabet indices """""" if len(seq) != self.dim: raise ValueError(f""Sequence length must be {self.dim}"") indices = [self.char_to_index.get(char, 0) for char in seq] return torch.tensor(indices, device=self._device) def _tensor_to_seq(self, x: torch.Tensor) -> str: """"""Convert a tensor of indices to a sequence string. Args: x: Tensor of alphabet indices Returns: Sequence string using the defined alphabet """""" if len(x.shape) > 1: raise ValueError(f""Expected 1D tensor, got shape {x.shape}"") indices = x.cpu().numpy().astype(int) return """".join(self.index_to_char[idx] for idx in indices) def _evaluate_true(self, X: torch.Tensor) -> torch.Tensor: """"""Evaluate the true function value (lookup the scores). Args: X: A `batch_shape x d`-dim tensor of inputs. Returns: A `batch_shape`-dim tensor of function values. """""" if X.ndim > 2: # If X has more than 2 dimensions, reshape it X_reshaped = X.reshape(-1, self.dim) Y = self._evaluate_true_batched(X_reshaped) # Make sure to return a 1D tensor of shape (batch_size,) return Y.reshape(-1) else: return self._evaluate_true_batched(X) # syntactic sugar for botorch<0.14 def evaluate_true(self, X: torch.Tensor) -> torch.Tensor: return self._evaluate_true(X) def forward(self, X: torch.Tensor, noise: bool = True) -> torch.Tensor: # cast X to float to ensure you can get noisy observations return super().forward(X.float(), noise) def _evaluate_true_batched(self, X: torch.Tensor) -> torch.Tensor: """"""Evaluate for a 2D batch of inputs. Args: X: A `batch_size x d`-dim tensor of inputs. Returns: A `batch_size`-dim tensor of function values (1D tensor). """""" # Ensure integer indices X_int = X.long() batch_size = X_int.shape[0] # Convert to sequences and lookup scores results = torch.zeros(batch_size, device=self._device) for i in range(batch_size): seq = self._tensor_to_seq(X_int[i]) # Get score from lookup dictionary, or a low value if not found score = self._lookup_dict.get(seq, -float(""inf"")) results[i] = torch.tensor(score, device=self._device) # Ensure it's a 1D tensor return results.reshape(-1) def random_solution(self, n: int = 1) -> torch.Tensor: """"""Generate random solutions. Args: n: Number of solutions to generate. Returns: Tensor of shape (n, dim) with random solutions, or (dim,) if n=1. """""" # Generate random indices from 0 to alphabet_size-1 X = torch.randint( low=0, high=self.num_states, size=(n, self.dim), device=self._device, ).float() if n == 1: return X.squeeze(0) return X def initial_solution(self, n: int = 1) -> torch.Tensor: """"""Generate initial solutions from the bottom 10% of the dataset. This makes optimization more interesting than starting with random solutions. Args: n: Number of solutions to generate. Returns: Tensor of shape (n, dim) with initial solutions, or (dim,) if n=1. """""" # Select sequences from the bottom 10% of scores bottom_10_percent = int(0.1 * len(self._sorted_seqs)) bottom_indices = np.random.choice(bottom_10_percent, size=n, replace=(n > bottom_10_percent)) X = torch.zeros(n, self.dim, device=self._device) for i, idx in enumerate(bottom_indices): seq = self._sorted_seqs[-(idx + 1)] # Get from the bottom X[i] = self._seq_to_tensor(seq) if n == 1: return X.squeeze(0) return X def optimal_solution(self, n: int = 1) -> Optional[torch.Tensor]: """"""Return the optimal solution(s). Args: n: Number of solutions to generate. Returns: Tensor of shape (n, dim) with optimal solutions or (dim,) if n=1, or None if no optimizers are available. """""" # If we have multiple optimizers, sample from them if self._optimizers and len(self._optimizers) > 0: indices = np.random.choice(len(self._optimizers), size=n, replace=(n > len(self._optimizers))) X = torch.stack([self._optimizers[i] for i in indices]) if n == 1: return X.squeeze(0) return X else: # If we don't have optimizers, warn and return None warnings.warn(f""No optimal solutions found for {self.__class__.__name__}."", stacklevel=2) return None def to(self, device, dtype=None): """"""Move the test function to the specified device and dtype. Args: device: torch.device The device to move to. dtype: torch.dtype The dtype to convert to. Returns: The test function on the specified device and with the specified dtype. """""" self._device = device # Convert optimizers to the right device and dtype if self._optimizers: if dtype is None: self._optimizers = [opt.to(device=device) for opt in self._optimizers] else: self._optimizers = [opt.to(device=device, dtype=dtype) for opt in self._optimizers] return self def __repr__(self): """"""String representation of the test function."""""" return ( f""{self.__class__.__name__}("" f""dim={self.dim}, "" f""alphabet_size={self.alphabet_size}, "" f""noise_std={self.noise_std}, "" f""negate={self.negate})"" ) ","Python" "Biophysics","prescient-design/holo-bench","holo/test_functions/lookup/_tfbind8.py",".py","5215","136","""""""Implementation of the TFBIND8 lookup function."""""" from typing import Dict, List, Optional, Tuple import numpy as np import pandas as pd import pooch import torch from holo.test_functions.lookup._abstract_lookup import AbstractLookup class TFBIND8Lookup(AbstractLookup): """""" TFBIND8 Lookup function. This is a lookup-based function for the 8-mer DNA transcription factor binding dataset. The dataset contains 65,792 sequences of 8 nucleotides and their corresponding binding affinity scores. The DNA alphabet is {A, C, G, T} encoded as integers {0, 1, 2, 3}. Args: noise_std: float, default=0.0 Standard deviation of Gaussian noise added to the output. negate: bool, default=False If True, negate the function values. Default is maximizing the binding affinity. dim: int, default=8 Sequence length. Must be 8 for this benchmark. transcription_factor: str, default=""SIX6_REF_R1"" The transcription factor dataset to use. """""" def __init__( self, noise_std: float = 0.0, negate: bool = False, dim: int = 8, # Added for config compatibility, but can't be changed transcription_factor: str = ""SIX6_REF_R1"", # Default TF device: Optional[torch.device] = None, ) -> None: """"""Initialize the TFBIND8 lookup function."""""" if dim != 8: raise ValueError(""TFBIND8Lookup has a fixed sequence length of 8 and cannot be changed."") self.transcription_factor = transcription_factor # Initialize the base class super().__init__( dim=dim, alphabet=""ACGT"", # DNA alphabet wildtype_sequence=None, # Will be determined from data if available noise_std=noise_std, negate=negate, device=device, ) def _load_data(self) -> Tuple[Dict[str, float], np.ndarray, List[str]]: """""" Load the TFBIND8 dataset using pooch. Returns: Tuple[Dict[str, float], np.ndarray, List[str]]: - lookup_dict: Dictionary mapping sequence strings to fitness scores - sorted_scores: Array of scores sorted in descending order - sorted_seqs: List of sequences sorted by descending score """""" # Remote URL for the data url = ""https://media.githubusercontent.com/media/francesding/variationalsearch/refs/heads/main/data/TFBIND8/tf_bind_8.csv"" # Use pooch to download and cache the data try: file_path = pooch.retrieve( url, known_hash=None, # We're not checking the hash for now fname=""tf_bind_8.csv"", path=pooch.os_cache(""tfbind8""), ) # Read the data file df = pd.read_csv(file_path) # Make sure the data has the expected columns required_columns = {""sequences"", ""fitness""} if not required_columns.issubset(df.columns): raise ValueError( f""TFBIND8 data missing required columns. Found: {df.columns}, needed: {required_columns}"" ) # Extract sequences and scores sequences = df[""sequences""].tolist() scores = df[""fitness""].values except Exception: # If there's an error with the CSV, fallback to the TF binding dataset from FLEXS url = f""https://raw.githubusercontent.com/samsinai/FLEXS/master/flexs/landscapes/data/tf_binding/{self.transcription_factor}_8mers.txt"" # Use pooch to download and cache the data file_path = pooch.retrieve( url, known_hash=None, # We're not checking the hash for now fname=f""{self.transcription_factor}_8mers.txt"", path=pooch.os_cache(""tfbind8""), ) # Read the data file df = pd.read_csv(file_path, sep=""\t"") # Extract sequences and scores sequences_1 = df[""8-mer""].tolist() sequences_2 = df[""8-mer.1""].tolist() if ""8-mer.1"" in df.columns else [] all_sequences = sequences_1 + sequences_2 # Extract E-scores and normalize them to [0, 1] e_scores = df[""E-score""].values # Normalize scores to [0, 1] normalized_scores = (e_scores - e_scores.min()) / (e_scores.max() - e_scores.min()) all_scores = np.concatenate( [normalized_scores, normalized_scores[: len(sequences_2)]] if sequences_2 else [normalized_scores] ) sequences = all_sequences scores = all_scores # Create lookup dictionary lookup_dict = {seq: score for seq, score in zip(sequences, scores)} # Sort sequences by score seqs = list(lookup_dict.keys()) scores = np.array([lookup_dict[seq] for seq in seqs]) sorted_indices = np.argsort(scores)[::-1] # Descending order sorted_scores = scores[sorted_indices] sorted_seqs = [seqs[i] for i in sorted_indices] return lookup_dict, sorted_scores, sorted_seqs ","Python" "Biophysics","prescient-design/holo-bench","holo/test_functions/lookup/_dhfr.py",".py","4255","110","""""""DHFR: DHFR 9-mer dihydrofolate reductase optimization benchmark. This test function is a lookup table for the DHFR dataset, a 9-mer DNA sequence optimization task for dihydrofolate reductase. The data comes from Papkou et al., 2023. The sequence space is 4^9 = 262,144 possible sequences. The benchmark task is to find sequences with high fitness. """""" from typing import Dict, List, Optional, Tuple import numpy as np import pandas as pd import pooch import torch from holo.test_functions.lookup._abstract_lookup import AbstractLookup class DHFRLookup(AbstractLookup): """"""DHFR 9-mer dihydrofolate reductase optimization benchmark. This benchmark represents the fitness landscape for a 9-nucleotide sequence optimization task for dihydrofolate reductase enzyme. The fitness values represent enzyme activity, with higher values being better. The sequence space consists of 9 nucleotide positions using the standard DNA alphabet (A, C, G, T), resulting in 4^9 = 262,144 possible sequences. The dataset contains measurements for a large subset of these sequences. Data source: Papkou et al., 2023. """""" def __init__( self, dim: int = 9, noise_std: Optional[float] = None, negate: bool = False, device: Optional[torch.device] = None, ) -> None: """"""Initialize DHFR lookup function. Args: dim: The dimension (sequence length). Must be 9 for this benchmark. noise_std: Standard deviation of the observation noise. negate: If True, negate the function value. device: The torch device to use. """""" if dim != 9: raise ValueError( f""DHFRLookup only supports dim=9 (got {dim}). "" f""This benchmark uses a fixed 9-nucleotide sequence."" ) # Initialize with a placeholder wildtype sequence, which will be updated after loading data super().__init__( dim=dim, alphabet=""ACGT"", # Standard DNA alphabet wildtype_sequence=""ATGGTTGAT"", # Placeholder - will be updated after loading data noise_std=noise_std, negate=negate, device=device, ) def _load_data(self) -> Tuple[Dict[str, float], np.ndarray, List[str]]: """"""Load the DHFR dataset from variationalsearch repository using pooch. Returns: A tuple containing: - lookup_dict: Dictionary mapping sequence strings to fitness scores - sorted_scores: Array of scores sorted in descending order - sorted_seqs: List of sequences sorted by descending score """""" # Remote URL for the data url = ""https://media.githubusercontent.com/media/francesding/variationalsearch/refs/heads/main/data/DHFR/DHFR_fitness_data_wt.csv"" # Use pooch to download and cache the data file_path = pooch.retrieve( url, known_hash=None, # We're not checking the hash for now fname=""DHFR_fitness_data_wt.csv"", path=pooch.os_cache(""dhfr""), ) # Read the data file df = pd.read_csv(file_path, index_col=0) # Make sure the data has the expected columns required_columns = {""SV"", ""m""} if not required_columns.issubset(df.columns): raise ValueError(f""DHFR data missing required columns. Found: {df.columns}, needed: {required_columns}"") # Extract sequences and scores sequences = df[""SV""].tolist() scores = df[""m""].values # 'm' is the target column for DHFR # Update wildtype sequence based on actual data self.wildtype_sequence = sequences[0] # First sequence is the wildtype in this dataset # Create lookup dictionary lookup_dict = {seq: score for seq, score in zip(sequences, scores)} # Sort sequences by score seqs = list(lookup_dict.keys()) scores = np.array([lookup_dict[seq] for seq in seqs]) sorted_indices = np.argsort(scores)[::-1] # Descending order sorted_scores = scores[sorted_indices] sorted_seqs = [seqs[i] for i in sorted_indices] return lookup_dict, sorted_scores, sorted_seqs ","Python" "Biophysics","prescient-design/holo-bench","holo/test_functions/lookup/_trpb.py",".py","4396","115","""""""TRPB: TrpB 4-residue tryptophan synthase optimization benchmark. This test function is a lookup table for the TrpB dataset, a 4-residue amino acid sequence optimization task for tryptophan synthase. The data comes from Johnston et al. 2024. The sequence space is 20^4 = 160,000 possible sequences (of which 153,620 are measured in the dataset). The benchmark task is to find sequences with high fitness (enzyme activity). """""" from typing import Dict, List, Optional, Tuple import numpy as np import pandas as pd import pooch import torch from holo.test_functions.lookup._abstract_lookup import AbstractLookup class TRPBLookup(AbstractLookup): """"""TrpB 4-residue tryptophan synthase optimization benchmark. This benchmark represents the fitness landscape for a 4-residue sequence optimization task for tryptophan synthase beta enzyme. The fitness values represent enzyme activity, with higher values being better. The sequence space consists of 4 amino acid positions using the standard 20-letter amino acid alphabet, resulting in 20^4 = 160,000 possible sequences. The dataset contains measurements for 153,620 of these sequences. Data source: Johnston et al., 2024. https://doi.org/10.22002/h5rah-5z170 ""Mapping protein sequence-function relationships using multiple large-scale inverse folding models"" """""" def __init__( self, dim: int = 4, noise_std: Optional[float] = None, negate: bool = False, device: Optional[torch.device] = None, ) -> None: """"""Initialize TrpB lookup function. Args: dim: The dimension (sequence length). Must be 4 for this benchmark. noise_std: Standard deviation of the observation noise. negate: If True, negate the function value. device: The torch device to use. """""" if dim != 4: raise ValueError( f""TrpBLookup only supports dim=4 (got {dim}). "" f""This benchmark uses a fixed 4-residue amino acid sequence."" ) # Initialize the base class super().__init__( dim=dim, alphabet=""ARNDCQEGHILKMFPSTWYV"", # Standard 20 amino acids wildtype_sequence=""VFVS"", # The wild-type sequence from the paper noise_std=noise_std, negate=negate, device=device, ) def _load_data(self) -> Tuple[Dict[str, float], np.ndarray, List[str]]: """"""Load the TrpB dataset from variationalsearch repository using pooch. Returns: A tuple containing: - lookup_dict: Dictionary mapping sequence strings to fitness scores - sorted_scores: Array of scores sorted in descending order - sorted_seqs: List of sequences sorted by descending score """""" # Remote URL for the data url = ""https://media.githubusercontent.com/media/francesding/variationalsearch/refs/heads/main/data/TRPB/four-site_simplified_AA_data.csv"" # Use pooch to download and cache the data file_path = pooch.retrieve( url, known_hash=None, # We're not checking the hash for now fname=""four-site_simplified_AA_data.csv"", path=pooch.os_cache(""trpb""), ) # Read the data file df = pd.read_csv(file_path) # Make sure the data has the expected columns required_columns = {""AAs"", ""fitness""} if not required_columns.issubset(df.columns): raise ValueError(f""TrpB data missing required columns. Found: {df.columns}, needed: {required_columns}"") # Remove rows with stop codons if that column exists if ""# Stop"" in df.columns: df = df[df[""# Stop""] < 1] # Extract sequences and scores sequences = df[""AAs""].tolist() scores = df[""fitness""].values # Create lookup dictionary lookup_dict = {seq: score for seq, score in zip(sequences, scores)} # Sort sequences by score seqs = list(lookup_dict.keys()) scores = np.array([lookup_dict[seq] for seq in seqs]) sorted_indices = np.argsort(scores)[::-1] # Descending order sorted_scores = scores[sorted_indices] sorted_seqs = [seqs[i] for i in sorted_indices] return lookup_dict, sorted_scores, sorted_seqs ","Python" "Biophysics","prescient-design/holo-bench","holo/test_functions/closed_form/__init__.py",".py","70","3","from ._ehrlich import Ehrlich from ._rough_mt_fuji import RoughMtFuji ","Python" "Biophysics","prescient-design/holo-bench","holo/test_functions/closed_form/_rough_mt_fuji.py",".py","3554","99","import torch from botorch.test_functions import SyntheticTestFunction from holo.test_functions.elemental import hamming_dist class RoughMtFuji(SyntheticTestFunction): """""" Implementation of the Rough Mt. Fuji fitness landscape as described in Neidhart et al. (2014) 'Adaptation in tunably rugged fitness landscapes: The Rough Mount Fuji model' https://arxiv.org/abs/1402.3065 """""" num_states = 2 num_centroids = 1 def __init__( self, dim: int = 2, additive_term: float = 0.25, random_term_std: float = 1.0, noise_std: float = 0.0, negate: bool = False, random_seed: int = 0, ): self.dim = dim self.categorical_inds = list(range(dim)) super().__init__( noise_std=noise_std, negate=negate, bounds=[(0.0, 1.0) for _ in range(dim)], ) self._random_seed = random_seed self._generator = torch.Generator().manual_seed(random_seed) self.centroids = torch.randint(0, 2, (1, dim), generator=self._generator) self._additive_term = additive_term self._random_term_std = random_term_std self._random_term = torch.randn(1, dim, generator=self._generator) * random_term_std def _evaluate_true(self, X: torch.Tensor) -> torch.Tensor: dist = hamming_dist(X, self.centroids, dim=-1) return -self._additive_term * dist + (self._random_term * X).sum(dim=-1) # syntactic sugar for botorch<0.14 def evaluate_true(self, X: torch.Tensor) -> torch.Tensor: return self._evaluate_true(X) def forward(self, X: torch.Tensor, noise: bool = True) -> torch.Tensor: # cast X to float to ensure you can get noisy observations return super().forward(X.float(), noise) def initial_solution(self, n: int = 1): # reset generator seed so initial solution is always the same self._generator = self._generator.manual_seed(self._random_seed) return self.random_solution(n) def random_solution(self, n: int = 1): unif_samples = torch.randint(self.num_states, (n, self.dim), device=self.centroids.device) if n == 1: return unif_samples.squeeze(0) return unif_samples @property def _optimal_value(self): return self.evaluate_true(self.optimal_solution()).squeeze() def optimal_solution(self): soln = self.centroids.clone() mask = self._random_term - self._additive_term > 0 mask = mask.to(device=soln.device) soln = torch.where(mask, torch.ones_like(soln), soln) mask = self._random_term + self._additive_term < 0 mask = mask.to(device=soln.device) soln = torch.where(mask, torch.zeros_like(soln), soln) return soln def to(self, device, dtype): self.centroids = self.centroids.to(device, dtype) self._generator = torch.Generator(device=device).manual_seed(self._random_seed) self._random_term = self._random_term.to(device) return self def __repr__(self): return ( f""RoughMtFuji("" f""num_states={self.num_states}, "" f""dim={self.dim}, "" f""additive_term={self._additive_term}, "" f""random_term={self._random_term}, "" f""random_term_std={self._random_term_std}, "" f""centroids={self.centroids}, "" f""noise_std={self.noise_std}, "" f""negate={self.negate}, "" f""random_seed={self._random_seed})"" ) ","Python" "Biophysics","prescient-design/holo-bench","holo/test_functions/closed_form/_ehrlich.py",".py","7338","189","import torch from botorch.test_functions import SyntheticTestFunction from holo.test_functions.elemental import ( dmp_sample_log_likelihood, dmp_stationary_dist, motif_search, sample_dmp, sample_sparse_ergodic_transition_matrix, ) class Ehrlich(SyntheticTestFunction): _optimal_value = 1.0 num_objectives = 1 def __init__( self, num_states: int = 5, dim: int = 7, num_motifs: int = 1, motif_length: int = 3, quantization: int | None = None, epistasis_factor: float = 0.0, noise_std: float = 0.0, negate: bool = False, random_seed: int = 0, ) -> None: bounds = [(0.0, float(num_states - 1)) for _ in range(dim)] self.num_states = num_states self.dim = dim self._random_seed = random_seed self._motif_length = motif_length self._quantization = quantization self.categorical_inds = list(range(dim)) super().__init__( noise_std=noise_std, negate=negate, bounds=bounds, ) self._generator = torch.Generator().manual_seed(random_seed) self._epistasis_factor = epistasis_factor self.initial_dist = torch.ones(num_states) / num_states bandwidth = int(num_states * 0.4) self.transition_matrix = sample_sparse_ergodic_transition_matrix( num_states, bandwidth, softmax_temp=0.5, generator=self._generator, repeats_always_possible=True, ) self.stationary_dist = dmp_stationary_dist(self.transition_matrix) slack_positions = dim - num_motifs * motif_length element_gaps = num_motifs * (motif_length - 1) max_spacing = 1 + slack_positions // element_gaps if max_spacing < 1: raise ValueError(""cannot guarantee a solution satisfying all motifs exists."") # draw motifs as single sequence from DMP and chunk to ensure feasible soln exists all_motifs = sample_dmp( initial_dist=self.stationary_dist.squeeze(-1), transition_matrix=self.transition_matrix, num_steps=num_motifs * motif_length, num_samples=1, generator=self._generator, ).squeeze(0) self.motifs = torch.chunk(all_motifs, num_motifs, dim=0) self.spacings = [] for _ in range(num_motifs): # draw random spacing # spacing = torch.randint(1, max_spacing + 1, (motif_length - 1,), generator=self._generator) # random draw from (motif_length - 1) simplex weights = torch.rand(motif_length - 1, generator=self._generator) weights /= weights.sum() spacing = (slack_positions // num_motifs) * weights # round down spacing = 1 + spacing.floor().to(torch.int64) self.spacings.append(spacing) def _evaluate_true(self, X: torch.Tensor) -> torch.Tensor: motif_contrib = [] for motif, spacing in zip(self.motifs, self.spacings): motif_present = motif_search( solution=X, motif=motif, spacing=spacing, mode=""present"", quantization=self._quantization, ) response = _cubic_response(motif_present, self._epistasis_factor) motif_contrib.append(response) all_motifs_contrib = torch.stack(motif_contrib).prod(dim=0) log_likelihood = dmp_sample_log_likelihood( samples=X, initial_dist=self.initial_dist, transition_matrix=self.transition_matrix, ) is_feasible = log_likelihood > -float(""inf"") return torch.where(is_feasible, all_motifs_contrib, -float(""inf"")) # syntactic sugar for botorch<0.14 def evaluate_true(self, X: torch.Tensor) -> torch.Tensor: return self._evaluate_true(X) def forward(self, X: torch.Tensor, noise: bool = True) -> torch.Tensor: # cast X to float to ensure you can get noisy observations return super().forward(X.float(), noise) def initial_solution(self, n: int = 1): # reset generator seed so initial solution is always the same self._generator = self._generator.manual_seed(self._random_seed) dmp_samples = sample_dmp( initial_dist=self.stationary_dist.squeeze(-1), transition_matrix=self.transition_matrix, num_steps=self.dim, num_samples=n, generator=self._generator, ) if n == 1: return dmp_samples.squeeze(0) return dmp_samples def random_solution(self, n: int = 1): unif_samples = torch.randint(self.num_states, (n, self.dim), device=self.initial_dist.device) if n == 1: return unif_samples.squeeze(0) return unif_samples def optimal_solution(self): # sample random sequence from DMP soln = torch.zeros(self.dim, dtype=torch.int64, device=self.initial_dist.device) # fill in spaced motifs with repeats position = 0 for motif, spacing in zip(self.motifs, self.spacings): spacing = torch.cat( [ torch.tensor([0], device=self.initial_dist.device), spacing, ] ) index = spacing.cumsum(0).tolist() motif = motif.tolist() for idx in range(index[-1] + 1): if idx in index: next_state = motif.pop(0) soln[position] = next_state position += 1 # fill in remaining states with last state of last motif soln[position:] = soln[position - 1] # check optimal value optimal_value = self.evaluate_true(soln.unsqueeze(0)) if not optimal_value == self._optimal_value: raise RuntimeError(""optimal value not achieved by optimal solution."") return soln def to(self, device, dtype): self.transition_matrix = self.transition_matrix.to(device, dtype) self.initial_dist = self.initial_dist.to(device, dtype) self.stationary_dist = self.stationary_dist.to(device, dtype) self.motifs = [motif.to(device) for motif in self.motifs] self.spacings = [spacing.to(device) for spacing in self.spacings] self._generator = torch.Generator(device=device).manual_seed(self._random_seed) return self def __repr__(self): motif_list = [f""motif_{i}: {motif.tolist()}"" for i, motif in enumerate(self.motifs)] spacing_list = [f""spacing_{i}: {spacing.tolist()}"" for i, spacing in enumerate(self.spacings)] return ( f""Ehrlich("" f""num_states={self.num_states}, "" f""dim={self.dim}, "" f""num_motifs={len(self.motifs)}, "" f""motifs=[{', '.join(motif_list)}], "" f""spacings=[{', '.join(spacing_list)}], "" f""quantization={self._quantization}, "" f""noise_std={self.noise_std}, "" f""negate={self.negate}, "" f""random_seed={self._random_seed})"" ) def _cubic_response(X: torch.Tensor, epistasis_factor: float): coeff = epistasis_factor * X * (X - 1.0) + 1.0 return coeff * X ","Python" "Biophysics","prescient-design/holo-bench","holo/test_functions/elemental/_discrete_markov_process.py",".py","5311","172","from typing import Optional import torch def banded_square_matrix( ndim: int, bandwidth: int, ): """""" Generate a banded square matrix with entries 0 or 1. The rows wrap around, so the number of non-zero entries in each row is 2 * bandwidth + 1. Args: ndim: An integer representing the dimension of the square matrix. bandwidth: An integer representing the bandwidth of the matrix. Returns: A tensor of shape (ndim, ndim) representing the banded square matrix. """""" matrix = torch.zeros(ndim, ndim) for i in range(ndim): for j in range(i - bandwidth, i + bandwidth + 1): matrix[i, j % ndim] = 1 return matrix def dmp_marginal_dist( initial_dist: torch.Tensor, transition_matrix: torch.Tensor, num_steps: int, ): """"""Compute the marginal distribution of a discrete Markov process. Args: initial_dist: A tensor of shape (n, 1) representing the initial distribution. transition_matrix: A tensor of shape (n, n) representing the transition matrix. num_steps: An integer representing the number of steps to take. Returns: A tensor of shape (n, 1) representing the marginal distribution after num_steps steps. """""" marginal_dist = initial_dist for _ in range(num_steps): marginal_dist = torch.matmul(transition_matrix, marginal_dist) return marginal_dist def dmp_stationary_dist( transition_matrix: torch.Tensor, tolerance: float = 1e-5, ): """"""Compute the stationary distribution of a discrete Markov process. Args: transition_matrix: A tensor of shape (n, n) representing the transition matrix. Returns: A tensor of shape (n, 1) representing the stationary distribution. """""" n = transition_matrix.shape[0] A = (torch.eye(n) - transition_matrix).T A = torch.cat([A, torch.ones(n).reshape(1, -1)], dim=0) b = torch.zeros(n + 1, 1) b[-1] = 1 try: # get QR decomposition Q, R = torch.linalg.qr(A) soln = torch.linalg.solve(R, Q.T @ b) resid = torch.norm(A @ soln - b) / torch.norm(b) if resid > tolerance: raise torch._C._LinAlgError except torch._C._LinAlgError as err: msg = ""Stationary distribution solve failed. "" ""Are you sure the stationary distribution exists?"" raise RuntimeError(msg) from err return soln def sample_sparse_ergodic_transition_matrix( num_states: int, bandwidth: int, softmax_temp: float = 1.0, generator: Optional[torch.Generator] = None, repeats_always_possible: bool = False, ): """""" Sample a transition matrix $P$ that satisfies the ergodicity conditions - irreducibility - aperiodicity - positive recurrence Additionally, some entries of the transition matrix must be zero. """""" if softmax_temp <= 0: msg = ""Softmax temperature must be greater than 0."" raise ValueError(msg) # set generator if generator is None: generator = torch.Generator() randn_matrix = torch.randn(num_states, num_states, generator=generator) dense_transition_matrix = (randn_matrix / softmax_temp).softmax(dim=-1) # construct mask as banded matrix mask = banded_square_matrix(num_states, bandwidth).bool() # shuffle the mask mask = mask[torch.randperm(num_states, generator=generator)] if repeats_always_possible: # set diagonal entries of mask to True mask = mask | torch.eye(num_states, dtype=torch.bool) transition_matrix = torch.where(mask, dense_transition_matrix, torch.zeros_like(dense_transition_matrix)) transition_matrix = transition_matrix / transition_matrix.sum(dim=-1, keepdim=True) # check Perron-Frobenius theorem m = (num_states - 1) ** 2 + 1 # compute P^m transition_matrix_m = transition_matrix for _ in range(m - 1): transition_matrix_m = transition_matrix_m @ transition_matrix if not torch.all(transition_matrix_m > 0): msg = ""Perron-Frobenius theorem not satisfied."" raise RuntimeError(msg) return transition_matrix def sample_dmp( initial_dist: torch.Tensor, transition_matrix: torch.Tensor, num_steps: int, num_samples: int = 1, generator: Optional[torch.Generator] = None, ): samples = torch.zeros(num_samples, num_steps, dtype=torch.int64) if generator is None: generator = torch.Generator(device=initial_dist.device) samples[:, 0] = torch.multinomial( initial_dist, num_samples, replacement=True, generator=generator, ) for t in range(1, num_steps): # import pdb; pdb.set_trace() samples[:, t] = torch.multinomial( transition_matrix[samples[:, t - 1]], 1, generator=generator, ).squeeze(-1) return samples.to(initial_dist.device) def dmp_sample_log_likelihood( samples: torch.Tensor, initial_dist: torch.Tensor, transition_matrix: torch.Tensor, ): samples = samples.long() # may need to cast from float log_likelihood = 0.0 log_likelihood += torch.log(initial_dist[samples[:, 0]]) for t in range(1, samples.size(1)): log_likelihood += torch.log(transition_matrix[samples[:, t - 1], samples[:, t]]) return log_likelihood ","Python" "Biophysics","prescient-design/holo-bench","holo/test_functions/elemental/_motif.py",".py","2203","68","import math from typing import Optional import torch def motif_search( solution: torch.LongTensor, motif: torch.LongTensor, spacing: Optional[torch.LongTensor] = None, mode: str = ""present"", quantization: Optional[int] = None, ): """""" Check if a spaced motif is present in a solution. The elements of the motif should be spaced according to `spacing`. If spacing is not provided, it is assumed to be 1. If `mode` is ""count"", the number of motifs in the solution is returned. If `strict` is True, only motifs that are fully satisfied are counted, otherwise the fraction of the motif that is satisfied is returned. """""" motif_size = motif.size(-1) if quantization is None: quantization = motif_size if spacing is None: size = solution.size()[:-1] spacing = torch.ones( *size, motif_size - 1, dtype=torch.long, device=solution.device, ) else: size = solution.size()[:-1] spacing = spacing.expand(*size, -1) # convert spacing into index tensor for gather base_index = torch.cat([torch.zeros_like(spacing[..., 0]).unsqueeze(-1), spacing.cumsum(-1)], dim=-1) # slide indices out to maximum length max_base = base_index.max() num_steps = solution.size(-1) - max_base index_delta = torch.arange(num_steps, device=solution.device) expand_args = [1] * len(base_index.shape) index_delta = index_delta.view(-1, *expand_args) index = base_index + index_delta # gather solution subsequences gathered = torch.stack([torch.gather(solution, -1, step) for step in index]) # check if motif is present is_equal = gathered.eq(motif) present_count = is_equal.float().sum(-1) # if strict, only count motifs that are fully satisfied # if strict: # frac_satisfied = frac_satisfied.eq(1.0).float() quant_factor_1 = math.ceil(motif_size / quantization) quant_factor_2 = motif_size / quant_factor_1 quantized_count = present_count // quant_factor_1 / quant_factor_2 if mode == ""count"": return quantized_count.sum(0) return quantized_count.max(0).values ","Python" "Biophysics","prescient-design/holo-bench","holo/test_functions/elemental/__init__.py",".py","281","11","from ._discrete_markov_process import ( banded_square_matrix, dmp_marginal_dist, dmp_sample_log_likelihood, dmp_stationary_dist, sample_dmp, sample_sparse_ergodic_transition_matrix, ) from ._hamming_dist import hamming_dist from ._motif import motif_search ","Python" "Biophysics","prescient-design/holo-bench","holo/test_functions/elemental/_hamming_dist.py",".py","176","6","import torch def hamming_dist(x: torch.Tensor, y: torch.Tensor, dim: int = 0, keepdim: bool = False) -> torch.Tensor: return (x - y).pow(2).sum(dim=dim, keepdim=keepdim) ","Python" "Biophysics","prescient-design/holo-bench","scripts/benchmark_optimizer.py",".py","2709","82","import random import hydra import numpy as np import torch # ruff: noqa: I001 import wandb from omegaconf import OmegaConf from holo.logging import wandb_setup @hydra.main(version_base=None, config_path=""../config/hydra"", config_name=""benchmark_optimizer"") def main(cfg): if cfg.optimizer.mutation_prob is None: cfg.optimizer.mutation_prob = 1.1 / cfg.test_function.dim if cfg.optimizer.recombine_prob is None: cfg.optimizer.recombine_prob = 1.1 / cfg.test_function.dim wandb_setup(cfg) random.seed(cfg.random_seed) np.random.seed(cfg.random_seed) torch.manual_seed(cfg.random_seed) print(OmegaConf.to_yaml(cfg, resolve=True)) dtype = torch.double if cfg.dtype == ""float64"" else torch.float device = torch.device(""cuda"" if torch.cuda.is_available() else ""cpu"") test_function = hydra.utils.instantiate(cfg.test_function) test_function = test_function.to(device, dtype) initial_solution = test_function.initial_solution().to(dtype) params = [torch.nn.Parameter(initial_solution)] print(f""Test function: {test_function}"") known_soln = test_function.optimal_solution() opt_val = test_function.optimal_value print(f""Known optimal solution: {known_soln}"") def closure(param_list): return test_function(param_list[0]) vocab = list(range(test_function.num_states)) optimizer = hydra.utils.instantiate(cfg.optimizer, params=params, vocab=vocab) print(f""Searching for solution with optimal value {opt_val}..."") cumulative_regret = 0.0 best_loss = float(""inf"") for t_idx in range(cfg.num_opt_steps): loss = optimizer.step(closure) if loss < best_loss: best_loss = loss.item() best_params = [p.data.clone() for p in params] simple_regret_best = best_loss - opt_val simple_regret_last = loss - opt_val cumulative_regret += best_loss - opt_val # frac_particles_feasible = optimizer.particle_loss.gt(-float(""inf"")).float().mean().item() frac_particles_feasible = optimizer.particle_loss.lt(float(""inf"")).float().mean().item() metrics = { ""simple_regret_best"": simple_regret_best, ""simple_regret_last"": simple_regret_last, ""cumulative_regret"": cumulative_regret, ""frac_particles_feasible"": frac_particles_feasible, ""timestep"": t_idx, } stop = simple_regret_best == 0 if t_idx % cfg.log_interval == 0 or stop: wandb.log(metrics) print(f""Step {t_idx}: Loss {loss}"") if stop: break print(f""Best solution: {best_params[0].long()}"") if __name__ == ""__main__"": main() ","Python" "Biophysics","prescient-design/holo-bench","tests/optim/test_discrete_evolution.py",".py","3071","117","import torch from holo.optim import DiscreteEvolution from holo.test_functions.closed_form import Ehrlich def test_discrete_evolution_single_param(): seq_len = 3 vocab_size = 5 num_steps = 20 mutation_prob = 0.2 recombine_prob = 0.5 params = [ torch.nn.Parameter( torch.tensor([vocab_size - 1] * seq_len).float(), ) ] vocab = list(range(vocab_size)) optimizer = DiscreteEvolution(params, vocab, mutation_prob=mutation_prob, recombine_prob=recombine_prob) def closure(param_list): return param_list[0].sum(-1) for _ in range(num_steps): loss = optimizer.step(closure) assert torch.allclose(loss, torch.zeros_like(loss)) assert torch.allclose(params[0].data, torch.zeros_like(params[0].data)) def test_discrete_evolution_param_groups(): seq_lens = [1, 3] vocab_size = 5 num_steps = 20 param_groups = [ { ""params"": [ torch.nn.Parameter( torch.tensor([vocab_size - 1] * seq_lens[0]).float(), ) ], ""mutation_prob"": 0.9, ""recombine_prob"": 0.1, }, { ""params"": [ torch.nn.Parameter( torch.tensor([vocab_size - 1] * seq_lens[1]).float(), ) ], ""mutation_prob"": 0.1, ""recombine_prob"": 0.9, }, ] vocab = list(range(vocab_size)) optimizer = DiscreteEvolution(param_groups, vocab) def closure(param_list): return sum(p.sum(-1) for p in param_list) for _ in range(num_steps): loss = optimizer.step(closure) assert torch.allclose(loss, torch.zeros_like(loss)) param_list = [p.data for group in param_groups for p in group[""params""]] cat_param = torch.cat(param_list, dim=-1) assert torch.allclose(cat_param, torch.zeros_like(cat_param)) def test_ehrlich_optimization(): num_states = 32 num_steps = 128 motif_length = 4 noise_std = 0.0 random_seed = 0 ehrlich = Ehrlich( num_states=num_states, dim=num_steps, num_motifs=1, motif_length=motif_length, noise_std=noise_std, negate=True, random_seed=random_seed, ) # initialization initial_solution = ehrlich.initial_solution() def closure(param_list): return ehrlich(param_list[0]) params = [torch.nn.Parameter(initial_solution.float())] mutation_prob = 1 / num_steps recombine_prob = 1 / num_steps survival_quantile = 0.01 num_particles = 4096 optimizer = DiscreteEvolution( params, vocab=list(range(num_states)), mutation_prob=mutation_prob, recombine_prob=recombine_prob, survival_quantile=survival_quantile, num_particles=num_particles, ) num_opt_steps = 256 best = float(""inf"") for t in range(num_opt_steps): loss = optimizer.step(closure) if loss < best: best = loss.item() assert best == -1.0 ","Python" "Biophysics","prescient-design/holo-bench","tests/test_functions/lookup/test_trpb.py",".py","5269","138","import os from typing import Dict, List, Tuple import numpy as np import pytest import torch from holo.test_functions.lookup import TRPBLookup # Mock implementation that doesn't download data class MockTRPBLookup(TRPBLookup): def _load_data(self) -> Tuple[Dict[str, float], np.ndarray, List[str]]: """"""Create synthetic data for testing instead of downloading."""""" np.random.seed(42) # For reproducibility lookup_dict = {} # Add wildtype with high score lookup_dict[self.wildtype_sequence] = 0.9 # Add some random sequences for _ in range(100): seq = """".join(np.random.choice(self.alphabet, size=self.dim)) if seq not in lookup_dict: lookup_dict[seq] = np.random.uniform(0.0, 1.0) # Sort sequences by score seqs = list(lookup_dict.keys()) scores = np.array([lookup_dict[seq] for seq in seqs]) sorted_indices = np.argsort(scores)[::-1] sorted_scores = scores[sorted_indices] sorted_seqs = [seqs[i] for i in sorted_indices] return lookup_dict, sorted_scores, sorted_seqs class TestTRPBLookup: @pytest.fixture def trpb_function(self): """"""Create a TRPBLookup instance for testing."""""" # Use mock implementation in CI is_ci = os.environ.get(""CI"", ""false"").lower() == ""true"" if is_ci: return MockTRPBLookup() # Use real implementation locally return TRPBLookup() def test_initialization(self, trpb_function): """"""Test that the function initializes properly."""""" assert trpb_function.dim == 4 assert trpb_function.alphabet_size == 20 assert """".join(trpb_function.alphabet) == ""ARNDCQEGHILKMFPSTWYV"" assert len(trpb_function._lookup_dict) > 0 assert trpb_function._optimal_value is not None assert len(trpb_function._optimizers) > 0 def test_evaluate_true(self, trpb_function): """"""Test function evaluation."""""" # Create a batch of random inputs batch_size = 5 X = trpb_function.random_solution(batch_size) # Evaluate y = trpb_function.evaluate_true(X) # Check output shape assert y.shape == (batch_size,) # Check output type assert y.dtype == torch.float # Test with 3D input X_3d = X.unsqueeze(1) # (batch_size, dim) -> (batch_size, 1, dim) y_3d = trpb_function.evaluate_true(X_3d) assert y_3d.shape == (batch_size,) def test_random_solution(self, trpb_function): """"""Test random solution generation."""""" # Single solution x_single = trpb_function.random_solution() assert x_single.shape == (trpb_function.dim,) assert torch.all((x_single >= 0) & (x_single < trpb_function.alphabet_size)) # Multiple solutions n = 10 x_multiple = trpb_function.random_solution(n) assert x_multiple.shape == (n, trpb_function.dim) assert torch.all((x_multiple >= 0) & (x_multiple < trpb_function.alphabet_size)) def test_initial_solution(self, trpb_function): """"""Test initial solution generation."""""" # Single solution x_single = trpb_function.initial_solution() assert x_single.shape == (trpb_function.dim,) assert torch.all((x_single >= 0) & (x_single < trpb_function.alphabet_size)) # Multiple solutions n = 10 x_multiple = trpb_function.initial_solution(n) assert x_multiple.shape == (n, trpb_function.dim) assert torch.all((x_multiple >= 0) & (x_multiple < trpb_function.alphabet_size)) def test_optimal_solution(self, trpb_function): """"""Test optimal solution retrieval."""""" x_opt = trpb_function.optimal_solution() assert x_opt is not None assert x_opt.shape == (trpb_function.dim,) # The optimal solution should achieve the optimal value y_opt = trpb_function.evaluate_true(x_opt.unsqueeze(0)) assert torch.isclose(y_opt[0], torch.tensor(trpb_function._optimal_value)) def test_seq_to_tensor_conversion(self, trpb_function): """"""Test conversion between sequence and tensor representations."""""" # Test wildtype sequence conversion seq = trpb_function.wildtype_sequence tensor = trpb_function._seq_to_tensor(seq) assert tensor.shape == (trpb_function.dim,) # Convert back to sequence seq_back = trpb_function._tensor_to_seq(tensor) assert seq_back == seq def test_out_of_vocabulary_sequence(self, trpb_function): """"""Test handling of sequences not in the lookup table."""""" # Create a batch with a sequence containing indices that, when converted # to a sequence, will likely not be in the lookup table X = torch.zeros(1, trpb_function.dim, device=trpb_function._device) # Evaluate (should return -inf for unknown sequences) y = trpb_function.evaluate_true(X) # Either the sequence is in the lookup table (unlikely) or it returns -inf if trpb_function._tensor_to_seq(X[0]) not in trpb_function._lookup_dict: assert y[0] == -float(""inf"") if __name__ == ""__main__"": pytest.main([""-xvs"", __file__]) ","Python" "Biophysics","prescient-design/holo-bench","tests/test_functions/lookup/test_tfbind8.py",".py","4890","129","import os from typing import Dict, List, Tuple import numpy as np import pytest import torch from holo.test_functions.lookup import TFBIND8Lookup # Mock implementation that doesn't download data class MockTFBIND8Lookup(TFBIND8Lookup): def _load_data(self) -> Tuple[Dict[str, float], np.ndarray, List[str]]: """"""Create synthetic data for testing instead of downloading."""""" np.random.seed(42) # For reproducibility lookup_dict = {} # Create some random sequences with scores for _ in range(100): seq = """".join(np.random.choice(self.alphabet, size=self.dim)) if seq not in lookup_dict: lookup_dict[seq] = np.random.uniform(0.0, 1.0) # Add a few optimal sequences with maximum score max_score = 1.0 optimal_seqs = ["""".join(np.random.choice(self.alphabet, size=self.dim)) for _ in range(2)] for seq in optimal_seqs: lookup_dict[seq] = max_score # Sort sequences by score seqs = list(lookup_dict.keys()) scores = np.array([lookup_dict[seq] for seq in seqs]) sorted_indices = np.argsort(scores)[::-1] sorted_scores = scores[sorted_indices] sorted_seqs = [seqs[i] for i in sorted_indices] return lookup_dict, sorted_scores, sorted_seqs class TestTFBIND8Lookup: @pytest.fixture def tfbind8_function(self): """"""Create a TFBIND8Lookup instance for testing."""""" # Use mock implementation in CI is_ci = os.environ.get(""CI"", ""false"").lower() == ""true"" if is_ci: return MockTFBIND8Lookup() # Use real implementation locally return TFBIND8Lookup() def test_initialization(self, tfbind8_function): """"""Test that the function initializes properly."""""" assert tfbind8_function.dim == 8 assert tfbind8_function.num_states == 4 assert tfbind8_function.alphabet == [""A"", ""C"", ""G"", ""T""] assert len(tfbind8_function._lookup_dict) > 0 assert tfbind8_function._optimal_value is not None assert len(tfbind8_function._optimizers) >= 1 def test_evaluate_true(self, tfbind8_function): """"""Test function evaluation."""""" # Create a batch of random inputs batch_size = 5 X = tfbind8_function.random_solution(batch_size) # Evaluate y = tfbind8_function.evaluate_true(X) # Check output shape assert y.shape == (batch_size,) # Check output type assert y.dtype == torch.float # Test with 3D input X_3d = X.unsqueeze(1) # (batch_size, dim) -> (batch_size, 1, dim) y_3d = tfbind8_function.evaluate_true(X_3d) assert y_3d.shape == (batch_size,) def test_random_solution(self, tfbind8_function): """"""Test random solution generation."""""" # Single solution x_single = tfbind8_function.random_solution() assert x_single.shape == (tfbind8_function.dim,) assert torch.all((x_single >= 0) & (x_single < tfbind8_function.num_states)) # Multiple solutions n = 10 x_multiple = tfbind8_function.random_solution(n) assert x_multiple.shape == (n, tfbind8_function.dim) assert torch.all((x_multiple >= 0) & (x_multiple < tfbind8_function.num_states)) def test_initial_solution(self, tfbind8_function): """"""Test initial solution generation."""""" # Single solution x_single = tfbind8_function.initial_solution() assert x_single.shape == (tfbind8_function.dim,) assert torch.all((x_single >= 0) & (x_single < tfbind8_function.num_states)) # Multiple solutions n = 10 x_multiple = tfbind8_function.initial_solution(n) assert x_multiple.shape == (n, tfbind8_function.dim) assert torch.all((x_multiple >= 0) & (x_multiple < tfbind8_function.num_states)) def test_optimal_solution(self, tfbind8_function): """"""Test optimal solution retrieval."""""" x_opt = tfbind8_function.optimal_solution() assert x_opt.shape == (tfbind8_function.dim,) # The optimal solution should achieve the optimal value y_opt = tfbind8_function.evaluate_true(x_opt.unsqueeze(0)) assert torch.isclose(y_opt[0], torch.tensor(tfbind8_function._optimal_value)) def test_to_device(self, tfbind8_function): """"""Test moving the function to a device."""""" # This test doesn't actually move to CUDA since it may not be available # but it tests the to() method functionality func_cpu = tfbind8_function.to(torch.device(""cpu""), torch.float32) assert func_cpu._device == torch.device(""cpu"") # Generate a solution and check device x = func_cpu.random_solution() assert x.device == torch.device(""cpu"") if __name__ == ""__main__"": pytest.main([""-xvs"", __file__]) ","Python" "Biophysics","prescient-design/holo-bench","tests/test_functions/lookup/test_dhfr.py",".py","5252","138","import os from typing import Dict, List, Tuple import numpy as np import pytest import torch from holo.test_functions.lookup import DHFRLookup # Mock implementation that doesn't download data class MockDHFRLookup(DHFRLookup): def _load_data(self) -> Tuple[Dict[str, float], np.ndarray, List[str]]: """"""Create synthetic data for testing instead of downloading."""""" np.random.seed(42) # For reproducibility lookup_dict = {} # Add wildtype with high score lookup_dict[self.wildtype_sequence] = 0.9 # Add some random sequences for _ in range(100): seq = """".join(np.random.choice(self.alphabet, size=self.dim)) if seq not in lookup_dict: lookup_dict[seq] = np.random.uniform(0.0, 1.0) # Sort sequences by score seqs = list(lookup_dict.keys()) scores = np.array([lookup_dict[seq] for seq in seqs]) sorted_indices = np.argsort(scores)[::-1] sorted_scores = scores[sorted_indices] sorted_seqs = [seqs[i] for i in sorted_indices] return lookup_dict, sorted_scores, sorted_seqs class TestDHFRLookup: @pytest.fixture def dhfr_function(self): """"""Create a DHFRLookup instance for testing."""""" # Use mock implementation in CI is_ci = os.environ.get(""CI"", ""false"").lower() == ""true"" if is_ci: return MockDHFRLookup() # Use real implementation locally return DHFRLookup() def test_initialization(self, dhfr_function): """"""Test that the function initializes properly."""""" assert dhfr_function.dim == 9 assert dhfr_function.alphabet_size == 4 assert """".join(dhfr_function.alphabet) == ""ACGT"" assert len(dhfr_function._lookup_dict) > 0 assert dhfr_function._optimal_value is not None assert len(dhfr_function._optimizers) > 0 def test_evaluate_true(self, dhfr_function): """"""Test function evaluation."""""" # Create a batch of random inputs batch_size = 5 X = dhfr_function.random_solution(batch_size) # Evaluate y = dhfr_function.evaluate_true(X) # Check output shape assert y.shape == (batch_size,) # Check output type assert y.dtype == torch.float # Test with 3D input X_3d = X.unsqueeze(1) # (batch_size, dim) -> (batch_size, 1, dim) y_3d = dhfr_function.evaluate_true(X_3d) assert y_3d.shape == (batch_size,) def test_random_solution(self, dhfr_function): """"""Test random solution generation."""""" # Single solution x_single = dhfr_function.random_solution() assert x_single.shape == (dhfr_function.dim,) assert torch.all((x_single >= 0) & (x_single < dhfr_function.alphabet_size)) # Multiple solutions n = 10 x_multiple = dhfr_function.random_solution(n) assert x_multiple.shape == (n, dhfr_function.dim) assert torch.all((x_multiple >= 0) & (x_multiple < dhfr_function.alphabet_size)) def test_initial_solution(self, dhfr_function): """"""Test initial solution generation."""""" # Single solution x_single = dhfr_function.initial_solution() assert x_single.shape == (dhfr_function.dim,) assert torch.all((x_single >= 0) & (x_single < dhfr_function.alphabet_size)) # Multiple solutions n = 10 x_multiple = dhfr_function.initial_solution(n) assert x_multiple.shape == (n, dhfr_function.dim) assert torch.all((x_multiple >= 0) & (x_multiple < dhfr_function.alphabet_size)) def test_optimal_solution(self, dhfr_function): """"""Test optimal solution retrieval."""""" x_opt = dhfr_function.optimal_solution() assert x_opt is not None assert x_opt.shape == (dhfr_function.dim,) # The optimal solution should achieve the optimal value y_opt = dhfr_function.evaluate_true(x_opt.unsqueeze(0)) assert torch.isclose(y_opt[0], torch.tensor(dhfr_function._optimal_value)) def test_seq_to_tensor_conversion(self, dhfr_function): """"""Test conversion between sequence and tensor representations."""""" # Test wildtype sequence conversion seq = dhfr_function.wildtype_sequence tensor = dhfr_function._seq_to_tensor(seq) assert tensor.shape == (dhfr_function.dim,) # Convert back to sequence seq_back = dhfr_function._tensor_to_seq(tensor) assert seq_back == seq def test_out_of_vocabulary_sequence(self, dhfr_function): """"""Test handling of sequences not in the lookup table."""""" # Create a batch with a sequence containing indices that, when converted # to a sequence, will likely not be in the lookup table X = torch.zeros(1, dhfr_function.dim, device=dhfr_function._device) # Evaluate (should return -inf for unknown sequences) y = dhfr_function.evaluate_true(X) # Either the sequence is in the lookup table (unlikely) or it returns -inf if dhfr_function._tensor_to_seq(X[0]) not in dhfr_function._lookup_dict: assert y[0] == -float(""inf"") if __name__ == ""__main__"": pytest.main([""-xvs"", __file__]) ","Python" "Biophysics","prescient-design/holo-bench","tests/test_functions/closed_form/test_motif.py",".py","1260","57","import torch from holo.test_functions.elemental import motif_search def test_motif_search(): cases = torch.tensor( [ [0, 1, 2, 3, 4], [0, 1, 2, 4, 5], [0, 1, 4, 5, 6], [0, 4, 5, 6, 7], [4, 5, 6, 7, 8], ] ) motif = cases[0, :-1] res = motif_search( solution=cases, motif=motif, spacing=None, mode=""present"", quantization=1, ) assert torch.all(res == torch.tensor([1.0, 0.0, 0.0, 0.0, 0.0])) res = motif_search( solution=cases, motif=motif, spacing=None, mode=""present"", quantization=4, ) assert torch.all(res == torch.tensor([1.0, 0.75, 0.5, 0.25, 0.0])) def test_spaced_motif_search(): cases = torch.tensor( [ [0, 1, 2, 3, 4], [0, 1, 2, 4, 5], [0, 1, 4, 5, 6], [0, 4, 5, 6, 7], [4, 5, 6, 7, 8], ] ) motif = cases[0, ::2] spacing = torch.tensor([2, 2]) res = motif_search( solution=cases, motif=motif, spacing=spacing, mode=""present"", quantization=1, ) assert torch.all(res == torch.tensor([1.0, 0.0, 0.0, 0.0, 0.0])) ","Python" "Biophysics","prescient-design/holo-bench","tests/test_functions/closed_form/test_discrete_markov_process.py",".py","2698","80","import torch from holo.test_functions.elemental import ( banded_square_matrix, dmp_sample_log_likelihood, dmp_stationary_dist, sample_dmp, sample_sparse_ergodic_transition_matrix, ) def test_banded_square_matrix(): ndim = 5 bandwidth = 1 matrix = banded_square_matrix(ndim, bandwidth) expected_matrix = torch.tensor( [ [1, 1, 0, 0, 1], [1, 1, 1, 0, 0], [0, 1, 1, 1, 0], [0, 0, 1, 1, 1], [1, 0, 0, 1, 1], ] ).float() assert torch.allclose(matrix, expected_matrix) def test_dmp_sample_log_likelihood(): ndim = 5 bandwidth = 1 num_steps = 11 num_samples = 7 random_seed = 0 initial_dist = torch.ones(ndim) / ndim generator = torch.Generator().manual_seed(random_seed) transition_matrix = sample_sparse_ergodic_transition_matrix(ndim, bandwidth, generator=generator) samples = sample_dmp(initial_dist, transition_matrix, num_steps, num_samples, generator=generator) log_likelihood = dmp_sample_log_likelihood(samples, initial_dist, transition_matrix) assert log_likelihood.shape == (num_samples,) assert torch.all(log_likelihood > -float(""inf"")) def test_dmp_stationary_dist(): ndim = 5 bandwidth = 1 random_seed = 1 generator = torch.Generator().manual_seed(random_seed) transition_matrix = sample_sparse_ergodic_transition_matrix(ndim, bandwidth, generator=generator) stationary_dist = dmp_stationary_dist(transition_matrix) total_prob = stationary_dist.sum() assert stationary_dist.size() == (ndim, 1) assert torch.allclose(total_prob, torch.tensor(1.0)) apply_transition = stationary_dist.t() @ transition_matrix assert torch.allclose(apply_transition, stationary_dist.t()) def test_sample_sparse_ergodic_transition_matrix(): ndim = 5 bandwidth = 1 random_seed = 2 generator = torch.Generator().manual_seed(random_seed) transition_matrix = sample_sparse_ergodic_transition_matrix(ndim, bandwidth, generator=generator) assert transition_matrix.size() == (ndim, ndim) assert torch.allclose(transition_matrix.sum(-1), torch.ones(ndim)) def test_sample_dmp(): ndim = 5 bandwidth = 1 num_steps = 11 num_samples = 7 random_seed = 3 generator = torch.Generator().manual_seed(random_seed) initial_dist = torch.ones(ndim) / ndim transition_matrix = sample_sparse_ergodic_transition_matrix(ndim, bandwidth, generator=generator) samples = sample_dmp(initial_dist, transition_matrix, num_steps, num_samples, generator=generator) assert samples.size() == (num_samples, num_steps) assert torch.all(samples.lt(ndim)) ","Python" "Biophysics","prescient-design/holo-bench","tests/test_functions/closed_form/test_ehrlich.py",".py","2539","95","import pytest import torch from holo.test_functions.closed_form import ( Ehrlich, ) from holo.test_functions.elemental import ( dmp_stationary_dist, sample_dmp, ) def test_ehrlich_single_motif(): num_states = 32 num_steps = 256 motif_length = 8 noise_std = 0.0 negate = False random_seed = 0 ehrlich = Ehrlich( num_states=num_states, dim=num_steps, motif_length=motif_length, noise_std=noise_std, negate=negate, random_seed=random_seed, ) num_samples = 4 stationary_dist = dmp_stationary_dist(ehrlich.transition_matrix) generator = torch.Generator().manual_seed(random_seed) dmp_samples = sample_dmp( initial_dist=stationary_dist.squeeze(), transition_matrix=ehrlich.transition_matrix, num_steps=ehrlich.dim, num_samples=num_samples, generator=generator, ) f = ehrlich.evaluate_true(dmp_samples) assert torch.all(f >= 0.0) assert torch.all(f <= 1.0) unif_samples = torch.randint(0, num_states, (num_samples, num_steps)) f = ehrlich.evaluate_true(unif_samples) assert torch.allclose(f, torch.full_like(f, -float(""inf""))) def test_ehrlich_multi_motif(): num_states = 32 num_steps = 256 motif_length = 8 random_seed = 0 ehrlich = Ehrlich( num_states=num_states, dim=num_steps, num_motifs=4, motif_length=motif_length, random_seed=random_seed, ) num_samples = 4 stationary_dist = dmp_stationary_dist(ehrlich.transition_matrix) generator = torch.Generator().manual_seed(random_seed) dmp_samples = sample_dmp( initial_dist=stationary_dist.squeeze(), transition_matrix=ehrlich.transition_matrix, num_steps=ehrlich.dim, num_samples=num_samples, generator=generator, ) f = ehrlich.evaluate_true(dmp_samples) assert torch.all(f >= 0.0) assert torch.all(f <= 1.0) unif_samples = torch.randint(0, num_states, (num_samples, num_steps)) f = ehrlich.evaluate_true(unif_samples) assert torch.allclose(f, torch.full_like(f, -float(""inf""))) def test_invalid_ehrlich(): with pytest.raises(ValueError): Ehrlich( num_states=32, dim=2, num_motifs=1, motif_length=8, ) with pytest.raises(ValueError): Ehrlich( num_states=32, dim=16, num_motifs=4, motif_length=8, random_seed=0, ) ","Python" "Biophysics","maxscheurer/pycontact","setup.py",".py","2253","58",""""""" pycontact setup by Maximilian Scheurer, Peter Rodenkirch """""" from setuptools import setup, find_packages from setuptools.extension import Extension from Cython.Distutils import build_ext from Cython.Build import cythonize extensions = [Extension(""PyContact.cy_modules.cy_gridsearch"", [""PyContact/cy_modules/cy_gridsearch.pyx""], language=""c++"", include_dirs=[""."", ""PyContact/cy_modules/src""], extra_compile_args=[""-std=c++0x""]), ] setup( name='pycontact', version='1.0.5', description='PyContact', long_description='Tool for analysis of non-covalent interactions in MD trajectories', url='https://github.com/maxscheurer/pycontact', author='Maximilian Scheurer, Peter Rodenkirch', author_email='mscheurer@ks.uiuc.edu', license='GPLv3', classifiers=[ 'Development Status :: 5 - Production/Stable', 'Intended Audience :: Science/Research', 'Topic :: Scientific/Engineering', 'License :: OSI Approved :: GNU General Public License v3 (GPLv3)', 'Programming Language :: Python :: 3.6', ], keywords='computational biophysics simulation biology bioinformatics visualization protein biomolecules dna', package_dir={'PyContact': 'PyContact'}, packages=find_packages(), python_requires="">=3.6"", setup_requires=['cython'], install_requires=['numpy >= 1.16', 'matplotlib', 'mdanalysis >= 0.20.0', 'cython', 'seaborn', 'scipy', 'PyQt5'], cmdclass={'build_ext': build_ext}, ext_modules=cythonize(extensions), package_data={'PyContact': ['exampleData/defaultsession', 'exampleData/*.psf', 'exampleData/*.pdb', 'exampleData/*.dcd', 'exampleData/*.tpr', 'exampleData/*.xtc', 'gui/*.tcl', 'db/aa.db', 'cy_modules/*.pyx', 'cy_modules/src/*']}, entry_points={ 'console_scripts': [ 'pycontact=PyContact.pycontact:main', ], }, ) ","Python" "Biophysics","maxscheurer/pycontact","testing/profiling.py",".py","255","8","from PyContact.core.ContactAnalyzer import * from PyContact.exampleData.datafiles import DCD, PSF import MDAnalysis as mda dcdfile = DCD psffile = PSF analyzer = Analyzer(psffile, dcdfile, 5.0, 2.5, 120, ""segid RN11"", ""segid UBQ"") analyzer.runFrameScan() ","Python" "Biophysics","maxscheurer/pycontact","testing/contact2text.py",".py","288","5","from PyContact.core.Scripting import PyContactJob, JobConfig job = PyContactJob(""PyContact/exampleData/rpn11_ubq.psf"", ""PyContact/exampleData/rpn11_ubq.dcd"", ""test"", JobConfig(5.0, 2.5, 120, [0,0,1,1,0], [0,0,1,1,0], ""segid RN11"", ""segid UBQ"")) job.runJob(1) job.writeContactDataToFile() ","Python" "Biophysics","maxscheurer/pycontact","testing/check.py",".py","468","24","import pickle s = pickle.load(open(""single_results.dat"")) print len(s) count = 0 for element in s: for c in element: count += len(c.hbondinfo) if len(c.hbondinfo) > 0: c.hbondinfo[0].toString() print count p = pickle.load(open(""parallel_results.dat"")) print len(s) count = 0 for element in p: for c in element: count += len(c.hbondinfo) if len(c.hbondinfo) > 0: c.hbondinfo[0].toString() print count ","Python" "Biophysics","maxscheurer/pycontact","testing/pca.py",".py","1308","44","from PyContact.core.Scripting import (PyContactJob, JobConfig) from PyContact.core.ContactFilters import ScoreFilter import numpy as np from numpy import linalg as LA import matplotlib.pyplot as plt from sklearn.decomposition import PCA from sklearn.manifold import TSNE jobAllMD = PyContactJob(""./PyContact/exampleData/rpn11_ubq_interface-ionized.psf"",""./PyContact/exampleData/short.dcd"", ""test"", JobConfig(5.0, 2.5, 120, [0,0,0,1,1,0], [0,0,0,1,1,0], ""segid UBQ"", ""segid RN11"")) jobAllMD.runJob(1) # jobAllMD.writeSessionToFile() contacts = jobAllMD.analyzer.finalAccumulatedContacts filter = ScoreFilter(""score"", ""greater"", 0.0, u""Median"") contacts = filter.filterContacts(contacts) N = len(contacts) frames = len(jobAllMD.analyzer.contactResults) print(""frms:"", frames) covMatrix = np.zeros((N, N)) idx1 = 0 r_vec = np.zeros((N, frames)) r_names = np.zeros(N).tolist() for c1 in contacts: for f in range(frames): r_vec[idx1, f] = c1.scoreArray[f] r_names[idx1] = c1.human_readable_title() idx1 += 1 pca = PCA(n_components=10) components = pca.fit_transform(r_vec) # print(components) # plt.plot(components[:,0], components[:,1], 'o') # plt.show() model = TSNE(n_components=2) results = model.fit_transform(components) plt.plot(results[:,0], results[:,1], 'o') plt.show() ","Python" "Biophysics","maxscheurer/pycontact","testing/tableview.py",".py","4571","121","import operator from PyQt5.QtCore import QAbstractTableModel,Qt,pyqtSlot from PyQt5.QtGui import * from PyQt5.QtWidgets import * class MyWindow(QWidget): def __init__(self, data_list, header, *args): QWidget.__init__(self, *args) # setGeometry(x_pos, y_pos, width, height) self.setGeometry(300, 200, 570, 450) self.setWindowTitle(""Click on column title to sort"") table_model = MyTableModel(self, data_list, header) table_view = QTableView() table_view.setModel(table_model) # set font font = QFont(""Courier New"", 14) table_view.setFont(font) # set column width to fit contents (set font first!) table_view.resizeColumnsToContents() # enable sorting table_view.setSortingEnabled(True) layout = QVBoxLayout(self) layout.addWidget(table_view) self.setLayout(layout) class MyTableModel(QAbstractTableModel): def __init__(self, parent, mylist, header, *args): QAbstractTableModel.__init__(self, parent, *args) self.mylist = mylist self.header = header def rowCount(self, parent): return len(self.mylist) def columnCount(self, parent): return len(self.mylist[0]) def data(self, index, role): if not index.isValid(): return None elif role != Qt.DisplayRole: return None return self.mylist[index.row()][index.column()] def headerData(self, col, orientation, role): if orientation == Qt.Horizontal and role == Qt.DisplayRole: return self.header[col] return None @pyqtSlot() def sort(self, col, order): """"""sort table by given column number col"""""" # self.emit(SIGNAL(""layoutAboutToBeChanged()"")) self.layoutAboutToBeChanged() self.mylist = sorted(self.mylist, key=operator.itemgetter(col)) if order == Qt.DescendingOrder: self.mylist.reverse() # self.emit(SIGNAL(""layoutChanged()"")) self.layoutChanged() # the solvent data ... header = ['Solvent Name', ' BP (deg C)', ' MP (deg C)', ' Density (g/ml)'] # use numbers for numeric data to sort properly data_list = [ ('ACETIC ACID', 117.9, 16.7, 1.049), ('ACETIC ANHYDRIDE', 140.1, -73.1, 1.087), ('ACETONE', 56.3, -94.7, 0.791), ('ACETONITRILE', 81.6, -43.8, 0.786), ('ANISOLE', 154.2, -37.0, 0.995), ('BENZYL ALCOHOL', 205.4, -15.3, 1.045), ('BENZYL BENZOATE', 323.5, 19.4, 1.112), ('BUTYL ALCOHOL NORMAL', 117.7, -88.6, 0.81), ('BUTYL ALCOHOL SEC', 99.6, -114.7, 0.805), ('BUTYL ALCOHOL TERTIARY', 82.2, 25.5, 0.786), ('CHLOROBENZENE', 131.7, -45.6, 1.111), ('CYCLOHEXANE', 80.7, 6.6, 0.779), ('CYCLOHEXANOL', 161.1, 25.1, 0.971), ('CYCLOHEXANONE', 155.2, -47.0, 0.947), ('DICHLOROETHANE 1 2', 83.5, -35.7, 1.246), ('DICHLOROMETHANE', 39.8, -95.1, 1.325), ('DIETHYL ETHER', 34.5, -116.2, 0.715), ('DIMETHYLACETAMIDE', 166.1, -20.0, 0.937), ('DIMETHYLFORMAMIDE', 153.3, -60.4, 0.944), ('DIMETHYLSULFOXIDE', 189.4, 18.5, 1.102), ('DIOXANE 1 4', 101.3, 11.8, 1.034), ('DIPHENYL ETHER', 258.3, 26.9, 1.066), ('ETHYL ACETATE', 77.1, -83.9, 0.902), ('ETHYL ALCOHOL', 78.3, -114.1, 0.789), ('ETHYL DIGLYME', 188.2, -45.0, 0.906), ('ETHYLENE CARBONATE', 248.3, 36.4, 1.321), ('ETHYLENE GLYCOL', 197.3, -13.2, 1.114), ('FORMIC ACID', 100.6, 8.3, 1.22), ('HEPTANE', 98.4, -90.6, 0.684), ('HEXAMETHYL PHOSPHORAMIDE', 233.2, 7.2, 1.027), ('HEXANE', 68.7, -95.3, 0.659), ('ISO OCTANE', 99.2, -107.4, 0.692), ('ISOPROPYL ACETATE', 88.6, -73.4, 0.872), ('ISOPROPYL ALCOHOL', 82.3, -88.0, 0.785), ('METHYL ALCOHOL', 64.7, -97.7, 0.791), ('METHYL ETHYLKETONE', 79.6, -86.7, 0.805), ('METHYL ISOBUTYL KETONE', 116.5, -84.0, 0.798), ('METHYL T-BUTYL ETHER', 55.5, -10.0, 0.74), ('METHYLPYRROLIDINONE N', 203.2, -23.5, 1.027), ('MORPHOLINE', 128.9, -3.1, 1.0), ('NITROBENZENE', 210.8, 5.7, 1.208), ('NITROMETHANE', 101.2, -28.5, 1.131), ('PENTANE', 36.1, ' -129.7', 0.626), ('PHENOL', 181.8, 40.9, 1.066), ('PROPANENITRILE', 97.1, -92.8, 0.782), ('PROPIONIC ACID', 141.1, -20.7, 0.993), ('PROPIONITRILE', 97.4, -92.8, 0.782), ('PROPYLENE GLYCOL', 187.6, -60.1, 1.04), ('PYRIDINE', 115.4, -41.6, 0.978), ('SULFOLANE', 287.3, 28.5, 1.262), ('TETRAHYDROFURAN', 66.2, -108.5, 0.887), ('TOLUENE', 110.6, -94.9, 0.867), ('TRIETHYL PHOSPHATE', 215.4, -56.4, 1.072), ('TRIETHYLAMINE', 89.5, -114.7, 0.726), ('TRIFLUOROACETIC ACID', 71.8, -15.3, 1.489), ('WATER', 100.0, 0.0, 1.0), ('XYLENES', 139.1, -47.8, 0.86) ] app = QApplication([]) win = MyWindow(data_list, header) win.show() app.exec_() ","Python" "Biophysics","maxscheurer/pycontact","testing/cython/setup.py",".py","309","10","from distutils.core import setup from distutils.extension import Extension from Cython.Distutils import build_ext setup( cmdclass = {'build_ext': build_ext}, ext_modules = [Extension(""wrap_cy"",[""wrap.pyx""],language=""c++"", extra_compile_args=[""-std=c++11""], extra_link_args=[""-std=c++11""]), ]) ","Python" "Biophysics","maxscheurer/pycontact","testing/cython/wrap.cpp",".cpp","731274","20120","/* 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Py_HUGE_VAL HUGE_VAL #endif #ifdef PYPY_VERSION #define CYTHON_COMPILING_IN_PYPY 1 #define CYTHON_COMPILING_IN_PYSTON 0 #define CYTHON_COMPILING_IN_CPYTHON 0 #undef CYTHON_USE_TYPE_SLOTS #define CYTHON_USE_TYPE_SLOTS 0 #undef CYTHON_USE_ASYNC_SLOTS #define CYTHON_USE_ASYNC_SLOTS 0 #undef CYTHON_USE_PYLIST_INTERNALS #define CYTHON_USE_PYLIST_INTERNALS 0 #undef CYTHON_USE_UNICODE_INTERNALS #define CYTHON_USE_UNICODE_INTERNALS 0 #undef CYTHON_USE_UNICODE_WRITER #define CYTHON_USE_UNICODE_WRITER 0 #undef CYTHON_USE_PYLONG_INTERNALS #define CYTHON_USE_PYLONG_INTERNALS 0 #undef CYTHON_AVOID_BORROWED_REFS #define CYTHON_AVOID_BORROWED_REFS 1 #undef CYTHON_ASSUME_SAFE_MACROS #define CYTHON_ASSUME_SAFE_MACROS 0 #undef CYTHON_UNPACK_METHODS #define CYTHON_UNPACK_METHODS 0 #undef CYTHON_FAST_THREAD_STATE #define CYTHON_FAST_THREAD_STATE 0 #undef CYTHON_FAST_PYCALL #define CYTHON_FAST_PYCALL 0 #elif defined(PYSTON_VERSION) #define CYTHON_COMPILING_IN_PYPY 0 #define CYTHON_COMPILING_IN_PYSTON 1 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PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b) #else #define __Pyx_PyString_Format(a, b) PyString_Format(a, b) #endif #if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII) #define PyObject_ASCII(o) PyObject_Repr(o) #endif #if PY_MAJOR_VERSION >= 3 #define PyBaseString_Type PyUnicode_Type #define PyStringObject PyUnicodeObject #define PyString_Type PyUnicode_Type #define PyString_Check PyUnicode_Check #define PyString_CheckExact PyUnicode_CheckExact #endif #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) #else #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj)) #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj)) #endif #ifndef PySet_CheckExact #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) #endif #define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) #define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception) #if PY_MAJOR_VERSION >= 3 #define PyIntObject PyLongObject #define PyInt_Type PyLong_Type #define PyInt_Check(op) PyLong_Check(op) #define PyInt_CheckExact(op) PyLong_CheckExact(op) #define PyInt_FromString PyLong_FromString #define PyInt_FromUnicode PyLong_FromUnicode #define PyInt_FromLong PyLong_FromLong #define PyInt_FromSize_t PyLong_FromSize_t #define PyInt_FromSsize_t PyLong_FromSsize_t #define PyInt_AsLong PyLong_AsLong #define PyInt_AS_LONG PyLong_AS_LONG #define PyInt_AsSsize_t PyLong_AsSsize_t #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask #define PyNumber_Int PyNumber_Long #endif #if PY_MAJOR_VERSION >= 3 #define PyBoolObject PyLongObject #endif #if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY #ifndef PyUnicode_InternFromString #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) #endif #endif #if PY_VERSION_HEX < 0x030200A4 typedef long Py_hash_t; #define __Pyx_PyInt_FromHash_t PyInt_FromLong #define __Pyx_PyInt_AsHash_t PyInt_AsLong #else #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t #endif #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func)) #else #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) #endif #if CYTHON_USE_ASYNC_SLOTS #if PY_VERSION_HEX >= 0x030500B1 #define __Pyx_PyAsyncMethodsStruct PyAsyncMethods #define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async) #else typedef struct { unaryfunc am_await; unaryfunc am_aiter; unaryfunc am_anext; } __Pyx_PyAsyncMethodsStruct; #define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved)) #endif #else #define __Pyx_PyType_AsAsync(obj) NULL #endif #ifndef CYTHON_RESTRICT #if defined(__GNUC__) #define CYTHON_RESTRICT __restrict__ #elif defined(_MSC_VER) && _MSC_VER >= 1400 #define CYTHON_RESTRICT __restrict #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L #define CYTHON_RESTRICT restrict #else #define CYTHON_RESTRICT #endif #endif #ifndef CYTHON_UNUSED # if defined(__GNUC__) # if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4)) # define CYTHON_UNUSED __attribute__ ((__unused__)) # else # define CYTHON_UNUSED # endif # elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER)) # define CYTHON_UNUSED __attribute__ ((__unused__)) # else # define CYTHON_UNUSED # endif #endif #ifndef CYTHON_MAYBE_UNUSED_VAR # if defined(__cplusplus) template void CYTHON_MAYBE_UNUSED_VAR( const T& ) { } # else # define CYTHON_MAYBE_UNUSED_VAR(x) (void)(x) # endif #endif #ifndef CYTHON_NCP_UNUSED # if CYTHON_COMPILING_IN_CPYTHON # define CYTHON_NCP_UNUSED # else # define CYTHON_NCP_UNUSED CYTHON_UNUSED # endif #endif #define __Pyx_void_to_None(void_result) ((void)(void_result), Py_INCREF(Py_None), Py_None) #ifndef __cplusplus #error ""Cython files generated with the C++ option must be compiled with a C++ compiler."" #endif #ifndef CYTHON_INLINE #if defined(__clang__) #define CYTHON_INLINE __inline__ __attribute__ ((__unused__)) #else #define CYTHON_INLINE inline #endif #endif template void __Pyx_call_destructor(T& x) { x.~T(); } template class __Pyx_FakeReference { public: __Pyx_FakeReference() : ptr(NULL) { } __Pyx_FakeReference(const T& ref) : ptr(const_cast(&ref)) { } T *operator->() { return ptr; } T *operator&() { return ptr; } operator T&() { return *ptr; } template bool operator ==(U other) { return *ptr == other; } template bool operator !=(U other) { return *ptr != other; } private: T *ptr; }; #if defined(WIN32) || defined(MS_WINDOWS) #define _USE_MATH_DEFINES #endif #include #ifdef NAN #define __PYX_NAN() ((float) NAN) #else static CYTHON_INLINE float __PYX_NAN() { float value; memset(&value, 0xFF, sizeof(value)); return value; } #endif #if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL) #define __Pyx_truncl trunc #else #define __Pyx_truncl truncl #endif #define __PYX_ERR(f_index, lineno, Ln_error) \ { \ __pyx_filename = __pyx_f[f_index]; __pyx_lineno = lineno; __pyx_clineno = __LINE__; goto Ln_error; \ } #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) #else #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) #endif #ifndef __PYX_EXTERN_C #ifdef __cplusplus #define __PYX_EXTERN_C extern ""C"" #else #define __PYX_EXTERN_C extern #endif #endif #define __PYX_HAVE__wrap_cy #define __PYX_HAVE_API__wrap_cy #include ""gridsearch.C"" #include ""pythread.h"" #include #include #include #include ""pystate.h"" #ifdef _OPENMP #include #endif /* _OPENMP */ #ifdef PYREX_WITHOUT_ASSERTIONS #define CYTHON_WITHOUT_ASSERTIONS #endif typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding; const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; #define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 #define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT 0 #define __PYX_DEFAULT_STRING_ENCODING """" #define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString #define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize #define __Pyx_uchar_cast(c) ((unsigned char)c) #define __Pyx_long_cast(x) ((long)x) #define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\ (sizeof(type) < sizeof(Py_ssize_t)) ||\ (sizeof(type) > sizeof(Py_ssize_t) &&\ likely(v < (type)PY_SSIZE_T_MAX ||\ v == (type)PY_SSIZE_T_MAX) &&\ (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\ v == (type)PY_SSIZE_T_MIN))) ||\ (sizeof(type) == sizeof(Py_ssize_t) &&\ (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\ v == (type)PY_SSIZE_T_MAX))) ) #if defined (__cplusplus) && __cplusplus >= 201103L #include #define __Pyx_sst_abs(value) std::abs(value) #elif SIZEOF_INT >= SIZEOF_SIZE_T #define __Pyx_sst_abs(value) abs(value) #elif SIZEOF_LONG >= SIZEOF_SIZE_T #define __Pyx_sst_abs(value) labs(value) #elif defined (_MSC_VER) && defined (_M_X64) #define __Pyx_sst_abs(value) _abs64(value) #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L #define __Pyx_sst_abs(value) llabs(value) #elif defined (__GNUC__) #define __Pyx_sst_abs(value) __builtin_llabs(value) #else #define __Pyx_sst_abs(value) ((value<0) ? -value : value) #endif static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject*); static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); #define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) #define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l) #define __Pyx_PyBytes_FromString PyBytes_FromString #define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); #if PY_MAJOR_VERSION < 3 #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize #else #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize #endif #define __Pyx_PyObject_AsSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) #define __Pyx_PyObject_AsUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) #define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) #define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) #define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) #define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) #define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) #if PY_MAJOR_VERSION < 3 static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { const Py_UNICODE *u_end = u; while (*u_end++) ; return (size_t)(u_end - u - 1); } #else #define __Pyx_Py_UNICODE_strlen Py_UNICODE_strlen #endif #define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) #define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode #define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode #define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) #define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) #define __Pyx_PyBool_FromLong(b) ((b) ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False)) static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*); static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x); static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t); #if CYTHON_ASSUME_SAFE_MACROS #define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x)) #else #define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x) #endif #define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x)) #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x)) #else #define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x)) #endif #define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x)) #if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII static int __Pyx_sys_getdefaultencoding_not_ascii; static int __Pyx_init_sys_getdefaultencoding_params(void) { PyObject* sys; PyObject* default_encoding = NULL; PyObject* ascii_chars_u = NULL; PyObject* ascii_chars_b = NULL; const char* default_encoding_c; sys = PyImport_ImportModule(""sys""); if (!sys) goto bad; default_encoding = PyObject_CallMethod(sys, (char*) ""getdefaultencoding"", NULL); Py_DECREF(sys); if (!default_encoding) goto bad; default_encoding_c = PyBytes_AsString(default_encoding); if (!default_encoding_c) goto bad; if (strcmp(default_encoding_c, ""ascii"") == 0) { __Pyx_sys_getdefaultencoding_not_ascii = 0; } else { char ascii_chars[128]; int c; for (c = 0; c < 128; c++) { ascii_chars[c] = c; } __Pyx_sys_getdefaultencoding_not_ascii = 1; ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL); if (!ascii_chars_u) goto bad; ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL); if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) { PyErr_Format( PyExc_ValueError, ""This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii."", default_encoding_c); goto bad; } Py_DECREF(ascii_chars_u); Py_DECREF(ascii_chars_b); } Py_DECREF(default_encoding); return 0; bad: Py_XDECREF(default_encoding); Py_XDECREF(ascii_chars_u); Py_XDECREF(ascii_chars_b); return -1; } #endif #if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3 #define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL) #else #define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL) #if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT static char* __PYX_DEFAULT_STRING_ENCODING; static int __Pyx_init_sys_getdefaultencoding_params(void) { PyObject* sys; PyObject* default_encoding = NULL; char* default_encoding_c; sys = PyImport_ImportModule(""sys""); if (!sys) goto bad; default_encoding = PyObject_CallMethod(sys, (char*) (const char*) ""getdefaultencoding"", NULL); Py_DECREF(sys); if (!default_encoding) goto bad; default_encoding_c = PyBytes_AsString(default_encoding); if (!default_encoding_c) goto bad; __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c)); if (!__PYX_DEFAULT_STRING_ENCODING) goto bad; strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c); Py_DECREF(default_encoding); return 0; bad: Py_XDECREF(default_encoding); return -1; } #endif #endif /* Test for GCC > 2.95 */ #if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95))) #define likely(x) __builtin_expect(!!(x), 1) #define unlikely(x) __builtin_expect(!!(x), 0) #else /* !__GNUC__ or GCC < 2.95 */ #define likely(x) (x) #define unlikely(x) (x) #endif /* __GNUC__ */ static PyObject *__pyx_m; static PyObject *__pyx_d; static PyObject *__pyx_b; static PyObject *__pyx_empty_tuple; static PyObject *__pyx_empty_bytes; static PyObject *__pyx_empty_unicode; static int __pyx_lineno; static int __pyx_clineno = 0; static const char * __pyx_cfilenm= __FILE__; static const char *__pyx_filename; static const char *__pyx_f[] = { ""on/wrap.pyx"", ""on/stringsource"", }; /* MemviewSliceStruct.proto */ struct __pyx_memoryview_obj; typedef struct { struct __pyx_memoryview_obj *memview; char *data; Py_ssize_t shape[8]; Py_ssize_t strides[8]; Py_ssize_t suboffsets[8]; } __Pyx_memviewslice; /* BufferFormatStructs.proto */ #define IS_UNSIGNED(type) (((type) -1) > 0) struct __Pyx_StructField_; #define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0) typedef struct { const char* name; struct __Pyx_StructField_* fields; size_t size; size_t arraysize[8]; int ndim; char typegroup; char is_unsigned; int flags; } __Pyx_TypeInfo; typedef struct __Pyx_StructField_ { __Pyx_TypeInfo* type; const char* name; size_t offset; } __Pyx_StructField; typedef struct { __Pyx_StructField* field; size_t parent_offset; } __Pyx_BufFmt_StackElem; typedef struct { __Pyx_StructField root; __Pyx_BufFmt_StackElem* head; size_t fmt_offset; size_t new_count, enc_count; size_t struct_alignment; int is_complex; char enc_type; char new_packmode; char enc_packmode; char is_valid_array; } __Pyx_BufFmt_Context; /* Atomics.proto */ #include #ifndef CYTHON_ATOMICS #define CYTHON_ATOMICS 1 #endif #define __pyx_atomic_int_type int #if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 ||\ (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) &&\ !defined(__i386__) #define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1) #define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1) #ifdef __PYX_DEBUG_ATOMICS #warning ""Using GNU atomics"" #endif #elif CYTHON_ATOMICS && defined(_MSC_VER) && 0 #include #undef __pyx_atomic_int_type #define __pyx_atomic_int_type LONG #define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value) #define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value) #ifdef __PYX_DEBUG_ATOMICS #pragma message (""Using MSVC atomics"") #endif #elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0 #define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value) #define __pyx_atomic_decr_aligned(value, lock) _InterlockedDecrement(value) #ifdef __PYX_DEBUG_ATOMICS #warning ""Using Intel atomics"" #endif #else #undef CYTHON_ATOMICS #define CYTHON_ATOMICS 0 #ifdef __PYX_DEBUG_ATOMICS #warning ""Not using atomics"" #endif #endif typedef volatile __pyx_atomic_int_type __pyx_atomic_int; #if CYTHON_ATOMICS #define __pyx_add_acquisition_count(memview)\ __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) #define __pyx_sub_acquisition_count(memview)\ __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) #else #define __pyx_add_acquisition_count(memview)\ __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) #define __pyx_sub_acquisition_count(memview)\ __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) #endif /*--- Type declarations ---*/ struct __pyx_array_obj; struct __pyx_MemviewEnum_obj; struct __pyx_memoryview_obj; struct __pyx_memoryviewslice_obj; /* ""View.MemoryView"":103 * * @cname(""__pyx_array"") * cdef class array: # <<<<<<<<<<<<<< * * cdef: */ struct __pyx_array_obj { PyObject_HEAD struct __pyx_vtabstruct_array *__pyx_vtab; char *data; Py_ssize_t len; char *format; int ndim; Py_ssize_t *_shape; Py_ssize_t *_strides; Py_ssize_t itemsize; PyObject *mode; PyObject *_format; void (*callback_free_data)(void *); int free_data; int dtype_is_object; }; /* ""View.MemoryView"":275 * * @cname('__pyx_MemviewEnum') * cdef class Enum(object): # <<<<<<<<<<<<<< * cdef object name * def __init__(self, name): */ struct __pyx_MemviewEnum_obj { PyObject_HEAD PyObject *name; }; /* ""View.MemoryView"":326 * * @cname('__pyx_memoryview') * cdef class memoryview(object): # <<<<<<<<<<<<<< * * cdef object obj */ struct __pyx_memoryview_obj { PyObject_HEAD struct __pyx_vtabstruct_memoryview *__pyx_vtab; PyObject *obj; PyObject *_size; PyObject *_array_interface; PyThread_type_lock lock; __pyx_atomic_int acquisition_count[2]; __pyx_atomic_int *acquisition_count_aligned_p; Py_buffer view; int flags; int dtype_is_object; __Pyx_TypeInfo *typeinfo; }; /* ""View.MemoryView"":951 * * @cname('__pyx_memoryviewslice') * cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<< * ""Internal class for passing memoryview slices to Python"" * */ struct __pyx_memoryviewslice_obj { struct __pyx_memoryview_obj __pyx_base; __Pyx_memviewslice from_slice; PyObject *from_object; PyObject *(*to_object_func)(char *); int (*to_dtype_func)(char *, PyObject *); }; /* ""View.MemoryView"":103 * * @cname(""__pyx_array"") * cdef class array: # <<<<<<<<<<<<<< * * cdef: */ struct __pyx_vtabstruct_array { PyObject *(*get_memview)(struct __pyx_array_obj *); }; static struct __pyx_vtabstruct_array *__pyx_vtabptr_array; /* ""View.MemoryView"":326 * * @cname('__pyx_memoryview') * cdef class memoryview(object): # <<<<<<<<<<<<<< * * cdef object obj */ struct __pyx_vtabstruct_memoryview { char *(*get_item_pointer)(struct __pyx_memoryview_obj *, PyObject *); PyObject *(*is_slice)(struct __pyx_memoryview_obj *, PyObject *); PyObject *(*setitem_slice_assignment)(struct __pyx_memoryview_obj *, PyObject *, PyObject *); PyObject *(*setitem_slice_assign_scalar)(struct __pyx_memoryview_obj *, struct __pyx_memoryview_obj *, PyObject *); PyObject *(*setitem_indexed)(struct __pyx_memoryview_obj *, PyObject *, PyObject *); PyObject *(*convert_item_to_object)(struct __pyx_memoryview_obj *, char *); 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#endif /* PyObjectCallOneArg.proto */ static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); /* PySequenceContains.proto */ static CYTHON_INLINE int __Pyx_PySequence_ContainsTF(PyObject* item, PyObject* seq, int eq) { int result = PySequence_Contains(seq, item); return unlikely(result < 0) ? result : (result == (eq == Py_EQ)); } /* ListAppend.proto */ #if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { PyListObject* L = (PyListObject*) list; Py_ssize_t len = Py_SIZE(list); if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) { Py_INCREF(x); PyList_SET_ITEM(list, len, x); Py_SIZE(list) = len+1; return 0; } return PyList_Append(list, x); } #else #define __Pyx_PyList_Append(L,x) PyList_Append(L,x) #endif /* PyObjectCallMethod1.proto */ static PyObject* __Pyx_PyObject_CallMethod1(PyObject* obj, PyObject* method_name, PyObject* arg); /* append.proto */ static CYTHON_INLINE int __Pyx_PyObject_Append(PyObject* L, PyObject* x); /* GetItemInt.proto */ #define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\ (is_list ? (PyErr_SetString(PyExc_IndexError, ""list index out of range""), (PyObject*)NULL) :\ __Pyx_GetItemInt_Generic(o, to_py_func(i)))) #define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ (PyErr_SetString(PyExc_IndexError, ""list index out of range""), (PyObject*)NULL)) static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, int wraparound, int boundscheck); #define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ (PyErr_SetString(PyExc_IndexError, ""tuple index out of range""), (PyObject*)NULL)) static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, int wraparound, int boundscheck); static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j); 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static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); #else #define __Pyx_ErrRestoreWithState(type, value, tb) PyErr_Restore(type, value, tb) #define __Pyx_ErrFetchWithState(type, value, tb) PyErr_Fetch(type, value, tb) #define __Pyx_ErrRestore(type, value, tb) PyErr_Restore(type, value, tb) #define __Pyx_ErrFetch(type, value, tb) PyErr_Fetch(type, value, tb) #endif /* RaiseException.proto */ static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); /* None.proto */ static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t, Py_ssize_t); /* UnaryNegOverflows.proto */ #define UNARY_NEG_WOULD_OVERFLOW(x)\ (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x))) static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *); /*proto*/ /* GetAttr.proto */ static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *); /* decode_c_string.proto */ static CYTHON_INLINE PyObject* __Pyx_decode_c_string( const char* cstring, Py_ssize_t start, Py_ssize_t stop, const char* encoding, const char* errors, PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)); /* RaiseTooManyValuesToUnpack.proto */ static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); /* RaiseNeedMoreValuesToUnpack.proto */ static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); /* RaiseNoneIterError.proto */ static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); /* ExtTypeTest.proto */ static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); /* SaveResetException.proto */ #if CYTHON_FAST_THREAD_STATE #define __Pyx_ExceptionSave(type, value, tb) __Pyx__ExceptionSave(__pyx_tstate, type, value, tb) static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); #define __Pyx_ExceptionReset(type, value, tb) __Pyx__ExceptionReset(__pyx_tstate, type, value, tb) static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); 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#else static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb); #endif static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ /* ListCompAppend.proto */ #if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { PyListObject* L = (PyListObject*) list; Py_ssize_t len = Py_SIZE(list); if (likely(L->allocated > len)) { Py_INCREF(x); PyList_SET_ITEM(list, len, x); Py_SIZE(list) = len+1; return 0; } return PyList_Append(list, x); } #else #define __Pyx_ListComp_Append(L,x) PyList_Append(L,x) #endif /* PyIntBinop.proto */ #if !CYTHON_COMPILING_IN_PYPY static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace); #else #define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace)\ (inplace ? 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struct __Pyx_CodeObjectCache { int count; int max_count; __Pyx_CodeObjectCacheEntry* entries; }; static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL}; static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line); static PyCodeObject *__pyx_find_code_object(int code_line); static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object); /* AddTraceback.proto */ static void __Pyx_AddTraceback(const char *funcname, int c_line, int py_line, const char *filename); #if PY_MAJOR_VERSION < 3 static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags); static void __Pyx_ReleaseBuffer(Py_buffer *view); #else #define __Pyx_GetBuffer PyObject_GetBuffer #define __Pyx_ReleaseBuffer PyBuffer_Release #endif /* BufferStructDeclare.proto */ typedef struct { Py_ssize_t shape, strides, suboffsets; } __Pyx_Buf_DimInfo; typedef struct { size_t refcount; Py_buffer pybuffer; } __Pyx_Buffer; typedef struct { __Pyx_Buffer *rcbuffer; char *data; __Pyx_Buf_DimInfo diminfo[8]; } __Pyx_LocalBuf_ND; /* None.proto */ static Py_ssize_t __Pyx_zeros[] = {0, 0, 0, 0, 0, 0, 0, 0}; static Py_ssize_t __Pyx_minusones[] = {-1, -1, -1, -1, -1, -1, -1, -1}; /* MemviewSliceIsContig.proto */ static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim); /* OverlappingSlices.proto */ static int __pyx_slices_overlap(__Pyx_memviewslice *slice1, __Pyx_memviewslice *slice2, int ndim, size_t itemsize); /* Capsule.proto */ static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig); /* CIntToPy.proto */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); /* CIntToPy.proto */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); /* Print.proto */ static int __Pyx_Print(PyObject*, PyObject *, int); #if CYTHON_COMPILING_IN_PYPY || PY_MAJOR_VERSION >= 3 static PyObject* __pyx_print = 0; static PyObject* __pyx_print_kwargs = 0; #endif /* MemviewSliceCopyTemplate.proto */ static __Pyx_memviewslice __pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, const char *mode, int ndim, size_t sizeof_dtype, int contig_flag, int dtype_is_object); /* CIntFromPy.proto */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); /* PrintOne.proto */ static int __Pyx_PrintOne(PyObject* stream, PyObject *o); /* CIntFromPy.proto */ static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *); /* CIntFromPy.proto */ static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); /* TypeInfoCompare.proto */ static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b); /* MemviewSliceValidateAndInit.proto */ static int __Pyx_ValidateAndInit_memviewslice( int *axes_specs, int c_or_f_flag, int buf_flags, int ndim, __Pyx_TypeInfo *dtype, __Pyx_BufFmt_StackElem stack[], __Pyx_memviewslice *memviewslice, PyObject *original_obj); /* ObjectToMemviewSlice.proto */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_int(PyObject *); /* ObjectToMemviewSlice.proto */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_float(PyObject *); /* CheckBinaryVersion.proto */ static int __Pyx_check_binary_version(void); /* InitStrings.proto */ static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/ static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/ static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/ static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/ static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ /* Module declarations from 'cython.view' */ /* Module declarations from 'wrap_cy' */ static PyTypeObject *__pyx_array_type = 0; static PyTypeObject *__pyx_MemviewEnum_type = 0; static PyTypeObject *__pyx_memoryview_type = 0; static PyTypeObject *__pyx_memoryviewslice_type = 0; static PyObject *generic = 0; static PyObject *strided = 0; static PyObject *indirect = 0; static PyObject *contiguous = 0; static PyObject *indirect_contiguous = 0; static int __pyx_memoryview_thread_locks_used; static PyThread_type_lock __pyx_memoryview_thread_locks[8]; static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/ static void *__pyx_align_pointer(void *, size_t); /*proto*/ static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/ static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/ static PyObject *_unellipsify(PyObject *, int); /*proto*/ static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/ static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/ static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/ static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/ static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/ static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/ static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/ static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/ static int __pyx_memoryview_err(PyObject *, char *); /*proto*/ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/ static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/ static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/ static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/ static __Pyx_TypeInfo __Pyx_TypeInfo_int = { ""int"", NULL, sizeof(int), { 0 }, 0, IS_UNSIGNED(int) ? 'U' : 'I', IS_UNSIGNED(int), 0 }; static __Pyx_TypeInfo __Pyx_TypeInfo_float = { ""float"", NULL, sizeof(float), { 0 }, 0, 'R', 0, 0 }; #define __Pyx_MODULE_NAME ""wrap_cy"" int __pyx_module_is_main_wrap_cy = 0; /* Implementation of 'wrap_cy' */ static PyObject *__pyx_builtin_ValueError; static PyObject *__pyx_builtin_MemoryError; static PyObject *__pyx_builtin_enumerate; static PyObject *__pyx_builtin_range; static PyObject *__pyx_builtin_Ellipsis; static PyObject *__pyx_builtin_TypeError; static PyObject *__pyx_builtin_id; static PyObject *__pyx_builtin_IndexError; static const char __pyx_k_[] = """"; static const char __pyx_k_C[] = ""C""; static const char __pyx_k_F[] = ""F""; static const char __pyx_k_H[] = ""H""; static const char __pyx_k_N[] = ""N""; static const char __pyx_k_O[] = ""O""; static const char __pyx_k_P[] = ""P""; static const char __pyx_k_S[] = ""S""; static const char __pyx_k_c[] = ""c""; static const char __pyx_k_i[] = ""i""; static const char __pyx_k_s[] = ""s""; static const char __pyx_k_u[] = ""u""; static const char __pyx_k_Mg[] = ""Mg""; static const char __pyx_k_id[] = ""id""; static const char __pyx_k_np[] = ""np""; static const char __pyx_k_ts[] = ""ts""; static const char __pyx_k_bla[] = ""bla""; static const char __pyx_k_dcd[] = ""dcd""; static const char __pyx_k_end[] = ""end""; static const char __pyx_k_get[] = ""get""; static const char __pyx_k_obj[] = ""obj""; static const char __pyx_k_psf[] = ""psf""; static const char __pyx_k_base[] = ""base""; static const char __pyx_k_file[] = ""file""; static const char __pyx_k_main[] = ""__main__""; static const char __pyx_k_mode[] = ""mode""; static const char __pyx_k_name[] = ""name""; static const char __pyx_k_ndim[] = ""ndim""; static const char __pyx_k_pack[] = ""pack""; static const char __pyx_k_sasa[] = ""sasa""; static const char __pyx_k_segs[] = ""segs""; static const char __pyx_k_size[] = ""size""; static const char __pyx_k_step[] = ""step""; static const char __pyx_k_stop[] = ""stop""; static const char __pyx_k_test[] = ""__test__""; static const char __pyx_k_ASCII[] = ""ASCII""; static const char __pyx_k_array[] = ""array""; static const char __pyx_k_atoms[] = ""atoms""; static const char __pyx_k_class[] = ""__class__""; static const char __pyx_k_dtype[] = ""dtype""; static const char __pyx_k_error[] = ""error""; static const char __pyx_k_flags[] = ""flags""; static const char __pyx_k_int32[] = ""int32""; static const char __pyx_k_nprad[] = ""nprad""; static const char __pyx_k_numpy[] = ""numpy""; static const char __pyx_k_print[] = ""print""; static const char __pyx_k_range[] = ""range""; static const char __pyx_k_shape[] = ""shape""; static const char __pyx_k_start[] = ""start""; static const char __pyx_k_append[] = ""append""; static const char __pyx_k_coords[] = ""coords""; static const char __pyx_k_encode[] = ""encode""; static const char __pyx_k_format[] = ""format""; static const char __pyx_k_import[] = ""__import__""; static const char __pyx_k_name_2[] = ""__name__""; static const char __pyx_k_natoms[] = ""natoms""; static const char __pyx_k_perres[] = ""perres""; static const char __pyx_k_radius[] = ""radius""; static const char __pyx_k_resids[] = ""resids""; static const char __pyx_k_ressel[] = ""ressel""; static const char __pyx_k_result[] = ""result""; static const char __pyx_k_segids[] = ""segids""; static const char __pyx_k_struct[] = ""struct""; static const char __pyx_k_unpack[] = ""unpack""; static const char __pyx_k_float32[] = ""float32""; static const char __pyx_k_fortran[] = ""fortran""; static const char __pyx_k_memview[] = ""memview""; static const char __pyx_k_reshape[] = ""reshape""; static const char __pyx_k_seltext[] = ""seltext""; static const char __pyx_k_wrap_cy[] = ""wrap_cy""; static const char __pyx_k_Ellipsis[] = ""Ellipsis""; static const char __pyx_k_Universe[] = ""Universe""; static const char __pyx_k_atomType[] = ""atomType""; static const char __pyx_k_c_coords[] = ""c_coords""; static const char __pyx_k_itemsize[] = ""itemsize""; static const char __pyx_k_npcoords[] = ""npcoords""; static const char __pyx_k_pairdist[] = ""pairdist""; static const char __pyx_k_seltext2[] = ""seltext2""; static const char __pyx_k_vdwRadii[] = ""vdwRadii""; static const char __pyx_k_TypeError[] = ""TypeError""; static const char __pyx_k_cy_radius[] = ""cy_radius""; static const char __pyx_k_enumerate[] = ""enumerate""; static const char __pyx_k_positions[] = ""positions""; static const char __pyx_k_selection[] = ""selection""; static const char __pyx_k_test_sasa[] = ""test_sasa""; static const char __pyx_k_vdwRadius[] = ""vdwRadius""; static const char __pyx_k_IndexError[] = ""IndexError""; static const char __pyx_k_MDAnalysis[] = ""MDAnalysis""; static const char __pyx_k_ValueError[] = ""ValueError""; static const char __pyx_k_pointstyle[] = ""pointstyle""; static const char __pyx_k_pyx_vtable[] = ""__pyx_vtable__""; static const char __pyx_k_resseltext[] = ""resseltext""; static const char __pyx_k_restricted[] = ""restricted""; static const char __pyx_k_segid_COH3[] = ""segid COH3""; static const char __pyx_k_segid_DOC3[] = ""segid DOC3""; static const char __pyx_k_trajectory[] = ""trajectory""; static const char __pyx_k_MemoryError[] = ""MemoryError""; static const char __pyx_k_probeRadius[] = ""probeRadius""; static const char __pyx_k_input_coords[] = ""input_coords""; static const char __pyx_k_select_atoms[] = ""select_atoms""; static const char __pyx_k_pyx_getbuffer[] = ""__pyx_getbuffer""; static const char __pyx_k_surfacePoints[] = ""surfacePoints""; static const char __pyx_k_restrictedList[] = ""restrictedList""; static const char __pyx_k_allocate_buffer[] = ""allocate_buffer""; static const char __pyx_k_dtype_is_object[] = ""dtype_is_object""; static const char __pyx_k_cy_restrictedList[] = ""cy_restrictedList""; static const char __pyx_k_strided_and_direct[] = """"; static const char __pyx_k_strided_and_indirect[] = """"; static const char __pyx_k_contiguous_and_direct[] = """"; static const char __pyx_k_MemoryView_of_r_object[] = """"; static const char __pyx_k_MemoryView_of_r_at_0x_x[] = """"; static const char __pyx_k_contiguous_and_indirect[] = """"; static const char __pyx_k_Cannot_index_with_type_s[] = ""Cannot index with type '%s'""; static const char __pyx_k_Invalid_shape_in_axis_d_d[] = ""Invalid shape in axis %d: %d.""; static const char __pyx_k_itemsize_0_for_cython_array[] = ""itemsize <= 0 for cython.array""; static const char __pyx_k_unable_to_allocate_array_data[] = ""unable to allocate array data.""; static const char __pyx_k_strided_and_direct_or_indirect[] = """"; static const char __pyx_k_home_max_Projects_pycontact_tes[] = ""/home/max/Projects/pycontact/testing/cython/wrap.pyx""; static const char __pyx_k_mnt_workspace_pycontactData_now[] = ""/mnt/workspace/pycontactData/nowater.psf""; static const char __pyx_k_mnt_workspace_pycontactData_tra[] = ""/mnt/workspace/pycontactData/trajectory_short.dcd""; static const char __pyx_k_Buffer_view_does_not_expose_stri[] = ""Buffer view does not expose strides""; static const char __pyx_k_Can_only_create_a_buffer_that_is[] = ""Can only create a buffer that is contiguous in memory.""; static const char __pyx_k_Empty_shape_tuple_for_cython_arr[] = ""Empty shape tuple for cython.array""; static const char __pyx_k_Indirect_dimensions_not_supporte[] = ""Indirect dimensions not supported""; static const char __pyx_k_Invalid_mode_expected_c_or_fortr[] = ""Invalid mode, expected 'c' or 'fortran', got %s""; static const char __pyx_k_Out_of_bounds_on_buffer_access_a[] = ""Out of bounds on buffer access (axis %d)""; static const char __pyx_k_Unable_to_convert_item_to_object[] = ""Unable to convert item to object""; static const char __pyx_k_got_differing_extents_in_dimensi[] = ""got differing extents in dimension %d (got %d and %d)""; static const char __pyx_k_segid_COH3_and_around_5_segid_DO[] = ""segid COH3 and around 5 segid DOC3""; static const char __pyx_k_unable_to_allocate_shape_and_str[] = ""unable to allocate shape and strides.""; static PyObject *__pyx_kp_s_; static PyObject *__pyx_n_s_ASCII; static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri; static PyObject *__pyx_n_s_C; static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is; static PyObject *__pyx_kp_s_Cannot_index_with_type_s; static PyObject *__pyx_n_s_Ellipsis; static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr; static PyObject *__pyx_n_s_F; static PyObject *__pyx_n_s_H; static PyObject *__pyx_n_s_IndexError; static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte; static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr; static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d; static PyObject *__pyx_n_s_MDAnalysis; static PyObject *__pyx_n_s_MemoryError; static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x; static PyObject *__pyx_kp_s_MemoryView_of_r_object; static PyObject *__pyx_n_s_Mg; static PyObject *__pyx_n_s_N; static PyObject *__pyx_n_b_O; static PyObject *__pyx_n_s_O; static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a; static PyObject *__pyx_n_s_P; static PyObject *__pyx_n_s_S; static PyObject *__pyx_n_s_TypeError; static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object; static PyObject *__pyx_n_s_Universe; static PyObject *__pyx_n_s_ValueError; static PyObject *__pyx_n_s_allocate_buffer; static PyObject *__pyx_n_s_append; static PyObject *__pyx_n_s_array; static PyObject *__pyx_n_s_atomType; static PyObject *__pyx_n_s_atoms; static PyObject *__pyx_n_s_base; static PyObject *__pyx_n_s_bla; static PyObject *__pyx_n_s_c; static PyObject *__pyx_n_u_c; static PyObject *__pyx_n_s_c_coords; static PyObject *__pyx_n_s_class; static PyObject *__pyx_kp_s_contiguous_and_direct; static PyObject *__pyx_kp_s_contiguous_and_indirect; static PyObject *__pyx_n_s_coords; static PyObject *__pyx_n_s_cy_radius; static PyObject *__pyx_n_s_cy_restrictedList; static PyObject *__pyx_n_s_dcd; static PyObject *__pyx_n_s_dtype; static PyObject *__pyx_n_s_dtype_is_object; static PyObject *__pyx_n_s_encode; static PyObject *__pyx_n_s_end; static PyObject *__pyx_n_s_enumerate; static PyObject *__pyx_n_s_error; static PyObject *__pyx_n_s_file; static PyObject *__pyx_n_s_flags; static PyObject *__pyx_n_s_float32; static PyObject *__pyx_n_s_format; static PyObject *__pyx_n_s_fortran; static PyObject *__pyx_n_u_fortran; static PyObject *__pyx_n_s_get; static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi; static PyObject *__pyx_kp_s_home_max_Projects_pycontact_tes; static PyObject *__pyx_n_s_i; static PyObject *__pyx_n_s_id; static PyObject *__pyx_n_s_import; static PyObject *__pyx_n_s_input_coords; static PyObject *__pyx_n_s_int32; static PyObject *__pyx_n_s_itemsize; static PyObject *__pyx_kp_s_itemsize_0_for_cython_array; static PyObject *__pyx_n_s_main; static PyObject *__pyx_n_s_memview; static PyObject *__pyx_kp_s_mnt_workspace_pycontactData_now; static PyObject *__pyx_kp_s_mnt_workspace_pycontactData_tra; static PyObject *__pyx_n_s_mode; static PyObject *__pyx_n_s_name; static PyObject *__pyx_n_s_name_2; static PyObject *__pyx_n_s_natoms; static PyObject *__pyx_n_s_ndim; static PyObject *__pyx_n_s_np; static PyObject *__pyx_n_s_npcoords; static PyObject *__pyx_n_s_nprad; static PyObject *__pyx_n_s_numpy; static PyObject *__pyx_n_s_obj; static PyObject *__pyx_n_s_pack; static PyObject *__pyx_n_s_pairdist; static PyObject *__pyx_n_s_perres; static PyObject *__pyx_n_s_pointstyle; static PyObject *__pyx_n_s_positions; static PyObject *__pyx_n_s_print; static PyObject *__pyx_n_s_probeRadius; static PyObject *__pyx_n_s_psf; static PyObject *__pyx_n_s_pyx_getbuffer; static PyObject *__pyx_n_s_pyx_vtable; static PyObject *__pyx_n_s_radius; static PyObject *__pyx_n_s_range; static PyObject *__pyx_n_s_reshape; static PyObject *__pyx_n_s_resids; static PyObject *__pyx_n_s_ressel; static PyObject *__pyx_n_s_resseltext; static PyObject 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__pyx_v_dim, int __pyx_v_new_ndim, int *__pyx_v_suboffset_dim, Py_ssize_t __pyx_v_start, Py_ssize_t __pyx_v_stop, Py_ssize_t __pyx_v_step, int __pyx_v_have_start, int __pyx_v_have_stop, int __pyx_v_have_step, int __pyx_v_is_slice) { Py_ssize_t __pyx_v_new_shape; int __pyx_v_negative_step; int __pyx_r; int __pyx_t_1; int __pyx_t_2; int __pyx_t_3; /* ""View.MemoryView"":813 * cdef bint negative_step * * if not is_slice: # <<<<<<<<<<<<<< * * if start < 0: */ __pyx_t_1 = ((!(__pyx_v_is_slice != 0)) != 0); if (__pyx_t_1) { /* ""View.MemoryView"":815 * if not is_slice: * * if start < 0: # <<<<<<<<<<<<<< * start += shape * if not 0 <= start < shape: */ __pyx_t_1 = ((__pyx_v_start < 0) != 0); if (__pyx_t_1) { /* ""View.MemoryView"":816 * * if start < 0: * start += shape # <<<<<<<<<<<<<< * if not 0 <= start < shape: * _err_dim(IndexError, ""Index out of bounds (axis %d)"", dim) */ __pyx_v_start = (__pyx_v_start + __pyx_v_shape); /* ""View.MemoryView"":815 * if not is_slice: * * if start < 0: # <<<<<<<<<<<<<< * start += shape * if not 0 <= start < shape: */ } /* ""View.MemoryView"":817 * if start < 0: * start += shape * if not 0 <= start < shape: # <<<<<<<<<<<<<< * _err_dim(IndexError, ""Index out of bounds (axis %d)"", dim) * else: */ __pyx_t_1 = (0 <= __pyx_v_start); if (__pyx_t_1) { __pyx_t_1 = (__pyx_v_start < __pyx_v_shape); } __pyx_t_2 = ((!(__pyx_t_1 != 0)) != 0); if (__pyx_t_2) { /* ""View.MemoryView"":818 * start += shape * if not 0 <= start < shape: * _err_dim(IndexError, ""Index out of bounds (axis %d)"", dim) # <<<<<<<<<<<<<< * else: * */ __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, ((char *)""Index out of bounds (axis %d)""), __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) __PYX_ERR(1, 818, __pyx_L1_error) /* ""View.MemoryView"":817 * if start < 0: * start += shape * if not 0 <= start < shape: # <<<<<<<<<<<<<< * _err_dim(IndexError, ""Index out of bounds (axis %d)"", dim) * else: */ } /* ""View.MemoryView"":813 * cdef bint negative_step * * if not is_slice: # <<<<<<<<<<<<<< * * if start < 0: */ goto __pyx_L3; } /* ""View.MemoryView"":821 * else: * * negative_step = have_step != 0 and step < 0 # <<<<<<<<<<<<<< * * if have_step and step == 0: */ /*else*/ { __pyx_t_1 = ((__pyx_v_have_step != 0) != 0); if (__pyx_t_1) { } else { __pyx_t_2 = __pyx_t_1; goto __pyx_L6_bool_binop_done; } __pyx_t_1 = ((__pyx_v_step < 0) != 0); __pyx_t_2 = __pyx_t_1; __pyx_L6_bool_binop_done:; __pyx_v_negative_step = __pyx_t_2; /* ""View.MemoryView"":823 * negative_step = have_step != 0 and step < 0 * * if have_step and step == 0: # <<<<<<<<<<<<<< * _err_dim(ValueError, ""Step may not be zero (axis %d)"", dim) * */ __pyx_t_1 = (__pyx_v_have_step != 0); if (__pyx_t_1) { } else { __pyx_t_2 = __pyx_t_1; goto __pyx_L9_bool_binop_done; } __pyx_t_1 = ((__pyx_v_step == 0) != 0); __pyx_t_2 = __pyx_t_1; __pyx_L9_bool_binop_done:; if (__pyx_t_2) { /* ""View.MemoryView"":824 * * if have_step and step == 0: * _err_dim(ValueError, ""Step may not be zero (axis %d)"", dim) # <<<<<<<<<<<<<< * * */ __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)""Step may not be zero (axis %d)""), __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) __PYX_ERR(1, 824, __pyx_L1_error) /* ""View.MemoryView"":823 * negative_step = have_step != 0 and step < 0 * * if have_step and step == 0: # <<<<<<<<<<<<<< * _err_dim(ValueError, ""Step may not be zero (axis %d)"", dim) * */ } /* ""View.MemoryView"":827 * * * if have_start: # <<<<<<<<<<<<<< * if start < 0: * start += shape */ __pyx_t_2 = (__pyx_v_have_start != 0); if (__pyx_t_2) { /* ""View.MemoryView"":828 * * if have_start: * if start < 0: # <<<<<<<<<<<<<< * start += shape * if start < 0: */ __pyx_t_2 = ((__pyx_v_start < 0) != 0); if (__pyx_t_2) { /* ""View.MemoryView"":829 * if have_start: * if start < 0: * start += shape # <<<<<<<<<<<<<< * if start < 0: * start = 0 */ __pyx_v_start = (__pyx_v_start + __pyx_v_shape); /* ""View.MemoryView"":830 * if start < 0: * start += shape * if start < 0: # <<<<<<<<<<<<<< * start = 0 * elif start >= shape: */ __pyx_t_2 = ((__pyx_v_start < 0) != 0); if (__pyx_t_2) { /* ""View.MemoryView"":831 * start += shape * if start < 0: * start = 0 # <<<<<<<<<<<<<< * elif start >= shape: * if negative_step: */ __pyx_v_start = 0; /* ""View.MemoryView"":830 * if start < 0: * start += shape * if start < 0: # <<<<<<<<<<<<<< * start = 0 * elif start >= shape: */ } /* ""View.MemoryView"":828 * * if have_start: * if start < 0: # <<<<<<<<<<<<<< * start += shape * if start < 0: */ goto __pyx_L12; } /* ""View.MemoryView"":832 * if start < 0: * start = 0 * elif start >= shape: # <<<<<<<<<<<<<< * if negative_step: * start = shape - 1 */ __pyx_t_2 = ((__pyx_v_start >= __pyx_v_shape) != 0); if (__pyx_t_2) { /* ""View.MemoryView"":833 * start = 0 * elif start >= shape: * if negative_step: # <<<<<<<<<<<<<< * start = shape - 1 * else: */ __pyx_t_2 = (__pyx_v_negative_step != 0); if (__pyx_t_2) { /* ""View.MemoryView"":834 * elif start >= shape: * if negative_step: * start = shape - 1 # <<<<<<<<<<<<<< * else: * start = shape */ __pyx_v_start = (__pyx_v_shape - 1); /* ""View.MemoryView"":833 * start = 0 * elif start >= shape: * if negative_step: # <<<<<<<<<<<<<< * start = shape - 1 * else: */ goto __pyx_L14; } /* ""View.MemoryView"":836 * start = shape - 1 * else: * start = shape # <<<<<<<<<<<<<< * else: * if negative_step: */ /*else*/ { __pyx_v_start = __pyx_v_shape; } __pyx_L14:; /* ""View.MemoryView"":832 * if start < 0: * start = 0 * elif start >= shape: # <<<<<<<<<<<<<< * if negative_step: * start = shape - 1 */ } __pyx_L12:; /* ""View.MemoryView"":827 * * * if have_start: # <<<<<<<<<<<<<< * if start < 0: * start += shape */ goto __pyx_L11; } /* ""View.MemoryView"":838 * start = shape * else: * if negative_step: # <<<<<<<<<<<<<< * start = shape - 1 * else: */ /*else*/ { __pyx_t_2 = (__pyx_v_negative_step != 0); if (__pyx_t_2) { /* ""View.MemoryView"":839 * else: * if negative_step: * start = shape - 1 # <<<<<<<<<<<<<< * else: * start = 0 */ __pyx_v_start = (__pyx_v_shape - 1); /* ""View.MemoryView"":838 * start = shape * else: * if negative_step: # <<<<<<<<<<<<<< * start = shape - 1 * else: */ goto __pyx_L15; } /* ""View.MemoryView"":841 * start = shape - 1 * else: * start = 0 # <<<<<<<<<<<<<< * * if have_stop: */ /*else*/ { __pyx_v_start = 0; } __pyx_L15:; } __pyx_L11:; /* ""View.MemoryView"":843 * start = 0 * * if have_stop: # <<<<<<<<<<<<<< * if stop < 0: * stop += shape */ __pyx_t_2 = (__pyx_v_have_stop != 0); if (__pyx_t_2) { /* ""View.MemoryView"":844 * * if have_stop: * if stop < 0: # <<<<<<<<<<<<<< * stop += shape * if stop < 0: */ __pyx_t_2 = ((__pyx_v_stop < 0) != 0); if (__pyx_t_2) { /* ""View.MemoryView"":845 * if have_stop: * if stop < 0: * stop += shape # <<<<<<<<<<<<<< * if stop < 0: * stop = 0 */ __pyx_v_stop = (__pyx_v_stop + __pyx_v_shape); /* ""View.MemoryView"":846 * if stop < 0: * stop += shape * if stop < 0: # <<<<<<<<<<<<<< * stop = 0 * elif stop > shape: */ __pyx_t_2 = ((__pyx_v_stop < 0) != 0); if 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__pyx_L16; } /* ""View.MemoryView"":851 * stop = shape * else: * if negative_step: # <<<<<<<<<<<<<< * stop = -1 * else: */ /*else*/ { __pyx_t_2 = (__pyx_v_negative_step != 0); if (__pyx_t_2) { /* ""View.MemoryView"":852 * else: * if negative_step: * stop = -1 # <<<<<<<<<<<<<< * else: * stop = shape */ __pyx_v_stop = -1L; /* ""View.MemoryView"":851 * stop = shape * else: * if negative_step: # <<<<<<<<<<<<<< * stop = -1 * else: */ goto __pyx_L19; } /* ""View.MemoryView"":854 * stop = -1 * else: * stop = shape # <<<<<<<<<<<<<< * * if not have_step: */ /*else*/ { __pyx_v_stop = __pyx_v_shape; } __pyx_L19:; } __pyx_L16:; /* ""View.MemoryView"":856 * stop = shape * * if not have_step: # <<<<<<<<<<<<<< * step = 1 * */ __pyx_t_2 = ((!(__pyx_v_have_step != 0)) != 0); if (__pyx_t_2) { /* ""View.MemoryView"":857 * * if not have_step: * step = 1 # <<<<<<<<<<<<<< * * */ __pyx_v_step = 1; /* ""View.MemoryView"":856 * stop = shape * * if not have_step: # <<<<<<<<<<<<<< * step = 1 * */ } /* 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memoryview_copy_from_slice(memview, &memviewslice) # <<<<<<<<<<<<<< * * @cname('__pyx_memoryview_copy_object_from_slice') */ __Pyx_XDECREF(__pyx_r); __pyx_t_1 = __pyx_memoryview_copy_object_from_slice(__pyx_v_memview, (&__pyx_v_memviewslice)); if (unlikely(!__pyx_t_1)) __PYX_ERR(1, 1067, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __pyx_r = __pyx_t_1; __pyx_t_1 = 0; goto __pyx_L0; /* ""View.MemoryView"":1063 * * @cname('__pyx_memoryview_copy_object') * cdef memoryview_copy(memoryview memview): # <<<<<<<<<<<<<< * ""Create a new memoryview object"" * cdef __Pyx_memviewslice memviewslice */ /* function exit code */ __pyx_L1_error:; __Pyx_XDECREF(__pyx_t_1); __Pyx_AddTraceback(""View.MemoryView.memoryview_copy"", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = 0; __pyx_L0:; __Pyx_XGIVEREF(__pyx_r); __Pyx_RefNannyFinishContext(); return __pyx_r; } /* ""View.MemoryView"":1070 * * @cname('__pyx_memoryview_copy_object_from_slice') * cdef memoryview_copy_from_slice(memoryview memview, __Pyx_memviewslice *memviewslice): # <<<<<<<<<<<<<< * """""" * Create a new memoryview object from a given memoryview object and slice. */ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *__pyx_v_memview, __Pyx_memviewslice *__pyx_v_memviewslice) { PyObject *(*__pyx_v_to_object_func)(char *); int (*__pyx_v_to_dtype_func)(char *, PyObject *); PyObject *__pyx_r = NULL; __Pyx_RefNannyDeclarations int __pyx_t_1; int __pyx_t_2; PyObject *(*__pyx_t_3)(char *); int (*__pyx_t_4)(char *, PyObject *); PyObject *__pyx_t_5 = NULL; __Pyx_RefNannySetupContext(""memoryview_copy_from_slice"", 0); /* ""View.MemoryView"":1077 * cdef int (*to_dtype_func)(char *, object) except 0 * * if isinstance(memview, _memoryviewslice): # <<<<<<<<<<<<<< * to_object_func = (<_memoryviewslice> memview).to_object_func * to_dtype_func = (<_memoryviewslice> memview).to_dtype_func */ __pyx_t_1 = __Pyx_TypeCheck(((PyObject *)__pyx_v_memview), __pyx_memoryviewslice_type); __pyx_t_2 = 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get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< * """""" * Figure out the best memory access order for a given slice. */ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim) { int __pyx_v_i; Py_ssize_t __pyx_v_c_stride; Py_ssize_t __pyx_v_f_stride; char __pyx_r; int __pyx_t_1; int __pyx_t_2; int __pyx_t_3; /* ""View.MemoryView"":1104 * """""" * cdef int i * cdef Py_ssize_t c_stride = 0 # <<<<<<<<<<<<<< * cdef Py_ssize_t f_stride = 0 * */ __pyx_v_c_stride = 0; /* ""View.MemoryView"":1105 * cdef int i * cdef Py_ssize_t c_stride = 0 * cdef Py_ssize_t f_stride = 0 # <<<<<<<<<<<<<< * * for i in range(ndim - 1, -1, -1): */ __pyx_v_f_stride = 0; /* ""View.MemoryView"":1107 * cdef Py_ssize_t f_stride = 0 * * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< * if mslice.shape[i] > 1: * c_stride = mslice.strides[i] */ for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1L; __pyx_t_1-=1) { __pyx_v_i = __pyx_t_1; /* 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= __pyx_t_3; /* ""View.MemoryView"":1113 * * for i in range(ndim): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< * f_stride = mslice.strides[i] * break */ __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); if (__pyx_t_2) { /* ""View.MemoryView"":1114 * for i in range(ndim): * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] # <<<<<<<<<<<<<< * break * */ __pyx_v_f_stride = (__pyx_v_mslice->strides[__pyx_v_i]); /* ""View.MemoryView"":1115 * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] * break # <<<<<<<<<<<<<< * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): */ goto __pyx_L7_break; /* ""View.MemoryView"":1113 * * for i in range(ndim): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< * f_stride = mslice.strides[i] * break */ } } __pyx_L7_break:; /* ""View.MemoryView"":1117 * break * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< * return 'C' * else: */ __pyx_t_2 = ((abs_py_ssize_t(__pyx_v_c_stride) <= abs_py_ssize_t(__pyx_v_f_stride)) != 0); if (__pyx_t_2) { /* ""View.MemoryView"":1118 * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): * return 'C' # <<<<<<<<<<<<<< * else: * return 'F' */ __pyx_r = 'C'; goto __pyx_L0; /* ""View.MemoryView"":1117 * break * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< * return 'C' * else: */ } /* ""View.MemoryView"":1120 * return 'C' * else: * return 'F' # <<<<<<<<<<<<<< * * @cython.cdivision(True) */ /*else*/ { __pyx_r = 'F'; goto __pyx_L0; } /* ""View.MemoryView"":1099 * * @cname('__pyx_get_best_slice_order') * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< * """""" * Figure out the best memory access order for a given slice. */ /* function exit code */ __pyx_L0:; return __pyx_r; } /* ""View.MemoryView"":1123 * * @cython.cdivision(True) * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< * char *dst_data, Py_ssize_t *dst_strides, * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, */ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v_src_strides, char *__pyx_v_dst_data, Py_ssize_t *__pyx_v_dst_strides, Py_ssize_t *__pyx_v_src_shape, Py_ssize_t *__pyx_v_dst_shape, int __pyx_v_ndim, size_t __pyx_v_itemsize) { CYTHON_UNUSED Py_ssize_t __pyx_v_i; CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent; Py_ssize_t __pyx_v_dst_extent; Py_ssize_t __pyx_v_src_stride; Py_ssize_t __pyx_v_dst_stride; int __pyx_t_1; int __pyx_t_2; int __pyx_t_3; Py_ssize_t __pyx_t_4; Py_ssize_t __pyx_t_5; /* ""View.MemoryView"":1130 * * cdef Py_ssize_t i * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<< * cdef Py_ssize_t dst_extent = dst_shape[0] * cdef Py_ssize_t src_stride = src_strides[0] */ __pyx_v_src_extent = (__pyx_v_src_shape[0]); /* ""View.MemoryView"":1131 * cdef Py_ssize_t i * cdef Py_ssize_t src_extent = src_shape[0] * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<< * cdef Py_ssize_t src_stride = src_strides[0] * cdef Py_ssize_t dst_stride = dst_strides[0] */ __pyx_v_dst_extent = (__pyx_v_dst_shape[0]); /* ""View.MemoryView"":1132 * cdef Py_ssize_t src_extent = src_shape[0] * cdef Py_ssize_t dst_extent = dst_shape[0] * cdef Py_ssize_t src_stride = src_strides[0] # <<<<<<<<<<<<<< * cdef Py_ssize_t dst_stride = dst_strides[0] * */ __pyx_v_src_stride = (__pyx_v_src_strides[0]); /* ""View.MemoryView"":1133 * cdef Py_ssize_t dst_extent = dst_shape[0] * cdef Py_ssize_t src_stride = src_strides[0] * cdef Py_ssize_t dst_stride = dst_strides[0] # <<<<<<<<<<<<<< * * if ndim == 1: */ __pyx_v_dst_stride = (__pyx_v_dst_strides[0]); /* ""View.MemoryView"":1135 * cdef Py_ssize_t dst_stride = dst_strides[0] * * if ndim == 1: # <<<<<<<<<<<<<< * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): */ __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); if (__pyx_t_1) { /* ""View.MemoryView"":1136 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * dst_extent) */ __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0); if (__pyx_t_2) { } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L5_bool_binop_done; } __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0); if (__pyx_t_2) { } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L5_bool_binop_done; } /* ""View.MemoryView"":1137 * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< * memcpy(dst_data, src_data, itemsize * dst_extent) * else: */ __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize); if (__pyx_t_2) { __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride)); } __pyx_t_3 = (__pyx_t_2 != 0); __pyx_t_1 = __pyx_t_3; __pyx_L5_bool_binop_done:; /* ""View.MemoryView"":1136 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * 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<<<<<<<<<<<<<< * * if not slice_is_contig(src, order, ndim): */ __pyx_t_2 = (__pyx_slices_overlap((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize) != 0); if (__pyx_t_2) { /* ""View.MemoryView"":1288 * if slices_overlap(&src, &dst, ndim, itemsize): * * if not slice_is_contig(src, order, ndim): # <<<<<<<<<<<<<< * order = get_best_order(&dst, ndim) * */ __pyx_t_2 = ((!(__pyx_memviewslice_is_contig(__pyx_v_src, __pyx_v_order, __pyx_v_ndim) != 0)) != 0); if (__pyx_t_2) { /* ""View.MemoryView"":1289 * * if not slice_is_contig(src, order, ndim): * order = get_best_order(&dst, ndim) # <<<<<<<<<<<<<< * * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) */ __pyx_v_order = __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim); /* ""View.MemoryView"":1288 * if slices_overlap(&src, &dst, ndim, itemsize): * * if not slice_is_contig(src, order, ndim): # <<<<<<<<<<<<<< * order = get_best_order(&dst, ndim) * */ } /* ""View.MemoryView"":1291 * order = get_best_order(&dst, ndim) * * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) # <<<<<<<<<<<<<< * src = tmp * */ __pyx_t_6 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_6 == NULL)) __PYX_ERR(1, 1291, __pyx_L1_error) __pyx_v_tmpdata = __pyx_t_6; /* ""View.MemoryView"":1292 * * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) * src = tmp # <<<<<<<<<<<<<< * * if not broadcasting: */ __pyx_v_src = __pyx_v_tmp; /* ""View.MemoryView"":1286 * _err_dim(ValueError, ""Dimension %d is not direct"", i) * * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< * * if not slice_is_contig(src, order, ndim): */ } /* ""View.MemoryView"":1294 * src = tmp * * if not broadcasting: # <<<<<<<<<<<<<< * * */ __pyx_t_2 = ((!(__pyx_v_broadcasting != 0)) != 0); if (__pyx_t_2) { /* ""View.MemoryView"":1297 * * * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< * direct_copy = slice_is_contig(dst, 'C', ndim) * elif slice_is_contig(src, 'F', ndim): */ __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'C', __pyx_v_ndim) != 0); if (__pyx_t_2) { /* ""View.MemoryView"":1298 * * if slice_is_contig(src, 'C', ndim): * direct_copy = slice_is_contig(dst, 'C', ndim) # <<<<<<<<<<<<<< * elif slice_is_contig(src, 'F', ndim): * direct_copy = slice_is_contig(dst, 'F', ndim) */ __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'C', __pyx_v_ndim); /* ""View.MemoryView"":1297 * * * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< * direct_copy = slice_is_contig(dst, 'C', ndim) * elif slice_is_contig(src, 'F', ndim): */ goto __pyx_L12; } /* ""View.MemoryView"":1299 * if slice_is_contig(src, 'C', ndim): * direct_copy = slice_is_contig(dst, 'C', ndim) * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< * direct_copy = slice_is_contig(dst, 'F', ndim) * */ __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'F', __pyx_v_ndim) != 0); if (__pyx_t_2) { /* ""View.MemoryView"":1300 * direct_copy = slice_is_contig(dst, 'C', 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__pyx_v_ndim, 0); /* ""View.MemoryView"":1305 * * refcount_copying(&dst, dtype_is_object, ndim, False) * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) # <<<<<<<<<<<<<< * refcount_copying(&dst, dtype_is_object, ndim, True) * free(tmpdata) */ memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim)); /* ""View.MemoryView"":1306 * refcount_copying(&dst, dtype_is_object, ndim, False) * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< * free(tmpdata) * return 0 */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); /* ""View.MemoryView"":1307 * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) * refcount_copying(&dst, dtype_is_object, ndim, True) * free(tmpdata) # <<<<<<<<<<<<<< * return 0 * */ free(__pyx_v_tmpdata); /* ""View.MemoryView"":1308 * refcount_copying(&dst, dtype_is_object, ndim, True) * free(tmpdata) 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__pyx_t_3 = (__pyx_v_inc != 0); if (__pyx_t_3) { /* ""View.MemoryView"":1368 * if ndim == 1: * if inc: * Py_INCREF(( data)[0]) # <<<<<<<<<<<<<< * else: * Py_DECREF(( data)[0]) */ Py_INCREF((((PyObject **)__pyx_v_data)[0])); /* ""View.MemoryView"":1367 * for i in range(shape[0]): * if ndim == 1: * if inc: # <<<<<<<<<<<<<< * Py_INCREF(( data)[0]) * else: */ goto __pyx_L6; } /* ""View.MemoryView"":1370 * Py_INCREF(( data)[0]) * else: * Py_DECREF(( data)[0]) # <<<<<<<<<<<<<< * else: * refcount_objects_in_slice(data, shape + 1, strides + 1, */ /*else*/ { Py_DECREF((((PyObject **)__pyx_v_data)[0])); } __pyx_L6:; /* ""View.MemoryView"":1366 * * for i in range(shape[0]): * if ndim == 1: # <<<<<<<<<<<<<< * if inc: * Py_INCREF(( data)[0]) */ goto __pyx_L5; } /* ""View.MemoryView"":1372 * Py_DECREF(( data)[0]) * else: * refcount_objects_in_slice(data, shape + 1, strides + 1, # <<<<<<<<<<<<<< * ndim - 1, inc) * */ /*else*/ { /* ""View.MemoryView"":1373 * else: * refcount_objects_in_slice(data, 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__pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item, int __pyx_v_dtype_is_object) { /* ""View.MemoryView"":1384 * size_t itemsize, void *item, * bint dtype_is_object) nogil: * refcount_copying(dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim, * itemsize, item) */ __pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 0); /* ""View.MemoryView"":1385 * bint dtype_is_object) nogil: * refcount_copying(dst, dtype_is_object, ndim, False) * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim, # <<<<<<<<<<<<<< * itemsize, item) * refcount_copying(dst, dtype_is_object, ndim, True) */ __pyx_memoryview__slice_assign_scalar(__pyx_v_dst->data, __pyx_v_dst->shape, __pyx_v_dst->strides, __pyx_v_ndim, __pyx_v_itemsize, __pyx_v_item); /* ""View.MemoryView"":1387 * _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim, * itemsize, item) * refcount_copying(dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< * * */ __pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 1); /* ""View.MemoryView"":1381 * * @cname('__pyx_memoryview_slice_assign_scalar') * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim, # <<<<<<<<<<<<<< * size_t itemsize, void *item, * bint dtype_is_object) nogil: */ /* function exit code */ } /* ""View.MemoryView"":1391 * * @cname('__pyx_memoryview__slice_assign_scalar') * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< * Py_ssize_t *strides, int ndim, * size_t itemsize, void *item) nogil: */ static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item) { CYTHON_UNUSED Py_ssize_t __pyx_v_i; Py_ssize_t __pyx_v_stride; Py_ssize_t __pyx_v_extent; int __pyx_t_1; Py_ssize_t __pyx_t_2; Py_ssize_t __pyx_t_3; /* ""View.MemoryView"":1395 * size_t itemsize, void *item) nogil: * cdef Py_ssize_t i * cdef Py_ssize_t stride = strides[0] # <<<<<<<<<<<<<< * cdef Py_ssize_t extent = shape[0] * */ __pyx_v_stride = (__pyx_v_strides[0]); /* ""View.MemoryView"":1396 * cdef Py_ssize_t i * cdef Py_ssize_t stride = strides[0] * cdef Py_ssize_t extent = shape[0] # <<<<<<<<<<<<<< * * if ndim == 1: */ __pyx_v_extent = (__pyx_v_shape[0]); /* ""View.MemoryView"":1398 * cdef Py_ssize_t extent = shape[0] * * if ndim == 1: # <<<<<<<<<<<<<< * for i in range(extent): * memcpy(data, item, itemsize) */ __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); if (__pyx_t_1) { /* ""View.MemoryView"":1399 * * if ndim == 1: * for i in range(extent): # <<<<<<<<<<<<<< * memcpy(data, item, itemsize) * data += stride */ __pyx_t_2 = __pyx_v_extent; for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; /* ""View.MemoryView"":1400 * if ndim == 1: * for i in range(extent): * memcpy(data, item, itemsize) # <<<<<<<<<<<<<< * data += stride * else: */ memcpy(__pyx_v_data, __pyx_v_item, __pyx_v_itemsize); /* ""View.MemoryView"":1401 * for i in range(extent): * memcpy(data, item, itemsize) * data += stride # <<<<<<<<<<<<<< * else: * for i in range(extent): */ __pyx_v_data = (__pyx_v_data + __pyx_v_stride); } /* ""View.MemoryView"":1398 * cdef Py_ssize_t extent = shape[0] * * if ndim == 1: # <<<<<<<<<<<<<< * for i in range(extent): * memcpy(data, item, itemsize) */ goto __pyx_L3; } /* ""View.MemoryView"":1403 * data += stride * else: * for i in range(extent): # <<<<<<<<<<<<<< * _slice_assign_scalar(data, shape + 1, strides + 1, * ndim - 1, itemsize, item) */ /*else*/ { __pyx_t_2 = __pyx_v_extent; for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; /* ""View.MemoryView"":1404 * else: * for i in range(extent): * _slice_assign_scalar(data, shape + 1, strides + 1, # <<<<<<<<<<<<<< * ndim - 1, itemsize, item) * data += stride */ __pyx_memoryview__slice_assign_scalar(__pyx_v_data, (__pyx_v_shape + 1), (__pyx_v_strides + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize, __pyx_v_item); /* ""View.MemoryView"":1406 * _slice_assign_scalar(data, shape + 1, strides + 1, * ndim - 1, itemsize, item) * data += stride # <<<<<<<<<<<<<< * * */ __pyx_v_data = (__pyx_v_data + __pyx_v_stride); } } __pyx_L3:; /* ""View.MemoryView"":1391 * * @cname('__pyx_memoryview__slice_assign_scalar') * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<< * Py_ssize_t *strides, int ndim, * size_t itemsize, void *item) nogil: */ /* function exit code */ } static struct __pyx_vtabstruct_array __pyx_vtable_array; static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k) { struct __pyx_array_obj *p; PyObject *o; if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { o = (*t->tp_alloc)(t, 0); } else { o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); } if (unlikely(!o)) return 0; p = ((struct __pyx_array_obj *)o); p->__pyx_vtab = __pyx_vtabptr_array; p->mode = ((PyObject*)Py_None); Py_INCREF(Py_None); p->_format = ((PyObject*)Py_None); Py_INCREF(Py_None); if (unlikely(__pyx_array___cinit__(o, a, k) < 0)) goto bad; return o; bad: Py_DECREF(o); o = 0; return NULL; } static void __pyx_tp_dealloc_array(PyObject *o) { struct __pyx_array_obj *p = (struct __pyx_array_obj *)o; #if PY_VERSION_HEX >= 0x030400a1 if (unlikely(Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) { if (PyObject_CallFinalizerFromDealloc(o)) return; } #endif { PyObject *etype, *eval, *etb; PyErr_Fetch(&etype, &eval, &etb); ++Py_REFCNT(o); __pyx_array___dealloc__(o); --Py_REFCNT(o); PyErr_Restore(etype, eval, etb); } Py_CLEAR(p->mode); Py_CLEAR(p->_format); (*Py_TYPE(o)->tp_free)(o); } static PyObject *__pyx_sq_item_array(PyObject *o, Py_ssize_t i) { PyObject *r; PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0; r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); Py_DECREF(x); return r; } static int __pyx_mp_ass_subscript_array(PyObject *o, PyObject *i, PyObject *v) { if (v) { return __pyx_array___setitem__(o, i, v); } else { PyErr_Format(PyExc_NotImplementedError, ""Subscript deletion not supported by %.200s"", Py_TYPE(o)->tp_name); return -1; } } static PyObject *__pyx_tp_getattro_array(PyObject *o, PyObject *n) { PyObject *v = PyObject_GenericGetAttr(o, n); if (!v && PyErr_ExceptionMatches(PyExc_AttributeError)) { PyErr_Clear(); v = __pyx_array___getattr__(o, n); } return v; } static PyObject *__pyx_getprop___pyx_array_memview(PyObject *o, CYTHON_UNUSED void *x) { return __pyx_pw_15View_dot_MemoryView_5array_7memview_1__get__(o); } static PyMethodDef __pyx_methods_array[] = { {""__getattr__"", (PyCFunction)__pyx_array___getattr__, METH_O|METH_COEXIST, 0}, {0, 0, 0, 0} }; static struct PyGetSetDef __pyx_getsets_array[] = { {(char *)""memview"", __pyx_getprop___pyx_array_memview, 0, (char *)0, 0}, {0, 0, 0, 0, 0} }; static PySequenceMethods __pyx_tp_as_sequence_array = { 0, /*sq_length*/ 0, /*sq_concat*/ 0, /*sq_repeat*/ __pyx_sq_item_array, /*sq_item*/ 0, /*sq_slice*/ 0, /*sq_ass_item*/ 0, /*sq_ass_slice*/ 0, /*sq_contains*/ 0, /*sq_inplace_concat*/ 0, /*sq_inplace_repeat*/ }; static PyMappingMethods __pyx_tp_as_mapping_array = { 0, /*mp_length*/ __pyx_array___getitem__, /*mp_subscript*/ __pyx_mp_ass_subscript_array, /*mp_ass_subscript*/ }; static PyBufferProcs __pyx_tp_as_buffer_array = { #if PY_MAJOR_VERSION < 3 0, /*bf_getreadbuffer*/ #endif #if PY_MAJOR_VERSION < 3 0, /*bf_getwritebuffer*/ #endif #if PY_MAJOR_VERSION < 3 0, /*bf_getsegcount*/ #endif #if PY_MAJOR_VERSION < 3 0, /*bf_getcharbuffer*/ #endif __pyx_array_getbuffer, /*bf_getbuffer*/ 0, /*bf_releasebuffer*/ }; static PyTypeObject __pyx_type___pyx_array = { PyVarObject_HEAD_INIT(0, 0) ""wrap_cy.array"", /*tp_name*/ sizeof(struct __pyx_array_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_array, /*tp_dealloc*/ 0, /*tp_print*/ 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 0, /*tp_compare*/ #endif #if PY_MAJOR_VERSION >= 3 0, /*tp_as_async*/ #endif 0, /*tp_repr*/ 0, /*tp_as_number*/ &__pyx_tp_as_sequence_array, /*tp_as_sequence*/ &__pyx_tp_as_mapping_array, /*tp_as_mapping*/ 0, /*tp_hash*/ 0, /*tp_call*/ 0, /*tp_str*/ __pyx_tp_getattro_array, /*tp_getattro*/ 0, /*tp_setattro*/ &__pyx_tp_as_buffer_array, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ 0, /*tp_doc*/ 0, /*tp_traverse*/ 0, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ __pyx_methods_array, /*tp_methods*/ 0, /*tp_members*/ __pyx_getsets_array, /*tp_getset*/ 0, /*tp_base*/ 0, /*tp_dict*/ 0, /*tp_descr_get*/ 0, /*tp_descr_set*/ 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ __pyx_tp_new_array, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ 0, /*tp_mro*/ 0, /*tp_cache*/ 0, /*tp_subclasses*/ 0, /*tp_weaklist*/ 0, /*tp_del*/ 0, /*tp_version_tag*/ #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif }; static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { struct __pyx_MemviewEnum_obj *p; PyObject *o; if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { o = (*t->tp_alloc)(t, 0); } else { o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); } if (unlikely(!o)) return 0; p = ((struct __pyx_MemviewEnum_obj *)o); p->name = Py_None; Py_INCREF(Py_None); return o; } static void __pyx_tp_dealloc_Enum(PyObject *o) { struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; #if PY_VERSION_HEX >= 0x030400a1 if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { if (PyObject_CallFinalizerFromDealloc(o)) return; } #endif PyObject_GC_UnTrack(o); Py_CLEAR(p->name); (*Py_TYPE(o)->tp_free)(o); } static int __pyx_tp_traverse_Enum(PyObject *o, visitproc v, void *a) { int e; struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; if (p->name) { e = (*v)(p->name, a); if (e) return e; } return 0; } static int __pyx_tp_clear_Enum(PyObject *o) { PyObject* tmp; struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; tmp = ((PyObject*)p->name); p->name = Py_None; Py_INCREF(Py_None); Py_XDECREF(tmp); return 0; } static PyMethodDef __pyx_methods_Enum[] = { {0, 0, 0, 0} }; static PyTypeObject __pyx_type___pyx_MemviewEnum = { PyVarObject_HEAD_INIT(0, 0) ""wrap_cy.Enum"", /*tp_name*/ sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_Enum, /*tp_dealloc*/ 0, /*tp_print*/ 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 0, /*tp_compare*/ #endif #if PY_MAJOR_VERSION >= 3 0, /*tp_as_async*/ #endif __pyx_MemviewEnum___repr__, /*tp_repr*/ 0, /*tp_as_number*/ 0, /*tp_as_sequence*/ 0, /*tp_as_mapping*/ 0, /*tp_hash*/ 0, /*tp_call*/ 0, /*tp_str*/ 0, /*tp_getattro*/ 0, /*tp_setattro*/ 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ 0, /*tp_doc*/ __pyx_tp_traverse_Enum, /*tp_traverse*/ __pyx_tp_clear_Enum, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ __pyx_methods_Enum, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ 0, /*tp_dict*/ 0, /*tp_descr_get*/ 0, /*tp_descr_set*/ 0, /*tp_dictoffset*/ __pyx_MemviewEnum___init__, /*tp_init*/ 0, /*tp_alloc*/ __pyx_tp_new_Enum, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ 0, /*tp_mro*/ 0, /*tp_cache*/ 0, /*tp_subclasses*/ 0, /*tp_weaklist*/ 0, /*tp_del*/ 0, /*tp_version_tag*/ #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif }; static struct __pyx_vtabstruct_memoryview __pyx_vtable_memoryview; static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k) { struct __pyx_memoryview_obj *p; PyObject *o; if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { o = (*t->tp_alloc)(t, 0); } else { o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); } if (unlikely(!o)) return 0; p = ((struct __pyx_memoryview_obj *)o); p->__pyx_vtab = __pyx_vtabptr_memoryview; p->obj = Py_None; Py_INCREF(Py_None); p->_size = Py_None; Py_INCREF(Py_None); p->_array_interface = Py_None; Py_INCREF(Py_None); p->view.obj = NULL; if (unlikely(__pyx_memoryview___cinit__(o, a, k) < 0)) goto bad; return o; bad: Py_DECREF(o); o = 0; return NULL; } static void __pyx_tp_dealloc_memoryview(PyObject *o) { struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; #if PY_VERSION_HEX >= 0x030400a1 if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { if (PyObject_CallFinalizerFromDealloc(o)) return; } #endif PyObject_GC_UnTrack(o); { PyObject *etype, *eval, *etb; PyErr_Fetch(&etype, &eval, &etb); ++Py_REFCNT(o); __pyx_memoryview___dealloc__(o); --Py_REFCNT(o); PyErr_Restore(etype, eval, etb); } Py_CLEAR(p->obj); Py_CLEAR(p->_size); Py_CLEAR(p->_array_interface); (*Py_TYPE(o)->tp_free)(o); } static int __pyx_tp_traverse_memoryview(PyObject *o, visitproc v, void *a) { int e; struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; if (p->obj) { e = (*v)(p->obj, a); if (e) return e; } if (p->_size) { e = (*v)(p->_size, a); if (e) return e; } if (p->_array_interface) { e = (*v)(p->_array_interface, a); if (e) return e; } if (p->view.obj) { e = (*v)(p->view.obj, a); if (e) return e; } return 0; } static int __pyx_tp_clear_memoryview(PyObject *o) { PyObject* tmp; struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; tmp = ((PyObject*)p->obj); p->obj = Py_None; Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->_size); p->_size = Py_None; Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->_array_interface); p->_array_interface = Py_None; Py_INCREF(Py_None); Py_XDECREF(tmp); Py_CLEAR(p->view.obj); return 0; } static PyObject *__pyx_sq_item_memoryview(PyObject *o, Py_ssize_t i) { PyObject *r; PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0; r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); Py_DECREF(x); return r; } static int __pyx_mp_ass_subscript_memoryview(PyObject *o, PyObject *i, PyObject *v) { if (v) { return __pyx_memoryview___setitem__(o, i, v); } else { PyErr_Format(PyExc_NotImplementedError, ""Subscript deletion not supported by %.200s"", Py_TYPE(o)->tp_name); return -1; } } static PyObject *__pyx_getprop___pyx_memoryview_T(PyObject *o, CYTHON_UNUSED void *x) { return __pyx_pw_15View_dot_MemoryView_10memoryview_1T_1__get__(o); } static PyObject *__pyx_getprop___pyx_memoryview_base(PyObject *o, CYTHON_UNUSED void *x) { return __pyx_pw_15View_dot_MemoryView_10memoryview_4base_1__get__(o); } static PyObject *__pyx_getprop___pyx_memoryview_shape(PyObject *o, CYTHON_UNUSED void *x) { return __pyx_pw_15View_dot_MemoryView_10memoryview_5shape_1__get__(o); } static PyObject *__pyx_getprop___pyx_memoryview_strides(PyObject *o, 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(__pyx_m) { if (__pyx_d) { __Pyx_AddTraceback(""init wrap_cy"", __pyx_clineno, __pyx_lineno, __pyx_filename); } Py_DECREF(__pyx_m); __pyx_m = 0; } else if (!PyErr_Occurred()) { PyErr_SetString(PyExc_ImportError, ""init wrap_cy""); } __pyx_L0:; __Pyx_RefNannyFinishContext(); #if PY_MAJOR_VERSION < 3 return; #else return __pyx_m; #endif } /* --- Runtime support code --- */ /* Refnanny */ #if CYTHON_REFNANNY static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname) { PyObject *m = NULL, *p = NULL; void *r = NULL; m = PyImport_ImportModule((char *)modname); if (!m) goto end; p = PyObject_GetAttrString(m, (char *)""RefNannyAPI""); if (!p) goto end; r = PyLong_AsVoidPtr(p); end: Py_XDECREF(p); Py_XDECREF(m); return (__Pyx_RefNannyAPIStruct *)r; } #endif /* GetBuiltinName */ static PyObject *__Pyx_GetBuiltinName(PyObject *name) { PyObject* result = __Pyx_PyObject_GetAttrStr(__pyx_b, name); if (unlikely(!result)) { PyErr_Format(PyExc_NameError, #if PY_MAJOR_VERSION >= 3 ""name '%U' is not defined"", name); #else ""name '%.200s' is not defined"", PyString_AS_STRING(name)); #endif } return result; } /* GetModuleGlobalName */ static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name) { PyObject *result; #if !CYTHON_AVOID_BORROWED_REFS result = PyDict_GetItem(__pyx_d, name); if (likely(result)) { Py_INCREF(result); } else { #else result = PyObject_GetItem(__pyx_d, name); if (!result) { PyErr_Clear(); #endif result = __Pyx_GetBuiltinName(name); } return result; } /* PyFunctionFastCall */ #if CYTHON_FAST_PYCALL #include ""frameobject.h"" static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args, Py_ssize_t na, PyObject *globals) { PyFrameObject *f; PyThreadState *tstate = PyThreadState_GET(); PyObject **fastlocals; Py_ssize_t i; PyObject *result; assert(globals != NULL); /* XXX Perhaps we should create a specialized PyFrame_New() that doesn't take locals, but does take builtins without sanity checking them. */ assert(tstate != NULL); f = PyFrame_New(tstate, co, globals, NULL); if (f == NULL) { return NULL; } fastlocals = f->f_localsplus; for (i = 0; i < na; i++) { Py_INCREF(*args); fastlocals[i] = *args++; } result = PyEval_EvalFrameEx(f,0); ++tstate->recursion_depth; Py_DECREF(f); --tstate->recursion_depth; return result; } #if 1 || PY_VERSION_HEX < 0x030600B1 static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, int nargs, PyObject *kwargs) { PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func); PyObject *globals = PyFunction_GET_GLOBALS(func); PyObject *argdefs = PyFunction_GET_DEFAULTS(func); PyObject *closure; #if PY_MAJOR_VERSION >= 3 PyObject *kwdefs; #endif PyObject *kwtuple, **k; PyObject **d; Py_ssize_t nd; Py_ssize_t nk; PyObject *result; assert(kwargs == NULL || PyDict_Check(kwargs)); nk = kwargs ? PyDict_Size(kwargs) : 0; if (Py_EnterRecursiveCall((char*)"" while calling a Python object"")) { return NULL; } if ( #if PY_MAJOR_VERSION >= 3 co->co_kwonlyargcount == 0 && #endif likely(kwargs == NULL || nk == 0) && co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) { if (argdefs == NULL && co->co_argcount == nargs) { result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals); goto done; } else if (nargs == 0 && argdefs != NULL && co->co_argcount == Py_SIZE(argdefs)) { /* function called with no arguments, but all parameters have a default value: use default values as arguments .*/ args = &PyTuple_GET_ITEM(argdefs, 0); result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals); goto done; } } if (kwargs != NULL) { Py_ssize_t pos, i; kwtuple = PyTuple_New(2 * nk); if (kwtuple == NULL) { result = NULL; goto done; } k = &PyTuple_GET_ITEM(kwtuple, 0); pos = i = 0; while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) { Py_INCREF(k[i]); Py_INCREF(k[i+1]); i += 2; } nk = i / 2; } else { kwtuple = NULL; k = NULL; } closure = PyFunction_GET_CLOSURE(func); #if PY_MAJOR_VERSION >= 3 kwdefs = PyFunction_GET_KW_DEFAULTS(func); #endif if (argdefs != NULL) { d = &PyTuple_GET_ITEM(argdefs, 0); nd = Py_SIZE(argdefs); } else { d = NULL; nd = 0; } #if PY_MAJOR_VERSION >= 3 result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, args, nargs, k, (int)nk, d, (int)nd, kwdefs, closure); #else result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, args, nargs, k, (int)nk, d, (int)nd, closure); #endif Py_XDECREF(kwtuple); done: Py_LeaveRecursiveCall(); return result; } #endif // CPython < 3.6 #endif // CYTHON_FAST_PYCALL /* PyCFunctionFastCall */ #if CYTHON_FAST_PYCCALL static CYTHON_INLINE PyObject * __Pyx_PyCFunction_FastCall(PyObject *func_obj, PyObject **args, Py_ssize_t nargs) { PyCFunctionObject *func = (PyCFunctionObject*)func_obj; PyCFunction meth = PyCFunction_GET_FUNCTION(func); PyObject *self = PyCFunction_GET_SELF(func); assert(PyCFunction_Check(func)); assert(METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST))); assert(nargs >= 0); assert(nargs == 0 || args != NULL); /* _PyCFunction_FastCallDict() must not be called with an exception set, because it may clear it (directly or indirectly) and so the caller loses its exception */ assert(!PyErr_Occurred()); return (*((__Pyx_PyCFunctionFast)meth)) (self, args, nargs, NULL); } #endif // CYTHON_FAST_PYCCALL /* PyObjectCall */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { PyObject *result; ternaryfunc call = func->ob_type->tp_call; if (unlikely(!call)) return PyObject_Call(func, arg, kw); if (unlikely(Py_EnterRecursiveCall((char*)"" while calling a Python object""))) return NULL; result = (*call)(func, arg, kw); Py_LeaveRecursiveCall(); if (unlikely(!result) && unlikely(!PyErr_Occurred())) { PyErr_SetString( PyExc_SystemError, ""NULL result without error in PyObject_Call""); } return result; } #endif /* Import */ static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { PyObject *empty_list = 0; PyObject *module = 0; PyObject *global_dict = 0; PyObject *empty_dict = 0; PyObject *list; #if PY_VERSION_HEX < 0x03030000 PyObject *py_import; py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); if (!py_import) goto bad; #endif if (from_list) list = from_list; else { empty_list = PyList_New(0); if (!empty_list) goto bad; list = empty_list; } global_dict = PyModule_GetDict(__pyx_m); if (!global_dict) goto bad; empty_dict = PyDict_New(); if (!empty_dict) goto bad; { #if PY_MAJOR_VERSION >= 3 if (level == -1) { if (strchr(__Pyx_MODULE_NAME, '.')) { #if PY_VERSION_HEX < 0x03030000 PyObject *py_level = PyInt_FromLong(1); if (!py_level) goto bad; module = PyObject_CallFunctionObjArgs(py_import, name, global_dict, empty_dict, list, py_level, NULL); Py_DECREF(py_level); #else module = PyImport_ImportModuleLevelObject( name, global_dict, empty_dict, list, 1); #endif if (!module) { if (!PyErr_ExceptionMatches(PyExc_ImportError)) goto bad; PyErr_Clear(); } } level = 0; } #endif if (!module) { #if PY_VERSION_HEX < 0x03030000 PyObject *py_level = PyInt_FromLong(level); if (!py_level) goto bad; module = PyObject_CallFunctionObjArgs(py_import, name, global_dict, empty_dict, list, py_level, NULL); Py_DECREF(py_level); #else module = PyImport_ImportModuleLevelObject( name, global_dict, empty_dict, list, level); #endif } } bad: #if PY_VERSION_HEX < 0x03030000 Py_XDECREF(py_import); #endif Py_XDECREF(empty_list); Py_XDECREF(empty_dict); return module; } /* BytesEquals */ static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) { #if CYTHON_COMPILING_IN_PYPY return PyObject_RichCompareBool(s1, s2, equals); #else if (s1 == s2) { return (equals == Py_EQ); } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) { const char *ps1, *ps2; Py_ssize_t length = PyBytes_GET_SIZE(s1); if (length != PyBytes_GET_SIZE(s2)) return (equals == Py_NE); ps1 = PyBytes_AS_STRING(s1); ps2 = PyBytes_AS_STRING(s2); if (ps1[0] != ps2[0]) { return (equals == Py_NE); } else if (length == 1) { return (equals == Py_EQ); } else { int result = memcmp(ps1, ps2, (size_t)length); return (equals == Py_EQ) ? (result == 0) : (result != 0); } } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) { return (equals == Py_NE); } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) { return (equals == Py_NE); } else { int result; PyObject* py_result = PyObject_RichCompare(s1, s2, equals); if (!py_result) return -1; result = __Pyx_PyObject_IsTrue(py_result); Py_DECREF(py_result); return result; } #endif } /* UnicodeEquals */ static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) { #if CYTHON_COMPILING_IN_PYPY return PyObject_RichCompareBool(s1, s2, equals); #else #if PY_MAJOR_VERSION < 3 PyObject* owned_ref = NULL; #endif int s1_is_unicode, s2_is_unicode; if (s1 == s2) { goto return_eq; } s1_is_unicode = PyUnicode_CheckExact(s1); s2_is_unicode = PyUnicode_CheckExact(s2); #if PY_MAJOR_VERSION < 3 if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) { owned_ref = PyUnicode_FromObject(s2); if (unlikely(!owned_ref)) return -1; s2 = owned_ref; s2_is_unicode = 1; } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) { owned_ref = PyUnicode_FromObject(s1); if (unlikely(!owned_ref)) return -1; s1 = owned_ref; s1_is_unicode = 1; } else if (((!s2_is_unicode) & (!s1_is_unicode))) { return __Pyx_PyBytes_Equals(s1, s2, equals); } #endif if (s1_is_unicode & s2_is_unicode) { Py_ssize_t length; int kind; void *data1, *data2; if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0)) return -1; length = __Pyx_PyUnicode_GET_LENGTH(s1); if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) { goto return_ne; } kind = __Pyx_PyUnicode_KIND(s1); if (kind != __Pyx_PyUnicode_KIND(s2)) { goto return_ne; } data1 = __Pyx_PyUnicode_DATA(s1); data2 = __Pyx_PyUnicode_DATA(s2); if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) { goto return_ne; } else if (length == 1) { goto return_eq; } else { int result = memcmp(data1, data2, (size_t)(length * kind)); #if PY_MAJOR_VERSION < 3 Py_XDECREF(owned_ref); #endif return (equals == Py_EQ) ? (result == 0) : (result != 0); } } else if ((s1 == Py_None) & s2_is_unicode) { goto return_ne; } else if ((s2 == Py_None) & s1_is_unicode) { goto return_ne; } else { int result; PyObject* py_result = PyObject_RichCompare(s1, s2, equals); if (!py_result) return -1; result = __Pyx_PyObject_IsTrue(py_result); Py_DECREF(py_result); return result; } return_eq: #if PY_MAJOR_VERSION < 3 Py_XDECREF(owned_ref); #endif return (equals == Py_EQ); return_ne: #if PY_MAJOR_VERSION < 3 Py_XDECREF(owned_ref); #endif return (equals == Py_NE); #endif } /* PyObjectCallMethO */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { PyObject *self, *result; PyCFunction cfunc; cfunc = PyCFunction_GET_FUNCTION(func); self = PyCFunction_GET_SELF(func); if (unlikely(Py_EnterRecursiveCall((char*)"" while calling a Python object""))) return NULL; result = cfunc(self, arg); Py_LeaveRecursiveCall(); if (unlikely(!result) && unlikely(!PyErr_Occurred())) { PyErr_SetString( PyExc_SystemError, ""NULL result without error in PyObject_Call""); } return result; } #endif /* PyObjectCallOneArg */ #if CYTHON_COMPILING_IN_CPYTHON static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { PyObject *result; PyObject *args = PyTuple_New(1); if (unlikely(!args)) return NULL; Py_INCREF(arg); PyTuple_SET_ITEM(args, 0, arg); result = __Pyx_PyObject_Call(func, args, NULL); Py_DECREF(args); return result; } static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { #if CYTHON_FAST_PYCALL if (PyFunction_Check(func)) { return __Pyx_PyFunction_FastCall(func, &arg, 1); } #endif #ifdef __Pyx_CyFunction_USED if (likely(PyCFunction_Check(func) || PyObject_TypeCheck(func, __pyx_CyFunctionType))) { #else if (likely(PyCFunction_Check(func))) { #endif if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { return __Pyx_PyObject_CallMethO(func, arg); #if CYTHON_FAST_PYCCALL } else if (PyCFunction_GET_FLAGS(func) & METH_FASTCALL) { return __Pyx_PyCFunction_FastCall(func, &arg, 1); #endif } } return __Pyx__PyObject_CallOneArg(func, arg); } #else static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { PyObject *result; PyObject *args = PyTuple_Pack(1, arg); if (unlikely(!args)) return NULL; result = __Pyx_PyObject_Call(func, args, NULL); Py_DECREF(args); return result; } #endif /* PyObjectCallMethod1 */ static PyObject* __Pyx_PyObject_CallMethod1(PyObject* obj, PyObject* method_name, PyObject* arg) { PyObject *method, *result = NULL; method = __Pyx_PyObject_GetAttrStr(obj, method_name); if (unlikely(!method)) goto done; #if CYTHON_UNPACK_METHODS if (likely(PyMethod_Check(method))) { PyObject *self = PyMethod_GET_SELF(method); if (likely(self)) { PyObject *args; PyObject *function = PyMethod_GET_FUNCTION(method); #if CYTHON_FAST_PYCALL if (PyFunction_Check(function)) { PyObject *args[2] = {self, arg}; result = __Pyx_PyFunction_FastCall(function, args, 2); goto done; } #endif #if CYTHON_FAST_PYCCALL if (__Pyx_PyFastCFunction_Check(function)) { PyObject *args[2] = {self, arg}; result = __Pyx_PyCFunction_FastCall(function, args, 2); goto done; } #endif args = PyTuple_New(2); if (unlikely(!args)) goto done; Py_INCREF(self); PyTuple_SET_ITEM(args, 0, self); Py_INCREF(arg); PyTuple_SET_ITEM(args, 1, arg); Py_INCREF(function); Py_DECREF(method); method = NULL; result = __Pyx_PyObject_Call(function, args, NULL); Py_DECREF(args); Py_DECREF(function); return result; } } #endif result = __Pyx_PyObject_CallOneArg(method, arg); done: Py_XDECREF(method); return result; } /* append */ static CYTHON_INLINE int __Pyx_PyObject_Append(PyObject* L, PyObject* x) { if (likely(PyList_CheckExact(L))) { if (unlikely(__Pyx_PyList_Append(L, x) < 0)) return -1; } else { PyObject* retval = __Pyx_PyObject_CallMethod1(L, __pyx_n_s_append, x); if (unlikely(!retval)) return -1; Py_DECREF(retval); } return 0; } /* GetItemInt */ static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { PyObject *r; if (!j) return NULL; r = PyObject_GetItem(o, j); Py_DECREF(j); return r; } static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) { #if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS if (wraparound & unlikely(i < 0)) i += PyList_GET_SIZE(o); if ((!boundscheck) || likely((0 <= i) & (i < PyList_GET_SIZE(o)))) { PyObject *r = PyList_GET_ITEM(o, i); Py_INCREF(r); return r; } return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); #else return PySequence_GetItem(o, i); #endif } static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) { #if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS if (wraparound & unlikely(i < 0)) i += PyTuple_GET_SIZE(o); if ((!boundscheck) || likely((0 <= i) & (i < PyTuple_GET_SIZE(o)))) { PyObject *r = PyTuple_GET_ITEM(o, i); Py_INCREF(r); return r; } return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); #else return PySequence_GetItem(o, i); #endif } static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) { #if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS if (is_list || PyList_CheckExact(o)) { Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); if ((!boundscheck) || (likely((n >= 0) & (n < PyList_GET_SIZE(o))))) { PyObject *r = PyList_GET_ITEM(o, n); Py_INCREF(r); return r; } } else if (PyTuple_CheckExact(o)) { Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); if ((!boundscheck) || likely((n >= 0) & (n < PyTuple_GET_SIZE(o)))) { PyObject *r = PyTuple_GET_ITEM(o, n); Py_INCREF(r); return r; } } else { PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; if (likely(m && m->sq_item)) { if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { Py_ssize_t l = m->sq_length(o); if (likely(l >= 0)) { i += l; } else { if (!PyErr_ExceptionMatches(PyExc_OverflowError)) return NULL; PyErr_Clear(); } } return m->sq_item(o, i); } } #else if (is_list || PySequence_Check(o)) { return PySequence_GetItem(o, i); } #endif return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); } /* BufferFormatCheck */ static CYTHON_INLINE int __Pyx_IsLittleEndian(void) { unsigned int n = 1; return *(unsigned char*)(&n) != 0; } static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, __Pyx_BufFmt_StackElem* stack, __Pyx_TypeInfo* type) { stack[0].field = &ctx->root; stack[0].parent_offset = 0; ctx->root.type = type; ctx->root.name = ""buffer dtype""; ctx->root.offset = 0; ctx->head = stack; ctx->head->field = &ctx->root; ctx->fmt_offset = 0; ctx->head->parent_offset = 0; ctx->new_packmode = '@'; ctx->enc_packmode = '@'; ctx->new_count = 1; ctx->enc_count = 0; ctx->enc_type = 0; ctx->is_complex = 0; ctx->is_valid_array = 0; ctx->struct_alignment = 0; while (type->typegroup == 'S') { ++ctx->head; ctx->head->field = type->fields; ctx->head->parent_offset = 0; type = type->fields->type; } } static int __Pyx_BufFmt_ParseNumber(const char** ts) { int count; const char* t = *ts; if (*t < '0' || *t > '9') { return -1; } else { count = *t++ - '0'; while (*t >= '0' && *t < '9') { count *= 10; count += *t++ - '0'; } } *ts = t; return count; } static int __Pyx_BufFmt_ExpectNumber(const char **ts) { int number = __Pyx_BufFmt_ParseNumber(ts); if (number == -1) PyErr_Format(PyExc_ValueError,\ ""Does not understand character buffer dtype format string ('%c')"", **ts); return number; } static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { PyErr_Format(PyExc_ValueError, ""Unexpected format string character: '%c'"", ch); } static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { switch (ch) { case 'c': return ""'char'""; case 'b': return ""'signed char'""; case 'B': return ""'unsigned char'""; case 'h': return ""'short'""; case 'H': return ""'unsigned short'""; case 'i': return ""'int'""; case 'I': return ""'unsigned int'""; case 'l': return ""'long'""; case 'L': return ""'unsigned long'""; case 'q': return ""'long long'""; case 'Q': return ""'unsigned long long'""; case 'f': return (is_complex ? ""'complex float'"" : ""'float'""); case 'd': return (is_complex ? ""'complex double'"" : ""'double'""); case 'g': return (is_complex ? ""'complex long double'"" : ""'long double'""); case 'T': return ""a struct""; case 'O': return ""Python object""; case 'P': return ""a pointer""; case 's': case 'p': return ""a string""; case 0: return ""end""; default: return ""unparseable format string""; } } static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { switch (ch) { case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return 2; case 'i': case 'I': case 'l': case 'L': return 4; case 'q': case 'Q': return 8; case 'f': return (is_complex ? 8 : 4); case 'd': return (is_complex ? 16 : 8); case 'g': { PyErr_SetString(PyExc_ValueError, ""Python does not define a standard format string size for long double ('g')..""); return 0; } case 'O': case 'P': return sizeof(void*); default: __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { switch (ch) { case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return sizeof(short); case 'i': case 'I': return sizeof(int); case 'l': case 'L': return sizeof(long); #ifdef HAVE_LONG_LONG case 'q': case 'Q': return sizeof(PY_LONG_LONG); #endif case 'f': return sizeof(float) * (is_complex ? 2 : 1); case 'd': return sizeof(double) * (is_complex ? 2 : 1); case 'g': return sizeof(long double) * (is_complex ? 2 : 1); case 'O': case 'P': return sizeof(void*); default: { __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } } typedef struct { char c; short x; } __Pyx_st_short; typedef struct { char c; int x; } __Pyx_st_int; typedef struct { char c; long x; } __Pyx_st_long; typedef struct { char c; float x; } __Pyx_st_float; typedef struct { char c; double x; } __Pyx_st_double; typedef struct { char c; long double x; } __Pyx_st_longdouble; typedef struct { char c; void *x; } __Pyx_st_void_p; #ifdef HAVE_LONG_LONG typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong; #endif static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) { switch (ch) { case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short); case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int); case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long); #ifdef HAVE_LONG_LONG case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG); #endif case 'f': return sizeof(__Pyx_st_float) - sizeof(float); case 'd': return sizeof(__Pyx_st_double) - sizeof(double); case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double); case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*); default: __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } /* These are for computing the padding at the end of the struct to align on the first member of the struct. This will probably the same as above, but we don't have any guarantees. */ typedef struct { short x; char c; } __Pyx_pad_short; typedef struct { int x; char c; } __Pyx_pad_int; typedef struct { long x; char c; } __Pyx_pad_long; typedef struct { float x; char c; } __Pyx_pad_float; typedef struct { double x; char c; } __Pyx_pad_double; typedef struct { long double x; char c; } __Pyx_pad_longdouble; typedef struct { void *x; char c; } __Pyx_pad_void_p; #ifdef HAVE_LONG_LONG typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong; #endif static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) { switch (ch) { case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short); case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int); case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long); #ifdef HAVE_LONG_LONG case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG); #endif case 'f': return sizeof(__Pyx_pad_float) - sizeof(float); case 'd': return sizeof(__Pyx_pad_double) - sizeof(double); case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double); case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*); default: __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { switch (ch) { case 'c': return 'H'; case 'b': case 'h': case 'i': case 'l': case 'q': case 's': case 'p': return 'I'; case 'B': case 'H': case 'I': case 'L': case 'Q': return 'U'; case 'f': case 'd': case 'g': return (is_complex ? 'C' : 'R'); case 'O': return 'O'; case 'P': return 'P'; default: { __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } } static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) { if (ctx->head == NULL || ctx->head->field == &ctx->root) { const char* expected; const char* quote; if (ctx->head == NULL) { expected = ""end""; quote = """"; } else { expected = ctx->head->field->type->name; quote = ""'""; } PyErr_Format(PyExc_ValueError, ""Buffer dtype mismatch, expected %s%s%s but got %s"", quote, expected, quote, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex)); } else { __Pyx_StructField* field = ctx->head->field; __Pyx_StructField* parent = (ctx->head - 1)->field; PyErr_Format(PyExc_ValueError, ""Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'"", field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex), parent->type->name, field->name); } } static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) { char group; size_t size, offset, arraysize = 1; if (ctx->enc_type == 0) return 0; if (ctx->head->field->type->arraysize[0]) { int i, ndim = 0; if (ctx->enc_type == 's' || ctx->enc_type == 'p') { ctx->is_valid_array = ctx->head->field->type->ndim == 1; ndim = 1; if (ctx->enc_count != ctx->head->field->type->arraysize[0]) { PyErr_Format(PyExc_ValueError, ""Expected a dimension of size %zu, got %zu"", ctx->head->field->type->arraysize[0], ctx->enc_count); return -1; } } if (!ctx->is_valid_array) { PyErr_Format(PyExc_ValueError, ""Expected %d dimensions, got %d"", ctx->head->field->type->ndim, ndim); return -1; } for (i = 0; i < ctx->head->field->type->ndim; i++) { arraysize *= ctx->head->field->type->arraysize[i]; } ctx->is_valid_array = 0; ctx->enc_count = 1; } group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex); do { __Pyx_StructField* field = ctx->head->field; __Pyx_TypeInfo* type = field->type; if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') { size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex); } else { size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex); } if (ctx->enc_packmode == '@') { size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex); size_t align_mod_offset; if (align_at == 0) return -1; align_mod_offset = ctx->fmt_offset % align_at; if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset; if (ctx->struct_alignment == 0) ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type, ctx->is_complex); } if (type->size != size || type->typegroup != group) { if (type->typegroup == 'C' && type->fields != NULL) { size_t parent_offset = ctx->head->parent_offset + field->offset; ++ctx->head; ctx->head->field = type->fields; ctx->head->parent_offset = parent_offset; continue; } if ((type->typegroup == 'H' || group == 'H') && type->size == size) { } else { __Pyx_BufFmt_RaiseExpected(ctx); return -1; } } offset = ctx->head->parent_offset + field->offset; if (ctx->fmt_offset != offset) { PyErr_Format(PyExc_ValueError, ""Buffer dtype mismatch; next field is at offset %"" CYTHON_FORMAT_SSIZE_T ""d but %"" CYTHON_FORMAT_SSIZE_T ""d expected"", (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset); return -1; } ctx->fmt_offset += size; if (arraysize) ctx->fmt_offset += (arraysize - 1) * size; --ctx->enc_count; while (1) { if (field == &ctx->root) { ctx->head = NULL; if (ctx->enc_count != 0) { __Pyx_BufFmt_RaiseExpected(ctx); return -1; } break; } ctx->head->field = ++field; if (field->type == NULL) { --ctx->head; field = ctx->head->field; continue; } else if (field->type->typegroup == 'S') { size_t parent_offset = ctx->head->parent_offset + field->offset; if (field->type->fields->type == NULL) continue; field = field->type->fields; ++ctx->head; ctx->head->field = field; ctx->head->parent_offset = parent_offset; break; } else { break; } } } while (ctx->enc_count); ctx->enc_type = 0; ctx->is_complex = 0; return 0; } static CYTHON_INLINE PyObject * __pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) { const char *ts = *tsp; int i = 0, number; int ndim = ctx->head->field->type->ndim; ; ++ts; if (ctx->new_count != 1) { PyErr_SetString(PyExc_ValueError, ""Cannot handle repeated arrays in format string""); return NULL; } if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; while (*ts && *ts != ')') { switch (*ts) { case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; default: break; } number = __Pyx_BufFmt_ExpectNumber(&ts); if (number == -1) return NULL; if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i]) return PyErr_Format(PyExc_ValueError, ""Expected a dimension of size %zu, got %d"", ctx->head->field->type->arraysize[i], number); if (*ts != ',' && *ts != ')') return PyErr_Format(PyExc_ValueError, ""Expected a comma in format string, got '%c'"", *ts); if (*ts == ',') ts++; i++; } if (i != ndim) return PyErr_Format(PyExc_ValueError, ""Expected %d dimension(s), got %d"", ctx->head->field->type->ndim, i); if (!*ts) { PyErr_SetString(PyExc_ValueError, ""Unexpected end of format string, expected ')'""); return NULL; } ctx->is_valid_array = 1; ctx->new_count = 1; *tsp = ++ts; return Py_None; } static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) { int got_Z = 0; while (1) { switch(*ts) { case 0: if (ctx->enc_type != 0 && ctx->head == NULL) { __Pyx_BufFmt_RaiseExpected(ctx); return NULL; } if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; if (ctx->head != NULL) { __Pyx_BufFmt_RaiseExpected(ctx); return NULL; } return ts; case ' ': case '\r': case '\n': ++ts; break; case '<': if (!__Pyx_IsLittleEndian()) { PyErr_SetString(PyExc_ValueError, ""Little-endian buffer not supported on big-endian compiler""); return NULL; } ctx->new_packmode = '='; ++ts; break; case '>': case '!': if (__Pyx_IsLittleEndian()) { PyErr_SetString(PyExc_ValueError, ""Big-endian buffer not supported on little-endian compiler""); return NULL; } ctx->new_packmode = '='; ++ts; break; case '=': case '@': case '^': ctx->new_packmode = *ts++; break; case 'T': { const char* ts_after_sub; size_t i, struct_count = ctx->new_count; size_t struct_alignment = ctx->struct_alignment; ctx->new_count = 1; ++ts; if (*ts != '{') { PyErr_SetString(PyExc_ValueError, ""Buffer acquisition: Expected '{' after 'T'""); return NULL; } if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; ctx->enc_type = 0; ctx->enc_count = 0; ctx->struct_alignment = 0; ++ts; ts_after_sub = ts; for (i = 0; i != struct_count; ++i) { ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts); if (!ts_after_sub) return NULL; } ts = ts_after_sub; if (struct_alignment) ctx->struct_alignment = struct_alignment; } break; case '}': { size_t alignment = ctx->struct_alignment; ++ts; if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; ctx->enc_type = 0; if (alignment && ctx->fmt_offset % alignment) { ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment); } } return ts; case 'x': if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; ctx->fmt_offset += ctx->new_count; ctx->new_count = 1; ctx->enc_count = 0; ctx->enc_type = 0; ctx->enc_packmode = ctx->new_packmode; ++ts; break; case 'Z': got_Z = 1; ++ts; if (*ts != 'f' && *ts != 'd' && *ts != 'g') { __Pyx_BufFmt_RaiseUnexpectedChar('Z'); return NULL; } case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': case 'l': case 'L': case 'q': case 'Q': case 'f': case 'd': case 'g': case 'O': case 'p': if (ctx->enc_type == *ts && got_Z == ctx->is_complex && ctx->enc_packmode == ctx->new_packmode) { ctx->enc_count += ctx->new_count; ctx->new_count = 1; got_Z = 0; ++ts; break; } case 's': if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; ctx->enc_count = ctx->new_count; ctx->enc_packmode = ctx->new_packmode; ctx->enc_type = *ts; ctx->is_complex = got_Z; ++ts; ctx->new_count = 1; got_Z = 0; break; case ':': ++ts; while(*ts != ':') ++ts; ++ts; break; case '(': if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL; break; default: { int number = __Pyx_BufFmt_ExpectNumber(&ts); if (number == -1) return NULL; ctx->new_count = (size_t)number; } } } } static CYTHON_INLINE void __Pyx_ZeroBuffer(Py_buffer* buf) { buf->buf = NULL; buf->obj = NULL; buf->strides = __Pyx_zeros; buf->shape = __Pyx_zeros; buf->suboffsets = __Pyx_minusones; } static CYTHON_INLINE int __Pyx_GetBufferAndValidate( Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack) { if (obj == Py_None || obj == NULL) { __Pyx_ZeroBuffer(buf); return 0; } buf->buf = NULL; if (__Pyx_GetBuffer(obj, buf, flags) == -1) goto fail; if (buf->ndim != nd) { PyErr_Format(PyExc_ValueError, ""Buffer has wrong number of dimensions (expected %d, got %d)"", nd, buf->ndim); goto fail; } if (!cast) { __Pyx_BufFmt_Context ctx; __Pyx_BufFmt_Init(&ctx, stack, dtype); if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; } if ((unsigned)buf->itemsize != dtype->size) { PyErr_Format(PyExc_ValueError, ""Item size of buffer (%"" CYTHON_FORMAT_SSIZE_T ""d byte%s) does not match size of '%s' (%"" CYTHON_FORMAT_SSIZE_T ""d byte%s)"", buf->itemsize, (buf->itemsize > 1) ? ""s"" : """", dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? ""s"" : """"); goto fail; } if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones; return 0; fail:; __Pyx_ZeroBuffer(buf); return -1; } static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) { if (info->buf == NULL) return; if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL; __Pyx_ReleaseBuffer(info); } /* MemviewSliceInit */ static int __Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, int ndim, __Pyx_memviewslice *memviewslice, int memview_is_new_reference) { __Pyx_RefNannyDeclarations int i, retval=-1; Py_buffer *buf = &memview->view; __Pyx_RefNannySetupContext(""init_memviewslice"", 0); if (!buf) { PyErr_SetString(PyExc_ValueError, ""buf is NULL.""); goto fail; } else if (memviewslice->memview || memviewslice->data) { PyErr_SetString(PyExc_ValueError, ""memviewslice is already initialized!""); goto fail; } if (buf->strides) { for (i = 0; i < ndim; i++) { memviewslice->strides[i] = buf->strides[i]; } } else { Py_ssize_t stride = buf->itemsize; for (i = ndim - 1; i >= 0; i--) { memviewslice->strides[i] = stride; stride *= buf->shape[i]; } } for (i = 0; i < ndim; i++) { memviewslice->shape[i] = buf->shape[i]; if (buf->suboffsets) { memviewslice->suboffsets[i] = buf->suboffsets[i]; } else { memviewslice->suboffsets[i] = -1; } } memviewslice->memview = memview; memviewslice->data = (char *)buf->buf; if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) { Py_INCREF(memview); } retval = 0; goto no_fail; fail: memviewslice->memview = 0; memviewslice->data = 0; retval = -1; no_fail: __Pyx_RefNannyFinishContext(); return retval; } static CYTHON_INLINE void __pyx_fatalerror(const char *fmt, ...) { va_list vargs; char msg[200]; #ifdef HAVE_STDARG_PROTOTYPES va_start(vargs, fmt); #else va_start(vargs); #endif vsnprintf(msg, 200, fmt, vargs); Py_FatalError(msg); va_end(vargs); } static CYTHON_INLINE int __pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count, PyThread_type_lock lock) { int result; PyThread_acquire_lock(lock, 1); result = (*acquisition_count)++; PyThread_release_lock(lock); return result; } static CYTHON_INLINE int __pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count, PyThread_type_lock lock) { int result; PyThread_acquire_lock(lock, 1); result = (*acquisition_count)--; PyThread_release_lock(lock); return result; } static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) { int first_time; struct __pyx_memoryview_obj *memview = memslice->memview; if (!memview || (PyObject *) memview == Py_None) return; if (__pyx_get_slice_count(memview) < 0) __pyx_fatalerror(""Acquisition count is %d (line %d)"", __pyx_get_slice_count(memview), lineno); first_time = __pyx_add_acquisition_count(memview) == 0; if (first_time) { if (have_gil) { Py_INCREF((PyObject *) memview); } else { PyGILState_STATE _gilstate = PyGILState_Ensure(); Py_INCREF((PyObject *) memview); PyGILState_Release(_gilstate); } } } static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) { int last_time; struct __pyx_memoryview_obj *memview = memslice->memview; if (!memview ) { return; } else if ((PyObject *) memview == Py_None) { memslice->memview = NULL; return; } if (__pyx_get_slice_count(memview) <= 0) __pyx_fatalerror(""Acquisition count is %d (line %d)"", __pyx_get_slice_count(memview), lineno); last_time = __pyx_sub_acquisition_count(memview) == 1; memslice->data = NULL; if (last_time) { if (have_gil) { Py_CLEAR(memslice->memview); } else { PyGILState_STATE _gilstate = PyGILState_Ensure(); Py_CLEAR(memslice->memview); PyGILState_Release(_gilstate); } } else { memslice->memview = NULL; } } /* BufferIndexError */ static void __Pyx_RaiseBufferIndexError(int axis) { PyErr_Format(PyExc_IndexError, ""Out of bounds on buffer access (axis %d)"", axis); } /* RaiseArgTupleInvalid */ static void __Pyx_RaiseArgtupleInvalid( const char* func_name, int exact, Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found) { Py_ssize_t num_expected; const char *more_or_less; if (num_found < num_min) { num_expected = num_min; more_or_less = ""at least""; } else { num_expected = num_max; more_or_less = ""at most""; } if (exact) { more_or_less = ""exactly""; } PyErr_Format(PyExc_TypeError, ""%.200s() takes %.8s %"" CYTHON_FORMAT_SSIZE_T ""d positional argument%.1s (%"" CYTHON_FORMAT_SSIZE_T ""d given)"", func_name, more_or_less, num_expected, (num_expected == 1) ? """" : ""s"", num_found); } /* RaiseDoubleKeywords */ static void __Pyx_RaiseDoubleKeywordsError( const char* func_name, PyObject* kw_name) { PyErr_Format(PyExc_TypeError, #if PY_MAJOR_VERSION >= 3 ""%s() got multiple values for keyword argument '%U'"", func_name, kw_name); #else ""%s() got multiple values for keyword argument '%s'"", func_name, PyString_AsString(kw_name)); #endif } /* ParseKeywords */ static int __Pyx_ParseOptionalKeywords( PyObject *kwds, PyObject **argnames[], PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args, const char* function_name) { PyObject *key = 0, *value = 0; Py_ssize_t pos = 0; PyObject*** name; PyObject*** first_kw_arg = argnames + num_pos_args; while (PyDict_Next(kwds, &pos, &key, &value)) { name = first_kw_arg; while (*name && (**name != key)) name++; if (*name) { values[name-argnames] = value; continue; } name = first_kw_arg; #if PY_MAJOR_VERSION < 3 if (likely(PyString_CheckExact(key)) || likely(PyString_Check(key))) { while (*name) { if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) && _PyString_Eq(**name, key)) { values[name-argnames] = value; break; } name++; } if (*name) continue; else { PyObject*** argname = argnames; while (argname != first_kw_arg) { if ((**argname == key) || ( (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key)) && _PyString_Eq(**argname, key))) { goto arg_passed_twice; } argname++; } } } else #endif if (likely(PyUnicode_Check(key))) { while (*name) { int cmp = (**name == key) ? 0 : #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 : #endif PyUnicode_Compare(**name, key); if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; if (cmp == 0) { values[name-argnames] = value; break; } name++; } if (*name) continue; else { PyObject*** argname = argnames; while (argname != first_kw_arg) { int cmp = (**argname == key) ? 0 : #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 : #endif PyUnicode_Compare(**argname, key); if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; if (cmp == 0) goto arg_passed_twice; argname++; } } } else goto invalid_keyword_type; if (kwds2) { if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad; } else { goto invalid_keyword; } } return 0; arg_passed_twice: __Pyx_RaiseDoubleKeywordsError(function_name, key); goto bad; invalid_keyword_type: PyErr_Format(PyExc_TypeError, ""%.200s() keywords must be strings"", function_name); goto bad; invalid_keyword: PyErr_Format(PyExc_TypeError, #if PY_MAJOR_VERSION < 3 ""%.200s() got an unexpected keyword argument '%.200s'"", function_name, PyString_AsString(key)); #else ""%s() got an unexpected keyword argument '%U'"", function_name, key); #endif bad: return -1; } /* ArgTypeTest */ static void __Pyx_RaiseArgumentTypeInvalid(const char* name, PyObject *obj, PyTypeObject *type) { PyErr_Format(PyExc_TypeError, ""Argument '%.200s' has incorrect type (expected %.200s, got %.200s)"", name, type->tp_name, Py_TYPE(obj)->tp_name); } static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed, const char *name, int exact) { if (unlikely(!type)) { PyErr_SetString(PyExc_SystemError, ""Missing type object""); return 0; } if (none_allowed && obj == Py_None) return 1; else if (exact) { if (likely(Py_TYPE(obj) == type)) return 1; #if PY_MAJOR_VERSION == 2 else if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1; #endif } else { if (likely(PyObject_TypeCheck(obj, type))) return 1; } __Pyx_RaiseArgumentTypeInvalid(name, obj, type); return 0; } /* PyErrFetchRestore */ #if CYTHON_FAST_THREAD_STATE static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { PyObject *tmp_type, *tmp_value, *tmp_tb; tmp_type = tstate->curexc_type; tmp_value = tstate->curexc_value; tmp_tb = tstate->curexc_traceback; tstate->curexc_type = type; tstate->curexc_value = value; tstate->curexc_traceback = tb; Py_XDECREF(tmp_type); Py_XDECREF(tmp_value); Py_XDECREF(tmp_tb); } static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { *type = tstate->curexc_type; *value = tstate->curexc_value; *tb = tstate->curexc_traceback; tstate->curexc_type = 0; tstate->curexc_value = 0; tstate->curexc_traceback = 0; } #endif /* RaiseException */ #if PY_MAJOR_VERSION < 3 static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, CYTHON_UNUSED PyObject *cause) { __Pyx_PyThreadState_declare Py_XINCREF(type); if (!value || value == Py_None) value = NULL; else Py_INCREF(value); if (!tb || tb == Py_None) tb = NULL; else { Py_INCREF(tb); if (!PyTraceBack_Check(tb)) { PyErr_SetString(PyExc_TypeError, ""raise: arg 3 must be a traceback or None""); goto raise_error; } } if (PyType_Check(type)) { #if CYTHON_COMPILING_IN_PYPY if (!value) { Py_INCREF(Py_None); value = Py_None; } #endif PyErr_NormalizeException(&type, &value, &tb); } else { if (value) { PyErr_SetString(PyExc_TypeError, ""instance exception may not have a separate value""); goto raise_error; } value = type; type = (PyObject*) Py_TYPE(type); Py_INCREF(type); if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { PyErr_SetString(PyExc_TypeError, ""raise: exception class must be a subclass of BaseException""); goto raise_error; } } __Pyx_PyThreadState_assign __Pyx_ErrRestore(type, value, tb); return; raise_error: Py_XDECREF(value); Py_XDECREF(type); Py_XDECREF(tb); return; } #else static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { PyObject* owned_instance = NULL; if (tb == Py_None) { tb = 0; } else if (tb && !PyTraceBack_Check(tb)) { PyErr_SetString(PyExc_TypeError, ""raise: arg 3 must be a traceback or None""); goto bad; } if (value == Py_None) value = 0; if (PyExceptionInstance_Check(type)) { if (value) { PyErr_SetString(PyExc_TypeError, ""instance exception may not have a separate value""); goto bad; } value = type; type = (PyObject*) Py_TYPE(value); } else if (PyExceptionClass_Check(type)) { PyObject *instance_class = NULL; if (value && PyExceptionInstance_Check(value)) { instance_class = (PyObject*) Py_TYPE(value); if (instance_class != type) { int is_subclass = PyObject_IsSubclass(instance_class, type); if (!is_subclass) { instance_class = NULL; } else if (unlikely(is_subclass == -1)) { goto bad; } else { type = instance_class; } } } if (!instance_class) { PyObject *args; if (!value) args = PyTuple_New(0); else if (PyTuple_Check(value)) { Py_INCREF(value); args = value; } else args = PyTuple_Pack(1, value); if (!args) goto bad; owned_instance = PyObject_Call(type, args, NULL); Py_DECREF(args); if (!owned_instance) goto bad; value = owned_instance; if (!PyExceptionInstance_Check(value)) { PyErr_Format(PyExc_TypeError, ""calling %R should have returned an instance of "" ""BaseException, not %R"", type, Py_TYPE(value)); goto bad; } } } else { PyErr_SetString(PyExc_TypeError, ""raise: exception class must be a subclass of BaseException""); goto bad; } #if PY_VERSION_HEX >= 0x03030000 if (cause) { #else if (cause && cause != Py_None) { #endif PyObject *fixed_cause; if (cause == Py_None) { fixed_cause = NULL; } else if (PyExceptionClass_Check(cause)) { fixed_cause = PyObject_CallObject(cause, NULL); if (fixed_cause == NULL) goto bad; } else if (PyExceptionInstance_Check(cause)) { fixed_cause = cause; Py_INCREF(fixed_cause); } else { PyErr_SetString(PyExc_TypeError, ""exception causes must derive from "" ""BaseException""); goto bad; } PyException_SetCause(value, fixed_cause); } PyErr_SetObject(type, value); if (tb) { #if CYTHON_COMPILING_IN_PYPY PyObject *tmp_type, *tmp_value, *tmp_tb; PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); Py_INCREF(tb); PyErr_Restore(tmp_type, tmp_value, tb); Py_XDECREF(tmp_tb); #else PyThreadState *tstate = PyThreadState_GET(); PyObject* tmp_tb = tstate->curexc_traceback; if (tb != tmp_tb) { Py_INCREF(tb); tstate->curexc_traceback = tb; Py_XDECREF(tmp_tb); } #endif } bad: Py_XDECREF(owned_instance); return; } #endif /* None */ static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t a, Py_ssize_t b) { Py_ssize_t q = a / b; Py_ssize_t r = a - q*b; q -= ((r != 0) & ((r ^ b) < 0)); return q; } /* GetAttr */ static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) { #if CYTHON_COMPILING_IN_CPYTHON #if PY_MAJOR_VERSION >= 3 if (likely(PyUnicode_Check(n))) #else if (likely(PyString_Check(n))) #endif return __Pyx_PyObject_GetAttrStr(o, n); #endif return PyObject_GetAttr(o, n); } /* decode_c_string */ static CYTHON_INLINE PyObject* __Pyx_decode_c_string( const char* cstring, Py_ssize_t start, Py_ssize_t stop, const char* encoding, const char* errors, PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) { Py_ssize_t length; if (unlikely((start < 0) | (stop < 0))) { size_t slen = strlen(cstring); if (unlikely(slen > (size_t) PY_SSIZE_T_MAX)) { PyErr_SetString(PyExc_OverflowError, ""c-string too long to convert to Python""); return NULL; } length = (Py_ssize_t) slen; if (start < 0) { start += length; if (start < 0) start = 0; } if (stop < 0) stop += length; } length = stop - start; if (unlikely(length <= 0)) return PyUnicode_FromUnicode(NULL, 0); cstring += start; if (decode_func) { return decode_func(cstring, length, errors); } else { return PyUnicode_Decode(cstring, length, encoding, errors); } } /* RaiseTooManyValuesToUnpack */ static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { PyErr_Format(PyExc_ValueError, ""too many values to unpack (expected %"" CYTHON_FORMAT_SSIZE_T ""d)"", expected); } /* RaiseNeedMoreValuesToUnpack */ static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { PyErr_Format(PyExc_ValueError, ""need more than %"" CYTHON_FORMAT_SSIZE_T ""d value%.1s to unpack"", index, (index == 1) ? """" : ""s""); } /* RaiseNoneIterError */ static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { PyErr_SetString(PyExc_TypeError, ""'NoneType' object is not iterable""); } /* ExtTypeTest */ static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { if (unlikely(!type)) { PyErr_SetString(PyExc_SystemError, ""Missing type object""); return 0; } if (likely(PyObject_TypeCheck(obj, type))) return 1; PyErr_Format(PyExc_TypeError, ""Cannot convert %.200s to %.200s"", Py_TYPE(obj)->tp_name, type->tp_name); return 0; } /* SaveResetException */ #if CYTHON_FAST_THREAD_STATE static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { *type = tstate->exc_type; *value = tstate->exc_value; *tb = tstate->exc_traceback; Py_XINCREF(*type); Py_XINCREF(*value); Py_XINCREF(*tb); } static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { PyObject *tmp_type, *tmp_value, *tmp_tb; tmp_type = tstate->exc_type; tmp_value = tstate->exc_value; tmp_tb = tstate->exc_traceback; tstate->exc_type = type; tstate->exc_value = value; tstate->exc_traceback = tb; Py_XDECREF(tmp_type); Py_XDECREF(tmp_value); Py_XDECREF(tmp_tb); } #endif /* PyErrExceptionMatches */ #if CYTHON_FAST_THREAD_STATE static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err) { PyObject *exc_type = tstate->curexc_type; if (exc_type == err) return 1; if (unlikely(!exc_type)) return 0; return PyErr_GivenExceptionMatches(exc_type, err); } #endif /* GetException */ #if CYTHON_FAST_THREAD_STATE static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { #else static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) { #endif PyObject *local_type, *local_value, *local_tb; #if CYTHON_FAST_THREAD_STATE PyObject *tmp_type, *tmp_value, *tmp_tb; local_type = tstate->curexc_type; local_value = tstate->curexc_value; local_tb = tstate->curexc_traceback; tstate->curexc_type = 0; tstate->curexc_value = 0; tstate->curexc_traceback = 0; #else PyErr_Fetch(&local_type, &local_value, &local_tb); #endif PyErr_NormalizeException(&local_type, &local_value, &local_tb); #if CYTHON_FAST_THREAD_STATE if (unlikely(tstate->curexc_type)) #else if (unlikely(PyErr_Occurred())) #endif goto bad; #if PY_MAJOR_VERSION >= 3 if (local_tb) { if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) goto bad; } #endif Py_XINCREF(local_tb); Py_XINCREF(local_type); Py_XINCREF(local_value); *type = local_type; *value = local_value; *tb = local_tb; #if CYTHON_FAST_THREAD_STATE tmp_type = tstate->exc_type; tmp_value = tstate->exc_value; tmp_tb = tstate->exc_traceback; tstate->exc_type = local_type; tstate->exc_value = local_value; tstate->exc_traceback = local_tb; Py_XDECREF(tmp_type); Py_XDECREF(tmp_value); Py_XDECREF(tmp_tb); #else PyErr_SetExcInfo(local_type, local_value, local_tb); #endif return 0; bad: *type = 0; *value = 0; *tb = 0; Py_XDECREF(local_type); Py_XDECREF(local_value); Py_XDECREF(local_tb); return -1; } /* SwapException */ #if CYTHON_FAST_THREAD_STATE static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { PyObject *tmp_type, *tmp_value, *tmp_tb; tmp_type = tstate->exc_type; tmp_value = tstate->exc_value; tmp_tb = tstate->exc_traceback; tstate->exc_type = *type; tstate->exc_value = *value; tstate->exc_traceback = *tb; *type = tmp_type; *value = tmp_value; *tb = tmp_tb; } #else static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) { PyObject *tmp_type, *tmp_value, *tmp_tb; PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb); PyErr_SetExcInfo(*type, *value, *tb); *type = tmp_type; *value = tmp_value; *tb = tmp_tb; } #endif /* PyIntBinop */ #if !CYTHON_COMPILING_IN_PYPY static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED int inplace) { #if PY_MAJOR_VERSION < 3 if (likely(PyInt_CheckExact(op1))) { const long b = intval; long x; long a = PyInt_AS_LONG(op1); x = (long)((unsigned long)a + b); if (likely((x^a) >= 0 || (x^b) >= 0)) return PyInt_FromLong(x); return PyLong_Type.tp_as_number->nb_add(op1, op2); } #endif #if CYTHON_USE_PYLONG_INTERNALS if (likely(PyLong_CheckExact(op1))) { const long b = intval; long a, x; #ifdef HAVE_LONG_LONG const PY_LONG_LONG llb = intval; PY_LONG_LONG lla, llx; #endif const digit* digits = ((PyLongObject*)op1)->ob_digit; const Py_ssize_t size = Py_SIZE(op1); if (likely(__Pyx_sst_abs(size) <= 1)) { a = likely(size) ? digits[0] : 0; if (size == -1) a = -a; } else { switch (size) { case -2: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } case 2: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } case -3: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } case 3: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } case -4: if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } case 4: if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; #ifdef HAVE_LONG_LONG } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; #endif } default: return PyLong_Type.tp_as_number->nb_add(op1, op2); } } x = a + b; return PyLong_FromLong(x); #ifdef HAVE_LONG_LONG long_long: llx = lla + llb; return PyLong_FromLongLong(llx); #endif } #endif if (PyFloat_CheckExact(op1)) { const long b = intval; double a = PyFloat_AS_DOUBLE(op1); double result; PyFPE_START_PROTECT(""add"", return NULL) result = ((double)a) + (double)b; PyFPE_END_PROTECT(result) return PyFloat_FromDouble(result); } return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); } #endif /* None */ static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) { PyErr_Format(PyExc_UnboundLocalError, ""local variable '%s' referenced before assignment"", varname); } /* None */ static CYTHON_INLINE long __Pyx_div_long(long a, long b) { long q = a / b; long r = a - q*b; q -= ((r != 0) & ((r ^ b) < 0)); return q; } /* WriteUnraisableException */ static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno, CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename, int full_traceback, CYTHON_UNUSED int nogil) { PyObject *old_exc, *old_val, *old_tb; PyObject *ctx; __Pyx_PyThreadState_declare #ifdef WITH_THREAD PyGILState_STATE state; if (nogil) state = PyGILState_Ensure(); #ifdef _MSC_VER else state = (PyGILState_STATE)-1; #endif #endif __Pyx_PyThreadState_assign __Pyx_ErrFetch(&old_exc, &old_val, &old_tb); if (full_traceback) { Py_XINCREF(old_exc); Py_XINCREF(old_val); Py_XINCREF(old_tb); __Pyx_ErrRestore(old_exc, old_val, old_tb); PyErr_PrintEx(1); } #if PY_MAJOR_VERSION < 3 ctx = PyString_FromString(name); #else ctx = PyUnicode_FromString(name); #endif __Pyx_ErrRestore(old_exc, old_val, old_tb); if (!ctx) { PyErr_WriteUnraisable(Py_None); } else { PyErr_WriteUnraisable(ctx); Py_DECREF(ctx); } #ifdef WITH_THREAD if (nogil) PyGILState_Release(state); #endif } /* SetVTable */ static int __Pyx_SetVtable(PyObject *dict, void *vtable) { #if PY_VERSION_HEX >= 0x02070000 PyObject *ob = PyCapsule_New(vtable, 0, 0); #else PyObject *ob = PyCObject_FromVoidPtr(vtable, 0); #endif if (!ob) goto bad; if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0) goto bad; Py_DECREF(ob); return 0; bad: Py_XDECREF(ob); return -1; } /* CodeObjectCache */ static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { int start = 0, mid = 0, end = count - 1; if (end >= 0 && code_line > entries[end].code_line) { return count; } while (start < end) { mid = start + (end - start) / 2; if (code_line < entries[mid].code_line) { end = mid; } else if (code_line > entries[mid].code_line) { start = mid + 1; } else { return mid; } } if (code_line <= entries[mid].code_line) { return mid; } else { return mid + 1; } } static PyCodeObject *__pyx_find_code_object(int code_line) { PyCodeObject* code_object; int pos; if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { return NULL; } pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { return NULL; } code_object = __pyx_code_cache.entries[pos].code_object; Py_INCREF(code_object); return code_object; } static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { int pos, i; __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; if (unlikely(!code_line)) { return; } if (unlikely(!entries)) { entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); if (likely(entries)) { __pyx_code_cache.entries = entries; __pyx_code_cache.max_count = 64; __pyx_code_cache.count = 1; entries[0].code_line = code_line; entries[0].code_object = code_object; Py_INCREF(code_object); } return; } pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { PyCodeObject* tmp = entries[pos].code_object; entries[pos].code_object = code_object; Py_DECREF(tmp); return; } if (__pyx_code_cache.count == __pyx_code_cache.max_count) { int new_max = __pyx_code_cache.max_count + 64; entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( __pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry)); if (unlikely(!entries)) { return; } __pyx_code_cache.entries = entries; __pyx_code_cache.max_count = new_max; } for (i=__pyx_code_cache.count; i>pos; i--) { entries[i] = entries[i-1]; } entries[pos].code_line = code_line; entries[pos].code_object = code_object; __pyx_code_cache.count++; Py_INCREF(code_object); } /* AddTraceback */ #include ""compile.h"" #include ""frameobject.h"" #include ""traceback.h"" static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( const char *funcname, int c_line, int py_line, const char *filename) { PyCodeObject *py_code = 0; PyObject *py_srcfile = 0; PyObject *py_funcname = 0; #if PY_MAJOR_VERSION < 3 py_srcfile = PyString_FromString(filename); #else py_srcfile = PyUnicode_FromString(filename); #endif if (!py_srcfile) goto bad; if (c_line) { #if PY_MAJOR_VERSION < 3 py_funcname = PyString_FromFormat( ""%s (%s:%d)"", funcname, __pyx_cfilenm, c_line); #else py_funcname = PyUnicode_FromFormat( ""%s (%s:%d)"", funcname, __pyx_cfilenm, c_line); #endif } else { #if PY_MAJOR_VERSION < 3 py_funcname = PyString_FromString(funcname); #else py_funcname = PyUnicode_FromString(funcname); #endif } if (!py_funcname) goto bad; py_code = __Pyx_PyCode_New( 0, 0, 0, 0, 0, __pyx_empty_bytes, /*PyObject *code,*/ __pyx_empty_tuple, /*PyObject *consts,*/ __pyx_empty_tuple, /*PyObject *names,*/ __pyx_empty_tuple, /*PyObject *varnames,*/ __pyx_empty_tuple, /*PyObject *freevars,*/ __pyx_empty_tuple, /*PyObject *cellvars,*/ py_srcfile, /*PyObject *filename,*/ py_funcname, /*PyObject *name,*/ py_line, __pyx_empty_bytes /*PyObject *lnotab*/ ); Py_DECREF(py_srcfile); Py_DECREF(py_funcname); return py_code; bad: Py_XDECREF(py_srcfile); Py_XDECREF(py_funcname); return NULL; } static void __Pyx_AddTraceback(const char *funcname, int c_line, int py_line, const char *filename) { PyCodeObject *py_code = 0; PyFrameObject *py_frame = 0; py_code = __pyx_find_code_object(c_line ? c_line : py_line); if (!py_code) { py_code = __Pyx_CreateCodeObjectForTraceback( funcname, c_line, py_line, filename); if (!py_code) goto bad; __pyx_insert_code_object(c_line ? c_line : py_line, py_code); } py_frame = PyFrame_New( PyThreadState_GET(), /*PyThreadState *tstate,*/ py_code, /*PyCodeObject *code,*/ __pyx_d, /*PyObject *globals,*/ 0 /*PyObject *locals*/ ); if (!py_frame) goto bad; __Pyx_PyFrame_SetLineNumber(py_frame, py_line); PyTraceBack_Here(py_frame); bad: Py_XDECREF(py_code); Py_XDECREF(py_frame); } #if PY_MAJOR_VERSION < 3 static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); if (PyObject_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags); if (PyObject_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags); PyErr_Format(PyExc_TypeError, ""'%.200s' does not have the buffer interface"", Py_TYPE(obj)->tp_name); return -1; } static void __Pyx_ReleaseBuffer(Py_buffer *view) { PyObject *obj = view->obj; if (!obj) return; if (PyObject_CheckBuffer(obj)) { PyBuffer_Release(view); return; } Py_DECREF(obj); view->obj = NULL; } #endif /* MemviewSliceIsContig */ static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim) { int i, index, step, start; Py_ssize_t itemsize = mvs.memview->view.itemsize; if (order == 'F') { step = 1; start = 0; } else { step = -1; start = ndim - 1; } for (i = 0; i < ndim; i++) { index = start + step * i; if (mvs.suboffsets[index] >= 0 || mvs.strides[index] != itemsize) return 0; itemsize *= mvs.shape[index]; } return 1; } /* OverlappingSlices */ static void __pyx_get_array_memory_extents(__Pyx_memviewslice *slice, void **out_start, void **out_end, int ndim, size_t itemsize) { char *start, *end; int i; start = end = slice->data; for (i = 0; i < ndim; i++) { Py_ssize_t stride = slice->strides[i]; Py_ssize_t extent = slice->shape[i]; if (extent == 0) { *out_start = *out_end = start; return; } else { if (stride > 0) end += stride * (extent - 1); else start += stride * (extent - 1); } } *out_start = start; *out_end = end + itemsize; } static int __pyx_slices_overlap(__Pyx_memviewslice *slice1, __Pyx_memviewslice *slice2, int ndim, size_t itemsize) { void *start1, *end1, *start2, *end2; __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize); __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize); return (start1 < end2) && (start2 < end1); } /* Capsule */ static CYTHON_INLINE PyObject * __pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig) { PyObject *cobj; #if PY_VERSION_HEX >= 0x02070000 cobj = PyCapsule_New(p, sig, NULL); #else cobj = PyCObject_FromVoidPtr(p, NULL); #endif return cobj; } /* CIntFromPyVerify */ #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) #define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) #define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ {\ func_type value = func_value;\ if (sizeof(target_type) < sizeof(func_type)) {\ if (unlikely(value != (func_type) (target_type) value)) {\ func_type zero = 0;\ if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ return (target_type) -1;\ if (is_unsigned && unlikely(value < zero))\ goto raise_neg_overflow;\ else\ goto raise_overflow;\ }\ }\ return (target_type) value;\ } /* CIntToPy */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { const int neg_one = (int) -1, const_zero = (int) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(int) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(int) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); #endif } } else { if (sizeof(int) <= sizeof(long)) { return PyInt_FromLong((long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); #endif } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(int), little, !is_unsigned); } } /* CIntToPy */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(long) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(long) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); #endif } } else { if (sizeof(long) <= sizeof(long)) { return PyInt_FromLong((long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); #endif } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(long), little, !is_unsigned); } } /* Print */ #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION < 3 static PyObject *__Pyx_GetStdout(void) { PyObject *f = PySys_GetObject((char *)""stdout""); if (!f) { PyErr_SetString(PyExc_RuntimeError, ""lost sys.stdout""); } return f; } static int __Pyx_Print(PyObject* f, PyObject *arg_tuple, int newline) { int i; if (!f) { if (!(f = __Pyx_GetStdout())) return -1; } Py_INCREF(f); for (i=0; i < PyTuple_GET_SIZE(arg_tuple); i++) { PyObject* v; if (PyFile_SoftSpace(f, 1)) { if (PyFile_WriteString("" "", f) < 0) goto error; } v = PyTuple_GET_ITEM(arg_tuple, i); if (PyFile_WriteObject(v, f, Py_PRINT_RAW) < 0) goto error; if (PyString_Check(v)) { char *s = PyString_AsString(v); Py_ssize_t len = PyString_Size(v); if (len > 0) { switch (s[len-1]) { case ' ': break; case '\f': case '\r': case '\n': case '\t': case '\v': PyFile_SoftSpace(f, 0); break; default: break; } } } } if (newline) { if (PyFile_WriteString(""\n"", f) < 0) goto error; PyFile_SoftSpace(f, 0); } Py_DECREF(f); return 0; error: Py_DECREF(f); return -1; } #else static int __Pyx_Print(PyObject* stream, PyObject *arg_tuple, int newline) { PyObject* kwargs = 0; PyObject* result = 0; PyObject* end_string; if (unlikely(!__pyx_print)) { __pyx_print = PyObject_GetAttr(__pyx_b, __pyx_n_s_print); if (!__pyx_print) return -1; } if (stream) { kwargs = PyDict_New(); if (unlikely(!kwargs)) return -1; if (unlikely(PyDict_SetItem(kwargs, __pyx_n_s_file, stream) < 0)) goto bad; if (!newline) { end_string = PyUnicode_FromStringAndSize("" "", 1); if (unlikely(!end_string)) goto bad; if (PyDict_SetItem(kwargs, __pyx_n_s_end, end_string) < 0) { Py_DECREF(end_string); goto bad; } Py_DECREF(end_string); } } else if (!newline) { if (unlikely(!__pyx_print_kwargs)) { __pyx_print_kwargs = PyDict_New(); if (unlikely(!__pyx_print_kwargs)) return -1; end_string = PyUnicode_FromStringAndSize("" "", 1); if (unlikely(!end_string)) return -1; if (PyDict_SetItem(__pyx_print_kwargs, __pyx_n_s_end, end_string) < 0) { Py_DECREF(end_string); return -1; } Py_DECREF(end_string); } kwargs = __pyx_print_kwargs; } result = PyObject_Call(__pyx_print, arg_tuple, kwargs); if (unlikely(kwargs) && (kwargs != __pyx_print_kwargs)) Py_DECREF(kwargs); if (!result) return -1; Py_DECREF(result); return 0; bad: if (kwargs != __pyx_print_kwargs) Py_XDECREF(kwargs); return -1; } #endif /* MemviewSliceCopyTemplate */ static __Pyx_memviewslice __pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, const char *mode, int ndim, size_t sizeof_dtype, int contig_flag, int dtype_is_object) { __Pyx_RefNannyDeclarations int i; __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } }; struct __pyx_memoryview_obj *from_memview = from_mvs->memview; Py_buffer *buf = &from_memview->view; PyObject *shape_tuple = NULL; PyObject *temp_int = NULL; struct __pyx_array_obj *array_obj = NULL; struct __pyx_memoryview_obj *memview_obj = NULL; __Pyx_RefNannySetupContext(""__pyx_memoryview_copy_new_contig"", 0); for (i = 0; i < ndim; i++) { if (from_mvs->suboffsets[i] >= 0) { PyErr_Format(PyExc_ValueError, ""Cannot copy memoryview slice with "" ""indirect dimensions (axis %d)"", i); goto fail; } } shape_tuple = PyTuple_New(ndim); if (unlikely(!shape_tuple)) { goto fail; } __Pyx_GOTREF(shape_tuple); for(i = 0; i < ndim; i++) { temp_int = PyInt_FromSsize_t(from_mvs->shape[i]); if(unlikely(!temp_int)) { goto fail; } else { PyTuple_SET_ITEM(shape_tuple, i, temp_int); temp_int = NULL; } } array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL); if (unlikely(!array_obj)) { goto fail; } __Pyx_GOTREF(array_obj); memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( (PyObject *) array_obj, contig_flag, dtype_is_object, from_mvs->memview->typeinfo); if (unlikely(!memview_obj)) goto fail; if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0)) goto fail; if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim, dtype_is_object) < 0)) goto fail; goto no_fail; fail: __Pyx_XDECREF(new_mvs.memview); new_mvs.memview = NULL; new_mvs.data = NULL; no_fail: __Pyx_XDECREF(shape_tuple); __Pyx_XDECREF(temp_int); __Pyx_XDECREF(array_obj); __Pyx_RefNannyFinishContext(); return new_mvs; } /* CIntFromPy */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { const int neg_one = (int) -1, const_zero = (int) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(int) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (int) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (int) 0; case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) case 2: if (8 * sizeof(int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; case 3: if (8 * sizeof(int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; case 4: if (8 * sizeof(int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (int) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(int) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) #endif } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (int) 0; case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) case -2: if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 2: if (8 * sizeof(int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case -3: if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 3: if (8 * sizeof(int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case -4: if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 4: if (8 * sizeof(int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; } #endif if (sizeof(int) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) #endif } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, ""_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers""); #else int val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (int) -1; } } else { int val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (int) -1; val = __Pyx_PyInt_As_int(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, ""value too large to convert to int""); return (int) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, ""can't convert negative value to int""); return (int) -1; } /* PrintOne */ #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION < 3 static int __Pyx_PrintOne(PyObject* f, PyObject *o) { if (!f) { if (!(f = __Pyx_GetStdout())) return -1; } Py_INCREF(f); if (PyFile_SoftSpace(f, 0)) { if (PyFile_WriteString("" "", f) < 0) goto error; } if (PyFile_WriteObject(o, f, Py_PRINT_RAW) < 0) goto error; if (PyFile_WriteString(""\n"", f) < 0) goto error; Py_DECREF(f); return 0; error: Py_DECREF(f); return -1; /* the line below is just to avoid C compiler * warnings about unused functions */ return __Pyx_Print(f, NULL, 0); } #else static int __Pyx_PrintOne(PyObject* stream, PyObject *o) { int res; PyObject* arg_tuple = PyTuple_Pack(1, o); if (unlikely(!arg_tuple)) return -1; res = __Pyx_Print(stream, arg_tuple, 1); Py_DECREF(arg_tuple); return res; } #endif /* CIntFromPy */ static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) { const char neg_one = (char) -1, const_zero = (char) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(char) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (char) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (char) 0; case 1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0]) case 2: if (8 * sizeof(char) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) { return (char) (((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); } } break; case 3: if (8 * sizeof(char) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) { return (char) (((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); } } break; case 4: if (8 * sizeof(char) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) { return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (char) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(char) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) #endif } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (char) 0; case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(char, digit, +digits[0]) case -2: if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { return (char) (((char)-1)*(((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case 2: if (8 * sizeof(char) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { return (char) ((((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case -3: if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { return (char) (((char)-1)*(((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case 3: if (8 * sizeof(char) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { return (char) ((((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case -4: if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { return (char) (((char)-1)*(((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case 4: if (8 * sizeof(char) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { return (char) ((((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; } #endif if (sizeof(char) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(char) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x)) #endif } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, ""_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers""); #else char val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (char) -1; } } else { char val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (char) -1; val = __Pyx_PyInt_As_char(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, ""value too large to convert to char""); return (char) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, ""can't convert negative value to char""); return (char) -1; } /* CIntFromPy */ static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(long) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (long) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (long) 0; case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) case 2: if (8 * sizeof(long) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; case 3: if (8 * sizeof(long) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; case 4: if (8 * sizeof(long) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (long) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(long) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) #endif } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (long) 0; case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) case -2: if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 2: if (8 * sizeof(long) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case -3: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 3: if (8 * sizeof(long) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case -4: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 4: if (8 * sizeof(long) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; } #endif if (sizeof(long) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) #endif } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, ""_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers""); #else long val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (long) -1; } } else { long val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (long) -1; val = __Pyx_PyInt_As_long(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, ""value too large to convert to long""); return (long) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, ""can't convert negative value to long""); return (long) -1; } /* TypeInfoCompare */ static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b) { int i; if (!a || !b) return 0; if (a == b) return 1; if (a->size != b->size || a->typegroup != b->typegroup || a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) { if (a->typegroup == 'H' || b->typegroup == 'H') { return a->size == b->size; } else { return 0; } } if (a->ndim) { for (i = 0; i < a->ndim; i++) if (a->arraysize[i] != b->arraysize[i]) return 0; } if (a->typegroup == 'S') { if (a->flags != b->flags) return 0; if (a->fields || b->fields) { if (!(a->fields && b->fields)) return 0; for (i = 0; a->fields[i].type && b->fields[i].type; i++) { __Pyx_StructField *field_a = a->fields + i; __Pyx_StructField *field_b = b->fields + i; if (field_a->offset != field_b->offset || !__pyx_typeinfo_cmp(field_a->type, field_b->type)) return 0; } return !a->fields[i].type && !b->fields[i].type; } } return 1; } /* MemviewSliceValidateAndInit */ static int __pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec) { if (buf->shape[dim] <= 1) return 1; if (buf->strides) { if (spec & __Pyx_MEMVIEW_CONTIG) { if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) { if (buf->strides[dim] != sizeof(void *)) { PyErr_Format(PyExc_ValueError, ""Buffer is not indirectly contiguous "" ""in dimension %d."", dim); goto fail; } } else if (buf->strides[dim] != buf->itemsize) { PyErr_SetString(PyExc_ValueError, ""Buffer and memoryview are not contiguous "" ""in the same dimension.""); goto fail; } } if (spec & __Pyx_MEMVIEW_FOLLOW) { Py_ssize_t stride = buf->strides[dim]; if (stride < 0) stride = -stride; if (stride < buf->itemsize) { PyErr_SetString(PyExc_ValueError, ""Buffer and memoryview are not contiguous "" ""in the same dimension.""); goto fail; } } } else { if (spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1) { PyErr_Format(PyExc_ValueError, ""C-contiguous buffer is not contiguous in "" ""dimension %d"", dim); goto fail; } else if (spec & (__Pyx_MEMVIEW_PTR)) { PyErr_Format(PyExc_ValueError, ""C-contiguous buffer is not indirect in "" ""dimension %d"", dim); goto fail; } else if (buf->suboffsets) { PyErr_SetString(PyExc_ValueError, ""Buffer exposes suboffsets but no strides""); goto fail; } } return 1; fail: return 0; } static int __pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec) { if (spec & __Pyx_MEMVIEW_DIRECT) { if (buf->suboffsets && buf->suboffsets[dim] >= 0) { PyErr_Format(PyExc_ValueError, ""Buffer not compatible with direct access "" ""in dimension %d."", dim); goto fail; } } if (spec & __Pyx_MEMVIEW_PTR) { if (!buf->suboffsets || (buf->suboffsets && buf->suboffsets[dim] < 0)) { PyErr_Format(PyExc_ValueError, ""Buffer is not indirectly accessible "" ""in dimension %d."", dim); goto fail; } } return 1; fail: return 0; } static int __pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag) { int i; if (c_or_f_flag & __Pyx_IS_F_CONTIG) { Py_ssize_t stride = 1; for (i = 0; i < ndim; i++) { if (stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1) { PyErr_SetString(PyExc_ValueError, ""Buffer not fortran contiguous.""); goto fail; } stride = stride * buf->shape[i]; } } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) { Py_ssize_t stride = 1; for (i = ndim - 1; i >- 1; i--) { if (stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1) { PyErr_SetString(PyExc_ValueError, ""Buffer not C contiguous.""); goto fail; } stride = stride * buf->shape[i]; } } return 1; fail: return 0; } static int __Pyx_ValidateAndInit_memviewslice( int *axes_specs, int c_or_f_flag, int buf_flags, int ndim, __Pyx_TypeInfo *dtype, __Pyx_BufFmt_StackElem stack[], __Pyx_memviewslice *memviewslice, PyObject *original_obj) { struct __pyx_memoryview_obj *memview, *new_memview; __Pyx_RefNannyDeclarations Py_buffer *buf; int i, spec = 0, retval = -1; __Pyx_BufFmt_Context ctx; int from_memoryview = __pyx_memoryview_check(original_obj); __Pyx_RefNannySetupContext(""ValidateAndInit_memviewslice"", 0); if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *) original_obj)->typeinfo)) { memview = (struct __pyx_memoryview_obj *) original_obj; new_memview = NULL; } else { memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( original_obj, buf_flags, 0, dtype); new_memview = memview; if (unlikely(!memview)) goto fail; } buf = &memview->view; if (buf->ndim != ndim) { PyErr_Format(PyExc_ValueError, ""Buffer has wrong number of dimensions (expected %d, got %d)"", ndim, buf->ndim); goto fail; } if (new_memview) { __Pyx_BufFmt_Init(&ctx, stack, dtype); if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; } if ((unsigned) buf->itemsize != dtype->size) { PyErr_Format(PyExc_ValueError, ""Item size of buffer (%"" CYTHON_FORMAT_SSIZE_T ""u byte%s) "" ""does not match size of '%s' (%"" CYTHON_FORMAT_SSIZE_T ""u byte%s)"", buf->itemsize, (buf->itemsize > 1) ? ""s"" : """", dtype->name, dtype->size, (dtype->size > 1) ? ""s"" : """"); goto fail; } for (i = 0; i < ndim; i++) { spec = axes_specs[i]; if (!__pyx_check_strides(buf, i, ndim, spec)) goto fail; if (!__pyx_check_suboffsets(buf, i, ndim, spec)) goto fail; } if (buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag)) goto fail; if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice, new_memview != NULL) == -1)) { goto fail; } retval = 0; goto no_fail; fail: Py_XDECREF(new_memview); retval = -1; no_fail: __Pyx_RefNannyFinishContext(); return retval; } /* ObjectToMemviewSlice */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_int(PyObject *obj) { __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; __Pyx_BufFmt_StackElem stack[1]; int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) }; int retcode; if (obj == Py_None) { result.memview = (struct __pyx_memoryview_obj *) Py_None; return result; } retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG, (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 1, &__Pyx_TypeInfo_int, stack, &result, obj); if (unlikely(retcode == -1)) goto __pyx_fail; return result; __pyx_fail: result.memview = NULL; result.data = NULL; return result; } /* ObjectToMemviewSlice */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_float(PyObject *obj) { __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; __Pyx_BufFmt_StackElem stack[1]; int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) }; int retcode; if (obj == Py_None) { result.memview = (struct __pyx_memoryview_obj *) Py_None; return result; } retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG, (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 1, &__Pyx_TypeInfo_float, stack, &result, obj); if (unlikely(retcode == -1)) goto __pyx_fail; return result; __pyx_fail: result.memview = NULL; result.data = NULL; return result; } /* CheckBinaryVersion */ static int __Pyx_check_binary_version(void) { char ctversion[4], rtversion[4]; PyOS_snprintf(ctversion, 4, ""%d.%d"", PY_MAJOR_VERSION, PY_MINOR_VERSION); PyOS_snprintf(rtversion, 4, ""%s"", Py_GetVersion()); if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) { char message[200]; PyOS_snprintf(message, sizeof(message), ""compiletime version %s of module '%.100s' "" ""does not match runtime version %s"", ctversion, __Pyx_MODULE_NAME, rtversion); return PyErr_WarnEx(NULL, message, 1); } return 0; } /* InitStrings */ static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { while (t->p) { #if PY_MAJOR_VERSION < 3 if (t->is_unicode) { *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); } else if (t->intern) { *t->p = PyString_InternFromString(t->s); } else { *t->p = PyString_FromStringAndSize(t->s, t->n - 1); } #else if (t->is_unicode | t->is_str) { if (t->intern) { *t->p = PyUnicode_InternFromString(t->s); } else if (t->encoding) { *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); } else { *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); } } else { *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); } #endif if (!*t->p) return -1; ++t; } return 0; } static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); } static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) { Py_ssize_t ignore; return __Pyx_PyObject_AsStringAndSize(o, &ignore); } static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { #if CYTHON_COMPILING_IN_CPYTHON && (__PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT) if ( #if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII __Pyx_sys_getdefaultencoding_not_ascii && #endif PyUnicode_Check(o)) { #if PY_VERSION_HEX < 0x03030000 char* defenc_c; PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); if (!defenc) return NULL; defenc_c = PyBytes_AS_STRING(defenc); #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII { char* end = defenc_c + PyBytes_GET_SIZE(defenc); char* c; for (c = defenc_c; c < end; c++) { if ((unsigned char) (*c) >= 128) { PyUnicode_AsASCIIString(o); return NULL; } } } #endif *length = PyBytes_GET_SIZE(defenc); return defenc_c; #else if (__Pyx_PyUnicode_READY(o) == -1) return NULL; #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII if (PyUnicode_IS_ASCII(o)) { *length = PyUnicode_GET_LENGTH(o); return PyUnicode_AsUTF8(o); } else { PyUnicode_AsASCIIString(o); return NULL; } #else return PyUnicode_AsUTF8AndSize(o, length); #endif #endif } else #endif #if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) if (PyByteArray_Check(o)) { *length = PyByteArray_GET_SIZE(o); return PyByteArray_AS_STRING(o); } else #endif { char* result; int r = PyBytes_AsStringAndSize(o, &result, length); if (unlikely(r < 0)) { return NULL; } else { return result; } } } static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { int is_true = x == Py_True; if (is_true | (x == Py_False) | (x == Py_None)) return is_true; else return PyObject_IsTrue(x); } static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { #if CYTHON_USE_TYPE_SLOTS PyNumberMethods *m; #endif const char *name = NULL; PyObject *res = NULL; #if PY_MAJOR_VERSION < 3 if (PyInt_Check(x) || PyLong_Check(x)) #else if (PyLong_Check(x)) #endif return __Pyx_NewRef(x); #if CYTHON_USE_TYPE_SLOTS m = Py_TYPE(x)->tp_as_number; #if PY_MAJOR_VERSION < 3 if (m && m->nb_int) { name = ""int""; res = PyNumber_Int(x); } else if (m && m->nb_long) { name = ""long""; res = PyNumber_Long(x); } #else if (m && m->nb_int) { name = ""int""; res = PyNumber_Long(x); } #endif #else res = PyNumber_Int(x); #endif if (res) { #if PY_MAJOR_VERSION < 3 if (!PyInt_Check(res) && !PyLong_Check(res)) { #else if (!PyLong_Check(res)) { #endif PyErr_Format(PyExc_TypeError, ""__%.4s__ returned non-%.4s (type %.200s)"", name, name, Py_TYPE(res)->tp_name); Py_DECREF(res); return NULL; } } else if (!PyErr_Occurred()) { PyErr_SetString(PyExc_TypeError, ""an integer is required""); } return res; } static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { Py_ssize_t ival; PyObject *x; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_CheckExact(b))) { if (sizeof(Py_ssize_t) >= sizeof(long)) return PyInt_AS_LONG(b); else return PyInt_AsSsize_t(x); } #endif if (likely(PyLong_CheckExact(b))) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)b)->ob_digit; const Py_ssize_t size = Py_SIZE(b); if (likely(__Pyx_sst_abs(size) <= 1)) { ival = likely(size) ? digits[0] : 0; if (size == -1) ival = -ival; return ival; } else { switch (size) { case 2: if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -2: if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case 3: if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -3: if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case 4: if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -4: if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; } } #endif return PyLong_AsSsize_t(b); } x = PyNumber_Index(b); if (!x) return -1; ival = PyInt_AsSsize_t(x); Py_DECREF(x); return ival; } static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { return PyInt_FromSize_t(ival); } #endif /* Py_PYTHON_H */ ","C++" "Biophysics","maxscheurer/pycontact","testing/cython/wrap_cython.py",".py","216","16","# testing wrapper import matplotlib.pyplot as plt from wrap_cy import bla, test_sasa a = bla(2) print(a) import time start = time.time() r = test_sasa() stop = time.time() print(stop-start) plt.plot(r) plt.show() ","Python" "Biophysics","maxscheurer/pycontact","testing/cython/wrap.c",".c","75941","1974","/* Generated by Cython 0.25.2 */ /* BEGIN: Cython Metadata { ""distutils"": { ""depends"": [ ""gridsearch.C"" ] }, ""module_name"": ""wrap"" } END: Cython Metadata */ #define PY_SSIZE_T_CLEAN #include ""Python.h"" #ifndef Py_PYTHON_H #error Python headers needed to compile C extensions, please install development version of Python. #elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03020000) #error Cython requires Python 2.6+ or Python 3.2+. #else #define CYTHON_ABI ""0_25_2"" #include #ifndef offsetof #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) #endif #if !defined(WIN32) && !defined(MS_WINDOWS) #ifndef __stdcall #define __stdcall #endif #ifndef __cdecl #define __cdecl #endif #ifndef __fastcall #define __fastcall #endif #endif #ifndef DL_IMPORT #define DL_IMPORT(t) t #endif #ifndef DL_EXPORT #define DL_EXPORT(t) t #endif #ifndef HAVE_LONG_LONG #if PY_VERSION_HEX >= 0x03030000 || (PY_MAJOR_VERSION == 2 && PY_VERSION_HEX >= 0x02070000) #define HAVE_LONG_LONG #endif #endif #ifndef PY_LONG_LONG #define PY_LONG_LONG LONG_LONG #endif #ifndef Py_HUGE_VAL #define Py_HUGE_VAL HUGE_VAL #endif #ifdef PYPY_VERSION #define CYTHON_COMPILING_IN_PYPY 1 #define CYTHON_COMPILING_IN_PYSTON 0 #define CYTHON_COMPILING_IN_CPYTHON 0 #undef CYTHON_USE_TYPE_SLOTS #define CYTHON_USE_TYPE_SLOTS 0 #undef CYTHON_USE_ASYNC_SLOTS #define CYTHON_USE_ASYNC_SLOTS 0 #undef CYTHON_USE_PYLIST_INTERNALS #define CYTHON_USE_PYLIST_INTERNALS 0 #undef CYTHON_USE_UNICODE_INTERNALS #define CYTHON_USE_UNICODE_INTERNALS 0 #undef CYTHON_USE_UNICODE_WRITER #define CYTHON_USE_UNICODE_WRITER 0 #undef CYTHON_USE_PYLONG_INTERNALS #define CYTHON_USE_PYLONG_INTERNALS 0 #undef CYTHON_AVOID_BORROWED_REFS #define CYTHON_AVOID_BORROWED_REFS 1 #undef CYTHON_ASSUME_SAFE_MACROS #define CYTHON_ASSUME_SAFE_MACROS 0 #undef CYTHON_UNPACK_METHODS #define CYTHON_UNPACK_METHODS 0 #undef CYTHON_FAST_THREAD_STATE #define CYTHON_FAST_THREAD_STATE 0 #undef CYTHON_FAST_PYCALL #define CYTHON_FAST_PYCALL 0 #elif defined(PYSTON_VERSION) #define CYTHON_COMPILING_IN_PYPY 0 #define CYTHON_COMPILING_IN_PYSTON 1 #define CYTHON_COMPILING_IN_CPYTHON 0 #ifndef CYTHON_USE_TYPE_SLOTS #define CYTHON_USE_TYPE_SLOTS 1 #endif #undef CYTHON_USE_ASYNC_SLOTS #define CYTHON_USE_ASYNC_SLOTS 0 #undef CYTHON_USE_PYLIST_INTERNALS #define CYTHON_USE_PYLIST_INTERNALS 0 #ifndef CYTHON_USE_UNICODE_INTERNALS #define CYTHON_USE_UNICODE_INTERNALS 1 #endif #undef CYTHON_USE_UNICODE_WRITER #define CYTHON_USE_UNICODE_WRITER 0 #undef CYTHON_USE_PYLONG_INTERNALS #define CYTHON_USE_PYLONG_INTERNALS 0 #ifndef CYTHON_AVOID_BORROWED_REFS #define CYTHON_AVOID_BORROWED_REFS 0 #endif #ifndef CYTHON_ASSUME_SAFE_MACROS #define CYTHON_ASSUME_SAFE_MACROS 1 #endif #ifndef CYTHON_UNPACK_METHODS #define CYTHON_UNPACK_METHODS 1 #endif #undef CYTHON_FAST_THREAD_STATE #define CYTHON_FAST_THREAD_STATE 0 #undef CYTHON_FAST_PYCALL #define CYTHON_FAST_PYCALL 0 #else #define CYTHON_COMPILING_IN_PYPY 0 #define CYTHON_COMPILING_IN_PYSTON 0 #define CYTHON_COMPILING_IN_CPYTHON 1 #ifndef CYTHON_USE_TYPE_SLOTS #define CYTHON_USE_TYPE_SLOTS 1 #endif #if PY_MAJOR_VERSION < 3 #undef CYTHON_USE_ASYNC_SLOTS #define CYTHON_USE_ASYNC_SLOTS 0 #elif !defined(CYTHON_USE_ASYNC_SLOTS) #define CYTHON_USE_ASYNC_SLOTS 1 #endif #if PY_VERSION_HEX < 0x02070000 #undef CYTHON_USE_PYLONG_INTERNALS #define CYTHON_USE_PYLONG_INTERNALS 0 #elif !defined(CYTHON_USE_PYLONG_INTERNALS) #define CYTHON_USE_PYLONG_INTERNALS 1 #endif #ifndef CYTHON_USE_PYLIST_INTERNALS #define CYTHON_USE_PYLIST_INTERNALS 1 #endif #ifndef CYTHON_USE_UNICODE_INTERNALS #define CYTHON_USE_UNICODE_INTERNALS 1 #endif #if PY_VERSION_HEX < 0x030300F0 #undef CYTHON_USE_UNICODE_WRITER #define CYTHON_USE_UNICODE_WRITER 0 #elif !defined(CYTHON_USE_UNICODE_WRITER) #define CYTHON_USE_UNICODE_WRITER 1 #endif #ifndef CYTHON_AVOID_BORROWED_REFS #define CYTHON_AVOID_BORROWED_REFS 0 #endif #ifndef CYTHON_ASSUME_SAFE_MACROS #define CYTHON_ASSUME_SAFE_MACROS 1 #endif #ifndef CYTHON_UNPACK_METHODS #define CYTHON_UNPACK_METHODS 1 #endif #ifndef CYTHON_FAST_THREAD_STATE #define CYTHON_FAST_THREAD_STATE 1 #endif #ifndef CYTHON_FAST_PYCALL #define CYTHON_FAST_PYCALL 1 #endif #endif #if !defined(CYTHON_FAST_PYCCALL) #define CYTHON_FAST_PYCCALL (CYTHON_FAST_PYCALL && PY_VERSION_HEX >= 0x030600B1) #endif #if CYTHON_USE_PYLONG_INTERNALS #include ""longintrepr.h"" #undef SHIFT #undef BASE #undef MASK #endif #if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) #define Py_OptimizeFlag 0 #endif #define __PYX_BUILD_PY_SSIZE_T ""n"" #define CYTHON_FORMAT_SSIZE_T ""z"" #if PY_MAJOR_VERSION < 3 #define __Pyx_BUILTIN_MODULE_NAME ""__builtin__"" #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #define __Pyx_DefaultClassType PyClass_Type #else #define __Pyx_BUILTIN_MODULE_NAME ""builtins"" #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #define __Pyx_DefaultClassType PyType_Type #endif #ifndef Py_TPFLAGS_CHECKTYPES #define Py_TPFLAGS_CHECKTYPES 0 #endif #ifndef Py_TPFLAGS_HAVE_INDEX #define Py_TPFLAGS_HAVE_INDEX 0 #endif #ifndef Py_TPFLAGS_HAVE_NEWBUFFER #define Py_TPFLAGS_HAVE_NEWBUFFER 0 #endif #ifndef Py_TPFLAGS_HAVE_FINALIZE #define Py_TPFLAGS_HAVE_FINALIZE 0 #endif #ifndef METH_FASTCALL #define METH_FASTCALL 0x80 typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject **args, Py_ssize_t nargs, PyObject *kwnames); #else #define __Pyx_PyCFunctionFast _PyCFunctionFast #endif #if CYTHON_FAST_PYCCALL #define __Pyx_PyFastCFunction_Check(func)\ ((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST))))) #else #define __Pyx_PyFastCFunction_Check(func) 0 #endif #if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) #define CYTHON_PEP393_ENABLED 1 #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ 0 : _PyUnicode_Ready((PyObject *)(op))) #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u) #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u) #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) #else #define CYTHON_PEP393_ENABLED 0 #define PyUnicode_1BYTE_KIND 1 #define PyUnicode_2BYTE_KIND 2 #define PyUnicode_4BYTE_KIND 4 #define __Pyx_PyUnicode_READY(op) (0) #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111) #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE)) #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u)) #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i])) #define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch) #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u)) #endif #if CYTHON_COMPILING_IN_PYPY #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) #else #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check) #define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format) #define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, ""__format__"", ""O"", fmt) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) #define PyObject_Malloc(s) PyMem_Malloc(s) #define PyObject_Free(p) PyMem_Free(p) #define PyObject_Realloc(p) PyMem_Realloc(p) #endif #if CYTHON_COMPILING_IN_PYSTON #define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co) #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno) #else #define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0) #define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno) #endif #define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? 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if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { return NULL; } code_object = __pyx_code_cache.entries[pos].code_object; Py_INCREF(code_object); return code_object; } static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { int pos, i; __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; if (unlikely(!code_line)) { return; } if (unlikely(!entries)) { entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); if (likely(entries)) { __pyx_code_cache.entries = entries; __pyx_code_cache.max_count = 64; __pyx_code_cache.count = 1; entries[0].code_line = code_line; entries[0].code_object = code_object; Py_INCREF(code_object); } return; } pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { PyCodeObject* tmp = entries[pos].code_object; entries[pos].code_object = code_object; Py_DECREF(tmp); return; } if (__pyx_code_cache.count == __pyx_code_cache.max_count) { int new_max = __pyx_code_cache.max_count + 64; entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( __pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry)); if (unlikely(!entries)) { return; } __pyx_code_cache.entries = entries; __pyx_code_cache.max_count = new_max; } for (i=__pyx_code_cache.count; i>pos; i--) { entries[i] = entries[i-1]; } entries[pos].code_line = code_line; entries[pos].code_object = code_object; __pyx_code_cache.count++; Py_INCREF(code_object); } /* AddTraceback */ #include ""compile.h"" #include ""frameobject.h"" #include ""traceback.h"" static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( const char *funcname, int c_line, int py_line, const char *filename) { PyCodeObject *py_code = 0; PyObject *py_srcfile = 0; PyObject *py_funcname = 0; #if PY_MAJOR_VERSION < 3 py_srcfile = PyString_FromString(filename); #else py_srcfile = PyUnicode_FromString(filename); #endif if (!py_srcfile) goto bad; if (c_line) { #if PY_MAJOR_VERSION < 3 py_funcname = PyString_FromFormat( ""%s (%s:%d)"", funcname, __pyx_cfilenm, c_line); #else py_funcname = PyUnicode_FromFormat( ""%s (%s:%d)"", funcname, __pyx_cfilenm, c_line); #endif } else { #if PY_MAJOR_VERSION < 3 py_funcname = PyString_FromString(funcname); #else py_funcname = PyUnicode_FromString(funcname); #endif } if (!py_funcname) goto bad; py_code = __Pyx_PyCode_New( 0, 0, 0, 0, 0, __pyx_empty_bytes, /*PyObject *code,*/ __pyx_empty_tuple, /*PyObject *consts,*/ __pyx_empty_tuple, /*PyObject *names,*/ __pyx_empty_tuple, /*PyObject *varnames,*/ __pyx_empty_tuple, /*PyObject *freevars,*/ __pyx_empty_tuple, /*PyObject *cellvars,*/ py_srcfile, /*PyObject *filename,*/ py_funcname, /*PyObject *name,*/ py_line, __pyx_empty_bytes /*PyObject *lnotab*/ ); Py_DECREF(py_srcfile); Py_DECREF(py_funcname); return py_code; bad: Py_XDECREF(py_srcfile); Py_XDECREF(py_funcname); return NULL; } static void __Pyx_AddTraceback(const char *funcname, int c_line, int py_line, const char *filename) { PyCodeObject *py_code = 0; PyFrameObject *py_frame = 0; py_code = __pyx_find_code_object(c_line ? c_line : py_line); if (!py_code) { py_code = __Pyx_CreateCodeObjectForTraceback( funcname, c_line, py_line, filename); if (!py_code) goto bad; __pyx_insert_code_object(c_line ? c_line : py_line, py_code); } py_frame = PyFrame_New( PyThreadState_GET(), /*PyThreadState *tstate,*/ py_code, /*PyCodeObject *code,*/ __pyx_d, /*PyObject *globals,*/ 0 /*PyObject *locals*/ ); if (!py_frame) goto bad; __Pyx_PyFrame_SetLineNumber(py_frame, py_line); PyTraceBack_Here(py_frame); bad: Py_XDECREF(py_code); Py_XDECREF(py_frame); } /* CIntToPy */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { const int neg_one = (int) -1, const_zero = (int) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(int) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(int) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); #endif } } else { if (sizeof(int) <= sizeof(long)) { return PyInt_FromLong((long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); #endif } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(int), little, !is_unsigned); } } /* Print */ #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION < 3 static PyObject *__Pyx_GetStdout(void) { PyObject *f = PySys_GetObject((char *)""stdout""); if (!f) { PyErr_SetString(PyExc_RuntimeError, ""lost sys.stdout""); } return f; } static int __Pyx_Print(PyObject* f, PyObject *arg_tuple, int newline) { int i; if (!f) { if (!(f = __Pyx_GetStdout())) return -1; } Py_INCREF(f); for (i=0; i < PyTuple_GET_SIZE(arg_tuple); i++) { PyObject* v; if (PyFile_SoftSpace(f, 1)) { if (PyFile_WriteString("" "", f) < 0) goto error; } v = PyTuple_GET_ITEM(arg_tuple, i); if (PyFile_WriteObject(v, f, Py_PRINT_RAW) < 0) goto error; if (PyString_Check(v)) { char *s = PyString_AsString(v); Py_ssize_t len = PyString_Size(v); if (len > 0) { switch (s[len-1]) { case ' ': break; case '\f': case '\r': case '\n': case '\t': case '\v': PyFile_SoftSpace(f, 0); break; default: break; } } } } if (newline) { if (PyFile_WriteString(""\n"", f) < 0) goto error; PyFile_SoftSpace(f, 0); } Py_DECREF(f); return 0; error: Py_DECREF(f); return -1; } #else static int __Pyx_Print(PyObject* stream, PyObject *arg_tuple, int newline) { PyObject* kwargs = 0; PyObject* result = 0; PyObject* end_string; if (unlikely(!__pyx_print)) { __pyx_print = PyObject_GetAttr(__pyx_b, __pyx_n_s_print); if (!__pyx_print) return -1; } if (stream) { kwargs = PyDict_New(); if (unlikely(!kwargs)) return -1; if (unlikely(PyDict_SetItem(kwargs, __pyx_n_s_file, stream) < 0)) goto bad; if (!newline) { end_string = PyUnicode_FromStringAndSize("" "", 1); if (unlikely(!end_string)) goto bad; if (PyDict_SetItem(kwargs, __pyx_n_s_end, end_string) < 0) { Py_DECREF(end_string); goto bad; } Py_DECREF(end_string); } } else if (!newline) { if (unlikely(!__pyx_print_kwargs)) { __pyx_print_kwargs = PyDict_New(); if (unlikely(!__pyx_print_kwargs)) return -1; end_string = PyUnicode_FromStringAndSize("" "", 1); if (unlikely(!end_string)) return -1; if (PyDict_SetItem(__pyx_print_kwargs, __pyx_n_s_end, end_string) < 0) { Py_DECREF(end_string); return -1; } Py_DECREF(end_string); } kwargs = __pyx_print_kwargs; } result = PyObject_Call(__pyx_print, arg_tuple, kwargs); if (unlikely(kwargs) && (kwargs != __pyx_print_kwargs)) Py_DECREF(kwargs); if (!result) return -1; Py_DECREF(result); return 0; bad: if (kwargs != __pyx_print_kwargs) Py_XDECREF(kwargs); return -1; } #endif /* PrintOne */ #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION < 3 static int __Pyx_PrintOne(PyObject* f, PyObject *o) { if (!f) { if (!(f = __Pyx_GetStdout())) return -1; } Py_INCREF(f); if (PyFile_SoftSpace(f, 0)) { if (PyFile_WriteString("" "", f) < 0) goto error; } if (PyFile_WriteObject(o, f, Py_PRINT_RAW) < 0) goto error; if (PyFile_WriteString(""\n"", f) < 0) goto error; Py_DECREF(f); return 0; error: Py_DECREF(f); return -1; /* the line below is just to avoid C compiler * warnings about unused functions */ return __Pyx_Print(f, NULL, 0); } #else static int __Pyx_PrintOne(PyObject* stream, PyObject *o) { int res; PyObject* arg_tuple = PyTuple_Pack(1, o); if (unlikely(!arg_tuple)) return -1; res = __Pyx_Print(stream, arg_tuple, 1); Py_DECREF(arg_tuple); return res; } #endif /* CIntToPy */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(long) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(long) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); #endif } } else { if (sizeof(long) <= sizeof(long)) { return PyInt_FromLong((long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); #endif } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(long), little, !is_unsigned); } } /* CIntFromPyVerify */ #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) #define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) #define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ {\ func_type value = func_value;\ if (sizeof(target_type) < sizeof(func_type)) {\ if (unlikely(value != (func_type) (target_type) value)) {\ func_type zero = 0;\ if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ return (target_type) -1;\ if (is_unsigned && unlikely(value < zero))\ goto raise_neg_overflow;\ else\ goto raise_overflow;\ }\ }\ return (target_type) value;\ } /* CIntFromPy */ static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(long) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (long) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (long) 0; case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) case 2: if (8 * sizeof(long) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; case 3: if (8 * sizeof(long) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; case 4: if (8 * sizeof(long) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (long) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(long) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) #endif } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (long) 0; case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) case -2: if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 2: if (8 * sizeof(long) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case -3: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 3: if (8 * sizeof(long) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case -4: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 4: if (8 * sizeof(long) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; } #endif if (sizeof(long) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) #endif } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, ""_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers""); #else long val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (long) -1; } } else { long val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (long) -1; val = __Pyx_PyInt_As_long(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, ""value too large to convert to long""); return (long) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, ""can't convert negative value to long""); return (long) -1; } /* CIntFromPy */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { const int neg_one = (int) -1, const_zero = (int) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(int) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (int) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (int) 0; case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) case 2: if (8 * sizeof(int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; case 3: if (8 * sizeof(int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; case 4: if (8 * sizeof(int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (int) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(int) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) #endif } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (int) 0; case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) case -2: if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 2: if (8 * sizeof(int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case -3: if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 3: if (8 * sizeof(int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case -4: if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 4: if (8 * sizeof(int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; } #endif if (sizeof(int) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) #endif } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, ""_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers""); #else int val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (int) -1; } } else { int val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (int) -1; val = __Pyx_PyInt_As_int(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, ""value too large to convert to int""); return (int) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, ""can't convert negative value to int""); return (int) -1; } /* CheckBinaryVersion */ static int __Pyx_check_binary_version(void) { char ctversion[4], rtversion[4]; PyOS_snprintf(ctversion, 4, ""%d.%d"", PY_MAJOR_VERSION, PY_MINOR_VERSION); PyOS_snprintf(rtversion, 4, ""%s"", Py_GetVersion()); if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) { char message[200]; PyOS_snprintf(message, sizeof(message), ""compiletime version %s of module '%.100s' "" ""does not match runtime version %s"", ctversion, __Pyx_MODULE_NAME, rtversion); return PyErr_WarnEx(NULL, message, 1); } return 0; } /* InitStrings */ static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { while (t->p) { #if PY_MAJOR_VERSION < 3 if (t->is_unicode) { *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); } else if (t->intern) { *t->p = PyString_InternFromString(t->s); } else { *t->p = PyString_FromStringAndSize(t->s, t->n - 1); } #else if (t->is_unicode | t->is_str) { if (t->intern) { *t->p = PyUnicode_InternFromString(t->s); } else if (t->encoding) { *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); } else { *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); } } else { *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); } #endif if (!*t->p) return -1; ++t; } return 0; } static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); } static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) { Py_ssize_t ignore; return __Pyx_PyObject_AsStringAndSize(o, &ignore); } static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { #if CYTHON_COMPILING_IN_CPYTHON && (__PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT) if ( #if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII __Pyx_sys_getdefaultencoding_not_ascii && #endif PyUnicode_Check(o)) { #if PY_VERSION_HEX < 0x03030000 char* defenc_c; PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); if (!defenc) return NULL; defenc_c = PyBytes_AS_STRING(defenc); #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII { char* end = defenc_c + PyBytes_GET_SIZE(defenc); char* c; for (c = defenc_c; c < end; c++) { if ((unsigned char) (*c) >= 128) { PyUnicode_AsASCIIString(o); return NULL; } } } #endif *length = PyBytes_GET_SIZE(defenc); return defenc_c; #else if (__Pyx_PyUnicode_READY(o) == -1) return NULL; #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII if (PyUnicode_IS_ASCII(o)) { *length = PyUnicode_GET_LENGTH(o); return PyUnicode_AsUTF8(o); } else { PyUnicode_AsASCIIString(o); return NULL; } #else return PyUnicode_AsUTF8AndSize(o, length); #endif #endif } else #endif #if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) if (PyByteArray_Check(o)) { *length = PyByteArray_GET_SIZE(o); return PyByteArray_AS_STRING(o); } else #endif { char* result; int r = PyBytes_AsStringAndSize(o, &result, length); if (unlikely(r < 0)) { return NULL; } else { return result; } } } static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { int is_true = x == Py_True; if (is_true | (x == Py_False) | (x == Py_None)) return is_true; else return PyObject_IsTrue(x); } static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { #if CYTHON_USE_TYPE_SLOTS PyNumberMethods *m; #endif const char *name = NULL; PyObject *res = NULL; #if PY_MAJOR_VERSION < 3 if (PyInt_Check(x) || PyLong_Check(x)) #else if (PyLong_Check(x)) #endif return __Pyx_NewRef(x); #if CYTHON_USE_TYPE_SLOTS m = Py_TYPE(x)->tp_as_number; #if PY_MAJOR_VERSION < 3 if (m && m->nb_int) { name = ""int""; res = PyNumber_Int(x); } else if (m && m->nb_long) { name = ""long""; res = PyNumber_Long(x); } #else if (m && m->nb_int) { name = ""int""; res = PyNumber_Long(x); } #endif #else res = PyNumber_Int(x); #endif if (res) { #if PY_MAJOR_VERSION < 3 if (!PyInt_Check(res) && !PyLong_Check(res)) { #else if (!PyLong_Check(res)) { #endif PyErr_Format(PyExc_TypeError, ""__%.4s__ returned non-%.4s (type %.200s)"", name, name, Py_TYPE(res)->tp_name); Py_DECREF(res); return NULL; } } else if (!PyErr_Occurred()) { PyErr_SetString(PyExc_TypeError, ""an integer is required""); } return res; } static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { Py_ssize_t ival; PyObject *x; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_CheckExact(b))) { if (sizeof(Py_ssize_t) >= sizeof(long)) return PyInt_AS_LONG(b); else return PyInt_AsSsize_t(x); } #endif if (likely(PyLong_CheckExact(b))) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)b)->ob_digit; const Py_ssize_t size = Py_SIZE(b); if (likely(__Pyx_sst_abs(size) <= 1)) { ival = likely(size) ? digits[0] : 0; if (size == -1) ival = -ival; return ival; } else { switch (size) { case 2: if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -2: if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case 3: if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -3: if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case 4: if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -4: if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; } } #endif return PyLong_AsSsize_t(b); } x = PyNumber_Index(b); if (!x) return -1; ival = PyInt_AsSsize_t(x); Py_DECREF(x); return ival; } static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { return PyInt_FromSize_t(ival); } #endif /* Py_PYTHON_H */ ","C" "Biophysics","maxscheurer/pycontact","testing/cython/ResizeArray.h",".h","4388","134","/*************************************************************************** *cr *cr (C) Copyright 1995-2011 The Board of Trustees of the *cr University of Illinois *cr All Rights Reserved *cr ***************************************************************************/ /*************************************************************************** * RCS INFORMATION: * * $RCSfile: ResizeArray.h,v $ * $Author: johns $ $Locker: $ $State: Exp $ * $Revision: 1.45 $ $Date: 2010/12/16 04:08:38 $ * *************************************************************************** * DESCRIPTION: * Automatically-adjusting single-dim array template. * * LICENSE: * UIUC Open Source License * http://www.ks.uiuc.edu/Research/vmd/plugins/pluginlicense.html * ***************************************************************************/ #ifndef RESIZEARRAY_TEMPLATE_H #define RESIZEARRAY_TEMPLATE_H #include /// A template class which implements a dynamically-growing, automatically /// resizing array of data of a given type. Elements in the array may be /// accessed via the [] operator. When new data is added to the end of an /// array, the size of the array is automatically increased if necessary. /// /// XXX Do not parametrize this class with a datatype which cannot be /// shallow-copied! This class uses memcpy to resize, and therefore /// classes which contain dynamically-allocated memory blocks will /// crash and burn if the ResizeArray ever gets resized. template class ResizeArray { private: T *allocate(size_t n) { return new T[n]; } void deallocate(T *p) { delete [] p; } T *data; ///< list of items, and pointer to current item. int sz; ///< max number of items that can be stored in the array int currSize; ///< largest index used + 1 public: /// Constructor /// The first argument is the initial internal size of the array, i.e. the /// initial number of elements for which to allocate memory (although the /// initial external size of the array will be zero). ResizeArray(int s = 3) { currSize = 0; sz = (s > 0 ? s : 10); data = allocate(sz); } ~ResizeArray() { deallocate(data); } int num(void) const { return currSize; } ///< current size of array T& operator[](int N) { return data[N]; } ///< unchecked accessor, for speed T const& operator[](int N) const { return data[N]; } ///< a const version of above /// add a new element to the end of the array. Return index of new item. void append(const T& val) { if (currSize == sz) { // extend size of array if necessary int newsize = (int)((float)sz * 1.3f); // guarantee minimum required size increase, since the scaled value // may truncate back to the original size value when the initial number // of elements is very small. if (newsize == sz) newsize++; // shallow copy the data to a newly allocated block since we can't // do something better like realloc() T *newdata = allocate(newsize); memcpy(newdata, data, currSize * sizeof(T)); deallocate(data); // save new values data = newdata; sz = newsize; } data[currSize++] = val; } /// remove an item from the array, shifting remaining items down by 1 void remove(int n) { if (n < 0 || n >= currSize) return; for (int i=n; i #ifndef offsetof #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) #endif #if !defined(WIN32) && !defined(MS_WINDOWS) #ifndef __stdcall #define __stdcall #endif #ifndef __cdecl #define __cdecl #endif #ifndef __fastcall #define __fastcall #endif #endif #ifndef DL_IMPORT #define DL_IMPORT(t) t #endif #ifndef DL_EXPORT #define DL_EXPORT(t) t #endif #ifndef HAVE_LONG_LONG #if PY_VERSION_HEX >= 0x03030000 || (PY_MAJOR_VERSION == 2 && PY_VERSION_HEX >= 0x02070000) #define HAVE_LONG_LONG #endif #endif #ifndef PY_LONG_LONG #define PY_LONG_LONG LONG_LONG #endif #ifndef Py_HUGE_VAL #define Py_HUGE_VAL HUGE_VAL #endif #ifdef PYPY_VERSION #define CYTHON_COMPILING_IN_PYPY 1 #define CYTHON_COMPILING_IN_PYSTON 0 #define CYTHON_COMPILING_IN_CPYTHON 0 #undef CYTHON_USE_TYPE_SLOTS #define CYTHON_USE_TYPE_SLOTS 0 #undef CYTHON_USE_ASYNC_SLOTS #define CYTHON_USE_ASYNC_SLOTS 0 #undef CYTHON_USE_PYLIST_INTERNALS #define CYTHON_USE_PYLIST_INTERNALS 0 #undef CYTHON_USE_UNICODE_INTERNALS #define CYTHON_USE_UNICODE_INTERNALS 0 #undef CYTHON_USE_UNICODE_WRITER #define CYTHON_USE_UNICODE_WRITER 0 #undef CYTHON_USE_PYLONG_INTERNALS #define CYTHON_USE_PYLONG_INTERNALS 0 #undef CYTHON_AVOID_BORROWED_REFS #define CYTHON_AVOID_BORROWED_REFS 1 #undef CYTHON_ASSUME_SAFE_MACROS #define CYTHON_ASSUME_SAFE_MACROS 0 #undef CYTHON_UNPACK_METHODS #define CYTHON_UNPACK_METHODS 0 #undef CYTHON_FAST_THREAD_STATE #define CYTHON_FAST_THREAD_STATE 0 #undef CYTHON_FAST_PYCALL #define CYTHON_FAST_PYCALL 0 #elif defined(PYSTON_VERSION) #define CYTHON_COMPILING_IN_PYPY 0 #define CYTHON_COMPILING_IN_PYSTON 1 #define CYTHON_COMPILING_IN_CPYTHON 0 #ifndef CYTHON_USE_TYPE_SLOTS #define CYTHON_USE_TYPE_SLOTS 1 #endif #undef CYTHON_USE_ASYNC_SLOTS #define CYTHON_USE_ASYNC_SLOTS 0 #undef CYTHON_USE_PYLIST_INTERNALS #define CYTHON_USE_PYLIST_INTERNALS 0 #ifndef CYTHON_USE_UNICODE_INTERNALS #define CYTHON_USE_UNICODE_INTERNALS 1 #endif #undef CYTHON_USE_UNICODE_WRITER #define CYTHON_USE_UNICODE_WRITER 0 #undef CYTHON_USE_PYLONG_INTERNALS #define CYTHON_USE_PYLONG_INTERNALS 0 #ifndef CYTHON_AVOID_BORROWED_REFS #define CYTHON_AVOID_BORROWED_REFS 0 #endif #ifndef CYTHON_ASSUME_SAFE_MACROS #define CYTHON_ASSUME_SAFE_MACROS 1 #endif #ifndef CYTHON_UNPACK_METHODS #define CYTHON_UNPACK_METHODS 1 #endif #undef CYTHON_FAST_THREAD_STATE #define CYTHON_FAST_THREAD_STATE 0 #undef CYTHON_FAST_PYCALL #define CYTHON_FAST_PYCALL 0 #else #define CYTHON_COMPILING_IN_PYPY 0 #define CYTHON_COMPILING_IN_PYSTON 0 #define CYTHON_COMPILING_IN_CPYTHON 1 #ifndef CYTHON_USE_TYPE_SLOTS #define CYTHON_USE_TYPE_SLOTS 1 #endif #if PY_MAJOR_VERSION < 3 #undef CYTHON_USE_ASYNC_SLOTS #define CYTHON_USE_ASYNC_SLOTS 0 #elif !defined(CYTHON_USE_ASYNC_SLOTS) #define CYTHON_USE_ASYNC_SLOTS 1 #endif #if PY_VERSION_HEX < 0x02070000 #undef CYTHON_USE_PYLONG_INTERNALS #define CYTHON_USE_PYLONG_INTERNALS 0 #elif !defined(CYTHON_USE_PYLONG_INTERNALS) #define CYTHON_USE_PYLONG_INTERNALS 1 #endif #ifndef CYTHON_USE_PYLIST_INTERNALS #define CYTHON_USE_PYLIST_INTERNALS 1 #endif #ifndef CYTHON_USE_UNICODE_INTERNALS #define CYTHON_USE_UNICODE_INTERNALS 1 #endif #if PY_VERSION_HEX < 0x030300F0 #undef CYTHON_USE_UNICODE_WRITER #define CYTHON_USE_UNICODE_WRITER 0 #elif !defined(CYTHON_USE_UNICODE_WRITER) #define CYTHON_USE_UNICODE_WRITER 1 #endif #ifndef CYTHON_AVOID_BORROWED_REFS #define CYTHON_AVOID_BORROWED_REFS 0 #endif #ifndef CYTHON_ASSUME_SAFE_MACROS #define CYTHON_ASSUME_SAFE_MACROS 1 #endif #ifndef CYTHON_UNPACK_METHODS #define CYTHON_UNPACK_METHODS 1 #endif #ifndef CYTHON_FAST_THREAD_STATE #define CYTHON_FAST_THREAD_STATE 1 #endif #ifndef CYTHON_FAST_PYCALL #define CYTHON_FAST_PYCALL 1 #endif #endif #if !defined(CYTHON_FAST_PYCCALL) #define CYTHON_FAST_PYCCALL (CYTHON_FAST_PYCALL && PY_VERSION_HEX >= 0x030600B1) #endif #if CYTHON_USE_PYLONG_INTERNALS #include ""longintrepr.h"" #undef SHIFT #undef BASE #undef MASK #endif #if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) #define Py_OptimizeFlag 0 #endif #define __PYX_BUILD_PY_SSIZE_T ""n"" #define CYTHON_FORMAT_SSIZE_T ""z"" #if PY_MAJOR_VERSION < 3 #define __Pyx_BUILTIN_MODULE_NAME ""__builtin__"" #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #define __Pyx_DefaultClassType PyClass_Type #else #define __Pyx_BUILTIN_MODULE_NAME ""builtins"" #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #define __Pyx_DefaultClassType PyType_Type #endif #ifndef Py_TPFLAGS_CHECKTYPES #define Py_TPFLAGS_CHECKTYPES 0 #endif #ifndef Py_TPFLAGS_HAVE_INDEX #define Py_TPFLAGS_HAVE_INDEX 0 #endif #ifndef Py_TPFLAGS_HAVE_NEWBUFFER #define Py_TPFLAGS_HAVE_NEWBUFFER 0 #endif #ifndef Py_TPFLAGS_HAVE_FINALIZE #define Py_TPFLAGS_HAVE_FINALIZE 0 #endif #ifndef METH_FASTCALL #define METH_FASTCALL 0x80 typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject **args, Py_ssize_t nargs, PyObject *kwnames); #else #define __Pyx_PyCFunctionFast _PyCFunctionFast #endif #if CYTHON_FAST_PYCCALL #define __Pyx_PyFastCFunction_Check(func)\ ((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST))))) #else #define __Pyx_PyFastCFunction_Check(func) 0 #endif #if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) #define CYTHON_PEP393_ENABLED 1 #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ 0 : _PyUnicode_Ready((PyObject *)(op))) #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u) #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u) #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) #else #define CYTHON_PEP393_ENABLED 0 #define PyUnicode_1BYTE_KIND 1 #define PyUnicode_2BYTE_KIND 2 #define PyUnicode_4BYTE_KIND 4 #define __Pyx_PyUnicode_READY(op) (0) #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111) #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE)) #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u)) #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i])) #define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch) #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u)) #endif #if CYTHON_COMPILING_IN_PYPY #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) #else #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check) #define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format) #define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, ""__format__"", ""O"", fmt) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) #define PyObject_Malloc(s) PyMem_Malloc(s) #define PyObject_Free(p) PyMem_Free(p) #define PyObject_Realloc(p) PyMem_Realloc(p) #endif #if CYTHON_COMPILING_IN_PYSTON #define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co) #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno) #else #define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0) #define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno) #endif #define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) #define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b) #else #define __Pyx_PyString_Format(a, b) PyString_Format(a, b) #endif #if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII) #define PyObject_ASCII(o) PyObject_Repr(o) #endif #if PY_MAJOR_VERSION >= 3 #define PyBaseString_Type PyUnicode_Type #define PyStringObject PyUnicodeObject #define PyString_Type PyUnicode_Type #define PyString_Check PyUnicode_Check #define PyString_CheckExact PyUnicode_CheckExact #endif #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) #else #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj)) #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj)) #endif #ifndef PySet_CheckExact #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) #endif #define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) #define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception) #if PY_MAJOR_VERSION >= 3 #define PyIntObject PyLongObject #define PyInt_Type PyLong_Type #define PyInt_Check(op) PyLong_Check(op) #define PyInt_CheckExact(op) PyLong_CheckExact(op) #define PyInt_FromString PyLong_FromString #define PyInt_FromUnicode PyLong_FromUnicode #define PyInt_FromLong PyLong_FromLong #define PyInt_FromSize_t PyLong_FromSize_t #define PyInt_FromSsize_t PyLong_FromSsize_t #define PyInt_AsLong PyLong_AsLong #define PyInt_AS_LONG PyLong_AS_LONG #define PyInt_AsSsize_t PyLong_AsSsize_t #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask #define PyNumber_Int PyNumber_Long #endif #if PY_MAJOR_VERSION >= 3 #define PyBoolObject PyLongObject #endif #if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY #ifndef PyUnicode_InternFromString #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) #endif #endif #if PY_VERSION_HEX < 0x030200A4 typedef long Py_hash_t; #define __Pyx_PyInt_FromHash_t PyInt_FromLong #define __Pyx_PyInt_AsHash_t PyInt_AsLong #else #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t #endif #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func)) #else #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) #endif #if CYTHON_USE_ASYNC_SLOTS #if PY_VERSION_HEX >= 0x030500B1 #define __Pyx_PyAsyncMethodsStruct PyAsyncMethods #define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async) #else typedef struct { unaryfunc am_await; unaryfunc am_aiter; unaryfunc am_anext; } __Pyx_PyAsyncMethodsStruct; #define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved)) #endif #else #define __Pyx_PyType_AsAsync(obj) NULL #endif #ifndef CYTHON_RESTRICT #if defined(__GNUC__) #define CYTHON_RESTRICT __restrict__ #elif defined(_MSC_VER) && _MSC_VER >= 1400 #define CYTHON_RESTRICT __restrict #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L #define CYTHON_RESTRICT restrict #else #define CYTHON_RESTRICT #endif #endif #ifndef CYTHON_UNUSED # if defined(__GNUC__) # if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4)) # define CYTHON_UNUSED __attribute__ ((__unused__)) # else # define CYTHON_UNUSED # endif # elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER)) # define CYTHON_UNUSED __attribute__ ((__unused__)) # else # define CYTHON_UNUSED # endif #endif #ifndef CYTHON_MAYBE_UNUSED_VAR # if defined(__cplusplus) template void CYTHON_MAYBE_UNUSED_VAR( const T& ) { } # else # define CYTHON_MAYBE_UNUSED_VAR(x) (void)(x) # endif #endif #ifndef CYTHON_NCP_UNUSED # if CYTHON_COMPILING_IN_CPYTHON # define CYTHON_NCP_UNUSED # else # define CYTHON_NCP_UNUSED CYTHON_UNUSED # endif #endif #define __Pyx_void_to_None(void_result) ((void)(void_result), Py_INCREF(Py_None), Py_None) #ifndef __cplusplus #error ""Cython files generated with the C++ option must be compiled with a C++ compiler."" #endif #ifndef CYTHON_INLINE #if defined(__clang__) #define CYTHON_INLINE __inline__ __attribute__ ((__unused__)) #else #define CYTHON_INLINE inline #endif #endif template void __Pyx_call_destructor(T& x) { x.~T(); } template class __Pyx_FakeReference { public: __Pyx_FakeReference() : ptr(NULL) { } __Pyx_FakeReference(const T& ref) : ptr(const_cast(&ref)) { } T *operator->() { return ptr; } T *operator&() { return ptr; } operator T&() { return *ptr; } template bool operator ==(U other) { return *ptr == other; } template bool operator !=(U other) { return *ptr != other; } private: T *ptr; }; #if defined(WIN32) || defined(MS_WINDOWS) #define _USE_MATH_DEFINES #endif #include #ifdef NAN #define __PYX_NAN() ((float) NAN) #else static CYTHON_INLINE float __PYX_NAN() { float value; memset(&value, 0xFF, sizeof(value)); return value; } #endif #if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL) #define __Pyx_truncl trunc #else #define __Pyx_truncl truncl #endif #define __PYX_ERR(f_index, lineno, Ln_error) \ { \ __pyx_filename = __pyx_f[f_index]; __pyx_lineno = lineno; __pyx_clineno = __LINE__; goto Ln_error; \ } #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) #else #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) #endif #ifndef __PYX_EXTERN_C #ifdef __cplusplus #define __PYX_EXTERN_C extern ""C"" #else #define __PYX_EXTERN_C extern #endif #endif #define __PYX_HAVE__wrap_vmd #define __PYX_HAVE_API__wrap_vmd #include ""gridsearch.C"" #ifdef _OPENMP #include #endif /* _OPENMP */ #ifdef PYREX_WITHOUT_ASSERTIONS #define CYTHON_WITHOUT_ASSERTIONS #endif typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding; const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; #define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 #define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT 0 #define __PYX_DEFAULT_STRING_ENCODING """" #define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString #define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize #define __Pyx_uchar_cast(c) ((unsigned char)c) #define __Pyx_long_cast(x) ((long)x) #define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\ (sizeof(type) < sizeof(Py_ssize_t)) ||\ (sizeof(type) > sizeof(Py_ssize_t) &&\ likely(v < (type)PY_SSIZE_T_MAX ||\ v == (type)PY_SSIZE_T_MAX) &&\ (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\ v == (type)PY_SSIZE_T_MIN))) ||\ (sizeof(type) == sizeof(Py_ssize_t) &&\ (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\ v == (type)PY_SSIZE_T_MAX))) ) #if defined (__cplusplus) && __cplusplus >= 201103L #include #define __Pyx_sst_abs(value) std::abs(value) #elif SIZEOF_INT >= SIZEOF_SIZE_T #define __Pyx_sst_abs(value) abs(value) #elif SIZEOF_LONG >= SIZEOF_SIZE_T #define __Pyx_sst_abs(value) labs(value) #elif defined (_MSC_VER) && defined (_M_X64) #define __Pyx_sst_abs(value) _abs64(value) #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L #define __Pyx_sst_abs(value) llabs(value) #elif defined (__GNUC__) #define __Pyx_sst_abs(value) __builtin_llabs(value) #else #define __Pyx_sst_abs(value) ((value<0) ? -value : value) #endif static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject*); static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); #define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) #define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l) #define __Pyx_PyBytes_FromString PyBytes_FromString #define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); #if PY_MAJOR_VERSION < 3 #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize #else #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize #endif #define __Pyx_PyObject_AsSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) #define __Pyx_PyObject_AsUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) #define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) #define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) #define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) #define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) #define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) #if PY_MAJOR_VERSION < 3 static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { const Py_UNICODE *u_end = u; while (*u_end++) ; return (size_t)(u_end - u - 1); } #else #define __Pyx_Py_UNICODE_strlen Py_UNICODE_strlen #endif #define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) #define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode #define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode #define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) #define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) #define __Pyx_PyBool_FromLong(b) ((b) ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False)) static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*); static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x); static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t); #if CYTHON_ASSUME_SAFE_MACROS #define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? 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if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { return NULL; } code_object = __pyx_code_cache.entries[pos].code_object; Py_INCREF(code_object); return code_object; } static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { int pos, i; __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; if (unlikely(!code_line)) { return; } if (unlikely(!entries)) { entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); if (likely(entries)) { __pyx_code_cache.entries = entries; __pyx_code_cache.max_count = 64; __pyx_code_cache.count = 1; entries[0].code_line = code_line; entries[0].code_object = code_object; Py_INCREF(code_object); } return; } pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { PyCodeObject* tmp = entries[pos].code_object; entries[pos].code_object = code_object; Py_DECREF(tmp); return; } if (__pyx_code_cache.count == __pyx_code_cache.max_count) { int new_max = __pyx_code_cache.max_count + 64; entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( __pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry)); if (unlikely(!entries)) { return; } __pyx_code_cache.entries = entries; __pyx_code_cache.max_count = new_max; } for (i=__pyx_code_cache.count; i>pos; i--) { entries[i] = entries[i-1]; } entries[pos].code_line = code_line; entries[pos].code_object = code_object; __pyx_code_cache.count++; Py_INCREF(code_object); } /* AddTraceback */ #include ""compile.h"" #include ""frameobject.h"" #include ""traceback.h"" static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( const char *funcname, int c_line, int py_line, const char *filename) { PyCodeObject *py_code = 0; PyObject *py_srcfile = 0; PyObject *py_funcname = 0; #if PY_MAJOR_VERSION < 3 py_srcfile = PyString_FromString(filename); #else py_srcfile = PyUnicode_FromString(filename); #endif if (!py_srcfile) goto bad; if (c_line) { #if PY_MAJOR_VERSION < 3 py_funcname = PyString_FromFormat( ""%s (%s:%d)"", funcname, __pyx_cfilenm, c_line); #else py_funcname = PyUnicode_FromFormat( ""%s (%s:%d)"", funcname, __pyx_cfilenm, c_line); #endif } else { #if PY_MAJOR_VERSION < 3 py_funcname = PyString_FromString(funcname); #else py_funcname = PyUnicode_FromString(funcname); #endif } if (!py_funcname) goto bad; py_code = __Pyx_PyCode_New( 0, 0, 0, 0, 0, __pyx_empty_bytes, /*PyObject *code,*/ __pyx_empty_tuple, /*PyObject *consts,*/ __pyx_empty_tuple, /*PyObject *names,*/ __pyx_empty_tuple, /*PyObject *varnames,*/ __pyx_empty_tuple, /*PyObject *freevars,*/ __pyx_empty_tuple, /*PyObject *cellvars,*/ py_srcfile, /*PyObject *filename,*/ py_funcname, /*PyObject *name,*/ py_line, __pyx_empty_bytes /*PyObject *lnotab*/ ); Py_DECREF(py_srcfile); Py_DECREF(py_funcname); return py_code; bad: Py_XDECREF(py_srcfile); Py_XDECREF(py_funcname); return NULL; } static void __Pyx_AddTraceback(const char *funcname, int c_line, int py_line, const char *filename) { PyCodeObject *py_code = 0; PyFrameObject *py_frame = 0; py_code = __pyx_find_code_object(c_line ? c_line : py_line); if (!py_code) { py_code = __Pyx_CreateCodeObjectForTraceback( funcname, c_line, py_line, filename); if (!py_code) goto bad; __pyx_insert_code_object(c_line ? c_line : py_line, py_code); } py_frame = PyFrame_New( PyThreadState_GET(), /*PyThreadState *tstate,*/ py_code, /*PyCodeObject *code,*/ __pyx_d, /*PyObject *globals,*/ 0 /*PyObject *locals*/ ); if (!py_frame) goto bad; __Pyx_PyFrame_SetLineNumber(py_frame, py_line); PyTraceBack_Here(py_frame); bad: Py_XDECREF(py_code); Py_XDECREF(py_frame); } /* CIntToPy */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(long) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(long) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); #endif } } else { if (sizeof(long) <= sizeof(long)) { return PyInt_FromLong((long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); #endif } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(long), little, !is_unsigned); } } /* CIntFromPyVerify */ #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) #define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) #define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ {\ func_type value = func_value;\ if (sizeof(target_type) < sizeof(func_type)) {\ if (unlikely(value != (func_type) (target_type) value)) {\ func_type zero = 0;\ if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ return (target_type) -1;\ if (is_unsigned && unlikely(value < zero))\ goto raise_neg_overflow;\ else\ goto raise_overflow;\ }\ }\ return (target_type) value;\ } /* CIntFromPy */ static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(long) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (long) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (long) 0; case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) case 2: if (8 * sizeof(long) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; case 3: if (8 * sizeof(long) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; case 4: if (8 * sizeof(long) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (long) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(long) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) #endif } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (long) 0; case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) case -2: if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 2: if (8 * sizeof(long) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case -3: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 3: if (8 * sizeof(long) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case -4: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 4: if (8 * sizeof(long) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; } #endif if (sizeof(long) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) #endif } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, ""_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers""); #else long val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (long) -1; } } else { long val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (long) -1; val = __Pyx_PyInt_As_long(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, ""value too large to convert to long""); return (long) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, ""can't convert negative value to long""); return (long) -1; } /* CIntFromPy */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { const int neg_one = (int) -1, const_zero = (int) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(int) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (int) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (int) 0; case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) case 2: if (8 * sizeof(int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; case 3: if (8 * sizeof(int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; case 4: if (8 * sizeof(int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (int) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(int) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) #endif } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (int) 0; case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) case -2: if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 2: if (8 * sizeof(int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case -3: if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 3: if (8 * sizeof(int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case -4: if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 4: if (8 * sizeof(int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; } #endif if (sizeof(int) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) #endif } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, ""_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers""); #else int val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (int) -1; } } else { int val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (int) -1; val = __Pyx_PyInt_As_int(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, ""value too large to convert to int""); return (int) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, ""can't convert negative value to int""); return (int) -1; } /* CheckBinaryVersion */ static int __Pyx_check_binary_version(void) { char ctversion[4], rtversion[4]; PyOS_snprintf(ctversion, 4, ""%d.%d"", PY_MAJOR_VERSION, PY_MINOR_VERSION); PyOS_snprintf(rtversion, 4, ""%s"", Py_GetVersion()); if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) { char message[200]; PyOS_snprintf(message, sizeof(message), ""compiletime version %s of module '%.100s' "" ""does not match runtime version %s"", ctversion, __Pyx_MODULE_NAME, rtversion); return PyErr_WarnEx(NULL, message, 1); } return 0; } /* InitStrings */ static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { while (t->p) { #if PY_MAJOR_VERSION < 3 if (t->is_unicode) { *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); } else if (t->intern) { *t->p = PyString_InternFromString(t->s); } else { *t->p = PyString_FromStringAndSize(t->s, t->n - 1); } #else if (t->is_unicode | t->is_str) { if (t->intern) { *t->p = PyUnicode_InternFromString(t->s); } else if (t->encoding) { *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); } else { *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); } } else { *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); } #endif if (!*t->p) return -1; ++t; } return 0; } static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); } static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) { Py_ssize_t ignore; return __Pyx_PyObject_AsStringAndSize(o, &ignore); } static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { #if CYTHON_COMPILING_IN_CPYTHON && (__PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT) if ( #if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII __Pyx_sys_getdefaultencoding_not_ascii && #endif PyUnicode_Check(o)) { #if PY_VERSION_HEX < 0x03030000 char* defenc_c; PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); if (!defenc) return NULL; defenc_c = PyBytes_AS_STRING(defenc); #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII { char* end = defenc_c + PyBytes_GET_SIZE(defenc); char* c; for (c = defenc_c; c < end; c++) { if ((unsigned char) (*c) >= 128) { PyUnicode_AsASCIIString(o); return NULL; } } } #endif *length = PyBytes_GET_SIZE(defenc); return defenc_c; #else if (__Pyx_PyUnicode_READY(o) == -1) return NULL; #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII if (PyUnicode_IS_ASCII(o)) { *length = PyUnicode_GET_LENGTH(o); return PyUnicode_AsUTF8(o); } else { PyUnicode_AsASCIIString(o); return NULL; } #else return PyUnicode_AsUTF8AndSize(o, length); #endif #endif } else #endif #if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) if (PyByteArray_Check(o)) { *length = PyByteArray_GET_SIZE(o); return PyByteArray_AS_STRING(o); } else #endif { char* result; int r = PyBytes_AsStringAndSize(o, &result, length); if (unlikely(r < 0)) { return NULL; } else { return result; } } } static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { int is_true = x == Py_True; if (is_true | (x == Py_False) | (x == Py_None)) return is_true; else return PyObject_IsTrue(x); } static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { #if CYTHON_USE_TYPE_SLOTS PyNumberMethods *m; #endif const char *name = NULL; PyObject *res = NULL; #if PY_MAJOR_VERSION < 3 if (PyInt_Check(x) || PyLong_Check(x)) #else if (PyLong_Check(x)) #endif return __Pyx_NewRef(x); #if CYTHON_USE_TYPE_SLOTS m = Py_TYPE(x)->tp_as_number; #if PY_MAJOR_VERSION < 3 if (m && m->nb_int) { name = ""int""; res = PyNumber_Int(x); } else if (m && m->nb_long) { name = ""long""; res = PyNumber_Long(x); } #else if (m && m->nb_int) { name = ""int""; res = PyNumber_Long(x); } #endif #else res = PyNumber_Int(x); #endif if (res) { #if PY_MAJOR_VERSION < 3 if (!PyInt_Check(res) && !PyLong_Check(res)) { #else if (!PyLong_Check(res)) { #endif PyErr_Format(PyExc_TypeError, ""__%.4s__ returned non-%.4s (type %.200s)"", name, name, Py_TYPE(res)->tp_name); Py_DECREF(res); return NULL; } } else if (!PyErr_Occurred()) { PyErr_SetString(PyExc_TypeError, ""an integer is required""); } return res; } static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { Py_ssize_t ival; PyObject *x; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_CheckExact(b))) { if (sizeof(Py_ssize_t) >= sizeof(long)) return PyInt_AS_LONG(b); else return PyInt_AsSsize_t(x); } #endif if (likely(PyLong_CheckExact(b))) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)b)->ob_digit; const Py_ssize_t size = Py_SIZE(b); if (likely(__Pyx_sst_abs(size) <= 1)) { ival = likely(size) ? digits[0] : 0; if (size == -1) ival = -ival; return ival; } else { switch (size) { case 2: if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -2: if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case 3: if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -3: if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case 4: if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -4: if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; } } #endif return PyLong_AsSsize_t(b); } x = PyNumber_Index(b); if (!x) return -1; ival = PyInt_AsSsize_t(x); Py_DECREF(x); return ival; } static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { return PyInt_FromSize_t(ival); } #endif /* Py_PYTHON_H */ ","C++" "Biophysics","maxscheurer/pycontact","testing/cython/gridsearch.C",".C","25071","824","#include #include #include #include #include ""ResizeArray.h"" #include // #include ""utilities.h"" #define FALSE 0 #define TRUE 1 void * find_within_routine( void *v ); struct AtomEntry { float x, y, z; int index; AtomEntry() {} AtomEntry(const float &_x, const float &_y, const float &_z, const int &_i) : x(_x), y(_y), z(_z), index(_i) {} }; using namespace std; extern ""C"" { struct GridSearchPair { int ind1, ind2; GridSearchPair *next; }; #define VMD_RAND_MAX 2147483647L long vmd_random(void) { #ifdef _MSC_VER return rand(); #else return random(); #endif } void vmd_srandom(unsigned int seed) { #ifdef _MSC_VER srand(seed); #else srandom(seed); #endif } float distance2(const float *a, const float *b) { float delta = a[0] - b[0]; float r2 = delta*delta; delta = a[1] - b[1]; r2 += delta*delta; delta = a[2] - b[2]; return r2 + delta*delta; } void vec_sub(float *a, const float *b, const float *c) { a[0]=b[0]-c[0]; a[1]=b[1]-c[1]; a[2]=b[2]-c[2]; } void find_minmax(const float *pos, int n, const int *on, float *min, float *max, int *oncount) { float x1, x2, y1, y2, z1, z2; int i, numon; // return immediately if there are no atoms, or no atoms are on. if (n < 1) return; // init on count, i = 0 because all atoms are on numon = 1; i = 0; // find first on atom EDIT: not needed // for (i=0; i x2) x2 = pos[0]; if (pos[1] < y1) y1 = pos[1]; else if (pos[1] > y2) y2 = pos[1]; if (pos[2] < z1) z1 = pos[2]; else if (pos[2] > z2) z2 = pos[2]; numon++; // } pos += 3; } min[0] = x1; min[1] = y1; min[2] = z1; max[0] = x2; max[1] = y2; max[2] = z2; if (oncount != NULL) *oncount = numon; } int find_minmax_selected(int n, const int *flgs, const float *pos, float &_xmin, float &_ymin, float &_zmin, float &_xmax, float &_ymax, float &_zmax) { int i; float xmin, xmax, ymin, ymax, zmin, zmax; for (i=0; ixi) xmin=xi; if (ymin>yi) ymin=yi; if (zmin>zi) zmin=zi; if (xmaxnext = (GridSearchPair *) malloc(sizeof(GridSearchPair)); link->next->ind1 = i; link->next->ind2 = j; link->next->next = NULL; } int make_neighborlist(int **nbrlist, int xb, int yb, int zb) { int xi, yi, zi, aindex, xytotb; if (nbrlist == NULL) return -1; xytotb = xb * yb; aindex = 0; for (zi=0; zi 0) nbrs[n++] = aindex - xb + 1; if (xi > 0 && zi < (zb-1)) nbrs[n++] = aindex + xytotb - 1; if (yi > 0 && zi < (zb-1)) nbrs[n++] = aindex + xytotb - xb; if (xi < (xb-1) && yi < (yb-1) && zi < (zb-1)) nbrs[n++] = aindex + xytotb + xb + 1; if (xi > 0 && yi < (yb-1) && zi < (zb-1)) nbrs[n++] = aindex + xytotb + xb - 1; if (xi < (xb-1) && yi > 0 && zi < (zb-1)) nbrs[n++] = aindex + xytotb - xb + 1; if (xi > 0 && yi > 0 && zi < (zb-1)) nbrs[n++] = aindex + xytotb - xb - 1; nbrs[n++] = -1; // mark end of list int *lst = (int *) malloc(n*sizeof(int)); if (lst == NULL) return -1; // return on failed allocations memcpy(lst, nbrs, n*sizeof(int)); nbrlist[aindex] = lst; aindex++; } } } return 0; } GridSearchPair *vmd_gridsearch1(const float *pos,int natoms, const int *on, float pairdist, int allow_double_counting, int maxpairs) { float min[3]={0,0,0}, max[3]={0,0,0}; float sqdist; int i, j, xb, yb, zb, xytotb, totb, aindex; int **boxatom, *numinbox, *maxinbox, **nbrlist; int numon = 0; float sidelen[3], volume; int paircount = 0; int maxpairsreached = 0; sqdist = pairdist * pairdist; printf(""nc: %d \n"",natoms); // find bounding box for selected atoms, and number of atoms in selection. find_minmax(pos, natoms, on, min, max, &numon); printf(""minmaxfound: %d,%f, min %f max %f\n"",numon,sqdist,min[0],max[0]); // do sanity checks and complain if we've got bogus atom coordinates, // we shouldn't ever have density higher than 0.1 atom/A^3, but we'll // be generous and allow much higher densities. if (maxpairs != -1) { vec_sub(sidelen, max, min); // include estimate for atom radius (1 Angstrom) in volume determination volume = fabsf((sidelen[0] + 2.0f) * (sidelen[1] + 2.0f) * (sidelen[2] + 2.0f)); if ((numon / volume) > 1.0) { // msgWarn << ""vmd_gridsearch1: insane atom density"" << sendmsg; } } // I don't want the grid to get too large, otherwise I could run out // of memory. Octrees would be cool, but I'll just limit the grid size // and let the performance degrade a little for pathological systems. // Note that sqdist is what gets used for the actual distance checks; // from here on out pairdist is only used to set the grid size, so we // can set it to anything larger than the original pairdist. const int MAXBOXES = 4000000; totb = MAXBOXES + 1; float newpairdist = pairdist; float xrange = max[0]-min[0]; float yrange = max[1]-min[1]; float zrange = max[2]-min[2]; do { // printf(""pairdist: %f\n"", pairdist); pairdist = newpairdist; const float invpairdist = 1.0f / pairdist; xb = ((int)(xrange*invpairdist))+1; yb = ((int)(yrange*invpairdist))+1; zb = ((int)(zrange*invpairdist))+1; xytotb = yb * xb; totb = xytotb * zb; newpairdist = pairdist * 1.26f; // cbrt(2) is about 1.26 } while (totb > MAXBOXES || totb < 1); // check for integer wraparound too printf(""boxbuild\n""); printf(""totb %d\n"", totb); // 2. Sort each atom into appropriate bins boxatom = (int **) calloc(1, totb*sizeof(int *)); numinbox = (int *) calloc(1, totb*sizeof(int)); maxinbox = (int *) calloc(1, totb*sizeof(int)); if (boxatom == NULL || numinbox == NULL || maxinbox == NULL) { if (boxatom != NULL) free(boxatom); if (numinbox != NULL) free(numinbox); if (maxinbox != NULL) free(maxinbox); // msgErr << ""Gridsearch memory allocation failed, bailing out"" << sendmsg; return NULL; // ran out of memory, bail out! } const float invpairdist = 1.0f / pairdist; for (i=0; i= xb) axb = xb-1; if (ayb >= yb) ayb = yb-1; if (azb >= zb) azb = zb-1; aindex = azb * xytotb + ayb * xb + axb; // grow box if necessary if ((num = numinbox[aindex]) == maxinbox[aindex]) { boxatom[aindex] = (int *) realloc(boxatom[aindex], (num+4)*sizeof(int)); maxinbox[aindex] += 4; } // store atom index in box boxatom[aindex][num] = i; numinbox[aindex]++; // } } free(maxinbox); nbrlist = (int **) calloc(1, totb*sizeof(int *)); if (make_neighborlist(nbrlist, xb, yb, zb)) { if (boxatom != NULL) { for (i=0; inext = NULL; cur = head; printf(""pairlist\n""); // wkfmsgtimer *msgt = wkf_msg_timer_create(5); for (aindex = 0; (aindex < totb) && (!maxpairsreached); aindex++) { // printf(""%d\n"", aindex); int *tmpbox, *tmpnbr, *nbr; tmpbox = boxatom[aindex]; tmpnbr = nbrlist[aindex]; // if (wkf_msg_timer_timeout(msgt)) { // char tmpbuf[128]; // sprintf(tmpbuf, ""%6.2f"", (100.0f * aindex) / (float) totb); // msgInfo << ""vmd_gridsearch1: "" << tmpbuf << ""% complete"" << sendmsg; // } for (nbr = tmpnbr; (*nbr != -1) && (!maxpairsreached); nbr++) { int *nbrbox = boxatom[*nbr]; for (i=0; (i sqdist) continue; if (maxpairs > 0) { if (paircount >= maxpairs) { maxpairsreached = 1; continue; } } add_link(cur, ind1, ind2); paircount++; // XXX double-counting still ignores atoms with same coords... if (allow_double_counting) { add_link(cur, ind2, ind1); paircount++; } cur = cur->next; cur->next = NULL; // } } } } } for (i=0; inext; free(head); // if (maxpairsreached) { // printf(""maxpairs reached \n""); // } return cur; } static int test_function(int i) { return i; } static double sasa_grid(const float *pos,int natoms, float pairdist, int allow_double_counting, int maxpairs, const float *radius,const int npts, double srad, int pointstyle, int restricted, const int* restrictedList) { int on[natoms]; fill_n(on,natoms,1); // printf(""natoms %d\n"", natoms); // printf(""pairdist %f\n"", pairdist); // printf(""maxpairs %d\n"", maxpairs); GridSearchPair* pairs = vmd_gridsearch1(pos,natoms, on, pairdist, allow_double_counting,maxpairs); // vector > v(natoms,vector()); // printf(""size: %d\n"", v.size()); ResizeArray *pairlist = new ResizeArray[natoms]; GridSearchPair *p, *tmp; for (p = pairs; p != NULL; p = tmp) { int ind1=p->ind1; int ind2=p->ind2; // v[ind1].push_back(ind2); // v[ind2].push_back(ind1); pairlist[ind1].append(ind2); pairlist[ind2].append(ind1); tmp = p->next; free(p); } float *spherepts = new float[3*npts]; if (pointstyle) { static const float RAND_MAX_INV = 1.0f/VMD_RAND_MAX; vmd_srandom(38572111); // All the spheres use the same random points. for (int i=0; i &nbrs = pairlist[i]; // printf(""neighbors: %d\n"", nbrs.num()); for (int j=0; j > v(natoms,vector()); // // printf(""size: %d\n"", v.size()); // // ResizeArray *pairlist = new ResizeArray[natoms]; // GridSearchPair *p, *tmp; // for (p = pairs; p != NULL; p = tmp) { // int ind1=p->ind1; // int ind2=p->ind2; // v[ind1].push_back(ind2); // v[ind2].push_back(ind1); // // printf(""%f\n"", v[ind2]); // // pairlist[ind1].append(ind2); // // pairlist[ind2].append(ind1); // // printf(""%d\n"", ind1); // tmp = p->next; // free(p); // } // PyGILState_STATE gstate = PyGILState_Ensure(); // PyObject* result = PyList_New(0); // vector< vector >::iterator row; // vector::iterator col; // for (row = v.begin(); row != v.end(); row++) { // // printf(""row %d\n"", *row); // PyObject* tempo = PyList_New(0); // for (col = row->begin(); col != row->end(); col++) { // // printf(""%d \n"", *col); // PyList_Append(tempo, PyInt_FromLong(*col)); // } // PyList_Append(result,tempo); // tempo = NULL; // } // PyGILState_Release(gstate); // return result; // } } typedef ResizeArray atomlist; struct FindWithinData { int nthreads; int tid; int totb; int xytotb; int xb; int yb; int zb; float r2; const float * xyz; const atomlist * flgatoms; const atomlist * otheratoms; int * flgs; FindWithinData() : flgatoms(0), otheratoms(0), flgs(0) {} ~FindWithinData() { if (flgs) free(flgs); } }; #define MAXGRIDDIM 31 extern ""C"" int* find_within(const float *xyz, int *flgs, const int *others, int num, float r) { int i; float xmin, xmax, ymin, ymax, zmin, zmax; float oxmin, oymin, ozmin, oxmax, oymax, ozmax; float xwidth, ywidth, zwidth; const float *pos; int *result = new int[num]; fill_n(result,num,0); // for (size_t i = 0; i < num; i++) { // pos=xyz+3*i; // printf(""%f %f %f\n"", pos[0],pos[1],pos[2]); // } // find min/max bounds of atom coordinates in flgs if (!find_minmax_selected(num, flgs, xyz, xmin, ymin, zmin, xmax, ymax, zmax) || !find_minmax_selected(num, others, xyz, oxmin, oymin, ozmin, oxmax, oymax, ozmax)) { memset(flgs, 0, num*sizeof(int)); return result; } // Find the set of atoms with the smallest extent; here we use the sum // of the box dimensions though other choices might be better. float size = xmax+ymax+zmax - (xmin+ymin+zmin); float osize = oxmax+oymax+ozmax - (oxmin+oymin+ozmin); if (osize < size) { xmin=oxmin; ymin=oymin; zmin=ozmin; xmax=oxmax; ymax=oymax; zmax=ozmax; } // Generate a grid of mesh size r based on the computed size of the molecule. // We limit the size of the grid cell dimensions so that we don't get too // many grid cells. xwidth = (xmax-xmin)/(MAXGRIDDIM-1); if (xwidth < r) xwidth = r; ywidth = (ymax-ymin)/(MAXGRIDDIM-1); if (ywidth < r) ywidth = r; zwidth = (zmax-zmin)/(MAXGRIDDIM-1); if (zwidth < r) zwidth = r; // Adjust the bounds so that we include atoms that are in the outermost // grid cells. xmin -= xwidth; xmax += xwidth; ymin -= ywidth; ymax += ywidth; zmin -= zwidth; zmax += zwidth; // The number of grid cells needed in each dimension is // (int)((xmax-xmin)/xwidth) + 1 const int xb = (int)((xmax-xmin)/xwidth) + 1; const int yb = (int)((ymax-ymin)/ywidth) + 1; const int zb = (int)((zmax-zmin)/zwidth) + 1; int xytotb = yb * xb; int totb = xytotb * zb; atomlist* flgatoms = new atomlist[totb]; atomlist* otheratoms = new atomlist[totb]; float ixwidth = 1.0f/xwidth; float iywidth = 1.0f/ywidth; float izwidth = 1.0f/zwidth; for (i=0; ixmax || yiymax || zizmax) { continue; } AtomEntry entry(xi,yi,zi,i); int axb = (int)((xi - xmin)*ixwidth); int ayb = (int)((yi - ymin)*iywidth); int azb = (int)((zi - zmin)*izwidth); // Due to floating point error in the calcuation of bin widths, we // have to range clamp the computed box indices. if (axb==xb) axb=xb-1; if (ayb==yb) ayb=yb-1; if (azb==zb) azb=zb-1; int aindex = azb*xytotb + ayb*xb + axb; // TODO maybe change so that others does not contain the atoms of flags if (others[i]) otheratoms[aindex].append(entry); if ( flgs[i]) flgatoms[aindex].append(entry); } memset(flgs, 0, num*sizeof(int)); const float r2 = (float) (r*r); // set up workspace for multithreaded calculation int nthreads; #ifdef VMDTHREADS nthreads = wkf_thread_numprocessors(); wkf_thread_t * threads = (wkf_thread_t *)calloc(nthreads, sizeof(wkf_thread_t)); #else nthreads = 1; #endif FindWithinData *data = new FindWithinData[nthreads]; for (i=0; inthreads; const int tid = data->tid; const int totb = data->totb; const int xytotb = data->xytotb; const int xb = data->xb; const int yb = data->yb; const int zb = data->zb; const float r2 = data->r2; const atomlist * flgatoms = data->flgatoms; const atomlist * otheratoms = data->otheratoms; int * flgs = data->flgs; // Loop over boxes, checking for flg atoms and other atoms within one // box of each other. When one is found, mark the flag. for (int aindex = tid; aindex 0) nbrs[n++] = aindex - xb + 1; if (xi > 0 && zi < (zb-1)) nbrs[n++] = aindex + xytotb - 1; if (yi > 0 && zi < (zb-1)) nbrs[n++] = aindex + xytotb - xb; if (xi < (xb-1) && yi < (yb-1) && zi < (zb-1)) nbrs[n++] = aindex + xytotb + xb + 1; if (xi > 0 && yi < (yb-1) && zi < (zb-1)) nbrs[n++] = aindex + xytotb + xb - 1; if (xi < (xb-1) && yi > 0 && zi < (zb-1)) nbrs[n++] = aindex + xytotb - xb + 1; if (xi > 0 && yi > 0 && zi < (zb-1)) nbrs[n++] = aindex + xytotb - xb - 1; const atomlist& boxflg = flgatoms[aindex]; // Compare the atoms in boxflg to those in nbrother int i; for (i=0; i #ifndef offsetof #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) #endif #if !defined(WIN32) && !defined(MS_WINDOWS) #ifndef __stdcall #define __stdcall #endif #ifndef __cdecl #define __cdecl #endif #ifndef __fastcall #define __fastcall #endif #endif #ifndef DL_IMPORT #define DL_IMPORT(t) t #endif #ifndef DL_EXPORT #define DL_EXPORT(t) t #endif #ifndef HAVE_LONG_LONG #if PY_VERSION_HEX >= 0x03030000 || (PY_MAJOR_VERSION == 2 && PY_VERSION_HEX >= 0x02070000) #define HAVE_LONG_LONG #endif #endif #ifndef PY_LONG_LONG #define PY_LONG_LONG LONG_LONG #endif #ifndef Py_HUGE_VAL #define Py_HUGE_VAL HUGE_VAL #endif #ifdef PYPY_VERSION #define CYTHON_COMPILING_IN_PYPY 1 #define CYTHON_COMPILING_IN_PYSTON 0 #define CYTHON_COMPILING_IN_CPYTHON 0 #undef CYTHON_USE_TYPE_SLOTS #define CYTHON_USE_TYPE_SLOTS 0 #undef CYTHON_USE_ASYNC_SLOTS #define CYTHON_USE_ASYNC_SLOTS 0 #undef CYTHON_USE_PYLIST_INTERNALS #define CYTHON_USE_PYLIST_INTERNALS 0 #undef CYTHON_USE_UNICODE_INTERNALS #define CYTHON_USE_UNICODE_INTERNALS 0 #undef CYTHON_USE_UNICODE_WRITER #define CYTHON_USE_UNICODE_WRITER 0 #undef CYTHON_USE_PYLONG_INTERNALS #define CYTHON_USE_PYLONG_INTERNALS 0 #undef CYTHON_AVOID_BORROWED_REFS #define CYTHON_AVOID_BORROWED_REFS 1 #undef CYTHON_ASSUME_SAFE_MACROS #define CYTHON_ASSUME_SAFE_MACROS 0 #undef CYTHON_UNPACK_METHODS #define CYTHON_UNPACK_METHODS 0 #undef CYTHON_FAST_THREAD_STATE #define CYTHON_FAST_THREAD_STATE 0 #undef CYTHON_FAST_PYCALL #define CYTHON_FAST_PYCALL 0 #elif defined(PYSTON_VERSION) #define CYTHON_COMPILING_IN_PYPY 0 #define CYTHON_COMPILING_IN_PYSTON 1 #define CYTHON_COMPILING_IN_CPYTHON 0 #ifndef CYTHON_USE_TYPE_SLOTS #define CYTHON_USE_TYPE_SLOTS 1 #endif #undef CYTHON_USE_ASYNC_SLOTS #define CYTHON_USE_ASYNC_SLOTS 0 #undef CYTHON_USE_PYLIST_INTERNALS #define CYTHON_USE_PYLIST_INTERNALS 0 #ifndef CYTHON_USE_UNICODE_INTERNALS #define CYTHON_USE_UNICODE_INTERNALS 1 #endif #undef CYTHON_USE_UNICODE_WRITER #define CYTHON_USE_UNICODE_WRITER 0 #undef CYTHON_USE_PYLONG_INTERNALS #define CYTHON_USE_PYLONG_INTERNALS 0 #ifndef CYTHON_AVOID_BORROWED_REFS #define CYTHON_AVOID_BORROWED_REFS 0 #endif #ifndef CYTHON_ASSUME_SAFE_MACROS #define CYTHON_ASSUME_SAFE_MACROS 1 #endif #ifndef CYTHON_UNPACK_METHODS #define CYTHON_UNPACK_METHODS 1 #endif #undef CYTHON_FAST_THREAD_STATE #define CYTHON_FAST_THREAD_STATE 0 #undef CYTHON_FAST_PYCALL #define CYTHON_FAST_PYCALL 0 #else #define CYTHON_COMPILING_IN_PYPY 0 #define CYTHON_COMPILING_IN_PYSTON 0 #define CYTHON_COMPILING_IN_CPYTHON 1 #ifndef CYTHON_USE_TYPE_SLOTS #define CYTHON_USE_TYPE_SLOTS 1 #endif #if PY_MAJOR_VERSION < 3 #undef CYTHON_USE_ASYNC_SLOTS #define CYTHON_USE_ASYNC_SLOTS 0 #elif !defined(CYTHON_USE_ASYNC_SLOTS) #define CYTHON_USE_ASYNC_SLOTS 1 #endif #if PY_VERSION_HEX < 0x02070000 #undef CYTHON_USE_PYLONG_INTERNALS #define CYTHON_USE_PYLONG_INTERNALS 0 #elif !defined(CYTHON_USE_PYLONG_INTERNALS) #define CYTHON_USE_PYLONG_INTERNALS 1 #endif #ifndef CYTHON_USE_PYLIST_INTERNALS #define CYTHON_USE_PYLIST_INTERNALS 1 #endif #ifndef CYTHON_USE_UNICODE_INTERNALS #define CYTHON_USE_UNICODE_INTERNALS 1 #endif #if PY_VERSION_HEX < 0x030300F0 #undef CYTHON_USE_UNICODE_WRITER #define CYTHON_USE_UNICODE_WRITER 0 #elif !defined(CYTHON_USE_UNICODE_WRITER) #define CYTHON_USE_UNICODE_WRITER 1 #endif #ifndef CYTHON_AVOID_BORROWED_REFS #define CYTHON_AVOID_BORROWED_REFS 0 #endif #ifndef CYTHON_ASSUME_SAFE_MACROS #define CYTHON_ASSUME_SAFE_MACROS 1 #endif #ifndef CYTHON_UNPACK_METHODS #define CYTHON_UNPACK_METHODS 1 #endif #ifndef CYTHON_FAST_THREAD_STATE #define CYTHON_FAST_THREAD_STATE 1 #endif #ifndef CYTHON_FAST_PYCALL #define CYTHON_FAST_PYCALL 1 #endif #endif #if !defined(CYTHON_FAST_PYCCALL) #define CYTHON_FAST_PYCCALL (CYTHON_FAST_PYCALL && PY_VERSION_HEX >= 0x030600B1) #endif #if CYTHON_USE_PYLONG_INTERNALS #include ""longintrepr.h"" #undef SHIFT #undef BASE #undef MASK #endif #if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) #define Py_OptimizeFlag 0 #endif #define __PYX_BUILD_PY_SSIZE_T ""n"" #define CYTHON_FORMAT_SSIZE_T ""z"" #if PY_MAJOR_VERSION < 3 #define __Pyx_BUILTIN_MODULE_NAME ""__builtin__"" #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #define __Pyx_DefaultClassType PyClass_Type #else #define __Pyx_BUILTIN_MODULE_NAME ""builtins"" #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #define __Pyx_DefaultClassType PyType_Type #endif #ifndef Py_TPFLAGS_CHECKTYPES #define Py_TPFLAGS_CHECKTYPES 0 #endif #ifndef Py_TPFLAGS_HAVE_INDEX #define Py_TPFLAGS_HAVE_INDEX 0 #endif #ifndef Py_TPFLAGS_HAVE_NEWBUFFER #define Py_TPFLAGS_HAVE_NEWBUFFER 0 #endif #ifndef Py_TPFLAGS_HAVE_FINALIZE #define Py_TPFLAGS_HAVE_FINALIZE 0 #endif #ifndef METH_FASTCALL #define METH_FASTCALL 0x80 typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject **args, Py_ssize_t nargs, PyObject *kwnames); #else #define __Pyx_PyCFunctionFast _PyCFunctionFast #endif #if CYTHON_FAST_PYCCALL #define __Pyx_PyFastCFunction_Check(func)\ ((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST))))) #else #define __Pyx_PyFastCFunction_Check(func) 0 #endif #if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) #define CYTHON_PEP393_ENABLED 1 #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ 0 : _PyUnicode_Ready((PyObject *)(op))) #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u) #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u) #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) #else #define CYTHON_PEP393_ENABLED 0 #define PyUnicode_1BYTE_KIND 1 #define PyUnicode_2BYTE_KIND 2 #define PyUnicode_4BYTE_KIND 4 #define __Pyx_PyUnicode_READY(op) (0) #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111) #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE)) #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u)) #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i])) #define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch) #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u)) #endif #if CYTHON_COMPILING_IN_PYPY #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) #else #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check) #define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format) #define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, ""__format__"", ""O"", fmt) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) #define PyObject_Malloc(s) PyMem_Malloc(s) #define PyObject_Free(p) PyMem_Free(p) #define PyObject_Realloc(p) PyMem_Realloc(p) #endif #if CYTHON_COMPILING_IN_PYSTON #define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co) #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno) #else #define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0) #define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno) #endif #define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) #define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b) #else #define __Pyx_PyString_Format(a, b) PyString_Format(a, b) #endif #if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII) #define PyObject_ASCII(o) PyObject_Repr(o) #endif #if PY_MAJOR_VERSION >= 3 #define PyBaseString_Type PyUnicode_Type #define PyStringObject PyUnicodeObject #define PyString_Type PyUnicode_Type #define PyString_Check PyUnicode_Check #define PyString_CheckExact PyUnicode_CheckExact #endif #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) #else #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj)) #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj)) #endif #ifndef PySet_CheckExact #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) #endif #define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) #define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception) #if PY_MAJOR_VERSION >= 3 #define PyIntObject PyLongObject #define PyInt_Type PyLong_Type #define PyInt_Check(op) PyLong_Check(op) #define PyInt_CheckExact(op) PyLong_CheckExact(op) #define PyInt_FromString PyLong_FromString #define PyInt_FromUnicode PyLong_FromUnicode #define PyInt_FromLong PyLong_FromLong #define PyInt_FromSize_t PyLong_FromSize_t #define PyInt_FromSsize_t PyLong_FromSsize_t #define PyInt_AsLong PyLong_AsLong #define PyInt_AS_LONG PyLong_AS_LONG #define PyInt_AsSsize_t PyLong_AsSsize_t #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask #define PyNumber_Int PyNumber_Long #endif #if PY_MAJOR_VERSION >= 3 #define PyBoolObject PyLongObject #endif #if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY #ifndef PyUnicode_InternFromString #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) #endif #endif #if PY_VERSION_HEX < 0x030200A4 typedef long Py_hash_t; #define __Pyx_PyInt_FromHash_t PyInt_FromLong #define __Pyx_PyInt_AsHash_t PyInt_AsLong #else #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t #endif #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func)) #else #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) #endif #if CYTHON_USE_ASYNC_SLOTS #if PY_VERSION_HEX >= 0x030500B1 #define __Pyx_PyAsyncMethodsStruct PyAsyncMethods #define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async) #else typedef struct { unaryfunc am_await; unaryfunc am_aiter; unaryfunc am_anext; } __Pyx_PyAsyncMethodsStruct; #define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved)) #endif #else #define __Pyx_PyType_AsAsync(obj) NULL #endif #ifndef CYTHON_RESTRICT #if defined(__GNUC__) #define CYTHON_RESTRICT __restrict__ #elif defined(_MSC_VER) && _MSC_VER >= 1400 #define CYTHON_RESTRICT __restrict #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L #define CYTHON_RESTRICT restrict #else #define CYTHON_RESTRICT #endif #endif #ifndef CYTHON_UNUSED # if defined(__GNUC__) # if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4)) # define CYTHON_UNUSED __attribute__ ((__unused__)) # else # define CYTHON_UNUSED # endif # elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER)) # define CYTHON_UNUSED __attribute__ ((__unused__)) # else # define CYTHON_UNUSED # endif #endif #ifndef CYTHON_MAYBE_UNUSED_VAR # if defined(__cplusplus) template void CYTHON_MAYBE_UNUSED_VAR( const T& ) { } # else # define CYTHON_MAYBE_UNUSED_VAR(x) (void)(x) # endif #endif #ifndef CYTHON_NCP_UNUSED # if CYTHON_COMPILING_IN_CPYTHON # define CYTHON_NCP_UNUSED # else # define CYTHON_NCP_UNUSED CYTHON_UNUSED # endif #endif #define __Pyx_void_to_None(void_result) ((void)(void_result), Py_INCREF(Py_None), Py_None) #ifndef CYTHON_INLINE #if defined(__clang__) #define CYTHON_INLINE __inline__ __attribute__ ((__unused__)) #elif defined(__GNUC__) #define CYTHON_INLINE __inline__ #elif defined(_MSC_VER) #define CYTHON_INLINE __inline #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L #define CYTHON_INLINE inline #else #define CYTHON_INLINE #endif #endif #if defined(WIN32) || defined(MS_WINDOWS) #define _USE_MATH_DEFINES #endif #include #ifdef NAN #define __PYX_NAN() ((float) NAN) #else static CYTHON_INLINE float __PYX_NAN() { float value; memset(&value, 0xFF, sizeof(value)); return value; } #endif #if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL) #define __Pyx_truncl trunc #else #define __Pyx_truncl truncl #endif #define __PYX_ERR(f_index, lineno, Ln_error) \ { \ __pyx_filename = __pyx_f[f_index]; __pyx_lineno = lineno; __pyx_clineno = __LINE__; goto Ln_error; \ } #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) #else #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) #endif #ifndef __PYX_EXTERN_C #ifdef __cplusplus #define __PYX_EXTERN_C extern ""C"" #else #define __PYX_EXTERN_C extern #endif #endif #define __PYX_HAVE__wrap_vmd #define __PYX_HAVE_API__wrap_vmd #include ""vmd_wrapper.cpp"" #ifdef _OPENMP #include #endif /* _OPENMP */ #ifdef PYREX_WITHOUT_ASSERTIONS #define CYTHON_WITHOUT_ASSERTIONS #endif typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding; const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; #define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 #define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT 0 #define __PYX_DEFAULT_STRING_ENCODING """" #define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString #define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize #define __Pyx_uchar_cast(c) ((unsigned char)c) #define __Pyx_long_cast(x) ((long)x) #define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\ (sizeof(type) < sizeof(Py_ssize_t)) ||\ (sizeof(type) > sizeof(Py_ssize_t) &&\ likely(v < (type)PY_SSIZE_T_MAX ||\ v == (type)PY_SSIZE_T_MAX) &&\ (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\ v == (type)PY_SSIZE_T_MIN))) ||\ (sizeof(type) == sizeof(Py_ssize_t) &&\ (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\ v == (type)PY_SSIZE_T_MAX))) ) #if defined (__cplusplus) && __cplusplus >= 201103L #include #define __Pyx_sst_abs(value) std::abs(value) #elif SIZEOF_INT >= SIZEOF_SIZE_T #define __Pyx_sst_abs(value) abs(value) #elif SIZEOF_LONG >= SIZEOF_SIZE_T #define __Pyx_sst_abs(value) labs(value) #elif defined (_MSC_VER) && defined (_M_X64) #define __Pyx_sst_abs(value) _abs64(value) #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L #define __Pyx_sst_abs(value) llabs(value) #elif defined (__GNUC__) #define __Pyx_sst_abs(value) __builtin_llabs(value) #else #define __Pyx_sst_abs(value) ((value<0) ? -value : value) #endif static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject*); static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); #define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) #define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l) #define __Pyx_PyBytes_FromString PyBytes_FromString #define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); #if PY_MAJOR_VERSION < 3 #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize #else #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize #endif #define __Pyx_PyObject_AsSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) #define __Pyx_PyObject_AsUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) #define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) #define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) #define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) #define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) #define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) #if PY_MAJOR_VERSION < 3 static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { const Py_UNICODE *u_end = u; while (*u_end++) ; return (size_t)(u_end - u - 1); } #else #define __Pyx_Py_UNICODE_strlen Py_UNICODE_strlen #endif #define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) #define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode #define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode #define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) #define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) #define __Pyx_PyBool_FromLong(b) ((b) ? 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__pyx_code_cache.entries; if (unlikely(!code_line)) { return; } if (unlikely(!entries)) { entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); if (likely(entries)) { __pyx_code_cache.entries = entries; __pyx_code_cache.max_count = 64; __pyx_code_cache.count = 1; entries[0].code_line = code_line; entries[0].code_object = code_object; Py_INCREF(code_object); } return; } pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { PyCodeObject* tmp = entries[pos].code_object; entries[pos].code_object = code_object; Py_DECREF(tmp); return; } if (__pyx_code_cache.count == __pyx_code_cache.max_count) { int new_max = __pyx_code_cache.max_count + 64; entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( __pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry)); if (unlikely(!entries)) { return; } __pyx_code_cache.entries = entries; __pyx_code_cache.max_count = new_max; } for (i=__pyx_code_cache.count; i>pos; i--) { entries[i] = entries[i-1]; } entries[pos].code_line = code_line; entries[pos].code_object = code_object; __pyx_code_cache.count++; Py_INCREF(code_object); } /* AddTraceback */ #include ""compile.h"" #include ""frameobject.h"" #include ""traceback.h"" static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( const char *funcname, int c_line, int py_line, const char *filename) { PyCodeObject *py_code = 0; PyObject *py_srcfile = 0; PyObject *py_funcname = 0; #if PY_MAJOR_VERSION < 3 py_srcfile = PyString_FromString(filename); #else py_srcfile = PyUnicode_FromString(filename); #endif if (!py_srcfile) goto bad; if (c_line) { #if PY_MAJOR_VERSION < 3 py_funcname = PyString_FromFormat( ""%s (%s:%d)"", funcname, __pyx_cfilenm, c_line); #else py_funcname = PyUnicode_FromFormat( ""%s (%s:%d)"", funcname, __pyx_cfilenm, c_line); #endif } else { #if PY_MAJOR_VERSION < 3 py_funcname = PyString_FromString(funcname); #else py_funcname = PyUnicode_FromString(funcname); #endif } if (!py_funcname) goto bad; py_code = __Pyx_PyCode_New( 0, 0, 0, 0, 0, __pyx_empty_bytes, /*PyObject *code,*/ __pyx_empty_tuple, /*PyObject *consts,*/ __pyx_empty_tuple, /*PyObject *names,*/ __pyx_empty_tuple, /*PyObject *varnames,*/ __pyx_empty_tuple, /*PyObject *freevars,*/ __pyx_empty_tuple, /*PyObject *cellvars,*/ py_srcfile, /*PyObject *filename,*/ py_funcname, /*PyObject *name,*/ py_line, __pyx_empty_bytes /*PyObject *lnotab*/ ); Py_DECREF(py_srcfile); Py_DECREF(py_funcname); return py_code; bad: Py_XDECREF(py_srcfile); Py_XDECREF(py_funcname); return NULL; } static void __Pyx_AddTraceback(const char *funcname, int c_line, int py_line, const char *filename) { PyCodeObject *py_code = 0; PyFrameObject *py_frame = 0; py_code = __pyx_find_code_object(c_line ? c_line : py_line); if (!py_code) { py_code = __Pyx_CreateCodeObjectForTraceback( funcname, c_line, py_line, filename); if (!py_code) goto bad; __pyx_insert_code_object(c_line ? c_line : py_line, py_code); } py_frame = PyFrame_New( PyThreadState_GET(), /*PyThreadState *tstate,*/ py_code, /*PyCodeObject *code,*/ __pyx_d, /*PyObject *globals,*/ 0 /*PyObject *locals*/ ); if (!py_frame) goto bad; __Pyx_PyFrame_SetLineNumber(py_frame, py_line); PyTraceBack_Here(py_frame); bad: Py_XDECREF(py_code); Py_XDECREF(py_frame); } /* CIntToPy */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(long) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(long) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); #endif } } else { if (sizeof(long) <= sizeof(long)) { return PyInt_FromLong((long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); #endif } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(long), little, !is_unsigned); } } /* CIntFromPyVerify */ #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) #define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) #define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ {\ func_type value = func_value;\ if (sizeof(target_type) < sizeof(func_type)) {\ if (unlikely(value != (func_type) (target_type) value)) {\ func_type zero = 0;\ if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ return (target_type) -1;\ if (is_unsigned && unlikely(value < zero))\ goto raise_neg_overflow;\ else\ goto raise_overflow;\ }\ }\ return (target_type) value;\ } /* CIntFromPy */ static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(long) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (long) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (long) 0; case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) case 2: if (8 * sizeof(long) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; case 3: if (8 * sizeof(long) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; case 4: if (8 * sizeof(long) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (long) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(long) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) #endif } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (long) 0; case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) case -2: if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 2: if (8 * sizeof(long) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case -3: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 3: if (8 * sizeof(long) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case -4: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 4: if (8 * sizeof(long) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; } #endif if (sizeof(long) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) #endif } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, ""_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers""); #else long val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (long) -1; } } else { long val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (long) -1; val = __Pyx_PyInt_As_long(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, ""value too large to convert to long""); return (long) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, ""can't convert negative value to long""); return (long) -1; } /* CIntFromPy */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { const int neg_one = (int) -1, const_zero = (int) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(int) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (int) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (int) 0; case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) case 2: if (8 * sizeof(int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; case 3: if (8 * sizeof(int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; case 4: if (8 * sizeof(int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (int) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(int) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) #endif } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (int) 0; case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) case -2: if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 2: if (8 * sizeof(int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case -3: if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 3: if (8 * sizeof(int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case -4: if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 4: if (8 * sizeof(int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; } #endif if (sizeof(int) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) #endif } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, ""_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers""); #else int val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (int) -1; } } else { int val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (int) -1; val = __Pyx_PyInt_As_int(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, ""value too large to convert to int""); return (int) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, ""can't convert negative value to int""); return (int) -1; } /* CheckBinaryVersion */ static int __Pyx_check_binary_version(void) { char ctversion[4], rtversion[4]; PyOS_snprintf(ctversion, 4, ""%d.%d"", PY_MAJOR_VERSION, PY_MINOR_VERSION); PyOS_snprintf(rtversion, 4, ""%s"", Py_GetVersion()); if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) { char message[200]; PyOS_snprintf(message, sizeof(message), ""compiletime version %s of module '%.100s' "" ""does not match runtime version %s"", ctversion, __Pyx_MODULE_NAME, rtversion); return PyErr_WarnEx(NULL, message, 1); } return 0; } /* InitStrings */ static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { while (t->p) { #if PY_MAJOR_VERSION < 3 if (t->is_unicode) { *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); } else if (t->intern) { *t->p = PyString_InternFromString(t->s); } else { *t->p = PyString_FromStringAndSize(t->s, t->n - 1); } #else if (t->is_unicode | t->is_str) { if (t->intern) { *t->p = PyUnicode_InternFromString(t->s); } else if (t->encoding) { *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); } else { *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); } } else { *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); } #endif if (!*t->p) return -1; ++t; } return 0; } static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); } static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) { Py_ssize_t ignore; return __Pyx_PyObject_AsStringAndSize(o, &ignore); } static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { #if CYTHON_COMPILING_IN_CPYTHON && (__PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT) if ( #if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII __Pyx_sys_getdefaultencoding_not_ascii && #endif PyUnicode_Check(o)) { #if PY_VERSION_HEX < 0x03030000 char* defenc_c; PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); if (!defenc) return NULL; defenc_c = PyBytes_AS_STRING(defenc); #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII { char* end = defenc_c + PyBytes_GET_SIZE(defenc); char* c; for (c = defenc_c; c < end; c++) { if ((unsigned char) (*c) >= 128) { PyUnicode_AsASCIIString(o); return NULL; } } } #endif *length = PyBytes_GET_SIZE(defenc); return defenc_c; #else if (__Pyx_PyUnicode_READY(o) == -1) return NULL; #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII if (PyUnicode_IS_ASCII(o)) { *length = PyUnicode_GET_LENGTH(o); return PyUnicode_AsUTF8(o); } else { PyUnicode_AsASCIIString(o); return NULL; } #else return PyUnicode_AsUTF8AndSize(o, length); #endif #endif } else #endif #if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) if (PyByteArray_Check(o)) { *length = PyByteArray_GET_SIZE(o); return PyByteArray_AS_STRING(o); } else #endif { char* result; int r = PyBytes_AsStringAndSize(o, &result, length); if (unlikely(r < 0)) { return NULL; } else { return result; } } } static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { int is_true = x == Py_True; if (is_true | (x == Py_False) | (x == Py_None)) return is_true; else return PyObject_IsTrue(x); } static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { #if CYTHON_USE_TYPE_SLOTS PyNumberMethods *m; #endif const char *name = NULL; PyObject *res = NULL; #if PY_MAJOR_VERSION < 3 if (PyInt_Check(x) || PyLong_Check(x)) #else if (PyLong_Check(x)) #endif return __Pyx_NewRef(x); #if CYTHON_USE_TYPE_SLOTS m = Py_TYPE(x)->tp_as_number; #if PY_MAJOR_VERSION < 3 if (m && m->nb_int) { name = ""int""; res = PyNumber_Int(x); } else if (m && m->nb_long) { name = ""long""; res = PyNumber_Long(x); } #else if (m && m->nb_int) { name = ""int""; res = PyNumber_Long(x); } #endif #else res = PyNumber_Int(x); #endif if (res) { #if PY_MAJOR_VERSION < 3 if (!PyInt_Check(res) && !PyLong_Check(res)) { #else if (!PyLong_Check(res)) { #endif PyErr_Format(PyExc_TypeError, ""__%.4s__ returned non-%.4s (type %.200s)"", name, name, Py_TYPE(res)->tp_name); Py_DECREF(res); return NULL; } } else if (!PyErr_Occurred()) { PyErr_SetString(PyExc_TypeError, ""an integer is required""); } return res; } static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { Py_ssize_t ival; PyObject *x; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_CheckExact(b))) { if (sizeof(Py_ssize_t) >= sizeof(long)) return PyInt_AS_LONG(b); else return PyInt_AsSsize_t(x); } #endif if (likely(PyLong_CheckExact(b))) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)b)->ob_digit; const Py_ssize_t size = Py_SIZE(b); if (likely(__Pyx_sst_abs(size) <= 1)) { ival = likely(size) ? digits[0] : 0; if (size == -1) ival = -ival; return ival; } else { switch (size) { case 2: if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -2: if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case 3: if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -3: if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case 4: if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -4: if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; } } #endif return PyLong_AsSsize_t(b); } x = PyNumber_Index(b); if (!x) return -1; ival = PyInt_AsSsize_t(x); Py_DECREF(x); return ival; } static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { return PyInt_FromSize_t(ival); } #endif /* Py_PYTHON_H */ ","C" "Biophysics","maxscheurer/pycontact","testing/cython/vmd/wrap_vmd.cpp",".cpp","75206","1928","/* Generated by Cython 0.25.2 */ #define PY_SSIZE_T_CLEAN #include ""Python.h"" #ifndef Py_PYTHON_H #error Python headers needed to compile C extensions, please install development version of Python. #elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03020000) #error Cython requires Python 2.6+ or Python 3.2+. #else #define CYTHON_ABI ""0_25_2"" #include #ifndef offsetof #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) #endif #if !defined(WIN32) && !defined(MS_WINDOWS) #ifndef __stdcall #define __stdcall #endif #ifndef __cdecl #define __cdecl #endif #ifndef __fastcall #define __fastcall #endif #endif #ifndef DL_IMPORT #define DL_IMPORT(t) t #endif #ifndef DL_EXPORT #define DL_EXPORT(t) t #endif #ifndef HAVE_LONG_LONG #if PY_VERSION_HEX >= 0x03030000 || (PY_MAJOR_VERSION == 2 && PY_VERSION_HEX >= 0x02070000) #define HAVE_LONG_LONG #endif #endif #ifndef PY_LONG_LONG #define PY_LONG_LONG LONG_LONG #endif #ifndef Py_HUGE_VAL #define Py_HUGE_VAL HUGE_VAL #endif #ifdef PYPY_VERSION #define CYTHON_COMPILING_IN_PYPY 1 #define CYTHON_COMPILING_IN_PYSTON 0 #define CYTHON_COMPILING_IN_CPYTHON 0 #undef CYTHON_USE_TYPE_SLOTS #define CYTHON_USE_TYPE_SLOTS 0 #undef CYTHON_USE_ASYNC_SLOTS #define CYTHON_USE_ASYNC_SLOTS 0 #undef CYTHON_USE_PYLIST_INTERNALS #define CYTHON_USE_PYLIST_INTERNALS 0 #undef CYTHON_USE_UNICODE_INTERNALS #define CYTHON_USE_UNICODE_INTERNALS 0 #undef CYTHON_USE_UNICODE_WRITER #define CYTHON_USE_UNICODE_WRITER 0 #undef CYTHON_USE_PYLONG_INTERNALS #define CYTHON_USE_PYLONG_INTERNALS 0 #undef CYTHON_AVOID_BORROWED_REFS #define CYTHON_AVOID_BORROWED_REFS 1 #undef CYTHON_ASSUME_SAFE_MACROS #define CYTHON_ASSUME_SAFE_MACROS 0 #undef CYTHON_UNPACK_METHODS #define CYTHON_UNPACK_METHODS 0 #undef CYTHON_FAST_THREAD_STATE #define CYTHON_FAST_THREAD_STATE 0 #undef CYTHON_FAST_PYCALL #define CYTHON_FAST_PYCALL 0 #elif defined(PYSTON_VERSION) #define CYTHON_COMPILING_IN_PYPY 0 #define CYTHON_COMPILING_IN_PYSTON 1 #define CYTHON_COMPILING_IN_CPYTHON 0 #ifndef CYTHON_USE_TYPE_SLOTS #define CYTHON_USE_TYPE_SLOTS 1 #endif #undef CYTHON_USE_ASYNC_SLOTS #define CYTHON_USE_ASYNC_SLOTS 0 #undef CYTHON_USE_PYLIST_INTERNALS #define CYTHON_USE_PYLIST_INTERNALS 0 #ifndef CYTHON_USE_UNICODE_INTERNALS #define CYTHON_USE_UNICODE_INTERNALS 1 #endif #undef CYTHON_USE_UNICODE_WRITER #define CYTHON_USE_UNICODE_WRITER 0 #undef CYTHON_USE_PYLONG_INTERNALS #define CYTHON_USE_PYLONG_INTERNALS 0 #ifndef CYTHON_AVOID_BORROWED_REFS #define CYTHON_AVOID_BORROWED_REFS 0 #endif #ifndef CYTHON_ASSUME_SAFE_MACROS #define CYTHON_ASSUME_SAFE_MACROS 1 #endif #ifndef CYTHON_UNPACK_METHODS #define CYTHON_UNPACK_METHODS 1 #endif #undef CYTHON_FAST_THREAD_STATE #define CYTHON_FAST_THREAD_STATE 0 #undef CYTHON_FAST_PYCALL #define CYTHON_FAST_PYCALL 0 #else #define CYTHON_COMPILING_IN_PYPY 0 #define CYTHON_COMPILING_IN_PYSTON 0 #define CYTHON_COMPILING_IN_CPYTHON 1 #ifndef CYTHON_USE_TYPE_SLOTS #define CYTHON_USE_TYPE_SLOTS 1 #endif #if PY_MAJOR_VERSION < 3 #undef CYTHON_USE_ASYNC_SLOTS #define CYTHON_USE_ASYNC_SLOTS 0 #elif !defined(CYTHON_USE_ASYNC_SLOTS) #define CYTHON_USE_ASYNC_SLOTS 1 #endif #if PY_VERSION_HEX < 0x02070000 #undef CYTHON_USE_PYLONG_INTERNALS #define CYTHON_USE_PYLONG_INTERNALS 0 #elif !defined(CYTHON_USE_PYLONG_INTERNALS) #define CYTHON_USE_PYLONG_INTERNALS 1 #endif #ifndef CYTHON_USE_PYLIST_INTERNALS #define CYTHON_USE_PYLIST_INTERNALS 1 #endif #ifndef CYTHON_USE_UNICODE_INTERNALS #define CYTHON_USE_UNICODE_INTERNALS 1 #endif #if PY_VERSION_HEX < 0x030300F0 #undef CYTHON_USE_UNICODE_WRITER #define CYTHON_USE_UNICODE_WRITER 0 #elif !defined(CYTHON_USE_UNICODE_WRITER) #define CYTHON_USE_UNICODE_WRITER 1 #endif #ifndef CYTHON_AVOID_BORROWED_REFS #define CYTHON_AVOID_BORROWED_REFS 0 #endif #ifndef CYTHON_ASSUME_SAFE_MACROS #define CYTHON_ASSUME_SAFE_MACROS 1 #endif #ifndef CYTHON_UNPACK_METHODS #define CYTHON_UNPACK_METHODS 1 #endif #ifndef CYTHON_FAST_THREAD_STATE #define CYTHON_FAST_THREAD_STATE 1 #endif #ifndef CYTHON_FAST_PYCALL #define CYTHON_FAST_PYCALL 1 #endif #endif #if !defined(CYTHON_FAST_PYCCALL) #define CYTHON_FAST_PYCCALL (CYTHON_FAST_PYCALL && PY_VERSION_HEX >= 0x030600B1) #endif #if CYTHON_USE_PYLONG_INTERNALS #include ""longintrepr.h"" #undef SHIFT #undef BASE #undef MASK #endif #if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) #define Py_OptimizeFlag 0 #endif #define __PYX_BUILD_PY_SSIZE_T ""n"" #define CYTHON_FORMAT_SSIZE_T ""z"" #if PY_MAJOR_VERSION < 3 #define __Pyx_BUILTIN_MODULE_NAME ""__builtin__"" #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #define __Pyx_DefaultClassType PyClass_Type #else #define __Pyx_BUILTIN_MODULE_NAME ""builtins"" #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #define __Pyx_DefaultClassType PyType_Type #endif #ifndef Py_TPFLAGS_CHECKTYPES #define Py_TPFLAGS_CHECKTYPES 0 #endif #ifndef Py_TPFLAGS_HAVE_INDEX #define Py_TPFLAGS_HAVE_INDEX 0 #endif #ifndef Py_TPFLAGS_HAVE_NEWBUFFER #define Py_TPFLAGS_HAVE_NEWBUFFER 0 #endif #ifndef Py_TPFLAGS_HAVE_FINALIZE #define Py_TPFLAGS_HAVE_FINALIZE 0 #endif #ifndef METH_FASTCALL #define METH_FASTCALL 0x80 typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject **args, Py_ssize_t nargs, PyObject *kwnames); #else #define __Pyx_PyCFunctionFast _PyCFunctionFast #endif #if CYTHON_FAST_PYCCALL #define __Pyx_PyFastCFunction_Check(func)\ ((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS 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PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) #else #define CYTHON_PEP393_ENABLED 0 #define PyUnicode_1BYTE_KIND 1 #define PyUnicode_2BYTE_KIND 2 #define PyUnicode_4BYTE_KIND 4 #define __Pyx_PyUnicode_READY(op) (0) #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111) #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE)) #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u)) #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i])) #define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch) #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u)) #endif #if CYTHON_COMPILING_IN_PYPY #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) #else #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check) #define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format) #define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, ""__format__"", ""O"", fmt) #endif #if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) #define PyObject_Malloc(s) PyMem_Malloc(s) #define PyObject_Free(p) PyMem_Free(p) #define PyObject_Realloc(p) PyMem_Realloc(p) #endif #if CYTHON_COMPILING_IN_PYSTON #define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co) #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno) #else #define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0) #define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno) #endif #define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? 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PyLong_FromUnsignedLong((unsigned long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); #endif } } else { if (sizeof(long) <= sizeof(long)) { return PyInt_FromLong((long) value); #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); #endif } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(long), little, !is_unsigned); } } /* CIntFromPyVerify */ #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) #define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) #define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ {\ func_type value = 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(long)digits[0]))); } } break; case -3: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 3: if (8 * sizeof(long) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case -4: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 4: if (8 * sizeof(long) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; } #endif if (sizeof(long) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) #endif } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, ""_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers""); #else long val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (long) -1; } } else { long val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (long) -1; val = __Pyx_PyInt_As_long(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, ""value too large to convert to long""); return (long) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, ""can't convert negative value to long""); return (long) -1; } /* CIntFromPy */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { const int neg_one = (int) -1, const_zero = (int) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(int) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (int) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (int) 0; case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) case 2: if (8 * sizeof(int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; case 3: if (8 * sizeof(int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; case 4: if (8 * sizeof(int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (int) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(int) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) #endif } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (int) 0; case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) case -2: if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 2: if (8 * sizeof(int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case -3: if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 3: if (8 * sizeof(int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case -4: if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 4: if (8 * sizeof(int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; } #endif if (sizeof(int) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) #ifdef HAVE_LONG_LONG } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) #endif } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, ""_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers""); #else int val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (int) -1; } } else { int val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (int) -1; val = __Pyx_PyInt_As_int(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, ""value too large to convert to int""); return (int) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, ""can't convert negative value to int""); return (int) -1; } /* CheckBinaryVersion */ static int __Pyx_check_binary_version(void) { char ctversion[4], rtversion[4]; PyOS_snprintf(ctversion, 4, ""%d.%d"", PY_MAJOR_VERSION, PY_MINOR_VERSION); PyOS_snprintf(rtversion, 4, ""%s"", Py_GetVersion()); if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) { char message[200]; PyOS_snprintf(message, sizeof(message), ""compiletime version %s of module '%.100s' "" ""does not match runtime version %s"", ctversion, __Pyx_MODULE_NAME, rtversion); return PyErr_WarnEx(NULL, message, 1); } return 0; } /* InitStrings */ static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { while (t->p) { #if PY_MAJOR_VERSION < 3 if (t->is_unicode) { *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); } else if (t->intern) { *t->p = PyString_InternFromString(t->s); } else { *t->p = PyString_FromStringAndSize(t->s, t->n - 1); } #else if (t->is_unicode | t->is_str) { if (t->intern) { *t->p = PyUnicode_InternFromString(t->s); } else if (t->encoding) { *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); } else { *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); } } else { *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); } #endif if (!*t->p) return -1; ++t; } return 0; } static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); } static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) { Py_ssize_t ignore; return __Pyx_PyObject_AsStringAndSize(o, &ignore); } static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { #if CYTHON_COMPILING_IN_CPYTHON && (__PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT) if ( #if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII __Pyx_sys_getdefaultencoding_not_ascii && #endif PyUnicode_Check(o)) { #if PY_VERSION_HEX < 0x03030000 char* defenc_c; PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); if (!defenc) return NULL; defenc_c = PyBytes_AS_STRING(defenc); #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII { char* end = defenc_c + PyBytes_GET_SIZE(defenc); char* c; for (c = defenc_c; c < end; c++) { if ((unsigned char) (*c) >= 128) { PyUnicode_AsASCIIString(o); return NULL; } } } #endif *length = PyBytes_GET_SIZE(defenc); return defenc_c; #else if (__Pyx_PyUnicode_READY(o) == -1) return NULL; #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII if (PyUnicode_IS_ASCII(o)) { *length = PyUnicode_GET_LENGTH(o); return PyUnicode_AsUTF8(o); } else { PyUnicode_AsASCIIString(o); return NULL; } #else return PyUnicode_AsUTF8AndSize(o, length); #endif #endif } else #endif #if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) if (PyByteArray_Check(o)) { *length = PyByteArray_GET_SIZE(o); return PyByteArray_AS_STRING(o); } else #endif { char* result; int r = PyBytes_AsStringAndSize(o, &result, length); if (unlikely(r < 0)) { return NULL; } else { return result; } } } static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { int is_true = x == Py_True; if (is_true | (x == Py_False) | (x == Py_None)) return is_true; else return PyObject_IsTrue(x); } static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { #if CYTHON_USE_TYPE_SLOTS PyNumberMethods *m; #endif const char *name = NULL; PyObject *res = NULL; #if PY_MAJOR_VERSION < 3 if (PyInt_Check(x) || PyLong_Check(x)) #else if (PyLong_Check(x)) #endif return __Pyx_NewRef(x); #if CYTHON_USE_TYPE_SLOTS m = Py_TYPE(x)->tp_as_number; #if PY_MAJOR_VERSION < 3 if (m && m->nb_int) { name = ""int""; res = PyNumber_Int(x); } else if (m && m->nb_long) { name = ""long""; res = PyNumber_Long(x); } #else if (m && m->nb_int) { name = ""int""; res = PyNumber_Long(x); } #endif #else res = PyNumber_Int(x); #endif if (res) { #if PY_MAJOR_VERSION < 3 if (!PyInt_Check(res) && !PyLong_Check(res)) { #else if (!PyLong_Check(res)) { #endif PyErr_Format(PyExc_TypeError, ""__%.4s__ returned non-%.4s (type %.200s)"", name, name, Py_TYPE(res)->tp_name); Py_DECREF(res); return NULL; } } else if (!PyErr_Occurred()) { PyErr_SetString(PyExc_TypeError, ""an integer is required""); } return res; } static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { Py_ssize_t ival; PyObject *x; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_CheckExact(b))) { if (sizeof(Py_ssize_t) >= sizeof(long)) return PyInt_AS_LONG(b); else return PyInt_AsSsize_t(x); } #endif if (likely(PyLong_CheckExact(b))) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)b)->ob_digit; const Py_ssize_t size = Py_SIZE(b); if (likely(__Pyx_sst_abs(size) <= 1)) { ival = likely(size) ? digits[0] : 0; if (size == -1) ival = -ival; return ival; } else { switch (size) { case 2: if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -2: if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case 3: if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -3: if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case 4: if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -4: if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; } } #endif return PyLong_AsSsize_t(b); } x = PyNumber_Index(b); if (!x) return -1; ival = PyInt_AsSsize_t(x); Py_DECREF(x); return ival; } static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { return PyInt_FromSize_t(ival); } #endif /* Py_PYTHON_H */ ","C++" "Biophysics","maxscheurer/pycontact","testing/cython/vmd/vmd_wrapper.cpp",".cpp","617","35","#include #include #include #include #include #include #include using namespace std; vmdsock_t vmdsock; static void start_vmd(int pt) { int port = pt; vmdsock = newvmdsock(""vmd"", port); vmdstream vmdscript(vmdsock); //draw a sphere vmdscript << ""draw sphere { 0 0 0 } radius 0.5"" << endl; //render to a file // vmdscript << ""render snapshot sphere.tga"" << endl; //quit vmd and exit // // // } static void stop_vmd() { // vmdscript << ""quit"" << endl; // vmdscript.flush(); closevmdsock(vmdsock); } ","C++" "Biophysics","maxscheurer/pycontact","PyContact/pycontact.py",".py","409","25",""""""" Authors: Maximilian Scheurer, Peter Rodenkirch Date created: May 2016 """""" import warnings import sys from PyQt5.QtWidgets import QApplication from .gui.MainWindow import MainWindow warnings.filterwarnings(""ignore"") def main(): """"""Pycontact main function."""""" app = QApplication(sys.argv) window = MainWindow() window.show() app.exec_() if __name__ == '__main__': main() ","Python" "Biophysics","maxscheurer/pycontact","PyContact/__init__.py",".py","0","0","","Python" "Biophysics","maxscheurer/pycontact","PyContact/db/DbReader.py",".py","875","30","import sqlite3 import os def dict_factory(cursor, row): d = {} for idx, col in enumerate(cursor.description): d[col[0]] = row[idx] return d def read_residue_db(selection, key, value): connection = sqlite3.connect(os.path.dirname(os.path.abspath(__file__)) + ""/aa.db"") connection.row_factory = dict_factory cursor = connection.cursor() cursor.execute(""SELECT ({sel}) FROM residues WHERE {key}=\'{value}\'"".format(sel=selection, key=key, value=value)) results = cursor.fetchall() connection.close() return results def read_residue_db_all(): connection = sqlite3.connect(os.path.dirname(os.path.abspath(__file__)) + ""/aa.db"") connection.row_factory = dict_factory cursor = connection.cursor() cursor.execute(""SELECT * FROM residues"") results = cursor.fetchall() connection.close() return results ","Python" "Biophysics","maxscheurer/pycontact","PyContact/db/__init__.py",".py","0","0","","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/LabelView.py",".py","2790","76","import sip from functools import partial from PyQt5.QtGui import QFont from PyQt5.QtWidgets import (QWidget, QPushButton, QLabel, QDialog, QGridLayout, QCheckBox) from PyQt5.Qt import Qt import numpy as np from ..core.Biochemistry import ContactType from .Plotters import ContactPlotter from .DetailWidget import Detail class LabelView(QWidget): """"""Proviedes more detailed statistics of the clicked contact in MainWindow."""""" def __init__(self, contacts): super(QWidget, self).__init__() self.contacts = contacts # self.vismode = False self.buttons = [] self.checkboxes = [] self.buttonWidths = [] self.detailView = None self.nsPerFrame = 0 self.threshold = 0 self.initUI() def clean(self): """"""Delete all labels."""""" allLabels = self.findChildren(QPushButton) for child in allLabels: sip.delete(child) allBoxes = self.findChildren(QCheckBox) for child in allBoxes: sip.delete(child) def initUI(self): """"""Create the labels to the corresponding contact"""""" start_text = 10 textoffset = 5 rowheight = 22 row = 0 checkboxOffset = 0 # next version... # if self.vismode: # checkboxOffset = 15 for c in self.contacts: cindex = self.contacts.index(c) self.buttons.append(QPushButton(c.title)) stylesheet = ""border: 0px solid #222222; background-color: "" + ContactType.colors[c.determine_ctype()] \ + "" ;"" # stylesheet = ""border: 0px solid #222222; background-color: "" + ContactType.colors[3] + "" ;"" self.buttons[-1].setStyleSheet(stylesheet) self.buttons[-1].clicked.connect(partial(self.handleButton, data=cindex)) self.buttons[-1].setParent(self) self.buttons[-1].move(start_text + checkboxOffset, row + textoffset) self.buttons[-1].setFont(QFont('Arial', 9)) self.buttons[-1].show() self.buttonWidths.append(self.buttons[-1].width()) # next version # if self.vismode: # self.checkboxes.append(QCheckBox()) # self.checkboxes[-1].setParent(self) # self.checkboxes[-1].move(start_text, row + textoffset - 2.0) # self.checkboxes[-1].show() row += rowheight # if len(self.buttonWidths): # self.setGeometry(0, 0, np.max(self.buttonWidths) + 10, row) def handleButton(self, data): """"""Show the detailed view when clicking on the contact label"""""" self.detailView = Detail(self.contacts[data], self.nsPerFrame, self.threshold) self.detailView.show() ","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/ExportTabWidget.py",".py","16959","407","import sip import os from PyQt5.QtWidgets import QTabWidget, QWidget, QGridLayout, QLabel, QPushButton, QComboBox, QLineEdit, QCheckBox, \ QFileDialog from PyQt5.QtCore import pyqtSignal from .Plotters import * from .ErrorBox import ErrorBox from .ErrorMessages import ErrorMessages class ExportTabWidget(QTabWidget): """"""Widget for data exporting purposes."""""" valueUpdated = pyqtSignal(str, str) def __init__(self, parent=None): super(ExportTabWidget, self).__init__(parent) self.checkboxes = [] self.keys = [] self.checkboxdict = [] self.tab1 = QWidget() self.tab2 = QWidget() self.tab3 = QWidget() self.tab4 = QWidget() self.tab5 = QWidget() self.grid1 = QGridLayout() self.grid2 = QGridLayout() self.grid3 = QGridLayout() self.grid4 = QGridLayout() self.addTab(self.tab1, ""View"") self.addTab(self.tab2, ""Histogram"") self.addTab(self.tab3, ""Contact Map"") self.addTab(self.tab4, ""VMD"") self.addTab(self.tab5, ""Plain Text"") self.tab1UI() self.tab2UI() self.tab3UI() self.tab4UI() self.tab5UI() self.setWindowTitle(""Export"") self.contacts = [] self.threshold = 0 self.nsPerFrame = 0 self.map1 = None self.map2 = None self.label1 = """" self.label2 = """" self.psf = """" self.dcd = """" def setThresholdAndNsPerFrame(self, currentThreshold, currentNsPerFrame): self.threshold = currentThreshold self.nsPerFrame = currentNsPerFrame def tab1UI(self): """"""Tab where the current view can be exported to file."""""" grid = QGridLayout() self.tab1.setLayout(grid) self.tab1.exportLabel = QLabel(""Export current view: "") self.tab1.saveButton = QPushButton(""Export"") self.tab1.saveButton.setAutoDefault(False) self.tab1.saveButton.clicked.connect(self.pushSave) self.tab1.formatBox = QComboBox() self.tab1.formatBox.addItem(""PNG"") self.tab1.formatBox.addItem(""SVG"") grid.addWidget(self.tab1.exportLabel, 0, 0) grid.addWidget(self.tab1.saveButton, 0, 1) grid.addWidget(self.tab1.formatBox, 2, 0) def tab2UI(self): """"""Tab where analyzed data can be visualized and exported as histograms."""""" self.tab2.setLayout(self.grid1) self.tab2.histPlot = HistPlotter(None, width=8, height=5, dpi=60) self.grid1.addWidget(self.tab2.histPlot, 3, 0, 1, 4) self.tab2.histTypeBox = QComboBox() self.tab2.histTypeBox.addItem(""General Histogram"") self.tab2.histTypeBox.addItem(""Bin per Contact"") self.grid1.addWidget(self.tab2.histTypeBox, 0, 3) self.tab2.attributeBox = QComboBox() self.tab2.attributeBox.addItem(""Mean Score"") self.tab2.attributeBox.addItem(""Median Score"") self.tab2.attributeBox.addItem(""Mean Lifetime"") self.tab2.attributeBox.addItem(""Median Lifetime"") self.tab2.attributeBox.addItem(""Hbond percentage"") self.grid1.addWidget(self.tab2.attributeBox, 1, 3) self.tab2.plotButton = QPushButton(""Show Preview"") self.tab2.plotButton.setAutoDefault(False) self.tab2.plotButton.clicked.connect(self.pushPlot) self.grid1.addWidget(self.tab2.plotButton, 0, 0, 1, 3) self.tab2.saveButton = QPushButton(""Save Histogram"") self.tab2.saveButton.setAutoDefault(False) self.tab2.saveButton.clicked.connect(self.saveHist) self.grid1.addWidget(self.tab2.saveButton, 1, 0, 1, 1) self.tab2.formatLabel = QLabel(""Format: "") self.grid1.addWidget(self.tab2.formatLabel, 1, 1) self.tab2.xTicksFontSizeLabel = QLabel(""bin per contact font size: "") self.grid1.addWidget(self.tab2.xTicksFontSizeLabel, 2, 0) self.tab2.xTicksFontSizeField = QLineEdit(""11"") self.grid1.addWidget(self.tab2.xTicksFontSizeField, 2, 1) self.tab2.formatBox = QComboBox() self.tab2.formatBox.addItem(""pdf"") self.tab2.formatBox.addItem(""png"") self.tab2.formatBox.addItem(""svg"") self.tab2.formatBox.addItem(""eps"") self.grid1.addWidget(self.tab2.formatBox, 1, 2) def tab3UI(self): """"""Tab where the contact map can be generated and exported."""""" self.tab3.setLayout(self.grid2) self.tab3.mapPlot = AnimateMapPlotter(None, width=8, height=5, dpi=60) self.grid2.addWidget(self.tab3.mapPlot, 3, 0, 1, 4) self.tab3.plotMapButton = QPushButton(""Show Preview"") self.tab3.plotMapButton.setAutoDefault(False) self.tab3.plotMapButton.clicked.connect(self.pushMapPlot) self.grid2.addWidget(self.tab3.plotMapButton, 0, 0, 1, 1) self.tab3.formatBox = QComboBox() self.tab3.formatBox.addItem(""pdf"") self.tab3.formatBox.addItem(""png"") self.tab3.formatBox.addItem(""svg"") self.tab3.formatBox.addItem(""eps"") self.grid2.addWidget(self.tab3.formatBox, 0, 2, 1, 1) self.tab3.saveButton = QPushButton(""Save Map"") self.tab3.saveButton.setAutoDefault(False) self.tab3.saveButton.clicked.connect(self.saveMap) self.grid2.addWidget(self.tab3.saveButton, 0, 3, 1, 1) self.tab3.attributeBox = QComboBox() self.tab3.attributeBox.addItem(""Mean Score"") self.tab3.attributeBox.addItem(""Median Score"") self.tab3.attributeBox.addItem(""Mean Lifetime"") self.tab3.attributeBox.addItem(""Median Lifetime"") self.tab3.attributeBox.addItem(""Hbond percentage"") self.grid2.addWidget(self.tab3.attributeBox, 0, 1) def tab4UI(self): """"""Tab where selected data can be visualized in VMD via a Tcl script generation."""""" self.tab4.setLayout(self.grid3) label = QLabel(""Split selections for each contact"") self.tab4.splitVisCheckbox = QCheckBox() self.grid3.addWidget(label, 0, 0) self.grid3.addWidget(self.tab4.splitVisCheckbox, 0, 1) self.tab4.additionalText1 = QLineEdit() self.tab4.additionalText2 = QLineEdit() additionalTextLabel1 = QLabel(""Additional seltext for selection 1"") additionalTextLabel2 = QLabel(""Additional seltext for selection 2"") self.tab4.button = QPushButton(""Create tcl script"") self.tab4.button.clicked.connect(self.createTclScriptVis) self.grid3.addWidget(self.tab4.button, 3, 0, 1, 2) self.grid3.addWidget(additionalTextLabel1, 1, 0) self.grid3.addWidget(additionalTextLabel2, 2, 0) self.grid3.addWidget(self.tab4.additionalText1, 1, 1) self.grid3.addWidget(self.tab4.additionalText2, 2, 1) def tab5UI(self): """"""Tab where the raw data can be exported to a text file."""""" self.tab5.setLayout(self.grid4) self.checkboxdict = {""mean_score"": ""Mean Score"", ""hbond_percentage"": ""HBond Percentage"", ""median_score"": ""Median Score"", ""contactTypeAsShortcut"": ""Contact Type"", ""getScoreArray"": ""Score List"", ""hbondFramesScan"": ""Hydrogen Bond Frames""} # let's define the key order ourselves self.keys = [""contactTypeAsShortcut"", ""mean_score"", ""median_score"", ""hbond_percentage"", ""getScoreArray"", ""hbondFramesScan""] propertyLabel = QLabel(""Select properties to export"") self.grid4.addWidget(propertyLabel, 0, 0) startLine = 1 for box in self.keys: checkBox = QCheckBox() checkBox.setChecked(True) boxLabel = QLabel(self.checkboxdict[box]) self.grid4.addWidget(boxLabel, startLine, 0) self.grid4.addWidget(checkBox, startLine, 1) self.checkboxes.append(checkBox) startLine += 1 self.tab5.button = QPushButton(""Export to text"") self.tab5.button.clicked.connect(self.saveText) self.grid4.addWidget(self.tab5.button, startLine, 5) def saveText(self): """"""Executes the conversion of the analysis results to raw text data."""""" fileName = QFileDialog.getSaveFileName(self, 'Export Path') if len(fileName[0]) > 0: path, file_extension = os.path.splitext(fileName[0]) boxIndex = 0 requestedParameters = [] for box in self.checkboxes: if box.isChecked(): requestedParameters.append(self.keys[boxIndex]) boxIndex += 1 tableHeadings = [] for par in requestedParameters: tableHeadings.append(self.checkboxdict[par]) f = open(path + "".txt"", ""w"") row_format = "" {:>20} "" * (len(requestedParameters) + 1) f.write(row_format.format("""", *tableHeadings)) f.write(""\n"") for c in self.contacts: row_format = "" {:>20} "" currentContactProperties = [] for p in requestedParameters: if not hasattr(c, p): continue propertyToAdd = getattr(c, p)() if isinstance(propertyToAdd, float): propertyToAdd = ""{0:.3f}"".format(propertyToAdd) currentContactProperties.append(propertyToAdd) if isinstance(propertyToAdd, list): row_format += "" {} "" else: row_format += "" {:>20} "" f.write(row_format.format(c.human_readable_title(), *currentContactProperties)) f.write(""\n"") f.close() def saveHist(self): """"""Saves the histogram to the picked file path."""""" self.plotHist() fileName = QFileDialog.getSaveFileName(self, 'Export Path') if len(fileName[0]) > 0: path, file_extension = os.path.splitext(fileName[0]) if file_extension == """": file_extension = ""."" + self.tab2.formatBox.currentText().lower() path += file_extension self.tab2.histPlot.saveFigure(path, self.tab2.formatBox.currentText()) def saveMap(self): """"""Saves the contact map to the picked file path."""""" self.plotMap() fileName = QFileDialog.getSaveFileName(self, 'Export Path') if len(fileName[0]) > 0: path, file_extension = os.path.splitext(fileName[0]) self.tab3.mapPlot.saveFigure(path, self.tab3.formatBox.currentText()) def pushPlot(self): """"""Triggers the histogram plotter."""""" self.plotHist() def pushMapPlot(self): """"""Triggers the contact map plotter."""""" self.plotMap() def plotHist(self): """"""Plots the histogram."""""" sip.delete(self.tab2.histPlot) self.tab2.histPlot = HistPlotter(None, width=8, height=5, dpi=60) self.grid1.addWidget(self.tab2.histPlot, 3, 0, 1, 4) if self.tab2.histTypeBox.currentText() == ""General Histogram"": self.tab2.histPlot.plotGeneralHist(self.contacts, self.tab2.attributeBox.currentText(), self.threshold, self.nsPerFrame) elif self.tab2.histTypeBox.currentText() == ""Bin per Contact"": self.tab2.histPlot.plotContactHist(self.contacts, self.tab2.attributeBox.currentText(), self.threshold, self.nsPerFrame, int(self.tab2.xTicksFontSizeField.text())) self.tab2.histPlot.update() def plotMap(self): """"""Plots the contact map."""""" sip.delete(self.tab3.mapPlot) self.tab3.mapPlot = MapPlotter(None, width=8, height=5, dpi=60) self.grid2.addWidget(self.tab3.mapPlot, 3, 0, 1, 4) if self.map1 is None or self.map2 is None or self.contacts is None or len(self.contacts) == 0: box = ErrorBox(ErrorMessages.RESID_REQUIRED) box.exec_() return res = self.tab3.mapPlot.plotMap(self.contacts, self.map1, self.map2, self.label1, self.label2, self.tab3.attributeBox.currentText(), self.threshold, self.nsPerFrame) if res == -1: box = ErrorBox(ErrorMessages.RESID_REQUIRED) box.exec_() self.tab3.mapPlot.update() def pushSave(self): """"""Saves the current view."""""" fileName = QFileDialog.getSaveFileName(self, 'Export Path') path, file_extension = os.path.splitext(fileName[0]) if file_extension == """": file_extension = ""."" + self.tab1.formatBox.currentText().lower() path += file_extension self.valueUpdated.emit(path, self.tab1.formatBox.currentText()) def setContacts(self, currentContacts): self.contacts = currentContacts def setFilePaths(self, *argv): """"""Sets the current trajectory paths from the main view."""""" self.psf = argv[0][0] self.dcd = argv[0][1] def setMaps(self, map1, map2): self.map1 = map1 self.map2 = map2 # labels for the contact map def setMapLabels(self, label1, label2): self.label1 = label1 self.label2 = label2 def createTclScriptVis(self): """"""Creates the Tcl script for VMD visualization of the selections."""""" if len(self.contacts) == 0: box = ErrorBox(ErrorMessages.NOCONTACTS) box.exec_() return fileName = QFileDialog.getSaveFileName(self, 'Save Path') if len(fileName[0]) > 0: path, file_extension = os.path.splitext(fileName[0]) if file_extension != "".tcl"": file_extension = "".tcl"" path += file_extension f = open(path, 'w') f.write('mol new %s \n' % self.psf) f.write('mol addfile %s \n' % self.dcd) f.write('mol delrep 0 top \n') f.write('mol representation NewCartoon \n') f.write('mol Color ColorID 3 \n') f.write('mol selection {all} \n') f.write('mol addrep top \n') if self.tab4.splitVisCheckbox.isChecked(): for cont in self.contacts: currentSel1 = [] index = 0 for item in cont.key1: if item != ""none"": currentSel1.append(AccumulationMapIndex.vmdsel[index] + "" "" + item) index += 1 currentSel1String = "" and "".join(currentSel1) currentSel2 = [] index = 0 for item in cont.key2: if item != ""none"": currentSel2.append(AccumulationMapIndex.vmdsel[index] + "" "" + item) index += 1 currentSel2String = "" and "".join(currentSel2) add1 = ("""" if self.tab4.additionalText1.text() == """" else ("" and "" + self.tab4.additionalText1.text())) add2 = ("""" if self.tab4.additionalText2.text() == """" else ("" and "" + self.tab4.additionalText2.text())) sel = ""(""+currentSel1String + add1 + "") or ("" + currentSel2String + add2 + "")"" f.write('mol representation Licorice \n') f.write('mol Color Name \n') f.write('mol selection {%s} \n' % sel) f.write('mol addrep top \n') else: total = [] for cont in self.contacts: currentSel1 = [] index = 0 for item in cont.key1: if item != ""none"": currentSel1.append(AccumulationMapIndex.vmdsel[index] + "" "" + item) index += 1 currentSel1String = "" and "".join(currentSel1) currentSel2 = [] index = 0 for item in cont.key2: if item != ""none"": currentSel2.append(AccumulationMapIndex.vmdsel[index] + "" "" + item) index += 1 currentSel2String = "" and "".join(currentSel2) add1 = ("""" if self.tab4.additionalText1.text() == """" else ("" and "" + self.tab4.additionalText1.text())) add2 = ("""" if self.tab4.additionalText2.text() == """" else ("" and "" + self.tab4.additionalText2.text())) sel = ""("" + currentSel1String + add1 + "") or ("" + currentSel2String + add2 + "")"" total.append(sel) seltext = "" or "".join(total) f.write('mol representation Licorice \n') f.write('mol Color Name \n') f.write('mol selection {%s} \n' % seltext) f.write('mol addrep top \n') f.close() ","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/Dialogues.py",".py","9711","265","from PyQt5.QtWidgets import QDialog, QGridLayout, QPushButton, QLabel, QLineEdit, QDialogButtonBox, QFileDialog, QCheckBox from PyQt5.QtCore import Qt from PyQt5.QtGui import QDoubleValidator from ..core.LoadConfiguration import Configuration from .HelpButton import HelpButton class TopoTrajLoaderDialog(QDialog): """"""Dialog to load the topology and trajectory file."""""" def __init__(self, parent=None): super(TopoTrajLoaderDialog, self).__init__(parent) self.setWindowTitle(""Load Data"") self.psf = """" self.dcd = """" grid = QGridLayout(self) buttonPsf = QPushButton(""Topology"") buttonPsf.clicked.connect(self.pick_psf) buttonDcd = QPushButton(""Trajectory"") buttonDcd.clicked.connect(self.pick_dcd) helpButton = HelpButton() grid.addWidget(buttonPsf, 0, 0) grid.addWidget(buttonDcd, 0, 1) buttons = QDialogButtonBox( QDialogButtonBox.Ok | QDialogButtonBox.Cancel, Qt.Horizontal, self) buttons.accepted.connect(self.accept) buttons.rejected.connect(self.reject) grid.addWidget(buttons, 1, 0) grid.addWidget(helpButton, 2, 0) def pick_psf(self): """"""Pick the topology file."""""" psfname = QFileDialog.getOpenFileNames(self, ""Open topology"") for file in psfname[0]: self.psf = file break def pick_dcd(self): """"""Pick the trajectory file."""""" dcdname = QFileDialog.getOpenFileNames(self, ""Open trajectory"") for file in dcdname[0]: self.dcd = file break def configuration(self): """"""Returns the chosen configuration."""""" config = [self.psf, self.dcd] return config @staticmethod def getConfig(parent=None): """"""Static method to create the dialog and return (date, time, accepted)."""""" dialog = TopoTrajLoaderDialog(parent) result = dialog.exec_() config = dialog.configuration() return config, result == QDialog.Accepted class FileLoaderDialog(QDialog): """"""Initial file loader dialog, including initial parameter settings."""""" def __init__(self, parent=None): super(FileLoaderDialog, self).__init__(parent) self.setWindowTitle(""Load Data"") self.psf = """" self.dcd = """" production = 1 grid = QGridLayout(self) buttonPsf = QPushButton(""Topology"") buttonPsf.clicked.connect(self.pick_psf) buttonDcd = QPushButton(""Trajectory"") buttonDcd.clicked.connect(self.pick_dcd) grid.addWidget(buttonPsf,0,0) grid.addWidget(buttonDcd,0,1) cutoffLabel = QLabel(""distance cutoff: "") cutoffAngleLabel = QLabel(""angle cutoff: "") cutoffHbondLabel = QLabel(""acc-h cutoff: "") selection1Label = QLabel(""selection 1: "") selection2Label = QLabel(""selection 2: "") topologyFileLabel = QLabel(""topology file: "") trajectoryFileLabel = QLabel(""trajectory file: "") self.topFileDisplay = QLabel(""-"") self.trajFileDisplay = QLabel(""-"") grid.addWidget(topologyFileLabel, 1, 0) grid.addWidget(trajectoryFileLabel, 2, 0) grid.addWidget(self.topFileDisplay, 1, 1) grid.addWidget(self.trajFileDisplay, 2, 1) self.cutoffField = QLineEdit(""5.0"") posDoubleValidator = QDoubleValidator() posDoubleValidator.setBottom(0) self.cutoffField.setValidator(posDoubleValidator) self.cutoffAngleField = QLineEdit(""120"") self.cutoffAngleField.setValidator(posDoubleValidator) self.cutoffHbondField = QLineEdit(""2.5"") self.cutoffHbondField.setValidator(posDoubleValidator) if production: self.selection1Field = QLineEdit("""") self.selection2Field = QLineEdit("""") else: self.selection1Field = QLineEdit(""segid RN11"") self.selection2Field = QLineEdit(""segid UBQ"") grid.addWidget(cutoffLabel, 3, 0) grid.addWidget(cutoffAngleLabel, 4, 0) grid.addWidget(cutoffHbondLabel, 5, 0) grid.addWidget(selection1Label, 6, 0) grid.addWidget(selection2Label, 7, 0) grid.addWidget(self.cutoffField, 3, 1) grid.addWidget(self.cutoffAngleField, 4, 1) grid.addWidget(self.cutoffHbondField, 5, 1) grid.addWidget(self.selection1Field, 6, 1) grid.addWidget(self.selection2Field, 7, 1) # OK and Cancel buttons buttons = QDialogButtonBox( QDialogButtonBox.Ok | QDialogButtonBox.Cancel, Qt.Horizontal, self) buttons.accepted.connect(self.accept) buttons.rejected.connect(self.reject) grid.addWidget(buttons, 8, 0) def pick_psf(self): """"""Pick topology file."""""" psfname = QFileDialog.getOpenFileNames(self, ""Open topology"") for file in psfname[0]: self.psf = file self.topFileDisplay.setText(self.psf.split(""/"")[-1]) break def pick_dcd(self): """"""Pick trajectory file."""""" dcdname = QFileDialog.getOpenFileNames(self, ""Open trajectory"") for file in dcdname[0]: self.dcd = file self.trajFileDisplay.setText(self.dcd.split(""/"")[-1]) break def configuration(self): """"""Returns the chosen configuration."""""" config = Configuration(self.psf, self.dcd, float(self.cutoffField.text()), float(self.cutoffHbondField.text()), float(self.cutoffAngleField.text()), self.selection1Field.text(), self.selection2Field.text()) return config @staticmethod def getConfig(parent=None): """"""Static method to create the dialog and return (date, time, accepted)."""""" dialog = FileLoaderDialog(parent) result = dialog.exec_() config = dialog.configuration() return config, result == QDialog.Accepted class AnalysisDialog(QDialog): """"""Dialog to define the Accumulation maps."""""" def __init__(self, parent=None): super(AnalysisDialog, self).__init__(parent) grid = QGridLayout(self) self.title1 = QLabel(""selection 1"") self.title2 = QLabel(""selection 2"") indexLabel = QLabel(""index: "") nameLabel = QLabel(""atom name: "") residLabel = QLabel(""resid: "") resnameLabel = QLabel(""resname: "") segidLabel = QLabel(""segid: "") self.setWindowTitle(""Analysis - Score Accumulation"") self.index1Checkbox = QCheckBox() self.name1Checkbox = QCheckBox() self.resid1Checkbox = QCheckBox() self.resname1Checkbox = QCheckBox() self.segid1Checkbox = QCheckBox() self.index2Checkbox = QCheckBox() self.name2Checkbox = QCheckBox() self.resid2Checkbox = QCheckBox() self.resname2Checkbox = QCheckBox() self.segid2Checkbox = QCheckBox() grid.addWidget(self.title1, 0, 1) grid.addWidget(self.title2, 0, 2) grid.addWidget(indexLabel, 1, 0) grid.addWidget(nameLabel, 2, 0) grid.addWidget(residLabel, 3, 0) grid.addWidget(resnameLabel, 4, 0) grid.addWidget(segidLabel, 5, 0) grid.addWidget(self.index1Checkbox, 1, 1) grid.addWidget(self.name1Checkbox, 2, 1) grid.addWidget(self.resid1Checkbox, 3, 1) grid.addWidget(self.resname1Checkbox, 4, 1) grid.addWidget(self.segid1Checkbox, 5, 1) grid.addWidget(self.index2Checkbox, 1, 2) grid.addWidget(self.name2Checkbox, 2, 2) grid.addWidget(self.resid2Checkbox, 3, 2) grid.addWidget(self.resname2Checkbox, 4, 2) grid.addWidget(self.segid2Checkbox, 5, 2) # OK and Cancel buttons buttons = QDialogButtonBox( QDialogButtonBox.Ok | QDialogButtonBox.Cancel, Qt.Horizontal, self) buttons.accepted.connect(self.accept) buttons.rejected.connect(self.reject) grid.addWidget(buttons, 6, 0) self.gridLayout = grid def mapping(self): """"""Creates the Accumulation maps from the checkbox values."""""" # atom types will not be supported in the future map1 = [self.index1Checkbox.isChecked(), self.name1Checkbox.isChecked(), self.resid1Checkbox.isChecked(), self.resname1Checkbox.isChecked(), self.segid1Checkbox.isChecked()] map2 = [self.index2Checkbox.isChecked(), self.name2Checkbox.isChecked(), self.resid2Checkbox.isChecked(), self.resname2Checkbox.isChecked(), self.segid2Checkbox.isChecked()] return [map1, map2] @staticmethod def getMapping(parent=None): """"""Static method to create the dialog and return (date, time, accepted)."""""" dialog = AnalysisDialog(parent) result = dialog.exec_() mapping = dialog.mapping() return mapping, result == QDialog.Accepted class AnalysisSingleDialog(AnalysisDialog): def __init__(self, parent=None): super(AnalysisSingleDialog, self).__init__(parent) self.index2Checkbox.setHidden(True) self.name2Checkbox.setHidden(True) self.resid2Checkbox.setHidden(True) self.resname2Checkbox.setHidden(True) self.segid2Checkbox.setHidden(True) self.title2.setHidden(True) self.title1.setText(""selection"") @staticmethod def getMapping(parent=None): """"""Static method to create the dialog and return (date, time, accepted)."""""" dialog = AnalysisSingleDialog(parent) result = dialog.exec_() mapping = dialog.mapping() return mapping[0], result == QDialog.Accepted ","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/MainQtGui.py",".py","32174","522","# -*- coding: utf-8 -*- # Form implementation generated from reading ui file 'MainQtGui.ui' # # Created by: PyQt5 UI code generator 5.6 # # WARNING! All changes made in this file will be lost! from PyQt5 import QtCore, QtGui, QtWidgets class Ui_MainWindow(object): def setupUi(self, MainWindow): MainWindow.setObjectName(""MainWindow"") MainWindow.resize(1270, 714) self.centralwidget = QtWidgets.QWidget(MainWindow) self.centralwidget.setObjectName(""centralwidget"") self.gridLayout = QtWidgets.QGridLayout(self.centralwidget) self.gridLayout.setObjectName(""gridLayout"") self.visModeButton = QtWidgets.QPushButton(self.centralwidget) self.visModeButton.setObjectName(""visModeButton"") self.gridLayout.addWidget(self.visModeButton, 0, 3, 1, 2) self.infoWidget = QtWidgets.QWidget(self.centralwidget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.infoWidget.sizePolicy().hasHeightForWidth()) self.infoWidget.setSizePolicy(sizePolicy) self.infoWidget.setObjectName(""infoWidget"") self.gridLayout_2 = QtWidgets.QGridLayout(self.infoWidget) self.gridLayout_2.setContentsMargins(0, 0, 0, 0) self.gridLayout_2.setObjectName(""gridLayout_2"") self.selection1label = QtWidgets.QLabel(self.infoWidget) self.selection1label.setObjectName(""selection1label"") self.gridLayout_2.addWidget(self.selection1label, 0, 5, 1, 1) self.selection1 = QtWidgets.QLabel(self.infoWidget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.selection1.sizePolicy().hasHeightForWidth()) self.selection1.setSizePolicy(sizePolicy) self.selection1.setObjectName(""selection1"") self.gridLayout_2.addWidget(self.selection1, 0, 4, 1, 1) self.status = QtWidgets.QLabel(self.infoWidget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.status.sizePolicy().hasHeightForWidth()) self.status.setSizePolicy(sizePolicy) self.status.setObjectName(""status"") self.gridLayout_2.addWidget(self.status, 0, 0, 1, 1) self.selection2label = QtWidgets.QLabel(self.infoWidget) self.selection2label.setObjectName(""selection2label"") self.gridLayout_2.addWidget(self.selection2label, 0, 7, 1, 1) self.statusLabel = QtWidgets.QLabel(self.infoWidget) self.statusLabel.setObjectName(""statusLabel"") self.gridLayout_2.addWidget(self.statusLabel, 0, 1, 1, 1) self.selection2 = QtWidgets.QLabel(self.infoWidget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.selection2.sizePolicy().hasHeightForWidth()) self.selection2.setSizePolicy(sizePolicy) self.selection2.setObjectName(""selection2"") self.gridLayout_2.addWidget(self.selection2, 0, 6, 1, 1) self.progressBar = QtWidgets.QProgressBar(self.infoWidget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.progressBar.sizePolicy().hasHeightForWidth()) self.progressBar.setSizePolicy(sizePolicy) self.progressBar.setMaximumSize(QtCore.QSize(150, 16777215)) self.progressBar.setProperty(""value"", 0) self.progressBar.setTextVisible(True) self.progressBar.setInvertedAppearance(False) self.progressBar.setObjectName(""progressBar"") self.gridLayout_2.addWidget(self.progressBar, 0, 2, 1, 1) self.line = QtWidgets.QFrame(self.infoWidget) self.line.setFrameShape(QtWidgets.QFrame.VLine) self.line.setFrameShadow(QtWidgets.QFrame.Sunken) self.line.setObjectName(""line"") self.gridLayout_2.addWidget(self.line, 0, 3, 1, 1) self.gridLayout.addWidget(self.infoWidget, 3, 0, 1, 10) self.scrollArea = QtWidgets.QScrollArea(self.centralwidget) self.scrollArea.setSizeAdjustPolicy(QtWidgets.QAbstractScrollArea.AdjustIgnored) self.scrollArea.setWidgetResizable(True) self.scrollArea.setObjectName(""scrollArea"") self.scrollAreaWidgetContents = QtWidgets.QWidget() self.scrollAreaWidgetContents.setGeometry(QtCore.QRect(0, 0, 916, 553)) self.scrollAreaWidgetContents.setObjectName(""scrollAreaWidgetContents"") self.scrollArea.setWidget(self.scrollAreaWidgetContents) self.gridLayout.addWidget(self.scrollArea, 2, 0, 1, 8) self.statisticsButton = QtWidgets.QPushButton(self.centralwidget) self.statisticsButton.setObjectName(""statisticsButton"") self.gridLayout.addWidget(self.statisticsButton, 0, 2, 1, 1) self.analysisButton = QtWidgets.QPushButton(self.centralwidget) self.analysisButton.setObjectName(""analysisButton"") self.gridLayout.addWidget(self.analysisButton, 0, 0, 1, 2) spacerItem = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout.addItem(spacerItem, 0, 5, 1, 1) self.filterFrame = QtWidgets.QFrame(self.centralwidget) self.filterFrame.setFrameShape(QtWidgets.QFrame.StyledPanel) self.filterFrame.setFrameShadow(QtWidgets.QFrame.Raised) self.filterFrame.setObjectName(""filterFrame"") self.gridLayout_3 = QtWidgets.QGridLayout(self.filterFrame) self.gridLayout_3.setObjectName(""gridLayout_3"") self.zoomSliderLabel = QtWidgets.QLabel(self.filterFrame) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.zoomSliderLabel.sizePolicy().hasHeightForWidth()) self.zoomSliderLabel.setSizePolicy(sizePolicy) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.zoomSliderLabel.setFont(font) self.zoomSliderLabel.setObjectName(""zoomSliderLabel"") self.gridLayout_3.addWidget(self.zoomSliderLabel, 0, 0, 1, 1) self.toLabel = QtWidgets.QLabel(self.filterFrame) self.toLabel.setMaximumSize(QtCore.QSize(25, 16777215)) font = QtGui.QFont() font.setItalic(False) self.toLabel.setFont(font) self.toLabel.setObjectName(""toLabel"") self.gridLayout_3.addWidget(self.toLabel, 2, 2, 1, 1) self.rangeLabel = QtWidgets.QLabel(self.filterFrame) self.rangeLabel.setMaximumSize(QtCore.QSize(300, 16777215)) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.rangeLabel.setFont(font) self.rangeLabel.setObjectName(""rangeLabel"") self.gridLayout_3.addWidget(self.rangeLabel, 2, 0, 1, 1) self.sepLine2 = QtWidgets.QFrame(self.filterFrame) self.sepLine2.setFrameShape(QtWidgets.QFrame.HLine) self.sepLine2.setFrameShadow(QtWidgets.QFrame.Sunken) self.sepLine2.setObjectName(""sepLine2"") self.gridLayout_3.addWidget(self.sepLine2, 4, 0, 1, 4) self.upperRangeField = QtWidgets.QLineEdit(self.filterFrame) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.upperRangeField.sizePolicy().hasHeightForWidth()) self.upperRangeField.setSizePolicy(sizePolicy) self.upperRangeField.setMaximumSize(QtCore.QSize(50, 16777215)) self.upperRangeField.setObjectName(""upperRangeField"") self.gridLayout_3.addWidget(self.upperRangeField, 2, 3, 1, 1) self.lowerRangeField = QtWidgets.QLineEdit(self.filterFrame) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.lowerRangeField.sizePolicy().hasHeightForWidth()) self.lowerRangeField.setSizePolicy(sizePolicy) self.lowerRangeField.setMaximumSize(QtCore.QSize(50, 16777215)) self.lowerRangeField.setObjectName(""lowerRangeField"") self.gridLayout_3.addWidget(self.lowerRangeField, 2, 1, 1, 1) self.filterRangeCheckbox = QtWidgets.QCheckBox(self.filterFrame) self.filterRangeCheckbox.setObjectName(""filterRangeCheckbox"") self.gridLayout_3.addWidget(self.filterRangeCheckbox, 3, 0, 1, 1) self.line_2 = QtWidgets.QFrame(self.filterFrame) self.line_2.setFrameShape(QtWidgets.QFrame.HLine) self.line_2.setFrameShadow(QtWidgets.QFrame.Sunken) self.line_2.setObjectName(""line_2"") self.gridLayout_3.addWidget(self.line_2, 1, 0, 1, 4) self.widget_2 = QtWidgets.QWidget(self.filterFrame) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.widget_2.sizePolicy().hasHeightForWidth()) self.widget_2.setSizePolicy(sizePolicy) self.widget_2.setObjectName(""widget_2"") self.gridLayout_5 = QtWidgets.QGridLayout(self.widget_2) self.gridLayout_5.setContentsMargins(0, 0, 0, 0) self.gridLayout_5.setObjectName(""gridLayout_5"") self.label_4 = QtWidgets.QLabel(self.widget_2) self.label_4.setMaximumSize(QtCore.QSize(50, 16777215)) self.label_4.setObjectName(""label_4"") self.gridLayout_5.addWidget(self.label_4, 1, 0, 1, 1) self.atomAIndexField = QtWidgets.QLineEdit(self.widget_2) self.atomAIndexField.setMaximumSize(QtCore.QSize(75, 16777215)) self.atomAIndexField.setObjectName(""atomAIndexField"") self.gridLayout_5.addWidget(self.atomAIndexField, 1, 1, 1, 1) self.label_10 = QtWidgets.QLabel(self.widget_2) self.label_10.setObjectName(""label_10"") self.gridLayout_5.addWidget(self.label_10, 5, 0, 1, 1) self.line_4 = QtWidgets.QFrame(self.widget_2) self.line_4.setFrameShape(QtWidgets.QFrame.HLine) self.line_4.setFrameShadow(QtWidgets.QFrame.Sunken) self.line_4.setObjectName(""line_4"") self.gridLayout_5.addWidget(self.line_4, 3, 0, 1, 4) self.atomANameField = QtWidgets.QLineEdit(self.widget_2) self.atomANameField.setMaximumSize(QtCore.QSize(75, 16777215)) self.atomANameField.setObjectName(""atomANameField"") self.gridLayout_5.addWidget(self.atomANameField, 2, 1, 1, 1) self.label_8 = QtWidgets.QLabel(self.widget_2) self.label_8.setMaximumSize(QtCore.QSize(75, 16777215)) self.label_8.setObjectName(""label_8"") self.gridLayout_5.addWidget(self.label_8, 2, 2, 1, 1) self.atomBNameField = QtWidgets.QLineEdit(self.widget_2) self.atomBNameField.setMaximumSize(QtCore.QSize(75, 16777215)) self.atomBNameField.setObjectName(""atomBNameField"") self.gridLayout_5.addWidget(self.atomBNameField, 2, 3, 1, 1) self.label_6 = QtWidgets.QLabel(self.widget_2) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.label_6.setFont(font) self.label_6.setObjectName(""label_6"") self.gridLayout_5.addWidget(self.label_6, 0, 0, 1, 1) self.label_7 = QtWidgets.QLabel(self.widget_2) self.label_7.setMaximumSize(QtCore.QSize(75, 16777215)) self.label_7.setObjectName(""label_7"") self.gridLayout_5.addWidget(self.label_7, 2, 0, 1, 1) self.atomBIndexField = QtWidgets.QLineEdit(self.widget_2) self.atomBIndexField.setMaximumSize(QtCore.QSize(75, 16777215)) self.atomBIndexField.setObjectName(""atomBIndexField"") self.gridLayout_5.addWidget(self.atomBIndexField, 1, 3, 1, 1) self.label_5 = QtWidgets.QLabel(self.widget_2) self.label_5.setMaximumSize(QtCore.QSize(50, 16777215)) self.label_5.setObjectName(""label_5"") self.gridLayout_5.addWidget(self.label_5, 1, 2, 1, 1) self.label_9 = QtWidgets.QLabel(self.widget_2) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.label_9.setFont(font) self.label_9.setObjectName(""label_9"") self.gridLayout_5.addWidget(self.label_9, 4, 0, 1, 1) self.label_11 = QtWidgets.QLabel(self.widget_2) self.label_11.setObjectName(""label_11"") self.gridLayout_5.addWidget(self.label_11, 5, 2, 1, 1) self.residBRangeField = QtWidgets.QLineEdit(self.widget_2) self.residBRangeField.setObjectName(""residBRangeField"") self.gridLayout_5.addWidget(self.residBRangeField, 5, 3, 1, 1) self.residARangeField = QtWidgets.QLineEdit(self.widget_2) self.residARangeField.setObjectName(""residARangeField"") self.gridLayout_5.addWidget(self.residARangeField, 5, 1, 1, 1) self.label_12 = QtWidgets.QLabel(self.widget_2) self.label_12.setObjectName(""label_12"") self.gridLayout_5.addWidget(self.label_12, 6, 0, 1, 1) self.residANameField = QtWidgets.QLineEdit(self.widget_2) self.residANameField.setObjectName(""residANameField"") self.gridLayout_5.addWidget(self.residANameField, 6, 1, 1, 1) self.label_13 = QtWidgets.QLabel(self.widget_2) self.label_13.setObjectName(""label_13"") self.gridLayout_5.addWidget(self.label_13, 6, 2, 1, 1) self.residBNameField = QtWidgets.QLineEdit(self.widget_2) self.residBNameField.setObjectName(""residBNameField"") self.gridLayout_5.addWidget(self.residBNameField, 6, 3, 1, 1) self.gridLayout_3.addWidget(self.widget_2, 7, 0, 1, 4) self.widget = QtWidgets.QWidget(self.filterFrame) self.widget.setObjectName(""widget"") self.gridLayout_4 = QtWidgets.QGridLayout(self.widget) self.gridLayout_4.setContentsMargins(0, 0, 0, 0) self.gridLayout_4.setObjectName(""gridLayout_4"") self.compareTotalTimeDropdown = QtWidgets.QComboBox(self.widget) self.compareTotalTimeDropdown.setMaximumSize(QtCore.QSize(90, 16777215)) font = QtGui.QFont() font.setBold(False) font.setItalic(False) font.setWeight(50) self.compareTotalTimeDropdown.setFont(font) self.compareTotalTimeDropdown.setObjectName(""compareTotalTimeDropdown"") self.compareTotalTimeDropdown.addItem("""") self.compareTotalTimeDropdown.addItem("""") self.gridLayout_4.addWidget(self.compareTotalTimeDropdown, 0, 1, 1, 1) self.compareScoreDropdown = QtWidgets.QComboBox(self.widget) self.compareScoreDropdown.setMaximumSize(QtCore.QSize(90, 16777215)) self.compareScoreDropdown.setObjectName(""compareScoreDropdown"") self.compareScoreDropdown.addItem("""") self.compareScoreDropdown.addItem("""") self.gridLayout_4.addWidget(self.compareScoreDropdown, 1, 1, 1, 1) self.label_2 = QtWidgets.QLabel(self.widget) self.label_2.setMaximumSize(QtCore.QSize(75, 16777215)) self.label_2.setObjectName(""label_2"") self.gridLayout_4.addWidget(self.label_2, 2, 0, 1, 1) self.sortingOrderDropdown = QtWidgets.QComboBox(self.widget) self.sortingOrderDropdown.setMaximumSize(QtCore.QSize(75, 16777215)) self.sortingOrderDropdown.setObjectName(""sortingOrderDropdown"") self.sortingOrderDropdown.addItem("""") self.sortingOrderDropdown.addItem("""") self.gridLayout_4.addWidget(self.sortingOrderDropdown, 2, 2, 1, 1) self.label = QtWidgets.QLabel(self.widget) self.label.setMaximumSize(QtCore.QSize(70, 16777215)) self.label.setObjectName(""label"") self.gridLayout_4.addWidget(self.label, 0, 0, 1, 1) self.meanDropdown = QtWidgets.QComboBox(self.widget) self.meanDropdown.setMaximumSize(QtCore.QSize(70, 16777215)) self.meanDropdown.setObjectName(""meanDropdown"") self.meanDropdown.addItem("""") self.meanDropdown.addItem("""") self.meanDropdown.addItem("""") self.gridLayout_4.addWidget(self.meanDropdown, 1, 0, 1, 1) self.scoreField = QtWidgets.QLineEdit(self.widget) self.scoreField.setMaximumSize(QtCore.QSize(75, 16777215)) self.scoreField.setObjectName(""scoreField"") self.gridLayout_4.addWidget(self.scoreField, 1, 2, 1, 1) self.activeTotalTimeCheckbox = QtWidgets.QCheckBox(self.widget) self.activeTotalTimeCheckbox.setText("""") self.activeTotalTimeCheckbox.setObjectName(""activeTotalTimeCheckbox"") self.gridLayout_4.addWidget(self.activeTotalTimeCheckbox, 0, 3, 1, 1) self.totalTimeField = QtWidgets.QLineEdit(self.widget) self.totalTimeField.setMaximumSize(QtCore.QSize(75, 16777215)) self.totalTimeField.setObjectName(""totalTimeField"") self.gridLayout_4.addWidget(self.totalTimeField, 0, 2, 1, 1) self.activeScoreCheckbox = QtWidgets.QCheckBox(self.widget) self.activeScoreCheckbox.setText("""") self.activeScoreCheckbox.setObjectName(""activeScoreCheckbox"") self.gridLayout_4.addWidget(self.activeScoreCheckbox, 1, 3, 1, 1) self.sortingKeyDropdown = QtWidgets.QComboBox(self.widget) self.sortingKeyDropdown.setMaximumSize(QtCore.QSize(90, 16777215)) self.sortingKeyDropdown.setObjectName(""sortingKeyDropdown"") self.sortingKeyDropdown.addItem("""") self.sortingKeyDropdown.addItem("""") self.sortingKeyDropdown.addItem("""") self.sortingKeyDropdown.addItem("""") self.sortingKeyDropdown.addItem("""") self.sortingKeyDropdown.addItem("""") self.sortingKeyDropdown.addItem("""") self.sortingKeyDropdown.addItem("""") self.sortingKeyDropdown.addItem("""") self.gridLayout_4.addWidget(self.sortingKeyDropdown, 2, 1, 1, 1) self.activeSortingBox = QtWidgets.QCheckBox(self.widget) self.activeSortingBox.setText("""") self.activeSortingBox.setObjectName(""activeSortingBox"") self.gridLayout_4.addWidget(self.activeSortingBox, 2, 3, 1, 1) self.label_3 = QtWidgets.QLabel(self.widget) self.label_3.setMaximumSize(QtCore.QSize(75, 16777215)) self.label_3.setObjectName(""label_3"") self.gridLayout_4.addWidget(self.label_3, 3, 0, 1, 1) self.selectOnlyToolbox = QtWidgets.QComboBox(self.widget) self.selectOnlyToolbox.setObjectName(""selectOnlyToolbox"") self.selectOnlyToolbox.addItem("""") self.selectOnlyToolbox.addItem("""") self.selectOnlyToolbox.addItem("""") self.selectOnlyToolbox.addItem("""") self.gridLayout_4.addWidget(self.selectOnlyToolbox, 3, 1, 1, 2) self.onlyBoxActiveCheckbox = QtWidgets.QCheckBox(self.widget) self.onlyBoxActiveCheckbox.setText("""") self.onlyBoxActiveCheckbox.setObjectName(""onlyBoxActiveCheckbox"") self.gridLayout_4.addWidget(self.onlyBoxActiveCheckbox, 3, 3, 1, 1) self.gridLayout_3.addWidget(self.widget, 5, 0, 1, 4) self.applyFilterButton = QtWidgets.QPushButton(self.filterFrame) self.applyFilterButton.setObjectName(""applyFilterButton"") self.gridLayout_3.addWidget(self.applyFilterButton, 9, 0, 1, 1) self.frameStrideField = QtWidgets.QLineEdit(self.filterFrame) self.frameStrideField.setMaximumSize(QtCore.QSize(70, 16777215)) self.frameStrideField.setObjectName(""frameStrideField"") self.gridLayout_3.addWidget(self.frameStrideField, 0, 1, 1, 1) self.line_3 = QtWidgets.QFrame(self.filterFrame) self.line_3.setFrameShape(QtWidgets.QFrame.HLine) self.line_3.setFrameShadow(QtWidgets.QFrame.Sunken) self.line_3.setObjectName(""line_3"") self.gridLayout_3.addWidget(self.line_3, 6, 0, 1, 4) spacerItem1 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_3.addItem(spacerItem1, 8, 0, 1, 1) self.gridLayout.addWidget(self.filterFrame, 2, 8, 1, 2) self.exportContactDataButton = QtWidgets.QPushButton(self.centralwidget) self.exportContactDataButton.setObjectName(""exportContactDataButton"") self.gridLayout.addWidget(self.exportContactDataButton, 0, 9, 1, 1) MainWindow.setCentralWidget(self.centralwidget) self.statusbar = QtWidgets.QStatusBar(MainWindow) self.statusbar.setObjectName(""statusbar"") MainWindow.setStatusBar(self.statusbar) self.menubar = QtWidgets.QMenuBar(MainWindow) self.menubar.setGeometry(QtCore.QRect(0, 0, 1270, 22)) self.menubar.setDefaultUp(False) self.menubar.setObjectName(""menubar"") self.menuFile = QtWidgets.QMenu(self.menubar) self.menuFile.setObjectName(""menuFile"") self.menuAbout = QtWidgets.QMenu(self.menubar) self.menuAbout.setObjectName(""menuAbout"") self.menuTools = QtWidgets.QMenu(self.menubar) self.menuTools.setObjectName(""menuTools"") self.menuSettings = QtWidgets.QMenu(self.menubar) self.menuSettings.setObjectName(""menuSettings"") MainWindow.setMenuBar(self.menubar) self.actionOpen = QtWidgets.QAction(MainWindow) self.actionOpen.setObjectName(""actionOpen"") self.actionExport = QtWidgets.QAction(MainWindow) self.actionExport.setObjectName(""actionExport"") self.actionRun_VMD_contact_search = QtWidgets.QAction(MainWindow) self.actionRun_VMD_contact_search.setObjectName(""actionRun_VMD_contact_search"") self.actionLoad_Data = QtWidgets.QAction(MainWindow) self.actionLoad_Data.setObjectName(""actionLoad_Data"") self.actionImport_Session = QtWidgets.QAction(MainWindow) self.actionImport_Session.setObjectName(""actionImport_Session"") self.actionExport_Session = QtWidgets.QAction(MainWindow) self.actionExport_Session.setObjectName(""actionExport_Session"") self.actionDefault = QtWidgets.QAction(MainWindow) self.actionDefault.setObjectName(""actionDefault"") self.actionShow_Info = QtWidgets.QAction(MainWindow) self.actionShow_Info.setObjectName(""actionShow_Info"") self.actionExportData = QtWidgets.QAction(MainWindow) self.actionExportData.setCheckable(False) self.actionExportData.setShortcutContext(QtCore.Qt.WindowShortcut) self.actionExportData.setObjectName(""actionExportData"") self.actionContact_Area_Calculations = QtWidgets.QAction(MainWindow) self.actionContact_Area_Calculations.setObjectName(""actionContact_Area_Calculations"") self.actionPreferences = QtWidgets.QAction(MainWindow) self.actionPreferences.setObjectName(""actionPreferences"") self.actionVMD_Remote_Control = QtWidgets.QAction(MainWindow) self.actionVMD_Remote_Control.setObjectName(""actionVMD_Remote_Control"") self.actionTrack_Molecule = QtWidgets.QAction(MainWindow) self.actionTrack_Molecule.setObjectName(""actionTrack_Molecule"") self.menuFile.addAction(self.actionLoad_Data) self.menuFile.addAction(self.actionImport_Session) self.menuFile.addAction(self.actionExport_Session) self.menuFile.addAction(self.actionDefault) self.menuAbout.addAction(self.actionShow_Info) self.menuTools.addAction(self.actionExportData) self.menuTools.addAction(self.actionContact_Area_Calculations) self.menuTools.addAction(self.actionVMD_Remote_Control) self.menuSettings.addAction(self.actionPreferences) self.menubar.addAction(self.menuFile.menuAction()) self.menubar.addAction(self.menuTools.menuAction()) self.menubar.addAction(self.menuSettings.menuAction()) self.menubar.addAction(self.menuAbout.menuAction()) self.retranslateUi(MainWindow) QtCore.QMetaObject.connectSlotsByName(MainWindow) MainWindow.setTabOrder(self.scrollArea, self.lowerRangeField) MainWindow.setTabOrder(self.lowerRangeField, self.upperRangeField) MainWindow.setTabOrder(self.upperRangeField, self.filterRangeCheckbox) MainWindow.setTabOrder(self.filterRangeCheckbox, self.visModeButton) def retranslateUi(self, MainWindow): _translate = QtCore.QCoreApplication.translate MainWindow.setWindowTitle(_translate(""MainWindow"", ""MainWindow"")) self.visModeButton.setText(_translate(""MainWindow"", ""Vismode"")) self.selection1label.setText(_translate(""MainWindow"", ""-"")) self.selection1.setText(_translate(""MainWindow"", ""Selection 1:"")) self.status.setText(_translate(""MainWindow"", ""Status:"")) self.selection2label.setText(_translate(""MainWindow"", ""-"")) self.statusLabel.setText(_translate(""MainWindow"", ""-"")) self.selection2.setText(_translate(""MainWindow"", ""Selection 2:"")) self.progressBar.setFormat(_translate(""MainWindow"", ""%p%"")) self.statisticsButton.setText(_translate(""MainWindow"", ""Statistics"")) self.analysisButton.setText(_translate(""MainWindow"", ""Accumulate Scores"")) self.zoomSliderLabel.setText(_translate(""MainWindow"", ""Frame Stride:"")) self.toLabel.setText(_translate(""MainWindow"", ""to"")) self.rangeLabel.setText(_translate(""MainWindow"", ""Timeline Range:"")) self.upperRangeField.setText(_translate(""MainWindow"", ""end"")) self.lowerRangeField.setText(_translate(""MainWindow"", ""1"")) self.filterRangeCheckbox.setText(_translate(""MainWindow"", ""Filter Range"")) self.label_4.setText(_translate(""MainWindow"", ""idx 1:"")) self.atomAIndexField.setText(_translate(""MainWindow"", ""all"")) self.label_10.setText(_translate(""MainWindow"", ""resid 1:"")) self.atomANameField.setText(_translate(""MainWindow"", ""all"")) self.label_8.setText(_translate(""MainWindow"", ""name 2:"")) self.atomBNameField.setText(_translate(""MainWindow"", ""all"")) self.label_6.setText(_translate(""MainWindow"", ""Atoms:"")) self.label_7.setText(_translate(""MainWindow"", ""name 1:"")) self.atomBIndexField.setText(_translate(""MainWindow"", ""all"")) self.label_5.setText(_translate(""MainWindow"", ""idx 2:"")) self.label_9.setText(_translate(""MainWindow"", ""Residues:"")) self.label_11.setText(_translate(""MainWindow"", ""resid 2:"")) self.residBRangeField.setText(_translate(""MainWindow"", ""all"")) self.residARangeField.setText(_translate(""MainWindow"", ""all"")) self.label_12.setText(_translate(""MainWindow"", ""resn. 1:"")) self.residANameField.setText(_translate(""MainWindow"", ""all"")) self.label_13.setText(_translate(""MainWindow"", ""resn. 2"")) self.residBNameField.setText(_translate(""MainWindow"", ""all"")) self.compareTotalTimeDropdown.setItemText(0, _translate(""MainWindow"", ""greater"")) self.compareTotalTimeDropdown.setItemText(1, _translate(""MainWindow"", ""smaller"")) self.compareScoreDropdown.setItemText(0, _translate(""MainWindow"", ""greater"")) self.compareScoreDropdown.setItemText(1, _translate(""MainWindow"", ""smaller"")) self.label_2.setText(_translate(""MainWindow"", ""Sort by:"")) self.sortingOrderDropdown.setItemText(0, _translate(""MainWindow"", ""asc."")) self.sortingOrderDropdown.setItemText(1, _translate(""MainWindow"", ""desc."")) self.label.setText(_translate(""MainWindow"", ""Total Time:"")) self.meanDropdown.setItemText(0, _translate(""MainWindow"", ""Mean"")) self.meanDropdown.setItemText(1, _translate(""MainWindow"", ""Median"")) self.meanDropdown.setItemText(2, _translate(""MainWindow"", ""HB %"")) self.scoreField.setText(_translate(""MainWindow"", ""0"")) self.totalTimeField.setText(_translate(""MainWindow"", ""0"")) self.sortingKeyDropdown.setItemText(0, _translate(""MainWindow"", ""mean"")) self.sortingKeyDropdown.setItemText(1, _translate(""MainWindow"", ""median"")) self.sortingKeyDropdown.setItemText(2, _translate(""MainWindow"", ""bb/sc type"")) self.sortingKeyDropdown.setItemText(3, _translate(""MainWindow"", ""contact type"")) self.sortingKeyDropdown.setItemText(4, _translate(""MainWindow"", ""total time"")) self.sortingKeyDropdown.setItemText(5, _translate(""MainWindow"", ""mean lifetime"")) self.sortingKeyDropdown.setItemText(6, _translate(""MainWindow"", ""median lifetime"")) self.sortingKeyDropdown.setItemText(7, _translate(""MainWindow"", ""resid 1"")) self.sortingKeyDropdown.setItemText(8, _translate(""MainWindow"", ""resid 2"")) self.label_3.setText(_translate(""MainWindow"", ""Show Only:"")) self.selectOnlyToolbox.setItemText(0, _translate(""MainWindow"", ""hbonds"")) self.selectOnlyToolbox.setItemText(1, _translate(""MainWindow"", ""hydrophobic"")) self.selectOnlyToolbox.setItemText(2, _translate(""MainWindow"", ""saltbridges"")) self.selectOnlyToolbox.setItemText(3, _translate(""MainWindow"", ""other"")) self.applyFilterButton.setText(_translate(""MainWindow"", ""Apply"")) self.frameStrideField.setText(_translate(""MainWindow"", ""1"")) self.exportContactDataButton.setText(_translate(""MainWindow"", ""Export Contact Data"")) self.menuFile.setTitle(_translate(""MainWindow"", ""File"")) self.menuAbout.setTitle(_translate(""MainWindow"", ""About"")) self.menuTools.setTitle(_translate(""MainWindow"", ""Tools"")) self.menuSettings.setTitle(_translate(""MainWindow"", ""Settings"")) self.actionOpen.setText(_translate(""MainWindow"", ""Open"")) self.actionOpen.setShortcut(_translate(""MainWindow"", ""Ctrl+O"")) self.actionExport.setText(_translate(""MainWindow"", ""Export"")) self.actionExport.setShortcut(_translate(""MainWindow"", ""Ctrl+E"")) self.actionRun_VMD_contact_search.setText(_translate(""MainWindow"", ""Run VMD contact search"")) self.actionLoad_Data.setText(_translate(""MainWindow"", ""Load Trajectory Data"")) self.actionLoad_Data.setShortcut(_translate(""MainWindow"", ""Ctrl+I"")) self.actionImport_Session.setText(_translate(""MainWindow"", ""Import Session"")) self.actionImport_Session.setShortcut(_translate(""MainWindow"", ""Ctrl+Shift+I"")) self.actionExport_Session.setText(_translate(""MainWindow"", ""Export Session"")) self.actionExport_Session.setShortcut(_translate(""MainWindow"", ""Ctrl+Shift+E"")) self.actionDefault.setText(_translate(""MainWindow"", ""Default"")) self.actionDefault.setShortcut(_translate(""MainWindow"", ""Ctrl+Shift+D"")) self.actionShow_Info.setText(_translate(""MainWindow"", ""Developer Info"")) self.actionExportData.setText(_translate(""MainWindow"", ""Export Contact Data"")) self.actionExportData.setShortcut(_translate(""MainWindow"", ""Ctrl+E"")) self.actionContact_Area_Calculations.setText(_translate(""MainWindow"", ""Contact Area Calculation"")) self.actionContact_Area_Calculations.setShortcut(_translate(""MainWindow"", ""Ctrl+A"")) self.actionPreferences.setText(_translate(""MainWindow"", ""Preferences"")) self.actionPreferences.setShortcut(_translate(""MainWindow"", ""Ctrl+,"")) self.actionVMD_Remote_Control.setText(_translate(""MainWindow"", ""VMD Remote Control"")) self.actionVMD_Remote_Control.setShortcut(_translate(""MainWindow"", ""Ctrl+V"")) self.actionTrack_Molecule.setText(_translate(""MainWindow"", ""Track Molecule"")) self.actionTrack_Molecule.setShortcut(_translate(""MainWindow"", ""Ctrl+T"")) ","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/DetailWidget.py",".py","2613","59","import sip import os from PyQt5.QtWidgets import QWidget, QFileDialog from .Plotters import ContactPlotter from .detail_ui import * from ..core.LogPool import * from .ErrorBox import ErrorBox class Detail(QWidget, Ui_Detail): def __init__(self, data, nsPerFrame, threshold, parent=None): super(QWidget, self).__init__(parent) self.setupUi(self) self.contact = data self.nsPerFrame = nsPerFrame self.threshold = threshold self.setWindowTitle(self.contact.title) self.labelTotalTime.setText(str(self.contact.total_time(self.nsPerFrame, self.threshold))) self.labelThreshold.setText(str(self.threshold)) self.labelMedianScore.setText(str(self.contact.median_score())) self.labelMeanScore.setText(str(self.contact.mean_score())) self.labelMedianLifetime.setText(str(self.contact.median_life_time(self.nsPerFrame, self.threshold))) self.labelMeanLifetime.setText(str(self.contact.mean_life_time(self.nsPerFrame, self.threshold))) self.labelBackboneSidechainA.setText(""%.2f/%.2f"" % (self.contact.bb1, self.contact.sc1)) self.labelBackboneSidechainB.setText(""%.2f/%.2f"" % (self.contact.bb2, self.contact.sc2)) self.savePlotButton.clicked.connect(self.savePlot) self.plotButton.clicked.connect(self.plotAttribute) self.contactPlotter = ContactPlotter(None, width=4, height=2, dpi=70) self.contactPlotter.plot_contact_figure(self.contact, self.nsPerFrame) self.plotGridLayout.addWidget(self.contactPlotter) def plotAttribute(self): """"""Plots the selected attribute."""""" sip.delete(self.contactPlotter) self.contactPlotter = ContactPlotter(None, width=4, height=2, dpi=70) if self.attributeBox.currentText() == ""Score"": self.contactPlotter.plot_contact_figure(self.contact, self.nsPerFrame) self.plotGridLayout.addWidget(self.contactPlotter) def savePlot(self): """"""Saves the current plot."""""" fileName = QFileDialog.getSaveFileName(self, 'Save Path') path, file_extension = os.path.splitext(fileName[0]) if file_extension == """": file_extension = ""png"" else: file_extension = file_extension[1:] try: self.contactPlotter.saveFigure(path, file_extension) except ValueError: box = ErrorBox(""File format "" + file_extension + "" is not supported.\nPlease choose from eps, pdf, pgf,"" "" png, ps, raw, rgba, svg, svgz. "") box.exec_() ","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/__init__.py",".py","0","0","","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/MainWindow.py",".py","22099","495","import multiprocessing import warnings import copy import sys import PyQt5.QtCore as QtCore from PyQt5.QtCore import pyqtSlot, QObject from PyQt5.QtWidgets import (QMainWindow, QTabWidget, QLabel, QDialog, QApplication, QGridLayout, QFileDialog, QWidget) from PyQt5.Qt import Qt from PyQt5.QtGui import QIntValidator from PyQt5.QtSvg import QSvgGenerator import numpy as np from . import MainQtGui from .SasaWidgets import SasaWidget from .Canvas import Canvas from .Dialogues import FileLoaderDialog, AnalysisDialog from .ExportTabWidget import ExportTabWidget from .Statistics import Statistics from .Plotters import * from ..core.ContactAnalyzer import * from .ErrorBox import ErrorBox from .ErrorMessages import ErrorMessages from ..core.LogPool import * from . import Preferences from ..exampleData.datafiles import DEFAULTSESSION, DEFAULTSESSION_PY3 from .VMDControlPanel import VMDControlPanel from ..core.DataHandler import DataHandler multiprocessing.log_to_stderr() np.set_printoptions(threshold=np.inf) with warnings.catch_warnings(): warnings.simplefilter(""ignore"") class MainWindow(QMainWindow, MainQtGui.Ui_MainWindow, QObject): """"""PyContact Application Main Window with timeline."""""" def closeEvent(self, event): """"""Closing application when Exit on MainWindow is clicked."""""" event.accept() QApplication.quit() def __init__(self, parent=None): self.config = None self.analysis = None self.maps = None super(MainWindow, self).__init__(parent) self.contacts = [] self.filteredContacts = [] self.setupUi(self) self.setWindowTitle(""PyContact"") # painter contains both labels and frame boxes for drawing self.painter = Canvas() self.scrollArea.setWidget(self.painter) self.scrollArea.horizontalScrollBar().valueChanged.connect(self.horizontalScrollBarChanged) self.actionExportData.triggered.connect(self.pushExport) self.exportContactDataButton.clicked.connect(self.pushExport) self.actionLoad_Data.triggered.connect(self.loadDataPushed) self.actionExport_Session.triggered.connect(self.exportSession) self.actionImport_Session.triggered.connect(self.importSession) self.actionShow_Info.triggered.connect(self.showDeveloperInfo) # settings and filters self.settingsView = PreferencesWidget() self.settingsView.applySettingsButton.clicked.connect(self.updateSettings) self.applyFilterButton.clicked.connect(self.updateFilters) # statistics self.statisticsButton.clicked.connect(self.showStatistics) # frames stride posIntValidator = QIntValidator() posIntValidator.setBottom(1) self.frameStrideField.setValidator(posIntValidator) # analysis button self.analysisButton.clicked.connect(self.analyzeDataPushed) # contact area button self.actionContact_Area_Calculations.triggered.connect(self.showContactAreaView) # preferences self.actionPreferences.triggered.connect(self.openPrefs) # apply color button, outdated? self.colorScheme = ColorScheme.bbsc self.actionDefault.triggered.connect(self.loadDefault) self.currentSelection1 = ""-"" self.currentSelection2 = ""-"" # setup of extra widgets self.exportWidget = ExportTabWidget() self.sasaView = SasaWidget() self.statisticsView = None self.analysis_state = False self.vismode = False self.visModeButton.setCheckable(True) self.visModeButton.setChecked(False) self.visModeButton.clicked.connect(self.switchedToVisMode) self.vmdpanel = VMDControlPanel() self.actionVMD_Remote_Control.triggered.connect(self.showVMDControlPanel) self.painter.clickedRowSignal.connect(self.updateVMDSelections) self.painter.clickedColumnSignal.connect(self.updateVMDFrame) self.updateSettings() self.updateFilters() # self.tableTest = Widget() # self.tableTest.setGeometry(100, 100, 400, 400) # self.tableTest.show() # from ..db.DbReader import read_residue_db_all # res = read_residue_db_all() # residueList = [] # 1st: name, 2nd scpolarity # for k in res: # residueList.appen([k[""name""], k[""scpolarity""]]) self.actionDefault.setText(""Load sample data"") def horizontalScrollBarChanged(self): x = self.scrollArea.horizontalScrollBar().value() y = self.painter.labelView.y() self.painter.labelView.move(x, y) def showVMDControlPanel(self): """"""Shows the VMD control panel, to remotely access VMD from PyContact."""""" self.vmdpanel.show() def showContactAreaView(self): """"""Shows the SASA computation panel."""""" self.sasaView.nsPerFrame = float(self.settingsView.nsPerFrameField.text()) self.sasaView.show() if self.analysis: self.sasaView.setFilePaths(self.analysis.getFilePaths()) def switchedToVisMode(self): """"""Switch to vis mode, to show selected contacts directly in VMD."""""" if self.visModeButton.isChecked(): self.vismode = True # conversions with clicked frames are not allowed self.frameStrideField.setText(""1"") else: self.vismode = False self.painter.switchToVisMode(self.vismode) self.updateSettings() self.updateFilters() @pyqtSlot() def updateVMDSelections(self): """"""Updates the selected contact in VMD via the vmd panel."""""" if self.vmdpanel.connected: self.vmdpanel.updateSelections(self.analysis.sel1text, self.analysis.sel2text, [self.filteredContacts[self.painter.globalClickedRow]]) @pyqtSlot() def updateVMDFrame(self): """"""Updates the selected frame in VMD via the vmd panel."""""" if self.vmdpanel.connected: self.vmdpanel.gotoVMDFrame(self.painter.clickedColumn) def updateSelectionLabels(self, sel1, sel2): """"""Updates the current selection in the info labels."""""" self.currentSelection1 = sel1 self.currentSelection2 = sel2 self.selection1label.setText(sel1) self.selection2label.setText(sel2) def importSession(self): """"""Imports a saved session from file."""""" fnames = QFileDialog.getOpenFileNames(self, ""Open file"") importfile = """" for f in fnames[0]: importfile = f break if importfile == """" or len(fnames) == 0: return self.contacts, arguments, trajArgs, self.maps, contactResults = DataHandler.importSessionFromFile(importfile) self.analysis = Analyzer(*arguments) self.analysis.contactResults = contactResults self.analysis.setTrajectoryData(*trajArgs) self.analysis.finalAccumulatedContacts = self.contacts self.sasaView.setFilePaths(*self.analysis.getFilePaths()) self.exportWidget.setFilePaths(*self.analysis.getFilePaths()) self.updateSelectionLabels(arguments[5], arguments[6]) self.updateSettings() self.updateFilters() def exportSession(self): """"""Exports the current session to file."""""" fileName = QFileDialog.getSaveFileName(self, 'Export file') filestring = fileName[0] if filestring == """": return if self.contacts is not None and self.analysis is not None: self.setInfoLabel(""Exporting current session..."") DataHandler.writeSessionToFile(filestring, self.analysis) self.cleanInfoLabel() else: box = ErrorBox(ErrorMessages.NOEXPDATA) box.exec_() return def loadDefault(self): """"""Loads the default session."""""" if (sys.version_info > (3, 0)): self.contacts, arguments, trajArgs, self.maps, contactResults = DataHandler.importSessionFromFile(DEFAULTSESSION_PY3) else: self.contacts, arguments, trajArgs, self.maps, contactResults = DataHandler.importSessionFromFile(DEFAULTSESSION) self.analysis = Analyzer(*arguments) self.analysis.contactResults = contactResults self.analysis.setTrajectoryData(*trajArgs) self.analysis.finalAccumulatedContacts = self.contacts self.sasaView.setFilePaths(*self.analysis.getFilePaths()) self.exportWidget.setFilePaths(*self.analysis.getFilePaths()) self.updateSelectionLabels(arguments[5], arguments[6]) self.updateSettings() self.updateFilters() def loadDataPushed(self): """"""Loads the trajectory data with the chosen initial parameters."""""" self.config, result = FileLoaderDialog.getConfig() if result == 1: QApplication.processEvents() self.setInfoLabel(""Loading trajectory and running atomic contact analysis..."") nproc = int(self.settingsView.coreBox.value()) self.analysis = Analyzer(self.config.psf, self.config.dcd, self.config.cutoff, self.config.hbondcutoff, self.config.hbondcutangle, self.config.sel1text, self.config.sel2text) QApplication.processEvents() try: self.analysis.runFrameScan(nproc) except: box = ErrorBox(""Error while loading data: Probably you specified an atom selection with 0 atoms or invalid input files."") box.exec_() self.loadDataPushed() self.setInfoLabel(""%d frames loaded."" % len(self.analysis.contactResults)) self.updateSelectionLabels(self.config.sel1text, self.config.sel2text) self.sasaView.setFilePaths(*self.analysis.getFilePaths()) self.exportWidget.setFilePaths(*self.analysis.getFilePaths()) @pyqtSlot(float) def updateAnalyzedFrames(self, value): """"""Handles the progress bar update."""""" self.progressBar.setValue(int(100 * value)) QApplication.processEvents() def setInfoLabel(self, txt): """"""Sets the Info label text."""""" self.statusLabel.setText(txt) def cleanInfoLabel(self): """"""Clears the Info label text."""""" self.setInfoLabel(""-"") def analyzeDataPushed(self): """"""Handles the Analyzer after the Accumulation maps have been set."""""" if self.analysis is None: box = ErrorBox(ErrorMessages.NODATA_PROMPTLOAD) box.exec_() return self.maps, result = AnalysisDialog.getMapping() if result == 1: self.analysis.frameUpdate.connect(self.updateAnalyzedFrames) self.setInfoLabel(""Analyzing contacts..."") map1 = self.maps[0] map2 = self.maps[1] nproc = int(self.settingsView.coreBox.value()) self.contacts = self.analysis.runContactAnalysis(map1, map2, nproc) self.progressBar.setValue(0) self.setInfoLabel(""Updating timeline..."") QApplication.processEvents() self.updateSettings() self.updateFilters() self.cleanInfoLabel() def updateSettings(self): """"""Updates the settings chosen from the settings view."""""" self.painter.nsPerFrame = float(self.settingsView.nsPerFrameField.text()) self.painter.threshold = float(self.settingsView.thresholdField.text()) self.painter.rendered = False self.painter.colorScheme = self.colorScheme # self.painter.customColor = self.customColor self.painter.repaint() self.painter.update() self.sasaView.nsPerFrame = float(self.settingsView.nsPerFrameField.text()) def updateFilters(self): """"""Updates the chosen filters in MainWindow."""""" if self.vismode is True: self.frameStrideField.setText(""1"") stride = int(self.frameStrideField.text()) if stride < 1: stride = 1 QApplication.processEvents() self.frameStrideField.setText(str(stride)) self.painter.merge = stride self.painter.labelView.clean() self.painter.showHbondScores = False # total time filter totalTimeActive = self.activeTotalTimeCheckbox.isChecked() scoreActive = self.activeScoreCheckbox.isChecked() sortingActive = self.activeSortingBox.isChecked() onlyActive = self.onlyBoxActiveCheckbox.isChecked() filterActive = (totalTimeActive or scoreActive or sortingActive or onlyActive) weightActive = False # only filter given range rangeFilterActive = self.filterRangeCheckbox.isChecked() if len(self.contacts) > 0: lower = int(self.lowerRangeField.text()) - 1 upper = self.upperRangeField.text() if upper == ""end"": upper = len(self.contacts[0].scoreArray) else: upper = int(upper) if lower < 0: lower = 0 self.painter.range = [lower, upper] self.painter.rangeFilterActive = False self.filteredContacts = copy.deepcopy(self.contacts) # residue range filter range_filter = RangeFilter(""resrange"") self.filteredContacts = range_filter.filterByRange(self.filteredContacts, self.residARangeField.text(), self.residBRangeField.text(), AccumulationMapIndex.resid) self.filteredContacts = range_filter.filterByRange(self.filteredContacts, self.atomAIndexField.text(), self.atomBIndexField.text(), AccumulationMapIndex.index) # aminoacids name filter name_filter = NameFilter(""name"") self.filteredContacts = name_filter.filterContactsByName(self.filteredContacts, self.residANameField.text(), self.residBNameField.text(), AccumulationMapIndex.resname) self.filteredContacts = name_filter.filterContactsByName(self.filteredContacts, self.atomANameField.text(), self.atomBNameField.text(), AccumulationMapIndex.name) # range filter if rangeFilterActive: self.painter.rangeFilterActive = True frameRangeFilter = FrameFilter(""framer"") self.filteredContacts = frameRangeFilter.extractFrameRange(self.filteredContacts, [lower, upper]) for c in self.filteredContacts: c.setScores() c.setContactType() # weight functions if weightActive: if self.currentFunctionType == FunctionType.sigmoid: x0 = float(self.sigX0Field.text()) L = float(self.sigLField.text()) k = float(self.sigKField.text()) y0 = float(self.sigY0Field.text()) sig = SigmoidWeightFunction(""sig"", np.arange(0, len(self.contacts[0].scoreArray), 1), x0, L, k, y0) self.filteredContacts = sig.weightContactFrames(self.filteredContacts) elif self.currentFunctionType == FunctionType.rect: x0 = float(self.rectX0Field.text()) x1 = float(self.rectX1Field.text()) h = float(self.rectHField.text()) y0 = float(self.rectY0Field.text()) rect = RectangularWeightFunction(""rect"", np.arange(0, len(self.contacts[0].scoreArray), 1), x0, x1, h, y0) self.filteredContacts = rect.weightContactFrames(self.filteredContacts) elif self.currentFunctionType == FunctionType.linear: y0 = float(self.linY0Field.text()) y1 = float(self.linY1Field.text()) lin = LinearWeightFunction(""rect"", np.arange(0, len(self.contacts[0].scoreArray), 1), y0, y1) self.filteredContacts = lin.weightContactFrames(self.filteredContacts) # other filters if filterActive: if totalTimeActive: operator = self.compareTotalTimeDropdown.currentText() value = float(self.totalTimeField.text()) filter = TotalTimeFilter(""tottime"", operator, value) self.filteredContacts = filter.filterContacts(self.filteredContacts) if scoreActive: operator = self.compareScoreDropdown.currentText() value = float(self.scoreField.text()) filter = ScoreFilter(""score"", operator, value, self.meanDropdown.currentText()) self.filteredContacts = filter.filterContacts(self.filteredContacts) if sortingActive: key = self.sortingKeyDropdown.currentText() descending = SortingOrder.mapping[self.sortingOrderDropdown.currentText()] sorter = Sorting(""sorting"", key, descending) sorter.setThresholdAndNsPerFrame(float(self.settingsView.thresholdField.text()), float(self.settingsView.nsPerFrameField.text())) self.filteredContacts = sorter.sortContacts(self.filteredContacts) if onlyActive: key = self.selectOnlyToolbox.currentText() only = OnlyFilter(""only"", key, 0) self.filteredContacts = only.filterContacts(self.filteredContacts) if key == ""hbonds"": self.painter.showHbondScores = True self.painter.contacts = self.filteredContacts self.painter.rendered = False self.painter.repaint() self.painter.update() if len(self.filteredContacts) == 0: self.painter.labelView.clean() else: # no weight or filters self.painter.showHbondScores = False self.painter.contacts = self.filteredContacts self.painter.rendered = False self.painter.repaint() self.painter.update() # Update data for export self.exportWidget.setContacts(self.filteredContacts) if self.maps is not None: self.exportWidget.setMaps(self.maps[0], self.maps[1]) self.exportWidget.setMapLabels(self.analysis.sel1text, self.analysis.sel2text) self.vmdpanel.sel1 = self.analysis.sel1text self.vmdpanel.sel2 = self.analysis.sel2text self.vmdpanel.filteredContactList = self.filteredContacts self.exportWidget.setThresholdAndNsPerFrame(self.painter.threshold, self.painter.nsPerFrame) def openPrefs(self): """"""Opens the preferences panel."""""" self.settingsView.show() def showStatistics(self): """"""Shows general statistics of the analyzed data over all frames."""""" if len(self.contacts) == 0 or self.contacts is None: box = ErrorBox(ErrorMessages.NOSCORES_PROMPTANALYSIS) box.exec_() return self.statisticsView = Statistics(self.contacts, float(self.settingsView.nsPerFrameField.text())) self.statisticsView.showNormal() def showDeveloperInfo(self): """"""Shows information about the contributing authors."""""" d = QDialog() grid = QGridLayout() d.setLayout(grid) info = QLabel(""Developers: Maximilian Scheurer and Peter Rodenkirch"") info2 = QLabel("""") mail = QLabel(""Contact: mscheurer@ks.uiuc.edu, rodenkirch@stud.uni-heidelberg.de"") copyright = QLabel(""Version 1.0.5"") grid.addWidget(info, 0, 0) grid.addWidget(info2, 1, 0) grid.addWidget(mail, 2, 0) grid.addWidget(copyright, 3, 0) d.setWindowTitle(""Developer Info"") d.setFixedSize(500,150) d.setWindowModality(Qt.ApplicationModal) d.exec_() def pushExport(self): """"""Opens the export panel."""""" self.exportWidget.valueUpdated.connect(self.handleExportUpdate) self.exportWidget.setContacts(self.filteredContacts) if self.maps is not None: self.exportWidget.setMaps(self.maps[0], self.maps[1]) self.exportWidget.setMapLabels(self.analysis.sel1text, self.analysis.sel2text) self.exportWidget.setThresholdAndNsPerFrame(self.painter.threshold, self.painter.nsPerFrame) self.exportWidget.show() @QtCore.Slot(str, str) def handleExportUpdate(self, fileName, fileType): """"""Handles the paint event after the export of the current view has been initiated."""""" if fileType == ""PNG"": if len(fileName) > 0: currentView = self.painter.grab() currentView.save(fileName) elif fileType == ""SVG"": if len(fileName) > 0: generator = QSvgGenerator() generator.setFileName(fileName) generator.setSize(self.painter.size()) generator.setViewBox(self.painter.rect()) self.painter.renderContact(generator) self.painter.rendered = False self.painter.repaint() self.painter.update() class PreferencesWidget(QTabWidget, Preferences.Ui_PreferencesPanel): """"""Defines the preferences panel"""""" def __init__(self, parent=None): super(QWidget, self).__init__(parent) self.setupUi(self) class ColorScheme: custom, bbsc = range(2) ","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/Preferences.py",".py","4068","77","# -*- coding: utf-8 -*- # Form implementation generated from reading ui file 'Preferences.ui' # # Created by: PyQt5 UI code generator 5.6 # # WARNING! All changes made in this file will be lost! from PyQt5 import QtCore, QtGui, QtWidgets class Ui_PreferencesPanel(object): def setupUi(self, PreferencesPanel): PreferencesPanel.setObjectName(""PreferencesPanel"") PreferencesPanel.resize(443, 253) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(PreferencesPanel.sizePolicy().hasHeightForWidth()) PreferencesPanel.setSizePolicy(sizePolicy) PreferencesPanel.setMinimumSize(QtCore.QSize(443, 253)) PreferencesPanel.setMaximumSize(QtCore.QSize(443, 253)) self.gridLayout = QtWidgets.QGridLayout(PreferencesPanel) self.gridLayout.setObjectName(""gridLayout"") self.label = QtWidgets.QLabel(PreferencesPanel) self.label.setObjectName(""label"") self.gridLayout.addWidget(self.label, 0, 0, 1, 1) self.coreBox = QtWidgets.QSpinBox(PreferencesPanel) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.coreBox.sizePolicy().hasHeightForWidth()) self.coreBox.setSizePolicy(sizePolicy) self.coreBox.setMinimum(1) self.coreBox.setMaximum(64) self.coreBox.setProperty(""value"", 4) self.coreBox.setObjectName(""coreBox"") self.gridLayout.addWidget(self.coreBox, 2, 1, 1, 1) self.applySettingsButton = QtWidgets.QPushButton(PreferencesPanel) self.applySettingsButton.setObjectName(""applySettingsButton"") self.gridLayout.addWidget(self.applySettingsButton, 4, 0, 1, 2) self.line_2 = QtWidgets.QFrame(PreferencesPanel) self.line_2.setFrameShape(QtWidgets.QFrame.HLine) self.line_2.setFrameShadow(QtWidgets.QFrame.Sunken) self.line_2.setObjectName(""line_2"") self.gridLayout.addWidget(self.line_2, 3, 0, 1, 2) self.thresholdField = QtWidgets.QLineEdit(PreferencesPanel) self.thresholdField.setClearButtonEnabled(True) self.thresholdField.setObjectName(""thresholdField"") self.gridLayout.addWidget(self.thresholdField, 1, 1, 1, 1) self.label_2 = QtWidgets.QLabel(PreferencesPanel) self.label_2.setObjectName(""label_2"") self.gridLayout.addWidget(self.label_2, 1, 0, 1, 1) self.label_4 = QtWidgets.QLabel(PreferencesPanel) self.label_4.setObjectName(""label_4"") self.gridLayout.addWidget(self.label_4, 2, 0, 1, 1) self.nsPerFrameField = QtWidgets.QLineEdit(PreferencesPanel) self.nsPerFrameField.setClearButtonEnabled(True) self.nsPerFrameField.setObjectName(""nsPerFrameField"") self.gridLayout.addWidget(self.nsPerFrameField, 0, 1, 1, 1) self.retranslateUi(PreferencesPanel) QtCore.QMetaObject.connectSlotsByName(PreferencesPanel) PreferencesPanel.setTabOrder(self.nsPerFrameField, self.thresholdField) PreferencesPanel.setTabOrder(self.thresholdField, self.coreBox) PreferencesPanel.setTabOrder(self.coreBox, self.applySettingsButton) def retranslateUi(self, PreferencesPanel): _translate = QtCore.QCoreApplication.translate PreferencesPanel.setWindowTitle(_translate(""PreferencesPanel"", ""Preferences"")) self.label.setText(_translate(""PreferencesPanel"", ""Nanoseconds/frame:"")) self.applySettingsButton.setText(_translate(""PreferencesPanel"", ""Apply"")) self.thresholdField.setText(_translate(""PreferencesPanel"", ""0.0"")) self.label_2.setText(_translate(""PreferencesPanel"", ""Score Threshold:"")) self.label_4.setText(_translate(""PreferencesPanel"", ""Cores:"")) self.nsPerFrameField.setText(_translate(""PreferencesPanel"", ""1.0"")) ","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/SasaWidgets.py",".py","12645","329","import sip import time import os from PyQt5.QtWidgets import QWidget, QProgressBar, QApplication, QFileDialog import MDAnalysis import numpy as np # import multiprocessing from .Plotters import SimplePlotter from .sasa_gui import * from ..core.multi_trajectory import chunks from ..core.Biochemistry import vdwRadius from ..core.LogPool import * from ..cy_modules import cy_gridsearch from .Dialogues import TopoTrajLoaderDialog from .ErrorBox import ErrorBox from .ErrorMessages import ErrorMessages # manage processes for SASA # sasaProgressManager = multiprocessing.Manager() # sasaProgressDict = sasaProgressManager.dict() # np.set_printoptions(threshold=np.inf) def calculate_sasa_parallel(input_coords, natoms, pairdist, nprad, surfacePoints, probeRadius, pointstyle, restricted, restrictedList, rank): """"""Computes the SASA in parallel."""""" temp_sasa = [] frames_processed = 0 # sasaProgressDict[rank] = frames_processed # print(len(input_coords)) for c in input_coords: coords = np.reshape(c, (1, natoms * 3)) npcoords = np.array(coords, dtype=np.float32) # print(""start C"") # startC = time.time() asa = cy_gridsearch.cy_sasa(npcoords, natoms, pairdist, 0, -1, nprad, surfacePoints, probeRadius, pointstyle, restricted, restrictedList) # stopC = time.time() # print(""time for grid search: "", (stopC - startC)) # print(""asa:"", asa) temp_sasa.append(asa) frames_processed += 1 # sasaProgressDict[rank] = frames_processed return temp_sasa class SasaWidget(QWidget, Ui_SasaWidget): """"""Provides a UI for the SASA calculation, including restriction selection and contact area calculation."""""" def __init__(self, parent=None): super(QtWidgets.QWidget, self).__init__(parent) self.setupUi(self) self.state = True self.name = None self.psf, self. dcd = """", """" self.allSasas = [] self.totalFramesToProcess = 0 self.nsPerFrame = 1.0 sip.delete(self.sasaProgressBar) self.sasaProgressBar = PbWidget(total=100) self.sasaProgressBar.setProperty(""value"", 0) self.sasaProgressBar.setTextVisible(True) self.sasaProgressBar.setInvertedAppearance(False) self.sasaProgressBar.setObjectName(""sasaProgressBar"") self.previewPlot = SimplePlotter(None, width=4, height=2, dpi=70) self.graphGridLayout.addWidget(self.previewPlot) self.gridLayout.addWidget(self.sasaProgressBar, 8, 1, 1, 2) self.calcSasaButton.clicked.connect(self.calculateSasa) self.loadDataButton.clicked.connect(self.loadData) self.clearDataButton.clicked.connect(self.clearData) self.savePlotButton.clicked.connect(self.savePlot) self.exportDataButton.clicked.connect(self.exportData) self.topoloader = TopoTrajLoaderDialog() def setFilePaths(self, *argv): """"""Sets the current trajectory paths from the main view."""""" self.psf = argv[0][0] self.dcd = argv[0][1] def loadData(self): """"""Sets the chosen trajectory and topology paths."""""" loadedData = self.topoloader.getConfig() self.psf = loadedData[0][0] self.dcd = loadedData[0][1] def clearData(self): """"""Clears the whole view and sets it to the initial state."""""" self.psf = """" self.dcd = """" self.allSasas = [] self.totalFramesToProcess = 0 self.sasaProgressBar.setProperty(""value"", 0) sip.delete(self.previewPlot) self.previewPlot = SimplePlotter(None, width=4, height=2, dpi=70) self.graphGridLayout.addWidget(self.previewPlot) self.sasaSelection1TextField.setText("""") self.sasaSelection2TextField.setText("""") self.sasaRestrictionTextField.setText("""") def savePlot(self): """"""Saves the generated SASA plot over all frames."""""" fileName = QFileDialog.getSaveFileName(self, 'Export Path') if len(fileName[0]) > 0: path, file_extension = os.path.splitext(fileName[0]) if file_extension == """": file_extension = "".png"" file_extension = file_extension[1:] try: self.previewPlot.saveFigure(path, file_extension) except ValueError: box = ErrorBox(""File format "" + file_extension + "" is not supported.\nPlease choose from eps, pdf, pgf,"" "" png, ps, raw, rgba, svg, svgz. "") box.exec_() def exportData(self): """"""Exports the computed SASA values of each frame to a text file."""""" fileName = QFileDialog.getSaveFileName(self, 'Export Path') if len(fileName[0]) > 0: path, file_extension = os.path.splitext(fileName[0]) if file_extension == """": file_extension = "".dat"" f = open(path + file_extension, ""w"") for i in range(self.totalFramesToProcess): f.write(str(i) + ""\t"" + str(self.allSasas[i]) + ""\n"") f.close() # TODO: move this somewhere else, e.g., core modules def calculateSasa(self): """"""Computes the SASA of the given selections."""""" self.allSasas = [] # load psf and trajectory, make lists with radii and coordinates if self.psf == """" or self.dcd == """": e = ErrorBox(ErrorMessages.CHOOSEFILE) e.exec_() return try: u = MDAnalysis.Universe(self.psf, self.dcd) except IOError: e = ErrorBox(ErrorMessages.FILE_NOT_FOUND) e.exec_() return probeRadius = 1.4 # seltext = ""segid UBQ"" # resseltext = ""segid UBQ and same residue as around 5.0 (segid RN11)"" seltext = self.sasaSelection1TextField.text() seltext2 = self.sasaSelection2TextField.text() resseltext = self.sasaRestrictionTextField.text() # 0=spiral, 1=random (VMD) pointstyle = 1 # number of points to approximate the sphere surfacePoints = 50 # pair distance pairdist = 2.0 * (2.0 + 1.4) if resseltext != """": restricted = 1 else: restricted = 0 selection = u.select_atoms(seltext) # natoms = len(selection.atoms) radius = [] restrictedList = [] if restricted: ressel = u.select_atoms(resseltext) for s in selection.atoms: if s in ressel.atoms: restrictedList.append(1) else: restrictedList.append(0) radius.append(vdwRadius(s.name[0])) else: restrictedList = [0] for s in selection.atoms: radius.append(vdwRadius(s.name[0])) natoms = len(selection) nprad = np.array(radius, dtype=np.float32) restrictedList = np.array(restrictedList, dtype=np.int32) # TODO: bug if selection is not static for all frames # TODO: dynamic allocation of positions in every frame! input_coords = [] for ts in u.trajectory: # ressel = u.select_atoms(resseltext) # print(""restricted: "", len(ressel.atoms)) input_coords.append(selection.positions) nprocs = self.coreBox.value() input_chunks = chunks(input_coords, nprocs) pool = LoggingPool(nprocs) results = [] rank = 0 trajLength = len(u.trajectory) self.totalFramesToProcess = trajLength for input_coords_chunk in input_chunks: results.append(pool.apply_async(calculate_sasa_parallel, args=(input_coords_chunk, natoms, pairdist, nprad, surfacePoints, probeRadius, pointstyle, restricted, restrictedList, rank))) rank += 1 self.state = True self.sasaEventListener() pool.close() pool.join() self.state = False for r in results: self.allSasas.extend(r.get()) del radius # TODO: one would call the ""external"" sasa module here again, # no need to duplicate the code if self.calculateContactAreaCheckbox.isChecked(): selection2 = u.select_atoms(seltext2) # natoms2 = len(selection2.atoms) radius2 = [] restrictedList2 = [] if restricted: ressel = u.select_atoms(resseltext) for s in selection2.atoms: if s in ressel.atoms: restrictedList2.append(1) else: restrictedList2.append(0) radius2.append(vdwRadius(s.name[0])) else: print(""You need a restricted selection for contact areas!"") natoms2 = len(selection2) nprad = np.array(radius2, dtype=np.float32) restrictedList2 = np.array(restrictedList2, dtype=np.int32) input_coords2 = [] for ts in u.trajectory: input_coords2.append(selection2.positions) input_chunks2 = chunks(input_coords2, nprocs) pool = LoggingPool(nprocs) results = [] rank = 0 trajLength = len(u.trajectory) self.totalFramesToProcess = trajLength for input_coords_chunk2 in input_chunks2: results.append(pool.apply_async(calculate_sasa_parallel, args=(input_coords_chunk2, natoms2, pairdist, nprad, surfacePoints, probeRadius, pointstyle, restricted, restrictedList2, rank))) rank += 1 self.state = True self.sasaEventListener() pool.close() pool.join() all_sasas2 = [] for r in results: all_sasas2.extend(r.get()) diff_list = [] for sasa_value1, sasa_value2 in zip(self.allSasas, all_sasas2): diff_list.append(sasa_value1 - sasa_value2) self.allSasas = diff_list sip.delete(self.previewPlot) self.previewPlot = SimplePlotter(None, width=4, height=2, dpi=70) self.previewPlot.plot(np.arange(0, trajLength, 1) * self.nsPerFrame, self.allSasas) self.previewPlot.axes.set_xlabel(""time [ns]"") if self.calculateContactAreaCheckbox.isChecked(): self.previewPlot.axes.set_ylabel(r'Contact Area [A$^{\circ}$$^{2}$]') else: self.previewPlot.axes.set_ylabel(r'SASA [A$^{\circ}$$^{2}$]') self.graphGridLayout.addWidget(self.previewPlot) self.previewPlot.update() def sasaEventListener(self): """"""Event listener for progress bar updates."""""" while self.state: QApplication.processEvents() progress = 0 # for each in sasaProgressDict.keys(): # progress += sasaProgressDict[each] # # sasaProgressDict[each] = 0 progress = float(progress) / float(self.totalFramesToProcess) * 100 # if (101 - self.sasaProgressBar.value()) < progress: # self.sasaProgressBar.update_bar(101 - self.sasaProgressBar.value()) if progress > 0: self.sasaProgressBar.setValue(progress) if int(progress) == 100: # for each in sasaProgressDict.keys(): # sasaProgressDict[each] = 0 # progress = 0 self.state = False class PbWidget(QProgressBar): """"""Subclassed progressbar for the SASA UI."""""" def __init__(self, total=100): super(PbWidget, self).__init__() self.setMinimum(0) self.setMaximum(total) self._active = False def update_bar(self, to_add_number): while True: time.sleep(0.01) value = self.value() + to_add_number self.setValue(value) qApp.processEvents() if not self._active or value >= self.maximum(): break self._active = False def closeEvent(self, event): self._active = False ","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/statistics_ui.py",".py","7158","141","# -*- coding: utf-8 -*- # Form implementation generated from reading ui file 'statistics.ui' # # Created by: PyQt5 UI code generator 5.6 # # WARNING! All changes made in this file will be lost! from PyQt5 import QtCore, QtGui, QtWidgets class Ui_Statistics(object): def setupUi(self, Statistics): Statistics.setObjectName(""Statistics"") Statistics.setWindowModality(QtCore.Qt.WindowModal) Statistics.resize(930, 642) self.gridLayout = QtWidgets.QGridLayout(Statistics) self.gridLayout.setObjectName(""gridLayout"") self.savePlotButton = QtWidgets.QPushButton(Statistics) self.savePlotButton.setObjectName(""savePlotButton"") self.gridLayout.addWidget(self.savePlotButton, 6, 3, 1, 1) self.label_6 = QtWidgets.QLabel(Statistics) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.label_6.setFont(font) self.label_6.setObjectName(""label_6"") self.gridLayout.addWidget(self.label_6, 2, 2, 1, 1) self.label_2 = QtWidgets.QLabel(Statistics) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.label_2.setFont(font) self.label_2.setObjectName(""label_2"") self.gridLayout.addWidget(self.label_2, 0, 0, 1, 1) self.label = QtWidgets.QLabel(Statistics) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.label.setFont(font) self.label.setObjectName(""label"") self.gridLayout.addWidget(self.label, 2, 0, 1, 1) self.labelNumFrames = QtWidgets.QLabel(Statistics) font = QtGui.QFont() font.setBold(False) font.setWeight(50) self.labelNumFrames.setFont(font) self.labelNumFrames.setText("""") self.labelNumFrames.setObjectName(""labelNumFrames"") self.gridLayout.addWidget(self.labelNumFrames, 0, 1, 1, 1) self.labelTotalContacts = QtWidgets.QLabel(Statistics) font = QtGui.QFont() font.setBold(False) font.setWeight(50) self.labelTotalContacts.setFont(font) self.labelTotalContacts.setText("""") self.labelTotalContacts.setObjectName(""labelTotalContacts"") self.gridLayout.addWidget(self.labelTotalContacts, 2, 1, 1, 1) self.label_5 = QtWidgets.QLabel(Statistics) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.label_5.setFont(font) self.label_5.setObjectName(""label_5"") self.gridLayout.addWidget(self.label_5, 0, 2, 1, 1) self.labelMedianScore = QtWidgets.QLabel(Statistics) self.labelMedianScore.setText("""") self.labelMedianScore.setObjectName(""labelMedianScore"") self.gridLayout.addWidget(self.labelMedianScore, 0, 3, 1, 1) self.labelMeanScore = QtWidgets.QLabel(Statistics) self.labelMeanScore.setText("""") self.labelMeanScore.setObjectName(""labelMeanScore"") self.gridLayout.addWidget(self.labelMeanScore, 2, 3, 1, 1) self.attributeBox = QtWidgets.QComboBox(Statistics) self.attributeBox.setObjectName(""attributeBox"") self.attributeBox.addItem("""") self.attributeBox.addItem("""") self.gridLayout.addWidget(self.attributeBox, 6, 0, 1, 1) self.line = QtWidgets.QFrame(Statistics) self.line.setFrameShape(QtWidgets.QFrame.HLine) self.line.setFrameShadow(QtWidgets.QFrame.Sunken) self.line.setObjectName(""line"") self.gridLayout.addWidget(self.line, 4, 0, 1, 4) self.plotWidget = QtWidgets.QWidget(Statistics) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.plotWidget.sizePolicy().hasHeightForWidth()) self.plotWidget.setSizePolicy(sizePolicy) self.plotWidget.setMinimumSize(QtCore.QSize(370, 128)) self.plotWidget.setObjectName(""plotWidget"") self.gridLayout_3 = QtWidgets.QGridLayout(self.plotWidget) self.gridLayout_3.setContentsMargins(0, 0, 0, 0) self.gridLayout_3.setObjectName(""gridLayout_3"") self.plotGridLayout = QtWidgets.QGridLayout() self.plotGridLayout.setObjectName(""plotGridLayout"") spacerItem = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.plotGridLayout.addItem(spacerItem, 0, 0, 1, 1) self.gridLayout_3.addLayout(self.plotGridLayout, 0, 1, 1, 1) self.gridLayout.addWidget(self.plotWidget, 5, 0, 1, 4) self.plotButton = QtWidgets.QPushButton(Statistics) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.plotButton.sizePolicy().hasHeightForWidth()) self.plotButton.setSizePolicy(sizePolicy) self.plotButton.setObjectName(""plotButton"") self.gridLayout.addWidget(self.plotButton, 6, 1, 1, 1) self.horizontalLayout = QtWidgets.QHBoxLayout() self.horizontalLayout.setObjectName(""horizontalLayout"") self.smoothCheckbox = QtWidgets.QCheckBox(Statistics) self.smoothCheckbox.setObjectName(""smoothCheckbox"") self.horizontalLayout.addWidget(self.smoothCheckbox) self.smoothStrideField = QtWidgets.QLineEdit(Statistics) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.smoothStrideField.sizePolicy().hasHeightForWidth()) self.smoothStrideField.setSizePolicy(sizePolicy) self.smoothStrideField.setMaximumSize(QtCore.QSize(50, 16777215)) self.smoothStrideField.setObjectName(""smoothStrideField"") self.horizontalLayout.addWidget(self.smoothStrideField) self.gridLayout.addLayout(self.horizontalLayout, 6, 2, 1, 1) self.retranslateUi(Statistics) QtCore.QMetaObject.connectSlotsByName(Statistics) def retranslateUi(self, Statistics): _translate = QtCore.QCoreApplication.translate Statistics.setWindowTitle(_translate(""Statistics"", ""Statistics"")) self.savePlotButton.setText(_translate(""Statistics"", ""Save"")) self.label_6.setText(_translate(""Statistics"", ""Mean Contact Score:"")) self.label_2.setText(_translate(""Statistics"", ""Number of Frames: "")) self.label.setText(_translate(""Statistics"", ""Total Number of Contacts: "")) self.label_5.setText(_translate(""Statistics"", ""Median Contact Score: "")) self.attributeBox.setItemText(0, _translate(""Statistics"", ""Score"")) self.attributeBox.setItemText(1, _translate(""Statistics"", ""hbond number"")) self.plotButton.setText(_translate(""Statistics"", ""Plot"")) self.smoothCheckbox.setText(_translate(""Statistics"", ""Smooth:"")) self.smoothStrideField.setText(_translate(""Statistics"", ""5"")) ","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/VMDControlPanel.py",".py","11968","311","from socket import * import subprocess from pkg_resources import resource_filename as res from PyQt5.QtWidgets import QWidget, QGridLayout, QLabel, QPushButton, QLineEdit from PyQt5 import QtCore from .Dialogues import TopoTrajLoaderDialog from ..core.Biochemistry import * # from ..cy_modules import wrap_vmd as vmd class VMDCommands: """"""Collection of useful commands to remotely control VMD."""""" @staticmethod def translateSelections(mdanalysis_text): """"""Replace segid and around to adopt the VMD syntax."""""" txt = mdanalysis_text.replace(""segid"", ""segname"") txt = txt.replace(""-"", "" to "") # around x y--> within x of y lst = txt.split("" "") idcs = [i for i, j in enumerate(lst) if j == 'around'] for idx in idcs: lst.insert(idx + 2, ""of"") txt = "" "".join(lst) txt = txt.replace(""around"", ""within"") return txt @staticmethod def gotoFrame(frame): """"""Selects and shows the given frame."""""" return ""animate goto %s"" % str(frame) @staticmethod def styleBackbone(): """"""Sets a suitable visualization style for the backbone in VMD."""""" return """""" mol addrep 0 mol modstyle top 0 NewCartoon 0.300000 10.000000 4.100000 0 mol modselect top 0 backbone mol modcolor top 0 Chain """""" @staticmethod def addSelection(sel, representations, colorID): idx = str(len(representations)) representations.append(sel) return ["""""" mol addrep top mol modstyle %s top Licorice mol modselect %s top (%s) mol modcolor %s top ColorID %d """""" % (idx, idx, sel, idx, colorID), representations] @staticmethod def addUserFieldSelection(sel, representations): idx = str(len(representations)) representations.append(sel) return ["""""" mol addrep top mol modstyle %s top QuickSurf 0.500000 0.500000 0.500000 1.000000 mol modselect %s top (%s) mol modcolor %s top User mol selupdate %s top 1 """""" % (idx, idx, sel, idx, idx), representations] @staticmethod def removeReps(index): # delrep rep_number molecule_number return """""" mol delrep %s top """""" % index @staticmethod def resetView(): return ""display resetview"" class VMDTcp: """"""Interface to VMD via tcp"""""" def __init__(self): self.commands = VMDCommands() self.rctl = res(__name__, './remote_ctl.tcl') self.HOST = 'localhost' self.PORT = 5050 self.ADDR = (self.HOST, self.PORT) self.tcpClientSocket = None def attemptConnection(self): self.tcpClientSocket = socket(AF_INET, SOCK_STREAM) self.tcpClientSocket.connect(self.ADDR) def start(self): subprocess.Popen([""vmd"", ""-e"", self.rctl]) try: self.attemptConnection() except Exception: return -1 def send_command(self, cmd): self.tcpClientSocket.send(str(cmd + ""\n"")) def stop(self): self.send_command(""quit"") self.tcpClientSocket.close() class VMDControlPanel(QWidget): """"""docstring for VMDControlPanel"""""" def __init__(self): super(QWidget, self).__init__() self.grid = QGridLayout() self.initUI() self.representations = [] self.connected = False def initUI(self): self.runningFancy = False self.fancyPrepared = False self.setLayout(self.grid) self.setWindowTitle(""VMD Control Panel"") self.resize(640, 444) self.grid.setGeometry(QtCore.QRect(10, 10, 621, 431)) self.startButton = QPushButton(""Start VMD"") self.startButton.clicked.connect(self.pushStartVMD) self.grid.addWidget(self.startButton, 0, 0) self.startButton.setEnabled(True) self.loadTopoTrajButton = QPushButton(""Load Molecules into VMD"") self.loadTopoTrajButton.clicked.connect(self.loadTopoTraj) self.grid.addWidget(self.loadTopoTrajButton, 2, 1) self.loadTopoTrajButton.setEnabled(False) self.connectButton = QPushButton(""Connect to VMD"") self.connectButton.clicked.connect(self.pushConnectVMD) self.grid.addWidget(self.connectButton, 0, 1) self.connectButton.setEnabled(False) self.infoLabel = QLabel(""No VMD session running"") self.grid.addWidget(self.infoLabel, 3, 0, 2, 2) self.stopButton = QPushButton(""Stop VMD"") self.stopButton.clicked.connect(self.pushStopVMD) self.grid.addWidget(self.stopButton, 0, 2) self.stopButton.setEnabled(False) # self.fancyVisButton = QPushButton(""Fancy"") # self.fancyVisButton.clicked.connect(self.fancy_vis) # self.grid.addWidget(self.fancyVisButton, 2, 2) # self.fancyVisButton.setEnabled(True) self.sel1 = """" self.sel2 = """" self.filteredContactList = [] # just for testing purposes # self.commandButton = QPushButton(""Send command"") # self.commandButton.clicked.connect(self.sendCommand) # self.grid.addWidget(self.commandButton, 4, 0) # self.commandButton.setEnabled(False) # self.commandField = QLineEdit() # self.grid.addWidget(self.commandField, 1, 0, 1, 2) self.vmd = VMDTcp() def addRep(self, txt): self.representations.append(txt) def prepareVMDWithTopoTraj(self, top, traj): self.vmd.send_command(""mol new %s"" % top) self.vmd.send_command(self.vmd.commands.removeReps(0)) self.vmd.send_command(""mol addfile %s waitfor all"" % traj) self.vmd.send_command(self.vmd.commands.styleBackbone()) self.vmd.send_command(self.vmd.commands.resetView()) self.vmd.send_command(self.vmd.commands.gotoFrame(0)) self.addRep(""initialBB"") def loadTopoTraj(self): topoloader = TopoTrajLoaderDialog() cfg, result = topoloader.getConfig() if result == 1: self.prepareVMDWithTopoTraj(cfg[0], cfg[1]) def gotoVMDFrame(self, frame): self.vmd.send_command(self.vmd.commands.gotoFrame(frame)) def updateSelections(self, main_sel1, main_sel2, cont_list): for s in reversed(range(1, len(self.representations) + 1)): self.vmd.send_command(self.vmd.commands.removeReps(s)) self.representations = self.representations[:1] sel1 = self.vmd.commands.translateSelections(main_sel1) + "" and ("" sel2 = self.vmd.commands.translateSelections(main_sel2) + "" and ("" for cont in cont_list: currentSel1 = [] index = 0 for item in cont.key1: if item != ""none"": currentSel1.append(AccumulationMapIndex.vmdsel[index] + "" "" + item) index += 1 currentSel1String = "" and "".join(currentSel1) sel1 += currentSel1String + "" or "" currentSel2 = [] index = 0 for item in cont.key2: if item != ""none"": currentSel2.append(AccumulationMapIndex.vmdsel[index] + "" "" + item) index += 1 currentSel2String = "" and "".join(currentSel2) sel2 += currentSel2String + "" or "" sel1 = sel1[:-3] + "")"" sel2 = sel2[:-3] + "")"" sel1command, self.representations = self.vmd.commands.addSelection(sel1, self.representations, 3) self.vmd.send_command(sel1command) sel2command, self.representations = self.vmd.commands.addSelection(sel2, self.representations, 4) self.vmd.send_command(sel2command) def updateInfoLabel(self, txt): self.infoLabel.setText(txt) def fancy_vis(self): if self.runningFancy and self.fancyPrepared: self.runningFancy = False self.vmd.send_command(""animate pause"") elif not self.fancyPrepared: self.runningFancy = True for s in reversed(range(1, len(self.representations) + 1)): self.vmd.send_command(self.vmd.commands.removeReps(s)) self.representations = self.representations[:1] for c in self.filteredContactList: sel1 = self.vmd.commands.translateSelections(self.sel1) sel2 = self.vmd.commands.translateSelections(self.sel2) currentFrame = 0 self.vmd.send_command(""animate goto 0"") currentSel1 = [] index = 0 for item in c.key1: if item != ""none"": currentSel1.append(AccumulationMapIndex.vmdsel[index] + "" "" + item) index += 1 currentSel1String = "" and "".join(currentSel1) sel1 += "" and "" + currentSel1String currentSel2 = [] index = 0 for item in c.key2: if item != ""none"": currentSel2.append(AccumulationMapIndex.vmdsel[index] + "" "" + item) index += 1 currentSel2String = "" and "".join(currentSel2) sel2 += "" and "" + currentSel2String self.vmd.send_command(""set ::remote_ctl::sel [atomselect top {(%s) or (%s)}]; $::remote_ctl::sel global"" % (sel1, sel2)) self.vmd.send_command(""$::remote_ctl::sel set beta 20"") for e in c.scoreArray: self.gotoVMDFrame(currentFrame) self.vmd.send_command(""animate goto %d"" % currentFrame) currentFrame += 1 self.vmd.send_command(""set ::remote_ctl::current [$::remote_ctl::sel get user]"") self.vmd.send_command(""$::remote_ctl::sel set user [::remote_ctl::addToList [list $::remote_ctl::current] %f]"" % e) # self.vmd.send_command(""$::remote_ctl::sel delete"") self.fancyPrepared = True sel1 = self.vmd.commands.translateSelections(self.sel1) sel2 = self.vmd.commands.translateSelections(self.sel2) s = ""noh and user > 0 and ((""+ sel1 + "") or ("" + sel2 + ""))"" sel1command, self.representations = self.vmd.commands.addUserFieldSelection(s, self.representations) self.vmd.send_command(sel1command) self.vmd.send_command(""color scale method BGR"") self.vmd.send_command(""animate forward"") else: pass def pushConnectVMD(self): try: self.vmd.attemptConnection() self.updateInfoLabel(""Connection established"") self.loadTopoTrajButton.setEnabled(True) self.connected = True except Exception: self.updateInfoLabel(""Could not connect to VMD!\nTry to connect using the Connect"" "" button\n when VMD is opened."") def pushStartVMD(self): self.startButton.setEnabled(False) self.stopButton.setEnabled(True) # self.commandButton.setEnabled(True) response = self.vmd.start() if response == -1: self.connectButton.setEnabled(True) self.updateInfoLabel(""Could not connect to VMD!\nTry to connect using the Connect button\n "" ""when VMD is opened."") else: self.loadTopoTrajButton.setEnabled(True) self.connected = True def pushStopVMD(self): self.representations = [] self.updateInfoLabel(""VMD stopped."") self.connectButton.setEnabled(False) self.startButton.setEnabled(True) self.stopButton.setEnabled(False) # self.commandButton.setEnabled(False) self.loadTopoTrajButton.setEnabled(False) self.vmd.stop() self.connected = False def sendCommand(self): self.vmd.send_command(self.commandField.text()) self.commandField.setText("""") ","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/sasa_gui.py",".py","9646","167","# -*- coding: utf-8 -*- # Form implementation generated from reading ui file 'sasa.ui' # # Created by: PyQt5 UI code generator 5.8 # # WARNING! All changes made in this file will be lost! from PyQt5 import QtCore, QtGui, QtWidgets class Ui_SasaWidget(object): def setupUi(self, SasaWidget): SasaWidget.setObjectName(""SasaWidget"") SasaWidget.resize(712, 514) self.gridLayout_2 = QtWidgets.QGridLayout(SasaWidget) self.gridLayout_2.setObjectName(""gridLayout_2"") self.gridWidget = QtWidgets.QWidget(SasaWidget) self.gridWidget.setObjectName(""gridWidget"") self.gridLayout = QtWidgets.QGridLayout(self.gridWidget) self.gridLayout.setContentsMargins(0, 0, 0, 0) self.gridLayout.setObjectName(""gridLayout"") self.gridWidget1 = QtWidgets.QWidget(self.gridWidget) self.gridWidget1.setObjectName(""gridWidget1"") self.gridLayout_3 = QtWidgets.QGridLayout(self.gridWidget1) self.gridLayout_3.setContentsMargins(0, 0, 0, 0) self.gridLayout_3.setObjectName(""gridLayout_3"") self.graphGridLayout = QtWidgets.QGridLayout() self.graphGridLayout.setObjectName(""graphGridLayout"") self.gridLayout_3.addLayout(self.graphGridLayout, 0, 0, 1, 1) self.gridLayout.addWidget(self.gridWidget1, 7, 1, 1, 2) self.sasaSelection2TextField = QtWidgets.QLineEdit(self.gridWidget) self.sasaSelection2TextField.setEnabled(True) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.sasaSelection2TextField.sizePolicy().hasHeightForWidth()) self.sasaSelection2TextField.setSizePolicy(sizePolicy) self.sasaSelection2TextField.setMinimumSize(QtCore.QSize(0, 0)) self.sasaSelection2TextField.setFocusPolicy(QtCore.Qt.StrongFocus) self.sasaSelection2TextField.setObjectName(""sasaSelection2TextField"") self.gridLayout.addWidget(self.sasaSelection2TextField, 5, 1, 1, 1) self.label_2 = QtWidgets.QLabel(self.gridWidget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_2.sizePolicy().hasHeightForWidth()) self.label_2.setSizePolicy(sizePolicy) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.label_2.setFont(font) self.label_2.setObjectName(""label_2"") self.gridLayout.addWidget(self.label_2, 4, 0, 1, 1) self.sasaSelection1TextField = QtWidgets.QLineEdit(self.gridWidget) self.sasaSelection1TextField.setObjectName(""sasaSelection1TextField"") self.gridLayout.addWidget(self.sasaSelection1TextField, 3, 1, 1, 1) spacerItem = QtWidgets.QSpacerItem(0, 40, QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Minimum) self.gridLayout.addItem(spacerItem, 5, 3, 1, 1) self.calcSasaButton = QtWidgets.QPushButton(self.gridWidget) self.calcSasaButton.setObjectName(""calcSasaButton"") self.gridLayout.addWidget(self.calcSasaButton, 8, 0, 1, 1) self.widget = QtWidgets.QWidget(self.gridWidget) self.widget.setObjectName(""widget"") self.verticalLayout = QtWidgets.QVBoxLayout(self.widget) self.verticalLayout.setContentsMargins(0, 0, 0, 0) self.verticalLayout.setObjectName(""verticalLayout"") self.loadDataButton = QtWidgets.QPushButton(self.widget) self.loadDataButton.setObjectName(""loadDataButton"") self.verticalLayout.addWidget(self.loadDataButton) self.clearDataButton = QtWidgets.QPushButton(self.widget) self.clearDataButton.setObjectName(""clearDataButton"") self.verticalLayout.addWidget(self.clearDataButton) self.savePlotButton = QtWidgets.QPushButton(self.widget) self.savePlotButton.setObjectName(""savePlotButton"") self.verticalLayout.addWidget(self.savePlotButton) self.exportDataButton = QtWidgets.QPushButton(self.widget) self.exportDataButton.setObjectName(""exportDataButton"") self.verticalLayout.addWidget(self.exportDataButton) spacerItem1 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.verticalLayout.addItem(spacerItem1) self.label_4 = QtWidgets.QLabel(self.widget) self.label_4.setAlignment(QtCore.Qt.AlignCenter) self.label_4.setObjectName(""label_4"") self.verticalLayout.addWidget(self.label_4) self.coreBox = QtWidgets.QSpinBox(self.widget) self.coreBox.setMinimum(1) self.coreBox.setMaximum(32) self.coreBox.setProperty(""value"", 4) self.coreBox.setObjectName(""coreBox"") self.verticalLayout.addWidget(self.coreBox) self.gridLayout.addWidget(self.widget, 7, 0, 1, 1) self.horizontalWidget = QtWidgets.QWidget(self.gridWidget) self.horizontalWidget.setObjectName(""horizontalWidget"") self.verticalLayout_2 = QtWidgets.QVBoxLayout(self.horizontalWidget) self.verticalLayout_2.setSizeConstraint(QtWidgets.QLayout.SetNoConstraint) self.verticalLayout_2.setContentsMargins(0, 0, 0, 0) self.verticalLayout_2.setObjectName(""verticalLayout_2"") self.sasaProgressBar = QtWidgets.QProgressBar(self.horizontalWidget) self.sasaProgressBar.setProperty(""value"", 0) self.sasaProgressBar.setTextVisible(True) self.sasaProgressBar.setInvertedAppearance(False) self.sasaProgressBar.setObjectName(""sasaProgressBar"") self.verticalLayout_2.addWidget(self.sasaProgressBar) self.gridLayout.addWidget(self.horizontalWidget, 8, 1, 1, 2) self.label = QtWidgets.QLabel(self.gridWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.label.setFont(font) self.label.setObjectName(""label"") self.gridLayout.addWidget(self.label, 3, 0, 1, 1) self.calculateContactAreaCheckbox = QtWidgets.QCheckBox(self.gridWidget) self.calculateContactAreaCheckbox.setObjectName(""calculateContactAreaCheckbox"") self.gridLayout.addWidget(self.calculateContactAreaCheckbox, 5, 2, 1, 1) self.sasaRestrictionTextField = QtWidgets.QLineEdit(self.gridWidget) self.sasaRestrictionTextField.setFocusPolicy(QtCore.Qt.StrongFocus) self.sasaRestrictionTextField.setObjectName(""sasaRestrictionTextField"") self.gridLayout.addWidget(self.sasaRestrictionTextField, 4, 1, 1, 1) spacerItem2 = QtWidgets.QSpacerItem(40, 40, QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Minimum) self.gridLayout.addItem(spacerItem2, 4, 2, 1, 1) spacerItem3 = QtWidgets.QSpacerItem(40, 40, QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Minimum) self.gridLayout.addItem(spacerItem3, 3, 2, 1, 2) self.label_3 = QtWidgets.QLabel(self.gridWidget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_3.sizePolicy().hasHeightForWidth()) self.label_3.setSizePolicy(sizePolicy) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.label_3.setFont(font) self.label_3.setObjectName(""label_3"") self.gridLayout.addWidget(self.label_3, 5, 0, 1, 1) self.line = QtWidgets.QFrame(self.gridWidget) self.line.setFrameShape(QtWidgets.QFrame.HLine) self.line.setFrameShadow(QtWidgets.QFrame.Sunken) self.line.setObjectName(""line"") self.gridLayout.addWidget(self.line, 6, 1, 1, 2) self.gridLayout_2.addWidget(self.gridWidget, 0, 0, 1, 1) self.retranslateUi(SasaWidget) QtCore.QMetaObject.connectSlotsByName(SasaWidget) SasaWidget.setTabOrder(self.sasaSelection1TextField, self.sasaRestrictionTextField) SasaWidget.setTabOrder(self.sasaRestrictionTextField, self.sasaSelection2TextField) SasaWidget.setTabOrder(self.sasaSelection2TextField, self.calculateContactAreaCheckbox) SasaWidget.setTabOrder(self.calculateContactAreaCheckbox, self.coreBox) SasaWidget.setTabOrder(self.coreBox, self.loadDataButton) SasaWidget.setTabOrder(self.loadDataButton, self.savePlotButton) SasaWidget.setTabOrder(self.savePlotButton, self.exportDataButton) SasaWidget.setTabOrder(self.exportDataButton, self.calcSasaButton) def retranslateUi(self, SasaWidget): _translate = QtCore.QCoreApplication.translate SasaWidget.setWindowTitle(_translate(""SasaWidget"", ""Surface Areas"")) self.label_2.setText(_translate(""SasaWidget"", ""Restriction:"")) self.calcSasaButton.setText(_translate(""SasaWidget"", ""Calculate"")) self.loadDataButton.setText(_translate(""SasaWidget"", ""Load Data"")) self.clearDataButton.setText(_translate(""SasaWidget"", ""Clear Data"")) self.savePlotButton.setText(_translate(""SasaWidget"", ""Save Plot"")) self.exportDataButton.setText(_translate(""SasaWidget"", ""Export Data"")) self.label_4.setText(_translate(""SasaWidget"", ""Cores:"")) self.label.setText(_translate(""SasaWidget"", ""Selection:"")) self.calculateContactAreaCheckbox.setText(_translate(""SasaWidget"", ""contact"")) self.label_3.setText(_translate(""SasaWidget"", ""Selection 2:"")) ","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/HelpButton.py",".py","727","25","from PyQt5.QtWidgets import QAbstractButton from PyQt5.QtGui import QPixmap, QImage, QPainter class PicButton(QAbstractButton): def __init__(self, pixmap, parent=None): super(PicButton, self).__init__(parent) self.pixmap = pixmap self.setMaximumWidth(30) self.setMaximumHeight(30) def paintEvent(self, event): painter = QPainter(self) painter.drawPixmap(event.rect(), self.pixmap) def sizeHint(self): return self.pixmap.size() class HelpButton(PicButton): def __init__(self, parent=None): helpImage = QImage(""/home/max/help.png"") helpPixmap = QPixmap.fromImage(helpImage) super(HelpButton, self).__init__(helpPixmap, parent) ","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/ErrorMessages.py",".py","718","18","class ErrorMessages(): """"""Error message shortcuts for the ErrorBox dialog."""""" NOEXPDATA = ""No data to export."" NODATA_PROMPTLOAD = ""No data loaded. Click on \""Files -> Import Trajectory Data\"" and load your MD trajectory."" NOSCORES_PROMPTANALYSIS = ""No data loaded. Click on \""Files -> Import Trajectory Data\"" "" \ ""and load your MD trajectory."" CHOOSEFILE = ""Please choose a topology and trajectory file!"" RESID_REQUIRED = ""Please analyze the trajectory with the resid box checked for both atom selections!"" NOCONTACTS = ""No data loaded or no filtered contacts available."" FILE_NOT_FOUND = ""Attempt to load trajectory failed. File does not exist."" ","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/Canvas.py",".py","8606","246","from PyQt5.QtGui import (QColor, QPainter, QFont, QPixmap) from PyQt5.QtWidgets import QWidget from PyQt5.QtCore import QSize from PyQt5.QtCore import pyqtSignal, QObject import numpy as np import math from ..core.ContactFilters import * from .LabelView import LabelView class ColorScheme: """"""Enum the color scheme, either custom or backbone-sidechain type."""""" custom, bbsc = range(2) class Canvas(QWidget, QObject): """"""Canvas where contact analysis results are drawn."""""" clickedRowSignal = pyqtSignal() clickedColumnSignal = pyqtSignal() def __init__(self): super(QWidget, self).__init__() self.clickedRow = 0 self.clickedColumn = 0 self.rendered = False self.contacts = 0 self.sizeX = 0 self.sizeY = 0 self.rendered = False self.pixmap = 0 self.merge = 1 self.labelView = LabelView([]) self.alphaFactor = 50 self.contacts = [] self.range = [0, 0] self.rangeFilterActive = False self.showHbondScores = False self.vismode = False self.timeLineXOrigin = 0 self.clickedRow = -1 self.clickedColumn = -1 self.offset = -1 self.globalClickedRow = -1 self.timeLineXOrigin = 0 self.rowh = 1 self.endOfTimeLine = 0 def mousePressEvent(self, event): pos = event.pos() x, y = pos.x(), pos.y() self.clickedRow = -1 if self.vismode and self.timeLineXOrigin < x < self.endOfTimeLine: self.clickedRow = int(y / self.rowh - 1) # -1 because of frame number line self.clickedColumn = int((x - self.timeLineXOrigin) / self.offset) # print(""clickedRow: "" + str(self.clickedRow)) self.rendered = False self.clickedRowSignal.emit() self.repaint() self.update() def mouseReleaseEvent(self, event): pass def mouseMoveEvent(self, event): # print(event.pos()) pos = event.pos() x, y = pos.x(), pos.y() self.clickedColumn = -1 if self.vismode and self.timeLineXOrigin < x < self.endOfTimeLine: self.clickedColumn = int((x - self.timeLineXOrigin) / self.offset) # print(""clicked on frame %d"",self.clickedColumn) self.clickedColumnSignal.emit() def switchToVisMode(self, vismode): """"""Visualize contacts directly in VMD by selecting a specific row."""""" self.vismode = vismode # self.labelView.vismode = vismode def paintEvent(self, event): qp = QPainter() qp.begin(self) # render pixmap to resolve performance issues if self.rendered: self.drawRenderedContact(qp) elif self.rendered is False and self.contacts: self.renderContact(False) self.rendered = True self.setMinimumSize(QSize(self.sizeX, self.sizeY)) qp.end() def renderContact(self, generator): """"""Render the contact with the defined colors."""""" # startx = 90 # orig_startx = startx start_text = 10 rowheight = 22 textoffset = 12 blackColor = QColor(0, 0, 0) whiteColor = QColor(255, 255, 255) merge = self.merge offset = 10 self.labelView.clean() self.labelView = LabelView(self.contacts) self.labelView.setParent(self) self.labelView.nsPerFrame = self.nsPerFrame self.labelView.threshold = self.threshold self.labelView.show() # startx has to be set according to maximum button length in labelview startx = np.max(self.labelView.buttonWidths) + 15 orig_startx = startx # probably included in next version... # if self.vismode: # textoffset += 15 # start_text += 15 # startx += 15 # orig_startx += 15 # print(orig_startx) self.timeLineXOrigin = orig_startx self.rowh = rowheight # self.sizeX = (len(self.contacts[0].scoreArray) + startx) * offset # self.sizeY = len(self.contacts) * rowheight if self.rangeFilterActive: self.sizeX = startx + (len(self.contacts[0].scoreArray) + merge * 2) * offset / merge else: self.sizeX = startx + (len(self.contacts[0].scoreArray[self.range[0]:self.range[1]]) + merge * 2) \ * offset / merge # add one row for frame numbers self.sizeY = (len(self.contacts)+1) * rowheight self.sizeX = int(self.sizeX) self.sizeY = int(self.sizeY) self.pixmap = QPixmap(QSize(self.sizeX, self.sizeY)) p = QPainter() if generator: p.begin(generator) else: p.begin(self.pixmap) p.fillRect(0, 0, self.sizeX, self.sizeY, whiteColor) row = 0 rownumber = 0 # print(""merge value"", merge) for c in self.contacts: self.alphaFactor = 50 bbScColor = BackboneSidechainContactType.colors[c.determineBackboneSidechainType()] i = 0 if not self.showHbondScores: if self.rangeFilterActive: rangedScores = c.scoreArray else: rangedScores = c.scoreArray[self.range[0]:self.range[1]] else: hbarray = c.hbondFramesScan() self.alphaFactor = 100 if self.rangeFilterActive: rangedScores = hbarray else: rangedScores = hbarray[self.range[0]:self.range[1]] if rownumber == 0: # show the frame numbers on top p.setFont(QFont('Arial', 8)) p.drawText(start_text, row + textoffset + 2, ""Frame:"") off = 0 if self.range[0] != 0: off = 1 for l in range(self.range[0] + off, self.range[1] + 1, 10)[off:]: if l == 0: continue # print(l) # TODO: sometimes errors occur! p.drawText(startx + (l - 1 - self.range[0]) * offset, row + textoffset + 2, str(l * merge)) self.labelView.move(0, rowheight) row += rowheight while i < len(rangedScores): p.setPen(blackColor) merged_score = 0 for j in range(merge): if (i + j) >= len(rangedScores): break x = rangedScores[i + j] merged_score += x merged_score /= merge alpha = int(merged_score * self.alphaFactor) if alpha > 255: alpha = 255 if math.isnan(alpha): alpha = 255 if self.colorScheme == ColorScheme.bbsc: # pass p.setBrush(QColor(bbScColor[0], bbScColor[1], bbScColor[2], alpha)) elif self.colorScheme == ColorScheme.custom: color = QColor(self.customColor) color.setAlpha(alpha) p.setBrush(color) if rownumber == self.clickedRow: p.setPen(QColor(250, 50, 50)) else: p.setPen(QColor(0, 0, 0)) p.drawRect(startx, row, offset, 20) startx += offset i += merge self.offset = offset self.endOfTimeLine = startx startx = orig_startx row += rowheight rownumber += 1 if generator: row = rowheight for c in self.contacts: p.setPen(0) # print(ContactType.colors[c.contactType]) p.setFont(QFont('Arial', 9)) # string = c.resA + c.residA + ""-"" + c.resB + c.residB string = c.title p.setBrush(ContactType.qcolors[c.determine_ctype()]) p.drawRect(0, row+3, orig_startx, rowheight-10) p.setPen(1) p.drawText(start_text, row + textoffset, string) row += rowheight p.end() self.globalClickedRow = self.clickedRow self.clickedRow = -1 def drawRenderedContact(self, qp): """"""Draws the rendered contact to the canvas."""""" qp.drawPixmap(0, 0, self.sizeX, self.sizeY, self.pixmap) ","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/Statistics.py",".py","2958","72","import sip import os from PyQt5.QtWidgets import QWidget, QFileDialog from PyQt5.QtGui import QIntValidator from .Plotters import ContactPlotter from .statistics_ui import * from ..core.LogPool import * from .ErrorBox import ErrorBox from ..core.Biochemistry import mean_score_of_contactArray, median_score_of_contactArray class Statistics(QWidget, Ui_Statistics): def __init__(self, data, nspf, parent=None): super(QWidget, self).__init__(parent) self.setupUi(self) self.contacts = data self.nsPerFrame = nspf self.labelNumFrames.setText(str(len(self.contacts[0].scoreArray))) self.labelTotalContacts.setText(str(len(self.contacts))) self.labelMeanScore.setText(str(mean_score_of_contactArray(self.contacts))) self.labelMedianScore.setText(str(median_score_of_contactArray(self.contacts))) self.savePlotButton.clicked.connect(self.savePlot) self.plotButton.clicked.connect(self.plotAttribute) posIntValidator = QIntValidator() posIntValidator.setBottom(3) self.smoothStrideField.setValidator(posIntValidator) self.contactPlotter = ContactPlotter(None, width=4, height=2, dpi=70) self.contactPlotter.plot_all_contacts_figure(self.contacts, 0, self.nsPerFrame) self.plotGridLayout.addWidget(self.contactPlotter) def plotAttribute(self): """"""Plots the selected attribute."""""" sip.delete(self.contactPlotter) self.contactPlotter = ContactPlotter(None, width=4, height=2, dpi=70) smoothOn = self.smoothCheckbox.isChecked() smooth = 0 limit = 5 if smoothOn: smooth = int(self.smoothStrideField.text()) if smooth < limit: smooth = limit if smooth % 2 == 0: smooth += 1 self.smoothStrideField.setText(str(smooth)) if self.attributeBox.currentText() == ""Score"": self.contactPlotter.plot_all_contacts_figure(self.contacts, smooth, self.nsPerFrame) elif self.attributeBox.currentText() == ""hbond number"": self.contactPlotter.plot_hbondNumber(self.contacts, smooth, self.nsPerFrame) self.plotGridLayout.addWidget(self.contactPlotter) def savePlot(self): """"""Saves the current plot."""""" fileName = QFileDialog.getSaveFileName(self, 'Save Path') if fileName == """": return path, file_extension = os.path.splitext(fileName[0]) if file_extension == """": file_extension = ""png"" else: file_extension = file_extension[1:] try: self.contactPlotter.saveFigure(path, file_extension) except ValueError: box = ErrorBox(""File format "" + file_extension + "" is not supported.\nPlease choose from eps, pdf, pgf,"" "" png, ps, raw, rgba, svg, svgz. "") box.exec_() ","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/Plotters.py",".py","15606","388","from PyQt5.QtWidgets import QSizePolicy, QApplication import numpy as np from math import factorial from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg \ as FigureCanvas from matplotlib.figure import Figure from matplotlib import cm from matplotlib import animation as ani import matplotlib import seaborn as sns from ..core.ContactFilters import * from ..core.Biochemistry import AccumulationMapIndex from matplotlib import pyplot as plt plt.style.use('ggplot') font = {'family' : 'normal', 'weight' : 'normal', 'size' : 14} matplotlib.rc('font', **font) sns.set() sns.set_context(""talk"") class MplPlotter(FigureCanvas): """"""Ultimately, this is a QWidget (as well as a FigureCanvasAgg, etc.)."""""" def __init__(self, parent=None, width=5, height=4, dpi=100): self.fig = Figure(figsize=(width, height), dpi=dpi) self.axes = self.fig.add_subplot(111) # We want the axes cleared every time plot() is called # self.axes.hold(False) self.compute_initial_figure() FigureCanvas.__init__(self, self.fig) self.setParent(parent) FigureCanvas.setSizePolicy(self, QSizePolicy.Expanding, QSizePolicy.Expanding) FigureCanvas.updateGeometry(self) def compute_initial_figure(self): pass class ContactPlotter(MplPlotter): """"""Plots a frame-score plot with lines."""""" def plot_contact_figure(self, contact, nsPerFrame): frames = np.arange(0, len(contact.scoreArray), 1) * nsPerFrame self.axes.plot(frames, contact.scoreArray) self.axes.set_xlabel(""time [ns]"") self.axes.set_ylabel(""score"") def plot_all_contacts_figure(self, contacts, smooth, nsPerFrame): values = [] for frame in range(len(contacts[0].scoreArray)): current = 0 for c in contacts: current += c.scoreArray[frame] values.append(current) frames = np.arange(0, len(values), 1) * nsPerFrame if smooth: val = self.savitzky_golay(np.array(values), smooth, 2) smaller = np.where(val < 0) val[smaller] = 0 self.axes.plot(val) else: self.axes.plot(values) self.axes.set_xlabel(""time [ns]"") self.axes.set_ylabel(""score"") def plot_hbondNumber(self, contacts, smooth, nsPerFrame): values = [] for c in contacts: c.hbondFramesScan() for frame in range(len(contacts[0].scoreArray)): current = 0 for c in contacts: current += c.hbondFrames[frame] values.append(current) frames = np.arange(0, len(values), 1) * nsPerFrame if smooth: val = self.savitzky_golay(np.array(values), smooth, 2) smaller = np.where(val < 0) val[smaller] = 0 self.axes.plot(frames, val) else: self.axes.plot(frames, values) self.axes.set_xlabel(""time [ns]"") self.axes.set_ylabel(""hbond number"") # from http://scipy.github.io/old-wiki/pages/Cookbook/SavitzkyGolay def savitzky_golay(self, y, window_size, order, deriv=0, rate=1): try: window_size = np.abs(np.int(window_size)) order = np.abs(np.int(order)) except ValueError: raise ValueError(""window_size and order have to be of type int"") if window_size % 2 != 1 or window_size < 1: raise TypeError(""window_size size must be a positive odd number"") if window_size < order + 2: raise TypeError(""window_size is too small for the polynomials order"") order_range = range(order+1) half_window = (window_size -1) // 2 # precompute coefficients b = np.mat([[k**i for i in order_range] for k in range(-half_window, half_window+1)]) m = np.linalg.pinv(b).A[deriv] * rate**deriv * factorial(deriv) # pad the signal at the extremes with # values taken from the signal itself firstvals = y[0] - np.abs( y[1:half_window+1][::-1] - y[0] ) lastvals = y[-1] + np.abs(y[-half_window-1:-1][::-1] - y[-1]) y = np.concatenate((firstvals, y, lastvals)) return np.convolve( m[::-1], y, mode='valid') def saveFigure(self, path, outputFormat): self.fig.savefig(path + ""."" + outputFormat, format=outputFormat) class ContactPlotParameters: """"""Parameter for the contact plotter."""""" mean, median, lifetime, median_life_time, hbond_percentage = range(5) mapping = [""Mean Score"", ""Median Score"", ""Mean Lifetime"", ""Median Lifetime"", ""Hbond percentage""] class HistPlotter(MplPlotter): """"""Simple canvas with an histogram plot."""""" def plotGeneralHist(self, currentContacts, attribute, threshold, nsPerFrame): values = [] if attribute == ""Mean Score"": for c in currentContacts: values.append(c.mean_score()) elif attribute == ""Median Score"": for c in currentContacts: values.append(c.median_score()) elif attribute == ""Mean Lifetime"": for c in currentContacts: values.append(c.mean_life_time(nsPerFrame, threshold)) elif attribute == ""Median Lifetime"": for c in currentContacts: values.append(c.median_life_time(nsPerFrame, threshold)) valuesNp = np.array(values, dtype=float) self.axes.hist(valuesNp, bins=20) self.axes.set_ylabel(""N"") self.axes.set_xlabel(attribute + "" bins"") self.fig.subplots_adjust(bottom=0.2, top=0.95, left=0.15, right=0.85) def plotContactHist(self, currentContacts, attribute, threshold, nsPerFrame, xticksfontsize): values = [] titles = [] if attribute == ""Mean Score"": for c in currentContacts: values.append(c.mean_score()) titles.append(c.title) elif attribute == ""Median Score"": for c in currentContacts: values.append(c.median_score()) titles.append(c.title) elif attribute == ""Mean Lifetime"": for c in currentContacts: values.append(c.mean_life_time(nsPerFrame, threshold)) titles.append(c.title) elif attribute == ""Median Lifetime"": for c in currentContacts: values.append(c.median_life_time(nsPerFrame, threshold)) titles.append(c.title) elif attribute == ""Hbond percentage"": for c in currentContacts: values.append(c.hbond_percentage()) titles.append(c.title) valuesNp = np.array(values, dtype=float) titlesNp = np.array(titles, dtype=str) x = range(len(currentContacts)) # h = self.axes.bar(x, valuesNp, color=""red"") h = self.axes.bar(x, valuesNp) xticks_pos = [0.7071 * patch.get_width() + patch.get_xy()[0] for patch in h] self.axes.set_xticklabels(titlesNp, ha='right', size=8, rotation=45) self.axes.set_xticks(xticks_pos) for tick in self.axes.xaxis.get_major_ticks(): tick.label.set_fontsize(xticksfontsize) self.axes.set_ylabel(attribute) self.fig.subplots_adjust(bottom=0.2, top=0.95, left=0.1, right=0.9) def saveFigure(self, path, outputFormat): self.fig.savefig(path + ""."" + outputFormat, format=outputFormat) class MapPlotter(MplPlotter): """"""Simple canvas with an 2d heatmap plot."""""" def plotMap(self, contacts, map1, map2, label1, label2, attribute, threshold, nsPerFrame): minmaxresids1 = [] minmaxresids2 = [] if not map1[AccumulationMapIndex.resid] or not map2[AccumulationMapIndex.resid]: return -1 for cont in contacts: minmaxresids1.append(int(cont.key1[AccumulationMapIndex.resid])) minmaxresids2.append(int(cont.key2[AccumulationMapIndex.resid])) x = np.arange(np.min(minmaxresids1), np.max(minmaxresids1)+1) y = np.arange(np.min(minmaxresids2), np.max(minmaxresids2)+1) minx = np.min(minmaxresids1) miny = np.min(minmaxresids2) data = np.zeros((len(y), len(x))) if attribute == ""Mean Score"": for c in contacts: r1 = int(c.key1[AccumulationMapIndex.resid])-minx r2 = int(c.key2[AccumulationMapIndex.resid])-miny data[r2, r1] = c.mean_score() elif attribute == ""Median Score"": for c in contacts: r1 = int(c.key1[AccumulationMapIndex.resid])-minx r2 = int(c.key2[AccumulationMapIndex.resid])-miny data[r2, r1] = c.median_score() elif attribute == ""Mean Lifetime"": for c in contacts: r1 = int(c.key1[AccumulationMapIndex.resid])-minx r2 = int(c.key2[AccumulationMapIndex.resid])-miny data[r2, r1] = c.mean_life_time(nsPerFrame, threshold) elif attribute == ""Median Lifetime"": for c in contacts: r1 = int(c.key1[AccumulationMapIndex.resid])-minx r2 = int(c.key2[AccumulationMapIndex.resid])-miny data[r2, r1] = c.median_life_time(nsPerFrame, threshold) elif attribute == ""Hbond percentage"": for c in contacts: r1 = int(c.key1[AccumulationMapIndex.resid])-minx r2 = int(c.key2[AccumulationMapIndex.resid])-miny data[r2, r1] = c.hbond_percentage() # cax = self.axes.matshow(data, cmap=cm.Greys, label=attribute) cax = self.axes.matshow(data, label=attribute, cmap=""YlGnBu"") # TODO: do this automatically stridex = 5 stridey = 5 self.axes.set_xticks(np.arange(0, x.size, stridex)) self.axes.set_xticklabels(np.arange(minx, x.size+minx, stridex)) # self.axes.set_title(""Contact Map"") self.axes.set_xlabel(label1) self.axes.set_ylabel(label2) self.axes.set_yticks(np.arange(0, y.size, stridey)) self.axes.set_yticklabels(np.arange(miny, y.size+miny, stridey)) cb = self.fig.colorbar(cax) cb.set_label(attribute) self.fig.tight_layout() def saveFigure(self, path, outputFormat): self.fig.savefig(path + ""."" + outputFormat, format=outputFormat) class SimplePlotter(MplPlotter): """"""Simple plotter, used in the SASA view."""""" def plot(self, x, y): self.axes.plot(x, y) self.axes.set_xlabel(""x"") self.axes.set_ylabel(""f(x)"") # self.axes.xaxis.set_label_position('top') def saveFigure(self, path, outputFormat): self.fig.savefig(path + ""."" + outputFormat, format=outputFormat) def clearFigure(self): self.fig.clf() class AnimateMapPlotter(MplPlotter): """"""Animated canvas with an 2d heatmap plot."""""" def plotMap(self, contacts, map1, map2, label1, label2, attribute, threshold, nsPerFrame): self.contacts = contacts self.map1 = map1 self.map2 = map2 self.label1 = label1 self.label2 = label2 self.attribute = attribute self.threshold = threshold self.nsPerFrame = nsPerFrame self.minmaxresids1 = [] self.minmaxresids2 = [] if not self.map1[AccumulationMapIndex.resid] or not self.map2[AccumulationMapIndex.resid]: return -1 for cont in self.contacts: self.minmaxresids1.append(int(cont.key1[AccumulationMapIndex.resid])) self.minmaxresids2.append(int(cont.key2[AccumulationMapIndex.resid])) self.x = np.arange(np.min(self.minmaxresids1), np.max(self.minmaxresids1) + 1) self.y = np.arange(np.min(self.minmaxresids2), np.max(self.minmaxresids2) + 1) self.minx = np.min(self.minmaxresids1) self.miny = np.min(self.minmaxresids2) rng = np.arange(len(contacts[0].scoreArray)) self.cax = None self.ttl = self.axes.set_title(""Map"") # TODO: do this automatically stridex = 5 stridey = 5 self.axes.set_xticks(np.arange(0, self.x.size, stridex)) self.axes.set_xticklabels(np.arange(self.minx, self.x.size + self.minx, stridex)) self.axes.set_xlabel(self.label1) self.axes.set_ylabel(self.label2) self.axes.set_yticks(np.arange(0, self.y.size, stridey)) self.axes.set_yticklabels(np.arange(self.miny, self.y.size + self.miny, stridey)) self.fig.tight_layout() self.cb = None animation = ani.FuncAnimation(self.fig, self.updateMap, rng, init_func=self.initFig, interval=200, blit=True, repeat=False) # animation = ani.FuncAnimation(self.fig, self.updateMap, 50, interval=200, blit=True) QApplication.processEvents() self.show() # writer = ani.writers['ffmpeg'](fps=30) # animation.save('demo.mp4',writer=writer,dpi=100) def initFig(self): data = np.zeros((len(self.y), len(self.x))) frame = 0 attribute = ""Mean Score"" if attribute == ""Mean Score"": for c in self.contacts: r1 = int(c.key1[AccumulationMapIndex.resid]) - self.minx r2 = int(c.key2[AccumulationMapIndex.resid]) - self.miny data[r2, r1] = c.scoreArray[frame] self.cax = self.axes.matshow(data, cmap=cm.Greys, label=self.attribute) self.ttl.set_text(""Frame 0"") if self.cb is None: self.cb = self.fig.colorbar(self.cax) self.cb.set_label(self.attribute) # mp_slider_ax = self.fig.add_axes([1, 1, 0.65, 0.03]) # sfreq = Slider(mp_slider_ax, 'Freq', 0.1, 30.0, valinit=10) self.draw() return self.cax, def updateMap(self, frame): data = np.zeros((len(self.y), len(self.x))) attribute = ""Mean Score"" if attribute == ""Mean Score"": for c in self.contacts: r1 = int(c.key1[AccumulationMapIndex.resid]) - self.minx r2 = int(c.key2[AccumulationMapIndex.resid]) - self.miny data[r2, r1] = c.scoreArray[frame] self.cax.set_data(data) # update the data self.ttl.set_text(""Frame "" + str(frame)) # elif attribute == ""Median Score"": # for c in contacts: # r1 = int(c.key1[AccumulationMapIndex.resid])-minx # r2 = int(c.key2[AccumulationMapIndex.resid])-miny # data[r2, r1] = c.median_score() # elif attribute == ""Mean Lifetime"": # for c in contacts: # r1 = int(c.key1[AccumulationMapIndex.resid])-minx # r2 = int(c.key2[AccumulationMapIndex.resid])-miny # data[r2, r1] = c.mean_life_time(nsPerFrame, threshold) # elif attribute == ""Median Lifetime"": # for c in contacts: # r1 = int(c.key1[AccumulationMapIndex.resid])-minx # r2 = int(c.key2[AccumulationMapIndex.resid])-miny # data[r2, r1] = c.median_life_time(nsPerFrame, threshold) # elif attribute == ""Hbond percentage"": # for c in contacts: # r1 = int(c.key1[AccumulationMapIndex.resid])-minx # r2 = int(c.key2[AccumulationMapIndex.resid])-miny # data[r2, r1] = c.hbond_percentage() self.draw() return self.cax, def saveFigure(self, path, outputFormat): self.fig.savefig(path + ""."" + outputFormat, format=outputFormat) ","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/detail_ui.py",".py","8145","170","# -*- coding: utf-8 -*- # Form implementation generated from reading ui file 'detail.ui' # # Created by: PyQt5 UI code generator 5.8.2 # # WARNING! All changes made in this file will be lost! from PyQt5 import QtCore, QtGui, QtWidgets class Ui_Detail(object): def setupUi(self, Detail): Detail.setObjectName(""Detail"") Detail.setWindowModality(QtCore.Qt.WindowModal) Detail.resize(788, 672) self.gridLayout = QtWidgets.QGridLayout(Detail) self.gridLayout.setObjectName(""gridLayout"") self.labelBackboneSidechainA = QtWidgets.QLabel(Detail) self.labelBackboneSidechainA.setText("""") self.labelBackboneSidechainA.setObjectName(""labelBackboneSidechainA"") self.gridLayout.addWidget(self.labelBackboneSidechainA, 3, 1, 1, 1) self.labelMedianLifetime = QtWidgets.QLabel(Detail) self.labelMedianLifetime.setText("""") self.labelMedianLifetime.setObjectName(""labelMedianLifetime"") self.gridLayout.addWidget(self.labelMedianLifetime, 3, 3, 1, 1) self.plotWidget = QtWidgets.QWidget(Detail) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.plotWidget.sizePolicy().hasHeightForWidth()) self.plotWidget.setSizePolicy(sizePolicy) self.plotWidget.setMinimumSize(QtCore.QSize(370, 128)) self.plotWidget.setObjectName(""plotWidget"") self.gridLayout_3 = QtWidgets.QGridLayout(self.plotWidget) self.gridLayout_3.setContentsMargins(0, 0, 0, 0) self.gridLayout_3.setObjectName(""gridLayout_3"") self.plotGridLayout = QtWidgets.QGridLayout() self.plotGridLayout.setObjectName(""plotGridLayout"") spacerItem = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.plotGridLayout.addItem(spacerItem, 0, 0, 1, 1) self.gridLayout_3.addLayout(self.plotGridLayout, 0, 1, 1, 1) self.gridLayout.addWidget(self.plotWidget, 6, 0, 1, 4) self.line = QtWidgets.QFrame(Detail) self.line.setFrameShape(QtWidgets.QFrame.HLine) self.line.setFrameShadow(QtWidgets.QFrame.Sunken) self.line.setObjectName(""line"") self.gridLayout.addWidget(self.line, 5, 0, 1, 4) self.labelMeanScore = QtWidgets.QLabel(Detail) self.labelMeanScore.setText("""") self.labelMeanScore.setObjectName(""labelMeanScore"") self.gridLayout.addWidget(self.labelMeanScore, 2, 3, 1, 1) self.labelThreshold = QtWidgets.QLabel(Detail) font = QtGui.QFont() font.setBold(False) font.setWeight(50) self.labelThreshold.setFont(font) self.labelThreshold.setText("""") self.labelThreshold.setObjectName(""labelThreshold"") self.gridLayout.addWidget(self.labelThreshold, 2, 1, 1, 1) self.label_5 = QtWidgets.QLabel(Detail) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.label_5.setFont(font) self.label_5.setObjectName(""label_5"") self.gridLayout.addWidget(self.label_5, 0, 2, 1, 1) self.labelMedianScore = QtWidgets.QLabel(Detail) self.labelMedianScore.setText("""") self.labelMedianScore.setObjectName(""labelMedianScore"") self.gridLayout.addWidget(self.labelMedianScore, 0, 3, 1, 1) self.label = QtWidgets.QLabel(Detail) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.label.setFont(font) self.label.setObjectName(""label"") self.gridLayout.addWidget(self.label, 2, 0, 1, 1) self.labelTotalTime = QtWidgets.QLabel(Detail) font = QtGui.QFont() font.setBold(False) font.setWeight(50) self.labelTotalTime.setFont(font) self.labelTotalTime.setText("""") self.labelTotalTime.setObjectName(""labelTotalTime"") self.gridLayout.addWidget(self.labelTotalTime, 0, 1, 1, 1) self.savePlotButton = QtWidgets.QPushButton(Detail) self.savePlotButton.setObjectName(""savePlotButton"") self.gridLayout.addWidget(self.savePlotButton, 7, 3, 1, 1) self.label_6 = QtWidgets.QLabel(Detail) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.label_6.setFont(font) self.label_6.setObjectName(""label_6"") self.gridLayout.addWidget(self.label_6, 2, 2, 1, 1) self.attributeBox = QtWidgets.QComboBox(Detail) self.attributeBox.setObjectName(""attributeBox"") self.attributeBox.addItem("""") self.gridLayout.addWidget(self.attributeBox, 7, 0, 1, 1) self.plotButton = QtWidgets.QPushButton(Detail) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.plotButton.sizePolicy().hasHeightForWidth()) self.plotButton.setSizePolicy(sizePolicy) self.plotButton.setObjectName(""plotButton"") self.gridLayout.addWidget(self.plotButton, 7, 1, 1, 1) self.label_2 = QtWidgets.QLabel(Detail) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.label_2.setFont(font) self.label_2.setObjectName(""label_2"") self.gridLayout.addWidget(self.label_2, 0, 0, 1, 1) self.label_4 = QtWidgets.QLabel(Detail) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.label_4.setFont(font) self.label_4.setObjectName(""label_4"") self.gridLayout.addWidget(self.label_4, 3, 0, 1, 1) self.label_3 = QtWidgets.QLabel(Detail) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.label_3.setFont(font) self.label_3.setObjectName(""label_3"") self.gridLayout.addWidget(self.label_3, 3, 2, 1, 1) self.label_9 = QtWidgets.QLabel(Detail) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.label_9.setFont(font) self.label_9.setObjectName(""label_9"") self.gridLayout.addWidget(self.label_9, 4, 0, 1, 1) self.labelBackboneSidechainB = QtWidgets.QLabel(Detail) self.labelBackboneSidechainB.setText("""") self.labelBackboneSidechainB.setObjectName(""labelBackboneSidechainB"") self.gridLayout.addWidget(self.labelBackboneSidechainB, 4, 1, 1, 1) self.label_11 = QtWidgets.QLabel(Detail) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.label_11.setFont(font) self.label_11.setObjectName(""label_11"") self.gridLayout.addWidget(self.label_11, 4, 2, 1, 1) self.labelMeanLifetime = QtWidgets.QLabel(Detail) self.labelMeanLifetime.setText("""") self.labelMeanLifetime.setObjectName(""labelMeanLifetime"") self.gridLayout.addWidget(self.labelMeanLifetime, 4, 3, 1, 1) self.retranslateUi(Detail) QtCore.QMetaObject.connectSlotsByName(Detail) def retranslateUi(self, Detail): _translate = QtCore.QCoreApplication.translate Detail.setWindowTitle(_translate(""Detail"", ""Statistics"")) self.label_5.setText(_translate(""Detail"", ""Median Contact Score: "")) self.label.setText(_translate(""Detail"", ""Current Threshold:"")) self.savePlotButton.setText(_translate(""Detail"", ""Save"")) self.label_6.setText(_translate(""Detail"", ""Mean Contact Score:"")) self.attributeBox.setItemText(0, _translate(""Detail"", ""Score"")) self.plotButton.setText(_translate(""Detail"", ""Plot"")) self.label_2.setText(_translate(""Detail"", ""Total Time [ns]:"")) self.label_4.setText(_translate(""Detail"", ""bb/sc score (A):"")) self.label_3.setText(_translate(""Detail"", ""Median Lifetime:"")) self.label_9.setText(_translate(""Detail"", ""bb/sc score (B):"")) self.label_11.setText(_translate(""Detail"", ""Mean Lifetime:"")) ","Python" "Biophysics","maxscheurer/pycontact","PyContact/gui/ErrorBox.py",".py","410","13","from PyQt5.QtWidgets import QMessageBox class ErrorBox(QMessageBox): """"""Creates an Error dialog which displays the corresponding error message 'msg'."""""" def __init__(self, msg): super(ErrorBox, self).__init__() self.msg = msg self.setIcon(QMessageBox.Warning) self.setText(self.msg) self.setWindowTitle(""Error"") self.setStandardButtons(QMessageBox.Ok) ","Python" "Biophysics","maxscheurer/pycontact","PyContact/core/DataHandler.py",".py","1221","29","import pickle class DataHandler: """"""Handles the import or export of a session."""""" @staticmethod def importSessionFromFile(fileName): """"""Imports a saved session from 'filename'."""""" importDict = pickle.load(open(fileName, ""rb"")) contacts = importDict[""contacts""] arguments = importDict[""analyzer""][0:-1] trajArgs = importDict[""trajectory""] maps = importDict[""maps""] contactResults = importDict[""analyzer""][-1] del importDict return [contacts, arguments, trajArgs, maps, contactResults] @staticmethod def writeSessionToFile(fileName, analysis): """"""Saves the current Session (analysis) at 'filename'."""""" analyzerArgs = [analysis.psf, analysis.dcd, analysis.cutoff, analysis.hbondcutoff, analysis.hbondcutangle, analysis.sel1text, analysis.sel2text, analysis.contactResults] trajArgs = analysis.getTrajectoryData() exportDict = {""contacts"": analysis.finalAccumulatedContacts, ""analyzer"": analyzerArgs, ""trajectory"": trajArgs, ""maps"": [analysis.lastMap1, analysis.lastMap2]} pickle.dump(exportDict, open(fileName, ""wb"")) ","Python" "Biophysics","maxscheurer/pycontact","PyContact/core/ContactFilters.py",".py","10307","288","from .Biochemistry import * class Operator(object): """"""Defines a comparison operator for contact filtering."""""" greater, smaller, equal, nequal = range(4) mapping = {u""greater"": greater, u""smaller"": smaller, u""equal"": equal, u""not equal"": nequal} def compare(self, value1, value2, operator): if operator == self.greater: return value1 > value2 elif operator == self.smaller: return value1 < value2 elif operator == self.equal: return value1 == value2 elif operator == self.nequal: return value1 != value2 class FrameFilter(object): """"""Filters contact with a given frame range."""""" def __init__(self, name): self.name = name @staticmethod def extractFrameRange(contacts, frameRange): lower = frameRange[0] upper = frameRange[1] for c in contacts: newScores = c.scoreArray[lower:upper] newAtoms = c.contributingAtoms[lower:upper] c.contributingAtoms = newAtoms c.scoreArray = newScores return contacts class NameFilter(object): """"""Filters contacts by name."""""" def __init__(self, name): self.name = name @staticmethod def filterContactsByName(contacts, nameA, nameB, mapindex): """"""Returns contacts, when their key is included in nameA and nameB."""""" filtered = [] for c in contacts: add = False # TODO: probably replace with if/else try: prop1 = c.key1[mapindex] prop2 = c.key2[mapindex] except IndexError: filtered.append(c) continue if nameA.lower() != u'all' and nameB.lower() != u'all': splitA = nameA.split(u"","") splitB = nameB.split(u"","") if prop1 in splitA and prop2 in splitB: add = True elif nameA.lower() != u'all' and nameB.lower() == u'all': splitA = nameA.split(u"","") if prop1 in splitA: add = True elif nameA.lower() == u'all' and nameB.lower() != u'all': splitB = nameB.split(u"","") if prop2 in splitB: add = True else: add = True if add: filtered.append(c) return filtered class RangeFilter(object): """"""Filters contacts with a given range."""""" def __init__(self, name): self.name = name @staticmethod def numberInRanges(number, ranges): result = False for r in ranges: if number in r: result = True return result def filterByRange(self, contacts, residRangeA, residRangeB, mapindex): """"""Returns contacts that lie in residRangeA and residRangeB."""""" splitA = residRangeA.split(u"","") splitB = residRangeB.split(u"","") notAllA = residRangeA.lower() != u'all' notAllB = residRangeB.lower() != u'all' if notAllA: aRanges = [] for ran in splitA: r = ran.split(u""-"") if len(r) == 1: aRanges.append(range(int(r[0]), int(r[0])+1)) else: aRanges.append(range(int(r[0]), int(r[1]) + 1)) if notAllB: bRanges = [] for ran in splitB: r = ran.split(u""-"") print(r) if len(r) == 1: bRanges.append(range(int(r[0]), int(r[0])+1)) else: bRanges.append(range(int(r[0]), int(r[1]) + 1)) filtered = [] for c in contacts: # TODO: probably replace with if/else try: prop1 = int(c.key1[mapindex]) prop2 = int(c.key2[mapindex]) except ValueError: filtered.append(c) continue add = False if notAllA and notAllB: if self.numberInRanges(prop1, aRanges) and self.numberInRanges(prop2, bRanges): add = True elif notAllA and not notAllB: if self.numberInRanges(prop1, aRanges): add = True elif not notAllA and notAllB: if self.numberInRanges(prop2, bRanges): add = True else: add = True if add: filtered.append(c) return filtered class BinaryFilter(object): """"""Implements a binary filter with a given operator."""""" def __init__(self, name, operator, value): self.name = name self.operator = Operator.mapping[operator] self.value = value def filterContacts(self, contacts): pass class OnlyFilter(object): """"""Implements a filter, that only selects contacts with specific properties, e.g.: hydrophobic."""""" def __init__(self, name, operator, value): self.name = name self.operator = operator self.value = value def filterContacts(self, contacts): filtered = [] if self.operator == ""hbonds"": for c in contacts: hb = c.hbondFramesScan() for bla in hb: if bla > 0: filtered.append(c) break elif self.operator == ""hydrophobic"": for c in contacts: if c.determine_ctype() == ContactType.hydrophobic: filtered.append(c) elif self.operator == ""saltbridges"": for c in contacts: if c.determine_ctype() == ContactType.saltbr: filtered.append(c) elif self.operator == ""other"": for c in contacts: if c.determine_ctype() == ContactType.other: filtered.append(c) return filtered class TotalTimeFilter(BinaryFilter): """"""Binary filter concerning the total contact time."""""" def __init__(self, name, operator, value): super(TotalTimeFilter, self).__init__(name, operator, value) def filterContacts(self, contacts): filtered = [] op = Operator() for c in contacts: if op.compare(c.total_time(1, 0), self.value, self.operator): filtered.append(c) print(unicode(len(filtered))) return filtered class ScoreFilter(BinaryFilter): """"""Compares contact score of every frame, only adds contact if true for all frames."""""" def __init__(self, name, operator, value, ftype): super(ScoreFilter, self).__init__(name, operator, value) self.ftype = ftype def filterContacts(self, contacts): filtered = [] op = Operator() if self.ftype == u""Mean"": for c in contacts: mean = c.mean_score() if op.compare(mean, self.value, self.operator): filtered.append(c) elif self.ftype == u""Median"": for c in contacts: med = c.median_score() if op.compare(med, self.value, self.operator): filtered.append(c) elif self.ftype == u""HB %"": for c in contacts: med = c.hbond_percentage() print(med) if op.compare(med, self.value, self.operator): filtered.append(c) return filtered class SortingOrder(object): """"""Defines the sorting order, ascending or descending."""""" ascending, descending = range(2) mapping = {u""asc."": ascending, u""desc."": descending} class Sorting(object): """"""Performs the sorting with respect to a specific key, e.g. mean lifetime."""""" def __init__(self, name, key, descending): self.name = name self. key = key self.descending = descending self.threshold = 0 self.nspf = 0 def setThresholdAndNsPerFrame(self, threshold, nspf): self.threshold = threshold self.nspf = nspf def sortContacts(self, contacts): sortedContacts = [] if self.key == u""mean"": sortedContacts = sorted(contacts, key=lambda c: c.meanScore, reverse=self.descending) elif self.key == u""median"": sortedContacts = sorted(contacts, key=lambda c: c.medianScore, reverse=self.descending) elif self.key == u""bb/sc type"": sortedContacts = sorted(contacts, key=lambda c: c.backboneSideChainType, reverse=self.descending) elif self.key == u""contact type"": sortedContacts = sorted(contacts, key=lambda c: c.contactType, reverse=self.descending) elif self.key == u""resid 1"": try: prop1 = contacts[0].key1[AccumulationMapIndex.resid] if prop1 != ""none"": sortedContacts = sorted(contacts, key=lambda c: int(c.key1[AccumulationMapIndex.resid]), reverse=self.descending) else: sortedContacts = contacts except IndexError: pass elif self.key == u""resid 2"": try: prop2 = contacts[0].key2[AccumulationMapIndex.resid] if prop2 != ""none"": sortedContacts = sorted(contacts, key=lambda c: int(c.key2[AccumulationMapIndex.resid]), reverse=self.descending) else: sortedContacts = contacts except IndexError: pass elif self.key == u""total time"": for con in contacts: con.total_time(self.nspf, self.threshold) sortedContacts = sorted(contacts, key=lambda c: c.ttime, reverse=self.descending) elif self.key == u""mean lifetime"": for con in contacts: con.mean_life_time(self.nspf, self.threshold) sortedContacts = sorted(contacts, key=lambda c: c.meanLifeTime, reverse=self.descending) elif self.key == u""median lifetime"": for con in contacts: con.median_life_time(self.nspf, self.threshold) sortedContacts = sorted(contacts, key=lambda c: c.medianLifeTime, reverse=self.descending) return sortedContacts ","Python" "Biophysics","maxscheurer/pycontact","PyContact/core/ContactAnalyzer.py",".py","30065","614","import re import time from .multi_trajectory import run_load_parallel from .LogPool import * from copy import deepcopy import MDAnalysis import numpy as np from PyQt5.QtCore import pyqtSignal, QObject # TODO: fix aroundPatch with gridsearch in C code using cython from .Biochemistry import (AccumulatedContact, AtomContact, AccumulationMapIndex, HydrogenBond, TempContactAccumulate, HydrogenBondAtoms) from ..cy_modules.cy_gridsearch import cy_find_contacts # MDAnalysis.core.flags['use_periodic_selections'] = False # MDAnalysis.core.flags['use_KDTree_routines'] = True class Analyzer(QObject): """"""Performs a contact search and analyzes the results."""""" frameUpdate = pyqtSignal(float) def __init__(self, psf, dcd, cutoff, hbondcutoff, hbondcutangle, sel1text, sel2text): super(Analyzer, self).__init__() self.psf = psf self.dcd = dcd self.cutoff = cutoff self.hbondcutoff = hbondcutoff self.hbondcutangle = hbondcutangle self.sel1text = sel1text self.sel2text = sel2text self.lastMap1 = [] self.lastMap2 = [] self.contactResults = [] self.contactResults = [] self.resname_array = [] self.resid_array = [] self.name_array = [] self.segids = [] self.backbone = [] self.finalAccumulatedContacts = [] self.bonds = [] self.totalFrameNumber = 0 self.currentFrameNumber = 0 self.analysis_state = False self.totalFramesToProcess = 1 def runFrameScan(self, nproc): """"""Performs a contact search using nproc threads."""""" try: if nproc == 1: self.contactResults = self.analyze_psf_dcd_grid(self.psf, self.dcd, self.cutoff, self.hbondcutoff, self.hbondcutangle, self.sel1text, self.sel2text) # old: original version but slower # self.contactResults = self.analyze_psf_dcd(self.psf, self.dcd, self.cutoff, self.hbondcutoff, # self.hbondcutangle, self.sel1text, self.sel2text) else: self.contactResults, self.resname_array, self.resid_array, self.name_array, self.segids, \ self.backbone = run_load_parallel(nproc, self.psf, self.dcd, self.cutoff, self.hbondcutoff, self.hbondcutangle, self.sel1text, self.sel2text) except: raise Exception def runContactAnalysis(self, map1, map2, nproc): """"""Performs a contadt analysis using nproc threads."""""" self.finalAccumulatedContacts = self.analyze_contactResultsWithMaps(self.contactResults, map1, map2) self.lastMap1 = map1 self.lastMap2 = map2 return deepcopy(self.finalAccumulatedContacts) def setTrajectoryData( self, resname_array, resid_array, name_array, segids, backbone, sel1text, sel2text): self.resname_array = resname_array self.resid_array = resid_array self.name_array = name_array self.segids = segids self.backbone = backbone self.sel1text = sel1text self.sel2text = sel2text def getTrajectoryData(self): return [self.resname_array, self.resid_array, self.name_array, self.segids, self.backbone, self.sel1text, self.sel2text] def getFilePaths(self): return self.psf, self.dcd # find a string in s between the strings first and last @staticmethod def find_between(s, first, last): try: start = s.index(first) + len(first) end = s.index(last, start) return s[start:end] except ValueError: return """" @staticmethod def weight_function(value): """"""weight function to score contact distances"""""" return 1.0 / (1.0 + np.exp(5.0 * (value - 4.0))) def makeKeyArraysFromMaps(self, map1, map2, contact): """"""Creates key Arrays from the chosen accumulation maps. maps contain information whether to consider an atom's property for contact accumulation map1 and map2 contain 5 boolean values each, cf. AccumulationMapIndex for a given contact, the corresponding value to a property is written to keys1 and keys2, respectively example input: map1 = [0,0,1,1,0] map2 = [0,0,1,1,0], meaning that residue and resname should be used for contact accumulation contact: idx1,idx2 results: (example!) keys1=[""none"",""none"",""none"",""14"", ""VAL"", ""none""] keys2=[""none"",""none"",""none"",""22"", ""ILE, ""none""] """""" idx1 = contact.idx1 idx2 = contact.idx2 counter = 0 keys1 = [] for val in map1: if val == 1: if counter == AccumulationMapIndex.index: keys1.append(idx1) elif counter == AccumulationMapIndex.name: keys1.append(self.name_array[idx1]) elif counter == AccumulationMapIndex.resid: keys1.append(self.resid_array[idx1]) elif counter == AccumulationMapIndex.resname: keys1.append(self.resname_array[idx1]) elif counter == AccumulationMapIndex.segid: keys1.append(self.segids[idx1]) else: keys1.append(""none"") counter += 1 counter = 0 keys2 = [] for val in map2: if val == 1: if counter == AccumulationMapIndex.index: keys2.append(idx2) elif counter == AccumulationMapIndex.name: keys2.append(self.name_array[idx2]) elif counter == AccumulationMapIndex.resid: keys2.append(self.resid_array[idx2]) elif counter == AccumulationMapIndex.resname: keys2.append(self.resname_array[idx2]) elif counter == AccumulationMapIndex.segid: keys2.append(self.segids[idx2]) else: keys2.append(""none"") counter += 1 return [keys1, keys2] def makeKeyArraysFromKey(self, key): """"""Converts a key to two key arrays. ""inverse"" function of makeKeyFromKeyArrays """""" keystring1, keystring2 = key.split(""-"") mapping = AccumulationMapIndex.mapping maximal = len(mapping) key1 = [] for i in range(0, maximal): current = mapping[i] if current not in keystring1: key1.append(""none"") continue if i == (maximal - 1): key1.append(keystring1[keystring1.index(current) + len(current):]) break nextCurrent = mapping[i + 1] if nextCurrent not in keystring1: nxt = """" for k in mapping[i + 1:]: if k in keystring1[keystring1.index(current) + len(current):]: nxt = k break if nxt != """": key1.append(keystring1[keystring1.index(current) + len(current):keystring1.index(nxt)]) else: key1.append(keystring1[keystring1.index(current) + len(current):]) continue else: currentValue = self.find_between(keystring1, current, nextCurrent) if currentValue == """": key1.append(""none"") else: key1.append(currentValue) key2 = [] for i in range(0, maximal): current = mapping[i] if current not in keystring2: key2.append(""none"") continue if i == (maximal - 1): key2.append(keystring2[keystring2.index(current) + len(current):]) break nextCurrent = mapping[i + 1] if nextCurrent not in keystring2: nxt = """" for k in mapping[i + 1:]: if k in keystring2[keystring2.index(current) + len(current):]: nxt = k break if nxt != """": key2.append(keystring2[keystring2.index(current) + len(current):keystring2.index(nxt)]) else: key2.append(keystring2[keystring2.index(current) + len(current):]) continue else: currentValue = self.find_between(keystring2, current, nextCurrent) if currentValue == """": key2.append(""none"") else: key2.append(currentValue) return [key1, key2] @staticmethod def make_single_title(key): """"""returns the title of the AccumulatedContact to be displayed in contact's label"""""" titleDict = {} counter = 0 for item in key: titleDict[AccumulationMapIndex.mapping[counter]] = (item if item != ""none"" else """") counter += 1 residueString = ""%s%s"" % (titleDict[AccumulationMapIndex.mapping[AccumulationMapIndex.resname]], str(titleDict[AccumulationMapIndex.mapping[AccumulationMapIndex.resid]])) atomIndexString = (""%s %s"" % (AccumulationMapIndex.mapping[AccumulationMapIndex.index], str(titleDict[AccumulationMapIndex.mapping[AccumulationMapIndex.index]])) if titleDict[AccumulationMapIndex.mapping[AccumulationMapIndex.index]] != """" else """") atomNameString = (""%s %s"" % (AccumulationMapIndex.mapping[AccumulationMapIndex.name], str(titleDict[AccumulationMapIndex.mapping[AccumulationMapIndex.name]])) if titleDict[AccumulationMapIndex.mapping[AccumulationMapIndex.name]] != """" else """") segnameString = (""%s %s"" % (AccumulationMapIndex.mapping[AccumulationMapIndex.segid], str(titleDict[AccumulationMapIndex.mapping[AccumulationMapIndex.segid]])) if titleDict[AccumulationMapIndex.mapping[AccumulationMapIndex.segid]] != """" else """") tempList = [residueString, atomIndexString, atomNameString, segnameString] finishedList = [] for string in tempList: if string != """": finishedList.append(string) finishedString = "", "".join(finishedList) return finishedString @staticmethod def makeKeyFromKeyArrays(key1, key2): """"""Returns a human readable key from two key arrays. example: keys1=[""none"",""none"",""14"", ""VAL"", ""none""] keys2=[""none"",""none"",""22"", ""ILE"", ""none""] returns a human readable key with the mapping identifiers in AccumulationMapIndex in the given example data: key=""r.14rn.VAL-r.22rn.ILE"" key is used to accumulated contacts in a dictionary (= a contact's unique identifier) """""" key = """" itemcounter = 0 for item in key1: if item != ""none"": key += AccumulationMapIndex.mapping[itemcounter] + str(item) itemcounter += 1 key += ""-"" itemcounter = 0 for item in key2: if item != ""none"": key += AccumulationMapIndex.mapping[itemcounter] + str(item) itemcounter += 1 return key # newer version, uses gridsearch to find contacts, much faster and less memory-intense def analyze_psf_dcd_grid(self, psf, dcd, cutoff, hbondcutoff, hbondcutangle, sel1text, sel2text): """"""Reading topology/trajectory and assessing hbonds"""""" # load psf and dcd file in memory u = MDAnalysis.Universe(psf, dcd) # TODO: think about doing u.select_atoms(sel1text + "" or "" + sel2text) all_sel = u.select_atoms(""all"") # all_sel = u.select_atoms(""%s or %s or name H.*"" % (sel1text, sel2text)) backbone_sel = u.select_atoms(""backbone"") self.resname_array = [] self.resid_array = [] self.name_array = [] self.segids = [] self.backbone = [] for atom in all_sel.atoms: self.resname_array.append(atom.resname) self.resid_array.append(atom.resid) self.name_array.append(atom.name) self.bonds.append(atom.bonds) self.segids.append(atom.segid) for atom in backbone_sel: self.backbone.append(atom.index) selfInteraction = False if sel2text == ""self"": sel1 = u.select_atoms(sel1text) sel2 = u.select_atoms(sel1text) selfInteraction = True else: sel1 = u.select_atoms(sel1text) sel2 = u.select_atoms(sel2text) if (len(sel1.atoms) == 0 or len(sel2.atoms) == 0): raise Exception contactResults = [] # loop over trajectory self.totalFrameNumber = len(u.trajectory) start = time.time() for ts in u.trajectory: # define selections according to sel1text and sel2text if ""around"" in sel1text: sel1 = u.select_atoms(sel1text) if ""around"" in sel2text: sel2 = u.select_atoms(sel2text) # write atomindices for each selection to list indices1 = [] for at in sel1.atoms: indices1.append(at.index) indices2 = [] for at in sel2.atoms: indices2.append(at.index) currentFrameContacts = [] frame = ts.frame self.currentFrameNumber = ts.frame # pass positions and distance to cython natoms1 = len(sel1.atoms) natoms2 = len(sel2.atoms) pos1 = np.array(np.reshape(sel1.positions, (1, natoms1 * 3)), dtype=np.float64) pos2 = np.array(np.reshape(sel2.positions, (1, natoms2 * 3)), dtype=np.float64) xyz1 = np.array(pos1, dtype=np.float32) xyz2 = np.array(pos2, dtype=np.float32) # 2d array with index of atom1 being the index of the first dimension # individual lists contain atom2 indices nbList1 = cy_find_contacts(xyz1, natoms1, xyz2, natoms2, cutoff) # we only need the 1st list # nbList1 = res[:natoms1] # nbList2 = res[natoms1:] idx1 = 0 for atom1sNeighbors in nbList1: for idx2 in atom1sNeighbors: convindex1 = indices1[idx1] # idx1 converted to global atom indexing convindex2 = indices2[idx2] # idx2 converted to global atom indexing # jump out of loop if hydrogen contacts are found, only contacts between heavy atoms are considered, # hydrogen bonds can still be detected! if re.match(""H(.*)"", self.name_array[convindex1]) or re.match(""H(.*)"", self.name_array[convindex2]): continue # distance between atom1 and atom2 # check if residues are more than 4 apart, and in the same segment if selfInteraction: if (self.resid_array[convindex1] - self.resid_array[convindex2]) < 5 and self.segids[convindex1] == self.segids[convindex2]: continue # distance = distarray[idx1, idx2] # weight = self.weight_function(distance) dvec = pos1[0][3*idx1:3*idx1+3] - pos2[0][3*idx2:3*idx2+3] distance = np.sqrt(dvec.dot(dvec)) # print(dvec, distance, dvec.dtype) # if (distance - distarray[idx1, idx2]) > 0.001: # print(""Error in distance calculations!"") # return # # print(convindex1, convindex2, distance, distarray[idx1, idx2]) # if (distance > cutoff): # print(""Distances must be smaller/equal cutoff!"") # return weight = self.weight_function(distance) # HydrogenBondAlgorithm hydrogenBonds = [] # FF independent hydrogen bonds if (self.name_array[convindex1][0] in HydrogenBondAtoms.atoms and self.name_array[convindex2][0] in HydrogenBondAtoms.atoms): # print(""hbond? %s - %s"" % (type_array[convindex1], type_array[convindex2])) # search for hatom, check numbering in bond!!!!!!!!!! b1 = self.bonds[convindex1] b2 = self.bonds[convindex2] # b1 = all_sel[convindex1].bonds # b2 = all_sel[convindex2].bonds # search for hydrogen atoms bound to atom 1 bondcount1 = 0 hydrogenAtomsBoundToAtom1 = [] # new code for bnd in b1: b = bnd.type hydrogen = next((x for x in b if x.startswith(""H"")), 0) # print(b) if hydrogen != 0: # print(""h bond to atom1"") bondindices1 = b1.to_indices()[bondcount1] # print bondindices1 # for j in bondindices1: # print(self.type_array[j+1]) hydrogenidx = next( (j for j in bondindices1 if self.name_array[j].startswith(""H"")), -1) if hydrogenidx != -1: # print(self.type_array[hydrogenidx]) hydrogenAtomsBoundToAtom1.append(hydrogenidx) bondcount1 += 1 # search for hydrogen atoms bound to atom 2 bondcount2 = 0 hydrogenAtomsBoundToAtom2 = [] # print(b2) for bnd2 in b2: b = bnd2.type hydrogen = next((x for x in b if x.startswith(""H"")), 0) # print(b) if hydrogen != 0: # print(""h bond to atom2"") bondindices2 = b2.to_indices()[bondcount2] hydrogenidx = next( (k for k in bondindices2 if self.name_array[k].startswith(""H"")), -1) if hydrogenidx != -1: # print(type_array[hydrogenidx]) hydrogenAtomsBoundToAtom2.append(hydrogenidx) bondcount2 += 1 # check hbond criteria for hydrogen atoms bound to first atom for global_hatom in hydrogenAtomsBoundToAtom1: conv_hatom = indices1.index(global_hatom) # print(typeHeavy) # # TODO: FF independent version # if (typeHeavy == AtomHBondType.acc or typeHeavy == AtomHBondType.both) and (distarray[conv_hatom, idx2] <= hbondcutoff): # dist = distarray[conv_hatom, idx2] # dist = np.linalg.norm(sel1.positions[conv_hatom] - sel2.positions[idx2]) dist = np.linalg.norm(pos1[0][3*conv_hatom:3*conv_hatom+3] - pos2[0][3*idx2:3*idx2+3]) if (dist <= hbondcutoff): donorPosition = sel1.positions[idx1] hydrogenPosition = np.array(sel1.positions[conv_hatom], dtype=np.float64) acceptorPosition = np.array(sel2.positions[idx2], dtype=np.float64) v1 = hydrogenPosition - acceptorPosition v2 = hydrogenPosition - donorPosition v1norm = np.linalg.norm(v1) v2norm = np.linalg.norm(v2) dot = np.dot(v1, v2) angle = np.degrees(np.arccos(dot / (v1norm * v2norm))) # print(angle) if angle >= hbondcutangle: # print(""new hbond"") new_hbond = HydrogenBond(convindex1, convindex2, global_hatom, dist, angle, hbondcutoff, hbondcutangle) hydrogenBonds.append(new_hbond) # print(str(convindex1) + "" "" + str(convindex2) # print(""hbond found: %d,%d,%d""%(convindex1,global_hatom,convindex2)) # print(angle) for global_hatom in hydrogenAtomsBoundToAtom2: conv_hatom = indices2.index(global_hatom) # TODO: FF independent version # if (typeHeavy == AtomHBondType.acc or typeHeavy == AtomHBondType.both) and (distarray[idx1, conv_hatom] <= hbondcutoff): # FIXME: WTF? # if (distarray[conv_hatom, idx2] <= hbondcutoff): # dist = distarray[idx1, conv_hatom] # dist = np.linalg.norm(sel1.positions[idx1] - sel2.positions[conv_hatom]) dist = np.linalg.norm(pos1[0][3*idx1:3*idx1+3] - pos2[0][3*conv_hatom:3*conv_hatom+3]) if (dist <= hbondcutoff): donorPosition = sel2.positions[idx2] hydrogenPosition = np.array(sel2.positions[conv_hatom], dtype=np.float64) acceptorPosition = np.array(sel1.positions[idx1], dtype=np.float64) v1 = hydrogenPosition - acceptorPosition v2 = hydrogenPosition - donorPosition v1norm = np.linalg.norm(v1) v2norm = np.linalg.norm(v2) dot = np.dot(v1, v2) angle = np.degrees(np.arccos(dot / (v1norm * v2norm))) if angle >= hbondcutangle: new_hbond = HydrogenBond(convindex2, convindex1, global_hatom, dist, angle, hbondcutoff, hbondcutangle) hydrogenBonds.append(new_hbond) # print str(convindex1) + "" "" + str(convindex2) # print ""hbond found: %d,%d,%d""%(convindex2,global_hatom,convindex1) # print angle # finalize newAtomContact = AtomContact(int(frame), float(distance), float(weight), int(convindex1), int(convindex2), hydrogenBonds) currentFrameContacts.append(newAtomContact) idx1 += 1 contactResults.append(currentFrameContacts) # pickle.dump(contactResults, open(""single_results_experimental.dat"", ""w"")) # for f in contactResults: # print(""experiment"", len(f)) stop = time.time() print(""grid:"",stop-start) return contactResults def analyze_contactResultsWithMaps(self, contactResults, map1, map2): """"""Analyzes contactsResults with the given maps."""""" ################################################# # contactResults evaluation # only depending on map1, map2 # part can be run without running the contact analysis algorithm again, # as it just prepares the results for displaying ################################################# # Data structure to process: # contactResults (list of frames) # ---> frame (list of AtomContacts) # --------> AtomContact frame_contacts_accumulated = [] # frame_contacts_accumulated (list of frames) # ---> frame_dict (dict) # --------> key vs. TempContactAccumulate # list of all contacts keys (= unique identifiers, determined by the given maps) start = time.time() allkeys = [] total = len(contactResults) counter = 1 for frame in contactResults: currentFrameAcc = {} for cont in frame: key1, key2 = self.makeKeyArraysFromMaps(map1, map2, cont) key = self.makeKeyFromKeyArrays(key1, key2) if key in currentFrameAcc: currentFrameAcc[key].fscore += cont.weight currentFrameAcc[key].contributingAtomContacts.append(cont) if cont.idx1 in self.backbone: currentFrameAcc[key].bb1score += cont.weight else: currentFrameAcc[key].sc1score += cont.weight if cont.idx2 in self.backbone: currentFrameAcc[key].bb2score += cont.weight else: currentFrameAcc[key].sc2score += cont.weight else: currentFrameAcc[key] = TempContactAccumulate(key1, key2) currentFrameAcc[key].fscore += cont.weight currentFrameAcc[key].contributingAtomContacts.append(cont) if cont.idx1 in self.backbone: currentFrameAcc[key].bb1score += cont.weight else: currentFrameAcc[key].sc1score += cont.weight if cont.idx2 in self.backbone: currentFrameAcc[key].bb2score += cont.weight else: currentFrameAcc[key].sc2score += cont.weight if key not in allkeys: allkeys.append(key) frame_contacts_accumulated.append(currentFrameAcc) self.frameUpdate.emit(float(counter) / float(total)) counter += 1 accumulatedContactsDict = {} stop = time.time() # print(stop - start) # accumulatedContactsDict (dict) # ---> key vs. list of TempContactAccumulated # # loop fills gaps with zero-score TempContactAccumulate of key if key is not occuring in a frame # provides clean data! start = time.time() for key in allkeys: accumulatedContactsDict[key] = [] for frame_dict in frame_contacts_accumulated: if key not in frame_dict: # puts empty score TempContactAccumulate in dict key1, key2 = self.makeKeyArraysFromKey(key) emptyCont = TempContactAccumulate(key1, key2) emptyCont.fscore = 0 frame_dict[key] = emptyCont accumulatedContactsDict[key].append(frame_dict[key]) # make a list of AccumulatedContacts from accumulatedContactsDict # probably, there is a much easier way to do that, but I am too tired at the moment and it works (M) finalAccumulatedContacts = [] # list of AccumulatedContacts for key in accumulatedContactsDict: key1, key2 = self.makeKeyArraysFromKey(key) acc = AccumulatedContact(key1, key2) for tempContact in accumulatedContactsDict[key]: acc.addScore(tempContact.fscore) acc.addContributingAtoms(tempContact.contributingAtomContacts) acc.bb1 += tempContact.bb1score acc.bb2 += tempContact.bb2score acc.sc1 += tempContact.sc1score acc.sc2 += tempContact.sc2score finalAccumulatedContacts.append(acc) # print(key, acc.bb1, acc.bb2, acc.sc1, acc.sc2) # print(len(acc.scoreArray)) stop = time.time() # print(stop - start) return finalAccumulatedContacts def analysisEventListener(self): """"""Event listener for the progress bar in MainWindow."""""" while self.analysis_state: progress = 0 for each in analysisProgressDict.keys(): progress += analysisProgressDict[each] progress = float(progress) / float(self.totalFramesToProcess) if progress > 0: self.frameUpdate.emit(progress) if progress == 1.0: for each in analysisProgressDict.keys(): analysisProgressDict[each] = 0 progress = 0 self.analysis_state = False ","Python" "Biophysics","maxscheurer/pycontact","PyContact/core/LoadConfiguration.py",".py","430","12","class Configuration(object): """"""Sets the current configuration."""""" def __init__(self, psf, dcd, cutoff, hbondcutoff, hbondcutangle, sel1text, sel2text): super(Configuration, self).__init__() self.psf = psf self.dcd = dcd self.cutoff = cutoff self.hbondcutoff = hbondcutoff self.hbondcutangle = hbondcutangle self.sel1text = sel1text self.sel2text = sel2text ","Python" "Biophysics","maxscheurer/pycontact","PyContact/core/Biochemistry.py",".py","16233","389","import collections import numpy as np from ..db.DbReader import read_residue_db compare = lambda x, y: collections.Counter(x) == collections.Counter(y) # NOTE: needed for sasa calculation, we should add more... # CHARMM radii, from VMD vdwRadii = {""H"": 1.0, ""C"": 1.5, ""N"": 1.399999976158142, ""O"": 1.2999999523162842, ""F"": 1.47, ""Mg"": 1.73, ""P"": 1.8, ""S"": 1.899999976158142} def vdwRadius(atomType): """"""Returns the van der Waals-radius matching the given atom type. Default value is 1.5 A."""""" return vdwRadii.get(atomType, 1.5) class AtomHBondType: """"""Defines the type of Atom concerning its hbond behaviour"""""" don, acc, both, none = range(4) mapping = {""don"": don, ""acc"": acc, ""both"": both, ""none"": none} class HydrogenBondAtoms: atoms = [""O"", ""N"", ""S""] class AtomType: """"""Represents MASS entry for atoms in CHARMM topology and parameter files."""""" def __init__(self, name, comment, htype): self.name = name # name = atomtype in CHARMM file self.comment = comment # properties/infos according to CHARMM file self.htype = htype # AtomHBondType of AtomType, parsed from extra comment in CHARMM file @staticmethod def parseParameterFileString(string): """"""Reads charmm parameter/topology file to determine AtomTypes and their AtomHBondType."""""" spl = string.split(""!"") name = spl[0].split()[2] comment = spl[1][1:] try: htype = spl[2] except IndexError: htype = ""none"" tp = AtomType(name, comment, AtomHBondType.mapping[htype]) return tp # contains all information of a contact, mapped by key1/key2 class AccumulatedContact(object): """"""Contains information about a contact accumulated from AtomContact to display in GUI"""""" def __init__(self, key1, key2): super(AccumulatedContact, self).__init__() self.scoreArray = [] # score for every frame, summed by settings given in key1,key2 self.contributingAtoms = [] # list of list of AtomContacts, contributing to the contact self.key1 = key1 # list of properties of sel1, cf. AccumulationMapIndex self.key2 = key2 # list of properties of sel2, cf. AccumulationMapIndex # TODO: human readable implementation of key/title # self.title = makeKeyFromKeyArrays(key1, key2) self.title = self.human_readable_title() self.bb1 = 0 self.sc1 = 0 self.bb2 = 0 self.sc2 = 0 self.atom1contactsBy = [] self.atom2contactsBy = [] self.backboneSideChainType = [] self.hbondFrames = [] self.ttime = 0 self.meanLifeTime = 0 self.medianLifeTime = 0 self.meanScore = 0 self.medianScore = 0 self.contactType = 0 def getScoreArray(self): return self.scoreArray def human_readable_title(self): """"""returns the title of the AccumulatedContact to be displayed in contact's label"""""" total = [] for key in [self.key1, self.key2]: titleDict = {} counter = 0 for item in key: titleDict[AccumulationMapIndex.mapping[counter]] = (item if item != ""none"" else """") counter += 1 residueString = ""%s%s"" % (titleDict[AccumulationMapIndex.mapping[AccumulationMapIndex.resname]], str(titleDict[AccumulationMapIndex.mapping[AccumulationMapIndex.resid]])) atomIndexString = (""%s %s"" % (AccumulationMapIndex.mapping[AccumulationMapIndex.index], str(titleDict[AccumulationMapIndex.mapping[AccumulationMapIndex.index]])) if titleDict[AccumulationMapIndex.mapping[AccumulationMapIndex.index]] != """" else """") atomNameString = (""%s %s"" % (AccumulationMapIndex.mapping[AccumulationMapIndex.name], str(titleDict[AccumulationMapIndex.mapping[AccumulationMapIndex.name]])) if titleDict[AccumulationMapIndex.mapping[AccumulationMapIndex.name]] != """" else """") segnameString = (""%s %s"" % (AccumulationMapIndex.mapping[AccumulationMapIndex.segid], str(titleDict[AccumulationMapIndex.mapping[AccumulationMapIndex.segid]])) if titleDict[AccumulationMapIndex.mapping[AccumulationMapIndex.segid]] != """" else """") tempList = [residueString, atomIndexString, atomNameString, segnameString] finishedList = [] for string in tempList: if string != """": finishedList.append(string) finishedString = "" , "".join(finishedList) total.append(finishedString) return "" - "".join(total) def addScore(self, newScore): """"""Appends a score to the scoreArray, e.g. when a new frame score is added."""""" self.scoreArray.append(newScore) def determineBackboneSidechainType(self): """"""Returns the Backbone-Sidechain type."""""" if self.bb1 > self.sc1: self.atom1contactsBy = BackboneSidechainType.contactsBb else: self.atom1contactsBy = BackboneSidechainType.contactsSc if self.bb2 > self.sc2: self.atom2contactsBy = BackboneSidechainType.contactsBb else: self.atom2contactsBy = BackboneSidechainType.contactsSc if self.atom1contactsBy == BackboneSidechainType.contactsBb \ and self.atom2contactsBy == BackboneSidechainType.contactsBb: self.backboneSideChainType = BackboneSidechainContactType.bb_only elif self.atom1contactsBy == BackboneSidechainType.contactsSc \ and self.atom2contactsBy == BackboneSidechainType.contactsSc: self.backboneSideChainType = BackboneSidechainContactType.sc_only else: self.backboneSideChainType = BackboneSidechainContactType.both return self.backboneSideChainType def addContributingAtoms(self, contAtoms): """"""append a list of contributing atom to the contributingAtoms list, e.g. when a new frame is added"""""" self.contributingAtoms.append(contAtoms) # used for temporary accumulation of contacts in data analysis def setScores(self): self.mean_score() self.median_score() def hbond_percentage(self): """"""Computes the hbond percentage of all contacts, using the scoreArray."""""" self.hbondFramesScan() fnumber = len(self.scoreArray) counter = 0 for element in self.hbondFrames: if element > 0: counter += 1 return float(counter)/float(fnumber) * 100 def total_time(self, ns_per_frame, threshold): """"""Returns the total time, the contact score is above the given threshold value."""""" time = 0 for score in self.scoreArray: if score > threshold: time += ns_per_frame self.ttime = time return self.ttime def mean_life_time(self, ns_per_frame, threshold): """"""Returns the mean life time, with the given threshold value."""""" self.meanLifeTime = np.mean(self.life_time(ns_per_frame, threshold)) return self.meanLifeTime def median_life_time(self, ns_per_frame, threshold): """"""Returns the mean life time, with the given threshold value."""""" self.medianLifeTime = np.median(self.life_time(ns_per_frame, threshold)) return self.medianLifeTime def mean_score(self): """"""Returns the mean score of the scoreArray."""""" mean = 0 for score in self.scoreArray: mean += score mean /= len(self.scoreArray) self.meanScore = mean return mean def median_score(self): """"""Returns the median score of the scoreArray."""""" med = np.median(self.scoreArray) self.medianScore = med return med def life_time(self, ns_per_frame, threshold): """"""Computes the life time of a contact in ns, with the given threshold."""""" lifeTimes = [] contactActive = False contactTime = 0 i = 0 for score in self.scoreArray: if contactActive is False and score > threshold: contactActive = True contactTime += ns_per_frame elif contactActive is True and score > threshold: contactTime += ns_per_frame elif contactActive is True and score <= threshold: contactActive = False lifeTimes.append(contactTime) contactTime = 0 if i == (len(self.scoreArray) - 1): lifeTimes.append(contactTime) i += 1 return lifeTimes def hbondFramesScan(self): self.hbondFrames = [] for frameList in self.contributingAtoms: currentFrame = 0 for contAtoms in frameList: length = len(contAtoms.hbondinfo) if length > 0: currentFrame += length self.hbondFrames.append(currentFrame) return self.hbondFrames def setContactType(self): self.contactType = self.determine_ctype() def contactTypeAsShortcut(self): return ContactType.shortcut[self.determine_ctype()] def determine_ctype(self): """"""Computes the contact type of the accumulated contacts."""""" # only works if both maps contain resname r1 = self.key1[AccumulationMapIndex.resname].lower() r2 = self.key2[AccumulationMapIndex.resname].lower() # if r1 == ""none"" or r2 == ""none"": # return ContactType.other self.determineBackboneSidechainType() try: sc1 = str(read_residue_db(""scpolarity"", ""name"", r1)[0][""scpolarity""]) scpol1 = SideChainPolarity.mapping[sc1] except IndexError: scpol1 = SideChainPolarity.other try: sc2 = str(read_residue_db(""scpolarity"", ""name"", r2)[0][""scpolarity""]) scpol2 = SideChainPolarity.mapping[sc2] except IndexError: scpol2 = SideChainPolarity.other # hydrogen bonds: donor, acceptor, both ishbond = 0 hb = self.hbondFramesScan() for bla in hb: if bla > 0: ishbond = 1 break if self.atom1contactsBy == BackboneSidechainType.contactsSc \ and self.atom2contactsBy == BackboneSidechainType.contactsSc: # check for saltbridge if (scpol1 == SideChainPolarity.positive and scpol2 == SideChainPolarity.negative) or \ (scpol2 == SideChainPolarity.positive and scpol1 == SideChainPolarity.negative): return ContactType.saltbr # check for hydrophobic contact if scpol1 == SideChainPolarity.nonpolar and scpol2 == SideChainPolarity.nonpolar: if ishbond == 0: return ContactType.hydrophobic if ishbond == 1: return ContactType.hbond return ContactType.other if ishbond == 1: return ContactType.hbond else: return ContactType.other # many TempContactAccumulated objects are later converted to AccumulatedContact class TempContactAccumulate(object): """"""Stores the frame's score as well as the key."""""" def __init__(self, key1, key2): super(TempContactAccumulate, self).__init__() self.fscore = 0 # score of current frame self.contributingAtomContacts = [] # contrib. atoms, # later appended to AccumulatedContact's contributingAtoms list self.key1 = key1 self.key2 = key2 self.bb1score = 0 self.bb2score = 0 self.sc1score = 0 self.sc2score = 0 class AtomContact: """"""Contains infos about an atom-atom contact."""""" def __init__(self, frame, distance, weight, idx1, idx2, hbondinfo): self.frame = int(frame) # frame the contact occured in self.distance = float(distance) # distance between atom1 and atom2 self.weight = float(weight) # weighted distance according to applied weight function self.idx1 = int(idx1) # global!!! index of atom1 self.idx2 = int(idx2) # global!!! index of atom2 self.hbondinfo = hbondinfo # list of HydrogenBonds for frame, empty list if no hbonds occured def toString(self): """"""Prints details about contact to console."""""" print(""frame: %d, dist: %f, weight: %f, idx1: %d, idx2: %d"" % ( self.frame, self.distance, self.weight, self.idx1, self.idx2)) class HydrogenBond: """"""Contains infos about a hydrogenbond corresponding to a contact between two heavyatoms."""""" def __init__(self, donorIndex, acceptorIndex, hydrogenIndex, acceptorHydrogenDistance, angle, usedCutoffDist, usedCutoffAngle): self.donorIndex = donorIndex # global! index of hbond donor: D-h ... a self.acceptorIndex = acceptorIndex # global! index of acceptor: d-h ... A self.hydrogenIndex = hydrogenIndex # global! index of hydrogen atom: d-H ... a self.acceptorHydrogenDistance = acceptorHydrogenDistance # distance of H and A: H-(acceptorHydrogenDistance)-A self.angle = angle # angle between D-H-A self.usedCutoffDist = usedCutoffDist # obvious self.usedCutoffAngle = usedCutoffAngle # obvious def toString(self): """"""Print details about hbond to console."""""" print(""donor: %d, acceptor: %d, hydrogen: %d, dist: %f, angle: %f, usedCutoffDist: %f, usedCutoffAngle: %f"" % ( self.donorIndex, self.acceptorIndex, self.hydrogenIndex, self.acceptorHydrogenDistance, self.angle, self.usedCutoffDist, self.usedCutoffAngle)) class AccumulationMapIndex: """"""Enum and mapping for atom properties. Used to dynamically define keys and have a bijective nomenclature for all properties """""" index, name, resid, resname, segid = range(5) mapping = [""i."", ""nm."", ""r."", ""rn."", ""s.""] vmdsel = [""index"", ""name"", ""resid"", ""resname"", ""segname""] class ContactType: """"""Defines the contact type. Possible types: saltbridge, hydrophobic, hbond, other """""" saltbr, hydrophobic, hbond, other = range(4) shortcut = [""saltbr"", ""hydrophobic"", ""hbond"", ""other""] colors = [""rgba(212, 66, 54 , 160)"", ""rgba(76, 9, 152, 90)"", ""rgba(254, 110, 167, 150)"", ""rgba(255, 255 ,255, 50)""] # qcolors = [QColor(255, 0, 0, 50), QColor(0, 0, 255, 50), QColor(255, 0, 255, 50), QColor(255, 255, 255, 50)] class SideChainPolarity: """"""Defines the side chain polarity."""""" nonpolar, positive, negative, polar, other = range(5) mapping = {""nonpolar"": nonpolar, ""positive"": positive, ""negative"": negative, ""polar"": polar, ""other"": other} class BackboneSidechainType: """"""Enum definition of the backbone-sidechain type."""""" contactsBb, contactsSc = range(2) class BackboneSidechainContactType: """"""Enum definition and mapping of the backbone-sidechain-contact type."""""" bb_only, both, sc_only = range(3) mapping = [[BackboneSidechainType.contactsBb, BackboneSidechainType.contactsBb], [BackboneSidechainType.contactsBb, BackboneSidechainType.contactsSc], [BackboneSidechainType.contactsSc, BackboneSidechainType.contactsSc]] # colors = [[0, 200, 200], [200, 200, 0], [0, 200, 0]] colors = [[0,137,254 ], [245,207,29], [114,199,11 ]] # colors = [[120, 180, 202], [215, 193, 104], [108, 165, 110]] # looks sad def mean_score_of_contactArray(contacts): """"""Computes the mean score using the contacts array."""""" meanList = [] for c in contacts: meanList = np.concatenate((meanList, c.scoreArray), axis=0) return np.mean(meanList) def median_score_of_contactArray(contacts): """"""Computes the mean score using the contacts array."""""" medianList = [] for c in contacts: medianList = np.concatenate((medianList, c.scoreArray), axis=0) return np.median(medianList) ","Python" "Biophysics","maxscheurer/pycontact","PyContact/core/__init__.py",".py","0","0","","Python" "Biophysics","maxscheurer/pycontact","PyContact/core/Scripting.py",".py","1812","43","""""""contains classes in order to faciliate scripting the PyContact package."""""" from PyContact.core.ContactAnalyzer import * from PyContact.core.DataHandler import DataHandler class JobConfig: """"""Configuration/Settings for a PyContact contact analysis job"""""" def __init__(self, cutoff, hbondcutoff, hbondcutangle, map1, map2, sel1, sel2): self.cutoff = cutoff self.hbondcutoff = hbondcutoff self.hbondcutangle = hbondcutangle self.map1 = map1 self.map2 = map2 self.sel1 = sel1 self.sel2 = sel2 class PyContactJob: """"""Job class that is given a JobConfig and input files and handles running/analyzing the job as such."""""" def __init__(self, topo, traj, name, configuration): self.topo = topo self.traj = traj self.name = name self.configuration = configuration self.analyzer = None def runJob(self, ncores=1): """"""Runs contact analysis and accumulation with ncores threads."""""" print(""Running job: "" + self.name + "" on "" + str(ncores) + "" cores."") self.analyzer = Analyzer(self.topo,self.traj, self.configuration.cutoff, self.configuration.hbondcutoff, self.configuration.hbondcutangle, self.configuration.sel1, self.configuration.sel2) self.analyzer.runFrameScan(ncores) self.analyzer.runContactAnalysis(self.configuration.map1, self.configuration.map2, ncores) def writeSessionToFile(self, fname=""""): """"""Writes the current analysis session to a file with either self.name + .session or fname as output filename"""""" if fname != """": DataHandler.writeSessionToFile(fname, self.analyzer) else: DataHandler.writeSessionToFile(self.name + "".session"", self.analyzer) print(""Wrote session to file"") ","Python" "Biophysics","maxscheurer/pycontact","PyContact/core/LogPool.py",".py","752","32","# from: # Shortcut to multiprocessing's logger import multiprocessing from multiprocessing.pool import Pool import traceback def error(msg, *args): return multiprocessing.get_logger().error(msg, *args) class LogExceptions(object): def __init__(self, argcallable): self.__callable = argcallable def __call__(self, *args, **kwargs): try: result = self.__callable(*args, **kwargs) except Exception: error(traceback.format_exc()) raise return result class LoggingPool(Pool): """"""Used for multiprocessing logging."""""" def apply_async(self, func, args=(), kwds={}, callback=None): return Pool.apply_async(self, LogExceptions(func), args, kwds, callback) ","Python" "Biophysics","maxscheurer/pycontact","PyContact/core/multi_trajectory.py",".py","22417","456","import re import time from copy import deepcopy import itertools import MDAnalysis from MDAnalysis.analysis import distances import numpy as np from .Biochemistry import * from .LogPool import * from ..cy_modules.cy_gridsearch import cy_find_contacts def weight_function(value): """"""weight function to score contact distances"""""" return 1.0 / (1.0 + np.exp(5.0 * (value - 4.0))) def chunks(seq, num): """"""splits the list seq in num (almost) equally sized chunks."""""" avg = len(seq) / float(num) out = [] last = 0.0 while last < len(seq): out.append(seq[int(last):int(last + avg)]) last += avg return out class ConvBond(object): """"""Python object of MDAnalysis bond for running jobs in parallel."""""" def __init__(self, bonds): super(ConvBond, self).__init__() self.types = [] self.indices = [] for b in bonds: self.indices.append(deepcopy(b.indices)) self.types.append(deepcopy(b.type)) def types(self): return self.types def to_indices(self): return self.indices # newer version with gridsearch def loop_trajectory_grid(sel1c, sel2c, indices1, indices2, config, suppl, selfInteraction): cutoff, hbondcutoff, hbondcutangle = config # resname_array = comm.bcast(resname_array, root=0) # resid_array = comm.bcast(resid_array, root=0) # name_array = comm.bcast(name_array, root=0) bonds = suppl[0] # segids = comm.bcast(segids, root=0) # backbone = comm.bcast(backbone, root=0) name_array = suppl[1] resid_array = [] segids = [] if (selfInteraction): resid_array = suppl[2] segids = suppl[3] allRankContacts = [] # start = time.time() for s1, s2 in zip(sel1c, sel2c): frame = 0 currentFrameContacts = [] natoms1 = len(s1) natoms2 = len(s2) pos1 = np.array(np.reshape(s1, (1, natoms1 * 3)), dtype=np.float64) pos2 = np.array(np.reshape(s2, (1, natoms2 * 3)), dtype=np.float64) xyz1 = np.array(pos1, dtype=np.float32) xyz2 = np.array(pos2, dtype=np.float32) # 2d array with index of atom1 being the index of the first dimension # individual lists contain atom2 indices nbList1 = cy_find_contacts(xyz1, natoms1, xyz2, natoms2, cutoff) # nbList1 = res[:natoms1] # nbList2 = res[natoms1:] idx1 = 0 for atom1sNeighbors in nbList1: for idx2 in atom1sNeighbors: convindex1 = indices1[frame][idx1] # idx1 converted to global atom indexing convindex2 = indices2[frame][idx2] # idx2 converted to global atom indexing # jump out of loop if hydrogen contacts are found, only contacts between heavy atoms are considered, # hydrogen bonds can still be detected! if re.match(""H(.*)"", name_array[convindex1]) or re.match(""H(.*)"", name_array[convindex2]): continue # distance between atom1 and atom2 # check if residues are more than 4 apart, and in the same segment if selfInteraction: if (resid_array[convindex1] - resid_array[convindex2]) < 5 and segids[convindex1] == segids[convindex2]: continue # distance = distarray[idx1, idx2] # weight = weight_function(distance) dvec = pos1[0][3*idx1:3*idx1+3] - pos2[0][3*idx2:3*idx2+3] distance = np.sqrt(dvec.dot(dvec)) # if (distance - distarray[idx1, idx2]) > 0.001: # print(""Error in distance calculations!"") # return # # print(convindex1, convindex2, distance, distarray[idx1, idx2]) # if (distance > cutoff): # print(""Distances must be smaller/equal cutoff!"") # return weight = weight_function(distance) # HydrogenBondAlgorithm hydrogenBonds = [] # FF independent hydrogen bonds if (name_array[convindex1][0] in HydrogenBondAtoms.atoms and name_array[convindex2][0] in HydrogenBondAtoms.atoms): # print(""hbond? %s - %s"" % (type_array[convindex1], type_array[convindex2])) # search for hatom, check numbering in bond!!!!!!!!!! b1 = bonds[convindex1] b2 = bonds[convindex2] # b1 = all_sel[convindex1].bonds # b2 = all_sel[convindex2].bonds # search for hydrogen atoms bound to atom 1 bondcount1 = 0 hydrogenAtomsBoundToAtom1 = [] # new code for b in b1.types: hydrogen = next((x for x in b if x.startswith(""H"")), 0) # print(b) if hydrogen != 0: # print(""h bond to atom1"") bondindices1 = b1.to_indices()[bondcount1] # print bondindices1 # for j in bondindices1: # print(type_array[j+1]) hydrogenidx = next( (j for j in bondindices1 if name_array[j].startswith(""H"")), -1) if hydrogenidx != -1: # print(type_array[hydrogenidx]) hydrogenAtomsBoundToAtom1.append(hydrogenidx) bondcount1 += 1 # search for hydrogen atoms bound to atom 2 bondcount2 = 0 hydrogenAtomsBoundToAtom2 = [] # print(b2) for b in b2.types: hydrogen = next((x for x in b if x.startswith(""H"")), 0) # print(b) if hydrogen != 0: # print(""h bond to atom2"") bondindices2 = b2.to_indices()[bondcount2] hydrogenidx = next( (k for k in bondindices2 if name_array[k].startswith(""H"")), -1) if hydrogenidx != -1: # print(type_array[hydrogenidx]) hydrogenAtomsBoundToAtom2.append(hydrogenidx) bondcount2 += 1 # check hbond criteria for hydrogen atoms bound to first atom for global_hatom in hydrogenAtomsBoundToAtom1: conv_hatom = np.where(indices1[frame] == global_hatom)[0][0] # print(typeHeavy) # # TODO: FF independent version # if (typeHeavy == AtomHBondType.acc or typeHeavy == AtomHBondType.both) and (distarray[conv_hatom, idx2] <= hbondcutoff): # dist = distarray[conv_hatom, idx2] # dist = np.linalg.norm(sel1.positions[conv_hatom] - sel2.positions[idx2]) dist = np.linalg.norm(pos1[0][3*conv_hatom:3*conv_hatom+3] - pos2[0][3*idx2:3*idx2+3]) if (dist <= hbondcutoff): donorPosition = s1[idx1] hydrogenPosition = np.array(s1[conv_hatom], dtype=np.float64) acceptorPosition = np.array(s2[idx2], dtype=np.float64) v1 = hydrogenPosition - acceptorPosition v2 = hydrogenPosition - donorPosition v1norm = np.linalg.norm(v1) v2norm = np.linalg.norm(v2) dot = np.dot(v1, v2) angle = np.degrees(np.arccos(dot / (v1norm * v2norm))) # print(angle) if angle >= hbondcutangle: # print(""new hbond"") new_hbond = HydrogenBond(convindex1, convindex2, global_hatom, dist, angle, hbondcutoff, hbondcutangle) hydrogenBonds.append(new_hbond) # print(str(convindex1) + "" "" + str(convindex2) # print(""hbond found: %d,%d,%d""%(convindex1,global_hatom,convindex2)) # print(angle) for global_hatom in hydrogenAtomsBoundToAtom2: conv_hatom = np.where(indices2[frame] == global_hatom)[0][0] # TODO: FF independent version # if (typeHeavy == AtomHBondType.acc or typeHeavy == AtomHBondType.both) and (distarray[idx1, conv_hatom] <= hbondcutoff): # FIXME: WTF? # if (distarray[conv_hatom, idx2] <= hbondcutoff): # dist = distarray[idx1, conv_hatom] # dist = np.linalg.norm(sel1.positions[idx1] - sel2.positions[conv_hatom]) dist = np.linalg.norm(pos1[0][3*idx1:3*idx1+3] - pos2[0][3*conv_hatom:3*conv_hatom+3]) if (dist <= hbondcutoff): donorPosition = s2[idx2] hydrogenPosition = np.array(s2[conv_hatom], dtype=np.float64) acceptorPosition = np.array(s1[idx1], dtype=np.float64) v1 = hydrogenPosition - acceptorPosition v2 = hydrogenPosition - donorPosition v1norm = np.linalg.norm(v1) v2norm = np.linalg.norm(v2) dot = np.dot(v1, v2) angle = np.degrees(np.arccos(dot / (v1norm * v2norm))) if angle >= hbondcutangle: new_hbond = HydrogenBond(convindex2, convindex1, global_hatom, dist, angle, hbondcutoff, hbondcutangle) hydrogenBonds.append(new_hbond) # print str(convindex1) + "" "" + str(convindex2) # print ""hbond found: %d,%d,%d""%(convindex2,global_hatom,convindex1) # print angle # finalize newAtomContact = AtomContact(int(frame), float(distance), float(weight), int(convindex1), int(convindex2), hydrogenBonds) currentFrameContacts.append(newAtomContact) idx1 += 1 allRankContacts.append(currentFrameContacts) frame += 1 return allRankContacts def loop_trajectory(sel1c, sel2c, indices1, indices2, config, suppl, selfInteraction): """"""Invoked to analyze trajectory chunk for contacts as a single thread."""""" # print(len(sel1c) , len(sel2c)) # indices1 = suppl[0] # indices2 = suppl[1] cutoff, hbondcutoff, hbondcutangle = config # resname_array = comm.bcast(resname_array, root=0) # resid_array = comm.bcast(resid_array, root=0) # name_array = comm.bcast(name_array, root=0) bonds = suppl[0] # segids = comm.bcast(segids, root=0) # backbone = comm.bcast(backbone, root=0) name_array = suppl[1] resid_array = [] segids = [] if (selfInteraction): resid_array = suppl[2] segids = suppl[3] allRankContacts = [] # start = time.time() for s1, s2 in zip(sel1c, sel2c): frame = 0 currentFrameContacts = [] result = np.ndarray(shape=(len(s1), len(s2)), dtype=float) distarray = distances.distance_array(s1, s2, box=None, result=result) contacts = np.where(distarray <= cutoff) for idx1, idx2 in itertools.izip(contacts[0], contacts[1]): convindex1 = indices1[frame][idx1] # idx1 converted to global atom indexing convindex2 = indices2[frame][idx2] # idx2 converted to global atom indexing # jump out of loop if hydrogen contacts are found, only contacts between heavy atoms are considered, # hydrogen bonds can still be detected! if re.match(""H(.*)"", name_array[convindex1]) or re.match(""H(.*)"", name_array[convindex2]): continue if selfInteraction: if (resid_array[convindex1] - resid_array[convindex2]) < 5 and segids[convindex1] == segids[convindex2]: continue # distance between atom1 and atom2 distance = distarray[idx1, idx2] weight = weight_function(distance) hydrogenBonds = [] if (name_array[convindex1][0] in HydrogenBondAtoms.atoms and name_array[convindex2][0] in HydrogenBondAtoms.atoms): # print(""hbond? %s - %s"" % (type_array[convindex1], type_array[convindex2])) # search for hatom, check numbering in bond!!!!!!!!!! b1 = bonds[convindex1] b2 = bonds[convindex2] bondcount1 = 0 hydrogenAtomsBoundToAtom1 = [] # new code for b in b1.types: # b = bnd.type hydrogen = next((xx for xx in b if xx.startswith(""H"")), 0) # print(b) if hydrogen != 0: # print(""h bond to atom1"") bondindices1 = b1.to_indices()[bondcount1] # print bondindices1 # for j in bondindices1: # print(self.type_array[j+1]) hydrogenidx = next( (j for j in bondindices1 if name_array[j].startswith(""H"")), -1) if hydrogenidx != -1: # print(self.type_array[hydrogenidx]) hydrogenAtomsBoundToAtom1.append(hydrogenidx) bondcount1 += 1 # search for hydrogen atoms bound to atom 2 bondcount2 = 0 hydrogenAtomsBoundToAtom2 = [] for b in b2.types: # b = bnd2.type hydrogen = next((xx for xx in b if xx.startswith(""H"")), 0) # print(b) if hydrogen != 0: # print(""h bond to atom2"") bondindices2 = b2.to_indices()[bondcount2] hydrogenidx = next( (k for k in bondindices2 if name_array[k].startswith(""H"")), -1) if hydrogenidx != -1: # print(type_array[hydrogenidx]) hydrogenAtomsBoundToAtom2.append(hydrogenidx) bondcount2 += 1 for global_hatom in hydrogenAtomsBoundToAtom1: conv_hatom = np.where(indices1[frame] == global_hatom)[0][0] dist = distarray[conv_hatom, idx2] if dist <= hbondcutoff: donorPosition = s1[idx1] hydrogenPosition = s1[conv_hatom] acceptorPosition = s2[idx2] v1 = hydrogenPosition - acceptorPosition v2 = hydrogenPosition - donorPosition v1norm = np.linalg.norm(v1) v2norm = np.linalg.norm(v2) dot = np.dot(v1, v2) angle = np.degrees(np.arccos(dot / (v1norm * v2norm))) if angle >= hbondcutangle: new_hbond = HydrogenBond(convindex1, convindex2, global_hatom, dist, angle, hbondcutoff, hbondcutangle) hydrogenBonds.append(new_hbond) # print str(convindex1) + "" "" + str(convindex2) # print ""hbond found: %d,%d,%d""%(convindex1,global_hatom,convindex2) # print angle for global_hatom in hydrogenAtomsBoundToAtom2: conv_hatom = np.where(indices2[frame] == global_hatom)[0][0] dist = distarray[idx1, conv_hatom] if dist <= hbondcutoff: donorPosition = s2[idx2] hydrogenPosition = s2[conv_hatom] acceptorPosition = s1[idx1] v1 = hydrogenPosition - acceptorPosition v2 = hydrogenPosition - donorPosition v1norm = np.linalg.norm(v1) v2norm = np.linalg.norm(v2) dot = np.dot(v1, v2) angle = np.degrees(np.arccos(dot / (v1norm * v2norm))) if angle >= hbondcutangle: new_hbond = HydrogenBond(convindex2, convindex1, global_hatom, dist, angle, hbondcutoff, hbondcutangle) hydrogenBonds.append(new_hbond) newAtomContact = AtomContact(int(frame), float(distance), float(weight), int(convindex1), int(convindex2), hydrogenBonds) currentFrameContacts.append(newAtomContact) allRankContacts.append(currentFrameContacts) frame += 1 return allRankContacts def run_load_parallel(nproc, psf, dcd, cutoff, hbondcutoff, hbondcutangle, sel1text, sel2text): """"""Invokes nproc threads to run trajectory loading and contact analysis in parallel."""""" # nproc = int(self.settingsView.coreBox.value()) pool = LoggingPool(nproc) # manager = multiprocessing.Manager() # d=manager.list(trajArgs) # load psf and dcd u = MDAnalysis.Universe(psf, dcd) # define selections according to sel1text and sel2text selfInteraction = False if sel2text == ""self"": sel1 = u.select_atoms(sel1text) sel2 = u.select_atoms(sel1text) selfInteraction = True else: sel1 = u.select_atoms(sel1text) sel2 = u.select_atoms(sel2text) # write properties of all atoms to lists all_sel = u.select_atoms(""all"") backbone_sel = u.select_atoms(""backbone"") resname_array = [] resid_array = [] name_array = [] bonds = [] segids = [] backbone = [] for atom in all_sel.atoms: resname_array.append(atom.resname) resid_array.append(atom.resid) name_array.append(atom.name) bonds.append(ConvBond(atom.bonds)) segids.append(atom.segid) for atom in backbone_sel: backbone.append(atom.index) if (len(sel1.atoms) == 0 or len(sel2.atoms) == 0): raise Exception sel1coords = [] sel2coords = [] start = time.time() indices1 = [] indices2 = [] for ts in u.trajectory: # define selections according to sel1text and sel2text if ""around"" in sel1text: sel1 = u.select_atoms(sel1text) if ""around"" in sel2text: sel2 = u.select_atoms(sel2text) # write atomindices for each selection to list sel1coords.append(sel1.positions) sel2coords.append(sel2.positions) # tempindices1 = [] # for at in sel1.atoms: # tempindices1.append(at.index) # tempindices2 = [] # for at in sel2.atoms: # tempindices2.append(at.index) indices1.append(sel1.indices) indices2.append(sel2.indices) # contactResults = [] # loop over trajectory # totalFrameNumber = len(u.trajectory) # start = time.time() sel1c = chunks(sel1coords, nproc) sel2c = chunks(sel2coords, nproc) sel1ind = chunks(indices1, nproc) sel2ind = chunks(indices2, nproc) # print(len(sel1ind), len(sel2ind)) # show trajectory information and selection information # print(""trajectory with %d frames loaded"" % len(u.trajectory)) print(""Running on %d cores"" % nproc) results = [] rank = 0 for c in zip(sel1c, sel2c, sel1ind, sel2ind): if (selfInteraction): results.append(pool.apply_async(loop_trajectory_grid, args=(c[0], c[1], c[2], c[3], [cutoff, hbondcutoff, hbondcutangle], [bonds, name_array, resid_array, segids], selfInteraction))) else: results.append(pool.apply_async(loop_trajectory_grid, args=(c[0], c[1], c[2], c[3], [cutoff, hbondcutoff, hbondcutangle], [bonds, name_array], selfInteraction))) rank += 1 pool.close() pool.join() # stop = time.time() allContacts = [] for res in results: rn = res.get() # print(len(rn)) allContacts.extend(rn) # pickle.dump(allContacts,open(""parallel_results.dat"",""w"")) # print(""frames: "", len(allContacts)) # print(""time: "", str(stop-start), rank) return [allContacts, resname_array, resid_array, name_array, segids, backbone] ","Python" "Biophysics","maxscheurer/pycontact","PyContact/exampleData/datafiles.py",".py","359","13","# location/paths for test/example data from pkg_resources import resource_filename as res DCD = res(__name__, './rpn11_ubq.dcd') PSF = res(__name__, './rpn11_ubq.psf') XTC = res(__name__, './md_noPBC.xtc') TPR = res(__name__, './md.tpr') DEFAULTSESSION = res(__name__, './defaultsession') DEFAULTSESSION_PY3 = res(__name__, './defaultsession_py3') del res ","Python" "Biophysics","maxscheurer/pycontact","PyContact/exampleData/__init__.py",".py","0","0","","Python" "Biophysics","maxscheurer/pycontact","PyContact/cy_modules/__init__.py",".py","0","0","","Python" "Biophysics","maxscheurer/pycontact","PyContact/cy_modules/src/ResizeArray.h",".h","4388","134","/*************************************************************************** *cr *cr (C) Copyright 1995-2011 The Board of Trustees of the *cr University of Illinois *cr All Rights Reserved *cr ***************************************************************************/ /*************************************************************************** * RCS INFORMATION: * * $RCSfile: ResizeArray.h,v $ * $Author: johns $ $Locker: $ $State: Exp $ * $Revision: 1.45 $ $Date: 2010/12/16 04:08:38 $ * *************************************************************************** * DESCRIPTION: * Automatically-adjusting single-dim array template. * * LICENSE: * UIUC Open Source License * http://www.ks.uiuc.edu/Research/vmd/plugins/pluginlicense.html * ***************************************************************************/ #ifndef RESIZEARRAY_TEMPLATE_H #define RESIZEARRAY_TEMPLATE_H #include /// A template class which implements a dynamically-growing, automatically /// resizing array of data of a given type. Elements in the array may be /// accessed via the [] operator. When new data is added to the end of an /// array, the size of the array is automatically increased if necessary. /// /// XXX Do not parametrize this class with a datatype which cannot be /// shallow-copied! This class uses memcpy to resize, and therefore /// classes which contain dynamically-allocated memory blocks will /// crash and burn if the ResizeArray ever gets resized. template class ResizeArray { private: T *allocate(size_t n) { return new T[n]; } void deallocate(T *p) { delete [] p; } T *data; ///< list of items, and pointer to current item. int sz; ///< max number of items that can be stored in the array int currSize; ///< largest index used + 1 public: /// Constructor /// The first argument is the initial internal size of the array, i.e. the /// initial number of elements for which to allocate memory (although the /// initial external size of the array will be zero). ResizeArray(int s = 3) { currSize = 0; sz = (s > 0 ? s : 10); data = allocate(sz); } ~ResizeArray() { deallocate(data); } int num(void) const { return currSize; } ///< current size of array T& operator[](int N) { return data[N]; } ///< unchecked accessor, for speed T const& operator[](int N) const { return data[N]; } ///< a const version of above /// add a new element to the end of the array. Return index of new item. void append(const T& val) { if (currSize == sz) { // extend size of array if necessary int newsize = (int)((float)sz * 1.3f); // guarantee minimum required size increase, since the scaled value // may truncate back to the original size value when the initial number // of elements is very small. if (newsize == sz) newsize++; // shallow copy the data to a newly allocated block since we can't // do something better like realloc() T *newdata = allocate(newsize); memcpy(newdata, data, currSize * sizeof(T)); deallocate(data); // save new values data = newdata; sz = newsize; } data[currSize++] = val; } /// remove an item from the array, shifting remaining items down by 1 void remove(int n) { if (n < 0 || n >= currSize) return; for (int i=n; i. */ /* *************************** vmstream.h A lightweight C++ library to open a TCP connection to VMD Aaron Keys, June 10, 2009 ***************************/ /** \mainpage VMD Streams Documentation \section intro_sec Introduction The vmdstreams library provides a simple interface for opening a TCP connection to VMD from C++. Once the TCP connection is established, the user can remote- control VMD from a C++ code to automate analysis, control movies, or make custom animations. All that is required is some knowledge of VMDs Tcl interface (see http://www.ks.uiuc.edu/Research/vmd/current/ug/node104.html). \section examples Examples The vmdstream object works the same as an ostream in C++. (That is, it works the same way as cout, cerr and ofstreams). Here is an example of drawing 20 spheres on the screen: \code #include using namespace std; int main( int argc, char *argv[] ) { //open a TCP connection to VMD vmdsock_t vmdsock = newvmdsock(); vmdstream vmd(vmdsock); //tell VMD to draw some spheres cout << ""drawing spheres\n""; for (int i=0; i<10; i++) { vmd << ""draw sphere {"" << i << "" 0 0}"" << endl; } for (int i=0; i<10; i++) { vmd << ""draw sphere {0 "" << i << "" 0}"" << endl; } //close the tcp connection cout << ""finished"" << endl; closevmdsock(vmdsock); } \endcode Notice that the ""draw sphere"" command is part of the VMD tcl scripting interface. In fact, we can control almost every aspect of VMD using Tcl commands. \section Installation The vmdstreams codes consists of a single header file. \section References This codes is based on the socket iostream library by David Ryan, released into public domain in Feb 2004. */ #ifndef DOXYGEN_SHOULD_SKIP_THIS #include #include #include #include #include #include #include #include #include #ifndef TIOCINQ #define TIOCINQ FIONREAD #endif class socket_buf : public std::streambuf { private: int _socket; char _inBuffer[1024]; char _outBuffer[1024]; public: socket_buf( int socket ) { _socket = socket; setg( _inBuffer, _inBuffer, _inBuffer ); setp( _outBuffer, _outBuffer+1024 ); } protected: int overflow(int x) { #ifdef DEBUG_MODE std::cout << ""socket_buf::overflow()"" << x << std::endl; #endif return x; } int sync() { #ifdef DEBUG_MODE std::cout << ""socket_buf::sync()"" << std::endl; #endif // if no data availalbe just return. if ( pbase() == pptr() ) return 0; // try and send the data. int len = pptr() - pbase(); int rc = send( _socket, pbase(), len, 0 ); if ( rc < 0 ) return rc; setp( _outBuffer, _outBuffer+1024 ); return 0; } int underflow() { #ifdef DEBUG_MODE std::cout << ""socket_buf::underflow() "" << std::endl; #endif if (gptr () < egptr ()) return *(unsigned char*)gptr (); int len; // find out how much data is available. if( ioctl( _socket, TIOCINQ, &len) < 0 ) { // error std::cerr << ""socket_buf error"" << std::endl; len = 1; } // make sure length is atleast 1. We will block. if ( len == 0 ) len = 1; // try and read in some data. int read = recv( _socket, &_inBuffer, len, 0 ); if ( read > 0 ) { setg( _inBuffer, _inBuffer, _inBuffer+read ); } else { return EOF; } return *(unsigned char*)gptr (); } }; class siostream: public std::iostream { private: socket_buf _buf; public: siostream( int socket ) :_buf( socket ), std::iostream( &_buf ) { } }; #endif typedef siostream vmdstream; void writevmdinitscript(int port=5555, std::string extra_commands="""") { std::ofstream os(""remote_ctl.tcl""); os << ""#------------------------------------------------------------------"" << ""\n""; os << ""# $Id: remote_ctl.tcl,v 1.6 2003/02/12 21:33:11 oliver Exp $"" << ""\n""; os << ""# based on bounce.tcl and vmdcollab.tcl"" << ""\n""; os << ""# from http://www.ks.uiuc.edu/Research/vmd/script_library/scripts/vmdcollab/"" << ""\n""; os << ""#"" << ""\n""; os << ""# start this in VMD and send commands to the listening port to have VMD"" << ""\n""; os << ""# execute them remotely"" << ""\n""; os << ""# (also see http://www.tcl.tk/scripting/netserver.html)"" << ""\n""; os << ""#"" << ""\n""; os << ""# Usage: vmd -e remote_ctl.tcl"" << ""\n""; os << ""# or vmd> source remote_ctl.tcl"" << ""\n""; os << ""#"" << ""\n""; os << ""# Security: we only allow connections from localhost (see acpt)"" << ""\n""; os << ""#"" << ""\n""; os << ""# Bugs:"" << ""\n""; os << ""# * once a wrong command was sent, the connection appears"" << ""\n""; os << ""# to 'block' and does not accept correct commands later"" << ""\n""; os << ""# * does not write result back to socket (one way connection...) so"" << ""\n""; os << ""# there is no way to inquire objects in vmd"" << ""\n""; os << """" << ""\n""; os << ""namespace eval remote_ctl {"" << ""\n""; os << ""variable main"" << ""\n""; os << ""variable clients"" << ""\n""; os << ""variable default_vmd_port"" << ""\n""; os << ""set default_vmd_port 5555"" << ""\n""; os << ""# I am too dumb to set the default value for port from"" << ""\n""; os << ""# $default_vmd_port so I put 5555 in there literally"" << ""\n""; os << ""proc start { {port "" << port << ""} } {"" << ""\n""; os << ""variable main"" << ""\n""; os << ""set main [socket -server remote_ctl::acpt $port]"" << ""\n""; os << ""putlog \""Listening on port $port\"""" << ""\n""; os << ""}"" << ""\n""; os << ""proc acpt { sock addr port } {"" << ""\n""; os << ""variable clients"" << ""\n""; os << ""if {[string compare $addr \""127.0.0.1\""] != 0} {"" << ""\n""; os << ""putlog \""Unauthorized connection attempt from $addr port $port\"""" << ""\n""; os << ""close $sock"" << ""\n""; os << ""return"" << ""\n""; os << ""}"" << ""\n""; os << ""putlog \""Accept $sock from $addr port $port\"""" << ""\n""; os << ""set clients($sock) 1"" << ""\n""; os << ""fconfigure $sock -buffering line"" << ""\n""; os << ""fileevent $sock readable [list remote_ctl::recv $sock]"" << ""\n""; os << ""}"" << ""\n""; os << ""proc recv { sock } {"" << ""\n""; os << ""variable main"" << ""\n""; os << ""variable clients"" << ""\n""; os << ""if { [eof $sock] || [catch {gets $sock line}]} {"" << ""\n""; os << ""# end of file or abnormal connection drop:"" << ""\n""; os << ""# shut down this connection"" << ""\n""; os << ""close $sock"" << ""\n""; os << ""putlog \""Closing $sock\"""" << ""\n""; os << ""unset clients($sock)"" << ""\n""; os << ""} else {"" << ""\n""; os << ""if {[string compare $line \""quit\""] == 0} {"" << ""\n""; os << ""# prevent new connections"" << ""\n""; os << ""# existing connections stay open"" << ""\n""; os << ""# No -- Bug(?): 'quit' closes VMD..."" << ""\n""; os << ""putlog \""Disallowing incoming connections by request of $sock\"""" << ""\n""; os << ""close $main"" << ""\n""; os << ""}"" << ""\n""; os << ""# execute the received commands"" << ""\n""; os << ""# should check for runtime errors which otherwise leave the connection"" << ""\n""; os << ""# in an unusable state"" << ""\n""; os << ""# eval $line"" << ""\n""; os << ""set rc [catch $line result]"" << ""\n""; os << ""if { $rc } {"" << ""\n""; os << ""#puts $sock \""Error executing comand '$line': n$result\"""" << ""\n""; os << ""puts \""Error executing comand '$line': n$result\"""" << ""\n""; os << ""} else {"" << ""\n""; os << ""#puts $sock $result"" << ""\n""; os << ""#puts $result"" << ""\n""; os << ""}"" << ""\n""; os << ""}"" << ""\n""; os << ""}"" << ""\n""; os << ""###### would like the last line from stdout in line ###########"" << ""\n""; os << ""# (or any working solution....)"" << ""\n""; os << ""proc send { sock line} {"" << ""\n""; os << ""variable clients"" << ""\n""; os << ""# send reply to connecting client"" << ""\n""; os << ""putlog \""send '$line' to $sock\"""" << ""\n""; os << ""puts $sock $line"" << ""\n""; os << ""}"" << ""\n""; os << """" << ""\n""; os << ""proc putlog { text } {"" << ""\n""; os << ""puts $text"" << ""\n""; os << ""return"" << ""\n""; os << ""}"" << ""\n""; os << ""}"" << ""\n""; os << """" << ""\n""; os << ""remote_ctl::putlog \""Starting remote_ctl server in vmd: connect with something like\"""" << ""\n""; os << ""remote_ctl::putlog \""telnet localhost "" << port << ""\"""" << ""\n""; os << ""remote_ctl::start"" << ""\n""; os << extra_commands; os.close(); } typedef int vmdsock_t; /** \brief opens a TCP connection to VMD and returns the socket file descriptor \param vmd_executable is the name of the vmd program as it is called from the command line. Typically, if vmd does not live in a global search path such as /usr/bin or /usr/local/bin, we make a dynamic link to the executable an place it in the /usr/bin directory. For example, on mac os, the VMD executable typically lives in an application package, for example: /Applications/VMD\ 1.8.6.app/Contents/vmd/vmd_MACOSXX86. In this case, it is easiest to make a dynamic link to the executable using ""ln"" and place the link in the /usr/bin folder \param port is the port to connect over \param extra_commands is a string containing a list of Tcl commands to parse on startup \return the socket file descriptor */ vmdsock_t newvmdsock( const char* vmd_executable=""vmd"", int port=5555, std::string extra_commands="""") { writevmdinitscript(port, extra_commands); int rv, s; int count; pid_t pid; pid = fork(); if (pid == -1) { std::cerr << ""ERROR: failed to fork child process\n""; exit(1); } else if (pid == 0) { //child std::ostringstream command; command << vmd_executable <<"" -e remote_ctl.tcl""; int good = system(command.str().c_str()); if (good != 0) { std::cerr << ""ERROR: vmd executable failed to launch\n""; std::cerr << ""Please check your path: "" << vmd_executable << ""\n""; exit(1); } std::cout << ""VMD killed via quit command\n""; exit(0); } else { //sleep(2); std::cout << ""test socket"" << std::endl; struct hostent *he=gethostbyname(""localhost""); struct sockaddr_in sa; memset(&sa, 0, sizeof(sa)); sa.sin_family = PF_INET; sa.sin_addr = *((struct in_addr *)he->h_addr); sa.sin_port = htons(port); for (count=0, rv=1; rv && count<20; count++) { s = socket(AF_INET, SOCK_STREAM, 0); rv = connect( s, (struct sockaddr*) &sa, sizeof(sa) ); std::cout << ""connect = "" << rv << std::endl; if (rv) { std::cerr << ""TCP connection to vmd failed\n""; sleep(2); close(s); } sleep(1); } } return s; } /** \brief closes the VMD socket connection \param socketfd is the file descriptor of the socket to close */ void closevmdsock(vmdsock_t socketfd) { shutdown(socketfd, SHUT_RDWR); close(socketfd); } ","Unknown" "Biophysics","maxscheurer/pycontact","PyContact/cy_modules/src/gridsearch.C",".C","36515","1163","#include #include #include #include #include ""ResizeArray.h"" #include #define FALSE 0 #define TRUE 1 void * find_within_routine( void *v ); struct AtomEntry { float x, y, z; int index; AtomEntry() {} AtomEntry(const float &_x, const float &_y, const float &_z, const int &_i) : x(_x), y(_y), z(_z), index(_i) {} }; using namespace std; extern ""C"" { struct GridSearchPair { int ind1, ind2; GridSearchPair *next; }; GridSearchPair *vmd_gridsearch3(const float *posA, int natomsA, const int *A, const float *posB, int natomsB, const int *B, float pairdist, int allow_double_counting, int maxpairs); #define VMD_RAND_MAX 2147483647L long vmd_random(void) { #ifdef _MSC_VER return rand(); #else return random(); #endif } void vmd_srandom(unsigned int seed) { #ifdef _MSC_VER srand(seed); #else srandom(seed); #endif } float distance2(const float *a, const float *b) { float delta = a[0] - b[0]; float r2 = delta*delta; delta = a[1] - b[1]; r2 += delta*delta; delta = a[2] - b[2]; return r2 + delta*delta; } void vec_sub(float *a, const float *b, const float *c) { a[0]=b[0]-c[0]; a[1]=b[1]-c[1]; a[2]=b[2]-c[2]; } void find_minmax(const float *pos, int n, const int *on, float *min, float *max, int *oncount) { float x1, x2, y1, y2, z1, z2; int i, numon; // return immediately if there are no atoms, or no atoms are on. if (n < 1) return; // init on count, i = 0 because all atoms are on numon = 1; i = 0; // find first on atom EDIT: not needed // for (i=0; i x2) x2 = pos[0]; if (pos[1] < y1) y1 = pos[1]; else if (pos[1] > y2) y2 = pos[1]; if (pos[2] < z1) z1 = pos[2]; else if (pos[2] > z2) z2 = pos[2]; numon++; // } pos += 3; } min[0] = x1; min[1] = y1; min[2] = z1; max[0] = x2; max[1] = y2; max[2] = z2; if (oncount != NULL) *oncount = numon; } int find_minmax_selected(int n, const int *flgs, const float *pos, float &_xmin, float &_ymin, float &_zmin, float &_xmax, float &_ymax, float &_zmax) { int i; float xmin, xmax, ymin, ymax, zmin, zmax; for (i=0; ixi) xmin=xi; if (ymin>yi) ymin=yi; if (zmin>zi) zmin=zi; if (xmaxnext = (GridSearchPair *) malloc(sizeof(GridSearchPair)); link->next->ind1 = i; link->next->ind2 = j; link->next->next = NULL; } int make_neighborlist(int **nbrlist, int xb, int yb, int zb) { int xi, yi, zi, aindex, xytotb; if (nbrlist == NULL) return -1; xytotb = xb * yb; aindex = 0; for (zi=0; zi 0) nbrs[n++] = aindex - xb + 1; if (xi > 0 && zi < (zb-1)) nbrs[n++] = aindex + xytotb - 1; if (yi > 0 && zi < (zb-1)) nbrs[n++] = aindex + xytotb - xb; if (xi < (xb-1) && yi < (yb-1) && zi < (zb-1)) nbrs[n++] = aindex + xytotb + xb + 1; if (xi > 0 && yi < (yb-1) && zi < (zb-1)) nbrs[n++] = aindex + xytotb + xb - 1; if (xi < (xb-1) && yi > 0 && zi < (zb-1)) nbrs[n++] = aindex + xytotb - xb + 1; if (xi > 0 && yi > 0 && zi < (zb-1)) nbrs[n++] = aindex + xytotb - xb - 1; nbrs[n++] = -1; // mark end of list int *lst = (int *) malloc(n*sizeof(int)); if (lst == NULL) return -1; // return on failed allocations memcpy(lst, nbrs, n*sizeof(int)); nbrlist[aindex] = lst; aindex++; } } } return 0; } GridSearchPair *vmd_gridsearch1(const float *pos,int natoms, const int *on, float pairdist, int allow_double_counting, int maxpairs) { float min[3]={0,0,0}, max[3]={0,0,0}; float sqdist; int i, j, xb, yb, zb, xytotb, totb, aindex; int **boxatom, *numinbox, *maxinbox, **nbrlist; int numon = 0; float sidelen[3], volume; int paircount = 0; int maxpairsreached = 0; sqdist = pairdist * pairdist; // printf(""nc: %d \n"",natoms); // find bounding box for selected atoms, and number of atoms in selection. find_minmax(pos, natoms, on, min, max, &numon); // printf(""minmaxfound: %d,%f, min %f max %f\n"",numon,sqdist,min[0],max[0]); // do sanity checks and complain if we've got bogus atom coordinates, // we shouldn't ever have density higher than 0.1 atom/A^3, but we'll // be generous and allow much higher densities. if (maxpairs != -1) { vec_sub(sidelen, max, min); // include estimate for atom radius (1 Angstrom) in volume determination volume = fabsf((sidelen[0] + 2.0f) * (sidelen[1] + 2.0f) * (sidelen[2] + 2.0f)); if ((numon / volume) > 1.0) { // msgWarn << ""vmd_gridsearch1: insane atom density"" << sendmsg; } } // I don't want the grid to get too large, otherwise I could run out // of memory. Octrees would be cool, but I'll just limit the grid size // and let the performance degrade a little for pathological systems. // Note that sqdist is what gets used for the actual distance checks; // from here on out pairdist is only used to set the grid size, so we // can set it to anything larger than the original pairdist. const int MAXBOXES = 4000000; totb = MAXBOXES + 1; float newpairdist = pairdist; float xrange = max[0]-min[0]; float yrange = max[1]-min[1]; float zrange = max[2]-min[2]; do { // printf(""pairdist: %f\n"", pairdist); pairdist = newpairdist; const float invpairdist = 1.0f / pairdist; xb = ((int)(xrange*invpairdist))+1; yb = ((int)(yrange*invpairdist))+1; zb = ((int)(zrange*invpairdist))+1; xytotb = yb * xb; totb = xytotb * zb; newpairdist = pairdist * 1.26f; // cbrt(2) is about 1.26 } while (totb > MAXBOXES || totb < 1); // check for integer wraparound too // printf(""boxbuild\n""); // printf(""totb %d\n"", totb); // 2. Sort each atom into appropriate bins boxatom = (int **) calloc(1, totb*sizeof(int *)); numinbox = (int *) calloc(1, totb*sizeof(int)); maxinbox = (int *) calloc(1, totb*sizeof(int)); if (boxatom == NULL || numinbox == NULL || maxinbox == NULL) { if (boxatom != NULL) free(boxatom); if (numinbox != NULL) free(numinbox); if (maxinbox != NULL) free(maxinbox); // msgErr << ""Gridsearch memory allocation failed, bailing out"" << sendmsg; return NULL; // ran out of memory, bail out! } const float invpairdist = 1.0f / pairdist; for (i=0; i= xb) axb = xb-1; if (ayb >= yb) ayb = yb-1; if (azb >= zb) azb = zb-1; aindex = azb * xytotb + ayb * xb + axb; // grow box if necessary if ((num = numinbox[aindex]) == maxinbox[aindex]) { boxatom[aindex] = (int *) realloc(boxatom[aindex], (num+4)*sizeof(int)); maxinbox[aindex] += 4; } // store atom index in box boxatom[aindex][num] = i; numinbox[aindex]++; // } } free(maxinbox); nbrlist = (int **) calloc(1, totb*sizeof(int *)); if (make_neighborlist(nbrlist, xb, yb, zb)) { if (boxatom != NULL) { for (i=0; inext = NULL; cur = head; // printf(""pairlist\n""); // wkfmsgtimer *msgt = wkf_msg_timer_create(5); for (aindex = 0; (aindex < totb) && (!maxpairsreached); aindex++) { // printf(""%d\n"", aindex); int *tmpbox, *tmpnbr, *nbr; tmpbox = boxatom[aindex]; tmpnbr = nbrlist[aindex]; // if (wkf_msg_timer_timeout(msgt)) { // char tmpbuf[128]; // sprintf(tmpbuf, ""%6.2f"", (100.0f * aindex) / (float) totb); // msgInfo << ""vmd_gridsearch1: "" << tmpbuf << ""% complete"" << sendmsg; // } for (nbr = tmpnbr; (*nbr != -1) && (!maxpairsreached); nbr++) { int *nbrbox = boxatom[*nbr]; for (i=0; (i sqdist) continue; if (maxpairs > 0) { if (paircount >= maxpairs) { maxpairsreached = 1; continue; } } add_link(cur, ind1, ind2); paircount++; // XXX double-counting still ignores atoms with same coords... if (allow_double_counting) { add_link(cur, ind2, ind1); paircount++; } cur = cur->next; cur->next = NULL; // } } } } } for (i=0; inext; free(head); // if (maxpairsreached) { // printf(""maxpairs reached \n""); // } return cur; } std::vector> find_contacts(const float *pos1, const float *pos2, int nAtoms1, int nAtoms2, double cutoff) { std::vector> pairlist1(nAtoms1+nAtoms2); GridSearchPair *p, *tmp; int allowDouble = 1; int A[nAtoms1]; fill_n(A, nAtoms1, 1); int B[nAtoms2]; fill_n(B, nAtoms2, 1); GridSearchPair* pairs = vmd_gridsearch3(pos1, nAtoms1, A, pos2, nAtoms2, B, cutoff, allowDouble, -1); for (p = pairs; p != NULL; p = tmp) { int ind1=p->ind1; int ind2=p->ind2; pairlist1[ind1].push_back(ind2); // pairlist1[nAtoms1+ind2].push_back(ind1); tmp = p->next; free(p); } return pairlist1; } static double sasa_grid(const float *pos,int natoms, float pairdist, int allow_double_counting, int maxpairs, const float *radius,const int npts, double srad, int pointstyle, int restricted, const int* restrictedList) { int on[natoms]; fill_n(on,natoms,1); // printf(""natoms %d\n"", natoms); // printf(""pairdist %f\n"", pairdist); // printf(""maxpairs %d\n"", maxpairs); GridSearchPair* pairs = vmd_gridsearch1(pos,natoms, on, pairdist, allow_double_counting,maxpairs); // vector > v(natoms,vector()); // printf(""size: %d\n"", v.size()); ResizeArray *pairlist = new ResizeArray[natoms]; GridSearchPair *p, *tmp; for (p = pairs; p != NULL; p = tmp) { int ind1=p->ind1; int ind2=p->ind2; // v[ind1].push_back(ind2); // v[ind2].push_back(ind1); pairlist[ind1].append(ind2); pairlist[ind2].append(ind1); tmp = p->next; free(p); } float *spherepts = new float[3*npts]; if (pointstyle) { static const float RAND_MAX_INV = 1.0f/VMD_RAND_MAX; vmd_srandom(38572111); // All the spheres use the same random points. for (int i=0; i &nbrs = pairlist[i]; // printf(""neighbors: %d\n"", nbrs.num()); for (int j=0; j > v(natoms,vector()); // // printf(""size: %d\n"", v.size()); // // ResizeArray *pairlist = new ResizeArray[natoms]; // GridSearchPair *p, *tmp; // for (p = pairs; p != NULL; p = tmp) { // int ind1=p->ind1; // int ind2=p->ind2; // v[ind1].push_back(ind2); // v[ind2].push_back(ind1); // // printf(""%f\n"", v[ind2]); // // pairlist[ind1].append(ind2); // // pairlist[ind2].append(ind1); // // printf(""%d\n"", ind1); // tmp = p->next; // free(p); // } // PyGILState_STATE gstate = PyGILState_Ensure(); // PyObject* result = PyList_New(0); // vector< vector >::iterator row; // vector::iterator col; // for (row = v.begin(); row != v.end(); row++) { // // printf(""row %d\n"", *row); // PyObject* tempo = PyList_New(0); // for (col = row->begin(); col != row->end(); col++) { // // printf(""%d \n"", *col); // PyList_Append(tempo, PyInt_FromLong(*col)); // } // PyList_Append(result,tempo); // tempo = NULL; // } // PyGILState_Release(gstate); // return result; // } } typedef ResizeArray atomlist; struct FindWithinData { int nthreads; int tid; int totb; int xytotb; int xb; int yb; int zb; float r2; const float * xyz; const atomlist * flgatoms; const atomlist * otheratoms; int * flgs; FindWithinData() : flgatoms(0), otheratoms(0), flgs(0) {} ~FindWithinData() { if (flgs) free(flgs); } }; #define MAXGRIDDIM 31 static int* find_within(const float *xyz, int *flgs, int *others, int num, float r) { int i; float xmin, xmax, ymin, ymax, zmin, zmax; float oxmin, oymin, ozmin, oxmax, oymax, ozmax; float xwidth, ywidth, zwidth; const float *pos; int *result = new int[num]; fill_n(result,num,0); // for (size_t i = 0; i < num; i++) { // pos=xyz+3*i; // printf(""%f %f %f\n"", pos[0],pos[1],pos[2]); // } // find min/max bounds of atom coordinates in flgs if (!find_minmax_selected(num, flgs, xyz, xmin, ymin, zmin, xmax, ymax, zmax) || !find_minmax_selected(num, others, xyz, oxmin, oymin, ozmin, oxmax, oymax, ozmax)) { memset(flgs, 0, num*sizeof(int)); return result; } // Find the set of atoms with the smallest extent; here we use the sum // of the box dimensions though other choices might be better. float size = xmax+ymax+zmax - (xmin+ymin+zmin); float osize = oxmax+oymax+ozmax - (oxmin+oymin+ozmin); if (osize < size) { xmin=oxmin; ymin=oymin; zmin=ozmin; xmax=oxmax; ymax=oymax; zmax=ozmax; } // Generate a grid of mesh size r based on the computed size of the molecule. // We limit the size of the grid cell dimensions so that we don't get too // many grid cells. xwidth = (xmax-xmin)/(MAXGRIDDIM-1); if (xwidth < r) xwidth = r; ywidth = (ymax-ymin)/(MAXGRIDDIM-1); if (ywidth < r) ywidth = r; zwidth = (zmax-zmin)/(MAXGRIDDIM-1); if (zwidth < r) zwidth = r; // Adjust the bounds so that we include atoms that are in the outermost // grid cells. xmin -= xwidth; xmax += xwidth; ymin -= ywidth; ymax += ywidth; zmin -= zwidth; zmax += zwidth; // The number of grid cells needed in each dimension is // (int)((xmax-xmin)/xwidth) + 1 const int xb = (int)((xmax-xmin)/xwidth) + 1; const int yb = (int)((ymax-ymin)/ywidth) + 1; const int zb = (int)((zmax-zmin)/zwidth) + 1; int xytotb = yb * xb; int totb = xytotb * zb; atomlist* flgatoms = new atomlist[totb]; atomlist* otheratoms = new atomlist[totb]; float ixwidth = 1.0f/xwidth; float iywidth = 1.0f/ywidth; float izwidth = 1.0f/zwidth; for (i=0; ixmax || yiymax || zizmax) { continue; } AtomEntry entry(xi,yi,zi,i); int axb = (int)((xi - xmin)*ixwidth); int ayb = (int)((yi - ymin)*iywidth); int azb = (int)((zi - zmin)*izwidth); // Due to floating point error in the calcuation of bin widths, we // have to range clamp the computed box indices. if (axb==xb) axb=xb-1; if (ayb==yb) ayb=yb-1; if (azb==zb) azb=zb-1; int aindex = azb*xytotb + ayb*xb + axb; // TODO maybe change so that others does not contain the atoms of flags if (others[i]) otheratoms[aindex].append(entry); if ( flgs[i]) flgatoms[aindex].append(entry); } memset(flgs, 0, num*sizeof(int)); const float r2 = (float) (r*r); // set up workspace for multithreaded calculation int nthreads; #ifdef VMDTHREADS nthreads = wkf_thread_numprocessors(); wkf_thread_t * threads = (wkf_thread_t *)calloc(nthreads, sizeof(wkf_thread_t)); #else nthreads = 1; #endif FindWithinData *data = new FindWithinData[nthreads]; for (i=0; inthreads; const int tid = data->tid; const int totb = data->totb; const int xytotb = data->xytotb; const int xb = data->xb; const int yb = data->yb; const int zb = data->zb; const float r2 = data->r2; const atomlist * flgatoms = data->flgatoms; const atomlist * otheratoms = data->otheratoms; int * flgs = data->flgs; // Loop over boxes, checking for flg atoms and other atoms within one // box of each other. When one is found, mark the flag. for (int aindex = tid; aindex 0) nbrs[n++] = aindex - xb + 1; if (xi > 0 && zi < (zb-1)) nbrs[n++] = aindex + xytotb - 1; if (yi > 0 && zi < (zb-1)) nbrs[n++] = aindex + xytotb - xb; if (xi < (xb-1) && yi < (yb-1) && zi < (zb-1)) nbrs[n++] = aindex + xytotb + xb + 1; if (xi > 0 && yi < (yb-1) && zi < (zb-1)) nbrs[n++] = aindex + xytotb + xb - 1; if (xi < (xb-1) && yi > 0 && zi < (zb-1)) nbrs[n++] = aindex + xytotb - xb + 1; if (xi > 0 && yi > 0 && zi < (zb-1)) nbrs[n++] = aindex + xytotb - xb - 1; const atomlist& boxflg = flgatoms[aindex]; // Compare the atoms in boxflg to those in nbrother int i; for (i=0; i max[i]) max[i] = maxB[i]; } // do sanity checks and complain if we've got bogus atom coordinates, // we shouldn't ever have density higher than 0.1 atom/A^3, but we'll // be generous and allow much higher densities. if (maxpairs != -1) { vec_sub(sidelen, max, min); // include estimate for atom radius (1 Angstrom) in volume determination volume = fabsf((sidelen[0] + 2.0f) * (sidelen[1] + 2.0f) * (sidelen[2] + 2.0f)); if (((numonA + numonB) / volume) > 1.0) { // msgWarn << ""vmd_gridsearch3: insane atom density"" << sendmsg; } } // I don't want the grid to get too large, otherwise I could run out // of memory. Octrees would be cool, but I'll just limit the grid size // and let the performance degrade a little for pathological systems. // Note that sqdist is what gets used for the actual distance checks; // from here on out pairdist is only used to set the grid size, so we // can set it to anything larger than the original pairdist. const int MAXBOXES = 4000000; totb = MAXBOXES + 1; float newpairdist = pairdist; float xrange = max[0]-min[0]; float yrange = max[1]-min[1]; float zrange = max[2]-min[2]; do { pairdist = newpairdist; const float invpairdist = 1.0f / pairdist; xb = ((int)(xrange*invpairdist))+1; yb = ((int)(yrange*invpairdist))+1; zb = ((int)(zrange*invpairdist))+1; xytotb = yb * xb; totb = xytotb * zb; newpairdist = pairdist * 1.26f; // cbrt(2) is about 1.26 } while (totb > MAXBOXES || totb < 1); // check for integer wraparound too // 2. Sort each atom into appropriate bins boxatomA = (int **) calloc(1, totb*sizeof(int *)); numinboxA = (int *) calloc(1, totb*sizeof(int)); maxinboxA = (int *) calloc(1, totb*sizeof(int)); if (boxatomA == NULL || numinboxA == NULL || maxinboxA == NULL) { if (boxatomA != NULL) free(boxatomA); if (numinboxA != NULL) free(numinboxA); if (maxinboxA != NULL) free(maxinboxA); // msgErr << ""Gridsearch memory allocation failed, bailing out"" << sendmsg; return NULL; // ran out of memory, bail out! } const float invpairdist = 1.0f / pairdist; for (i=0; i= xb) axb = xb-1; if (ayb >= yb) ayb = yb-1; if (azb >= zb) azb = zb-1; aindex = azb * xytotb + ayb * xb + axb; // grow box if necessary if ((num = numinboxA[aindex]) == maxinboxA[aindex]) { boxatomA[aindex] = (int *) realloc(boxatomA[aindex], (num+4)*sizeof(int)); maxinboxA[aindex] += 4; } // store atom index in box boxatomA[aindex][num] = i; numinboxA[aindex]++; } } free(maxinboxA); boxatomB = (int **) calloc(1, totb*sizeof(int *)); numinboxB = (int *) calloc(1, totb*sizeof(int)); maxinboxB = (int *) calloc(1, totb*sizeof(int)); if (boxatomB == NULL || numinboxB == NULL || maxinboxB == NULL) { if (boxatomB != NULL) free(boxatomB); if (numinboxB != NULL) free(numinboxB); if (maxinboxB != NULL) free(maxinboxB); // msgErr << ""Gridsearch memory allocation failed, bailing out"" << sendmsg; return NULL; // ran out of memory, bail out! } for (i=0; i= xb) axb = xb-1; if (ayb >= yb) ayb = yb-1; if (azb >= zb) azb = zb-1; aindex = azb * xytotb + ayb * xb + axb; // grow box if necessary if ((num = numinboxB[aindex]) == maxinboxB[aindex]) { boxatomB[aindex] = (int *) realloc(boxatomB[aindex], (num+4)*sizeof(int)); maxinboxB[aindex] += 4; } // store atom index in box boxatomB[aindex][num] = i; numinboxB[aindex]++; } } free(maxinboxB); // 3. Build pairlists of atoms less than sqrtdist apart nbrlist = (int **) calloc(1, totb*sizeof(int *)); if (make_neighborlist_sym(nbrlist, xb, yb, zb)) { if (boxatomA != NULL) { for (i=0; inext = NULL; cur = head; for (aindex = 0; aindex < totb; aindex++) { int *tmpbox, *tmpnbr, *nbr; tmpbox = boxatomA[aindex]; tmpnbr = nbrlist[aindex]; for (nbr = tmpnbr; (*nbr != -1) && (!maxpairsreached); nbr++) { int *nbrboxB = boxatomB[*nbr]; for (i=0; (i sqdist) continue; if (maxpairs > 0) { if (paircount >= maxpairs) { maxpairsreached = 1; continue; } } add_link(cur, ind1, ind2); paircount++; cur = cur->next; cur->next = NULL; } } } } for (i=0; inext; free(head); // if (maxpairsreached) // msgErr << ""gridsearch3: exceeded pairlist sanity check, aborted"" << sendmsg; return cur; } ","C" "Biophysics","maxscheurer/pycontact","examples/automation.py",".py","342","9","from PyContact.core.Scripting import PyContactJob, JobConfig # define input files and parameters job = PyContactJob(""/path/to/topology"", ""/path/to/trajectory"", ""title"", JobConfig(5.0, 2.5, 120, [0,0,1,1,0], [0,0,1,1,0], ""segid A"", ""segid B"")) # running the job on 4 cores job.runJob(4) # writing the session to file job.writeSessionToFile() ","Python" "Biophysics","maxscheurer/pycontact","tests/map_animate.py",".py","2624","95",""""""" A simple example of an animated plot """""" import numpy as np import matplotlib.pyplot as plt import matplotlib.animation as animation import matplotlib matplotlib.use(""qt5agg"") from PyContact.core.Scripting import PyContactJob, JobConfig from PyContact.core.Biochemistry import AccumulationMapIndex jobAllMD = PyContactJob(""./PyContact/exampleData/rpn11_ubq_interface-ionized.psf"", ""./PyContact/exampleData/short.dcd"", ""md_all"", JobConfig(5.0, 2.5, 120, [0,0,0,1,1,0], [0,0,0,1,1,0], ""segid UBQ"", ""segid RN11"")) jobAllMD.runJob(1) contacts = jobAllMD.analyzer.finalAccumulatedContacts map1 = [0,0,0,1,1,0] map2 = [0,0,0,1,1,0] label1 = ""UBQ"" label2 = ""RN11"" attribute = ""test"" threshold = 0.0 nsPerFrame = 1.0 minmaxresids1 = [] minmaxresids2 = [] for cont in contacts: minmaxresids1.append(int(cont.key1[AccumulationMapIndex.resid])) minmaxresids2.append(int(cont.key2[AccumulationMapIndex.resid])) x = np.arange(np.min(minmaxresids1), np.max(minmaxresids1) + 1) y = np.arange(np.min(minmaxresids2), np.max(minmaxresids2) + 1) fig, ax = plt.subplots() data = np.ones((len(x), len(y))) # data = np.random.rand(len(x), len(y)) print(data.shape) print(data) # cax = ax.matshow(data, cmap=plt.cm.gray) cax = None ttl = ax.set_title(""test"") plt.draw() minx = np.min(minmaxresids1) miny = np.min(minmaxresids2) rng = np.arange(len(contacts[0].scoreArray)) # ttl = ax.text(30, -10, ' ') def animate(i): print(i) global cax data = np.zeros((len(x), len(y))) attribute = ""Mean Score"" if attribute == ""Mean Score"": for c in contacts: r1 = int(c.key1[AccumulationMapIndex.resid]) - minx r2 = int(c.key2[AccumulationMapIndex.resid]) - miny data[r1, r2] = c.scoreArray[i] print(data[r1, r2]) cax.set_data(data) # update the data ttl.set_text(str(i)) plt.draw() return cax, # Init only required for blitting to give a clean slate. def init(): global cax data = np.zeros((len(x), len(y))) frame = 0 print(""frame: "", frame) attribute = ""Mean Score"" if attribute == ""Mean Score"": for c in contacts: r1 = int(c.key1[AccumulationMapIndex.resid]) - minx r2 = int(c.key2[AccumulationMapIndex.resid]) - miny data[r1, r2] = c.scoreArray[frame] print(data[r1, r2]) # data.fill(10) # data = np.zeros((len(x), len(y))) cax = ax.matshow(data, cmap=plt.cm.gray) ttl.set_text(""init"") plt.draw() return cax, ani = animation.FuncAnimation(fig, animate, rng, init_func=init, blit=True, repeat=False) plt.show() ","Python" "Biophysics","maxscheurer/pycontact","tests/__init__.py",".py","0","0","","Python" "Biophysics","maxscheurer/pycontact","tests/test_basic.py",".py","3256","91","from unittest import TestCase import sys from os import path from PyContact.core.ContactAnalyzer import * from PyContact.exampleData.datafiles import DCD, PSF, TPR, XTC import MDAnalysis as mda import multiprocessing multiprocessing.log_to_stderr() sys.path.append(path.dirname(path.dirname(path.abspath(__file__)))) class PsfDcdReadingTest(TestCase): def setUp(self): self.dcdfile = DCD self.psffile = PSF self.tpr = TPR self.xtc = XTC def tearDown(self): del self.dcdfile del self.psffile def test_import_dcd_file(self): mda.Universe(self.psffile, self.dcdfile) def test_import_xtc_file(self): # seg_0_Protein_chain_U # seg_1_Protein_chain_R mda.Universe(self.tpr, self.xtc) def test_singleCore_analysis(self): analyzer = Analyzer(self.psffile, self.dcdfile, 5.0, 2.5, 120, ""segid RN11"", ""segid UBQ"") analyzer.runFrameScan(1) self.assertEqual(len(analyzer.contactResults), 50) map1 = [0, 0, 1, 1, 0] map2 = [0, 0, 1, 1, 0] analyzer.runContactAnalysis(map1, map2, 1) self.assertEqual(len(analyzer.finalAccumulatedContacts), 148) hbond_sum = 0 for c in analyzer.finalAccumulatedContacts: hbond_sum += c.hbond_percentage() self.assertEqual(hbond_sum, 676.0) def test_selfInteraction_analysis(self): analyzer = Analyzer(self.psffile, self.dcdfile, 5.0, 2.5, 120, ""segid RN11"", ""self"") analyzer.runFrameScan(1) self.assertEqual(len(analyzer.contactResults), 50) map1 = [0, 0, 1, 1, 0] map2 = [0, 0, 1, 1, 0] analyzer.runContactAnalysis(map1, map2, 1) def test_zero_atomselection(self): analyzer = Analyzer(self.psffile, self.dcdfile, 5.0, 2.5, 120, ""segid A"", ""resid 100"") try: analyzer.runFrameScan(1) except: print(""Error in atom selection caught."") try: analyzer.runFrameScan(4) except: print(""Error in atom selection (multicore) caught."") def test_selfInteraction_analysis_parallel(self): analyzer = Analyzer(self.psffile, self.dcdfile, 5.0, 2.5, 120, ""segid RN11"", ""self"") analyzer.runFrameScan(2) self.assertEqual(len(analyzer.contactResults), 50) map1 = [0, 0, 1, 1, 0] map2 = [0, 0, 1, 1, 0] analyzer.runContactAnalysis(map1, map2, 1) def test_multiCore_analysis(self): analyzer = Analyzer(self.psffile, self.dcdfile, 5.0, 2.5, 120, ""segid RN11"", ""segid UBQ"") analyzer.runFrameScan(2) self.assertEqual(len(analyzer.contactResults), 50) map1 = [0, 0, 1, 1, 0] map2 = [0, 0, 1, 1, 0] analyzer.runContactAnalysis(map1, map2, 2) self.assertEqual(len(analyzer.finalAccumulatedContacts), 148) hbond_sum = 0 for c in analyzer.finalAccumulatedContacts: hbond_sum += c.hbond_percentage() self.assertEqual(hbond_sum, 676.0) def test_around_selection_patch(self): univ = mda.Universe(self.psffile, self.dcdfile) aroundText = ""segid UBQ and around 5 segid RN11"" sel = univ.select_atoms(aroundText) self.assertEqual(len(sel), 261) ","Python"