Removed docs and example from repo since documentation will be done in the wiki
This commit is contained in:
parent
4ace860436
commit
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doc/Makefile
195
doc/Makefile
@ -1,195 +0,0 @@
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# Makefile for Sphinx documentation
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#
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# You can set these variables from the command line.
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SPHINXOPTS =
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SPHINXBUILD = sphinx-build
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PAPER =
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BUILDDIR = _build
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# User-friendly check for sphinx-build
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ifeq ($(shell which $(SPHINXBUILD) >/dev/null 2>&1; echo $$?), 1)
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$(error The '$(SPHINXBUILD)' command was not found. Make sure you have Sphinx installed, then set the SPHINXBUILD environment variable to point to the full path of the '$(SPHINXBUILD)' executable. Alternatively you can add the directory with the executable to your PATH. If you don't have Sphinx installed, grab it from http://sphinx-doc.org/)
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endif
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# Internal variables.
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||||
PAPEROPT_a4 = -D latex_paper_size=a4
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PAPEROPT_letter = -D latex_paper_size=letter
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ALLSPHINXOPTS = -d $(BUILDDIR)/doctrees $(PAPEROPT_$(PAPER)) $(SPHINXOPTS) .
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# the i18n builder cannot share the environment and doctrees with the others
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I18NSPHINXOPTS = $(PAPEROPT_$(PAPER)) $(SPHINXOPTS) .
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.PHONY: help clean html dirhtml singlehtml pickle json htmlhelp qthelp devhelp epub latex latexpdf text man changes linkcheck doctest coverage gettext
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help:
|
||||
@echo "Please use \`make <target>' where <target> is one of"
|
||||
@echo " html to make standalone HTML files"
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||||
@echo " dirhtml to make HTML files named index.html in directories"
|
||||
@echo " singlehtml to make a single large HTML file"
|
||||
@echo " pickle to make pickle files"
|
||||
@echo " json to make JSON files"
|
||||
@echo " htmlhelp to make HTML files and a HTML help project"
|
||||
@echo " qthelp to make HTML files and a qthelp project"
|
||||
@echo " applehelp to make an Apple Help Book"
|
||||
@echo " devhelp to make HTML files and a Devhelp project"
|
||||
@echo " epub to make an epub"
|
||||
@echo " latex to make LaTeX files, you can set PAPER=a4 or PAPER=letter"
|
||||
@echo " latexpdf to make LaTeX files and run them through pdflatex"
|
||||
@echo " latexpdfja to make LaTeX files and run them through platex/dvipdfmx"
|
||||
@echo " text to make text files"
|
||||
@echo " man to make manual pages"
|
||||
@echo " texinfo to make Texinfo files"
|
||||
@echo " info to make Texinfo files and run them through makeinfo"
|
||||
@echo " gettext to make PO message catalogs"
|
||||
@echo " changes to make an overview of all changed/added/deprecated items"
|
||||
@echo " xml to make Docutils-native XML files"
|
||||
@echo " pseudoxml to make pseudoxml-XML files for display purposes"
|
||||
@echo " linkcheck to check all external links for integrity"
|
||||
@echo " doctest to run all doctests embedded in the documentation (if enabled)"
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@echo " coverage to run coverage check of the documentation (if enabled)"
|
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|
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clean:
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rm -rf $(BUILDDIR)/*
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|
||||
html:
|
||||
$(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html
|
||||
@echo
|
||||
@echo "Build finished. The HTML pages are in $(BUILDDIR)/html."
|
||||
|
||||
dirhtml:
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||||
$(SPHINXBUILD) -b dirhtml $(ALLSPHINXOPTS) $(BUILDDIR)/dirhtml
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@echo
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||||
@echo "Build finished. The HTML pages are in $(BUILDDIR)/dirhtml."
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|
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singlehtml:
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$(SPHINXBUILD) -b singlehtml $(ALLSPHINXOPTS) $(BUILDDIR)/singlehtml
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@echo
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@echo "Build finished. The HTML page is in $(BUILDDIR)/singlehtml."
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|
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pickle:
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$(SPHINXBUILD) -b pickle $(ALLSPHINXOPTS) $(BUILDDIR)/pickle
|
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@echo
|
||||
@echo "Build finished; now you can process the pickle files."
|
||||
|
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json:
|
||||
$(SPHINXBUILD) -b json $(ALLSPHINXOPTS) $(BUILDDIR)/json
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@echo
|
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@echo "Build finished; now you can process the JSON files."
|
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|
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htmlhelp:
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$(SPHINXBUILD) -b htmlhelp $(ALLSPHINXOPTS) $(BUILDDIR)/htmlhelp
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@echo
|
||||
@echo "Build finished; now you can run HTML Help Workshop with the" \
|
||||
".hhp project file in $(BUILDDIR)/htmlhelp."
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||||
|
||||
qthelp:
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||||
$(SPHINXBUILD) -b qthelp $(ALLSPHINXOPTS) $(BUILDDIR)/qthelp
|
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@echo
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||||
@echo "Build finished; now you can run "qcollectiongenerator" with the" \
|
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".qhcp project file in $(BUILDDIR)/qthelp, like this:"
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||||
@echo "# qcollectiongenerator $(BUILDDIR)/qthelp/mdevaluate.qhcp"
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@echo "To view the help file:"
|
||||
@echo "# assistant -collectionFile $(BUILDDIR)/qthelp/mdevaluate.qhc"
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||||
|
||||
applehelp:
|
||||
$(SPHINXBUILD) -b applehelp $(ALLSPHINXOPTS) $(BUILDDIR)/applehelp
|
||||
@echo
|
||||
@echo "Build finished. The help book is in $(BUILDDIR)/applehelp."
|
||||
@echo "N.B. You won't be able to view it unless you put it in" \
|
||||
"~/Library/Documentation/Help or install it in your application" \
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"bundle."
|
||||
|
||||
devhelp:
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||||
$(SPHINXBUILD) -b devhelp $(ALLSPHINXOPTS) $(BUILDDIR)/devhelp
|
||||
@echo
|
||||
@echo "Build finished."
|
||||
@echo "To view the help file:"
|
||||
@echo "# mkdir -p $$HOME/.local/share/devhelp/mdevaluate"
|
||||
@echo "# ln -s $(BUILDDIR)/devhelp $$HOME/.local/share/devhelp/mdevaluate"
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@echo "# devhelp"
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|
||||
epub:
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||||
$(SPHINXBUILD) -b epub $(ALLSPHINXOPTS) $(BUILDDIR)/epub
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@echo
|
||||
@echo "Build finished. The epub file is in $(BUILDDIR)/epub."
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|
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latex:
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$(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex
|
||||
@echo
|
||||
@echo "Build finished; the LaTeX files are in $(BUILDDIR)/latex."
|
||||
@echo "Run \`make' in that directory to run these through (pdf)latex" \
|
||||
"(use \`make latexpdf' here to do that automatically)."
|
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|
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latexpdf:
|
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$(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex
|
||||
@echo "Running LaTeX files through pdflatex..."
|
||||
$(MAKE) -C $(BUILDDIR)/latex all-pdf
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@echo "pdflatex finished; the PDF files are in $(BUILDDIR)/latex."
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|
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latexpdfja:
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$(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex
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@echo "Running LaTeX files through platex and dvipdfmx..."
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$(MAKE) -C $(BUILDDIR)/latex all-pdf-ja
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@echo "pdflatex finished; the PDF files are in $(BUILDDIR)/latex."
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|
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text:
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||||
$(SPHINXBUILD) -b text $(ALLSPHINXOPTS) $(BUILDDIR)/text
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@echo
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@echo "Build finished. The text files are in $(BUILDDIR)/text."
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man:
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$(SPHINXBUILD) -b man $(ALLSPHINXOPTS) $(BUILDDIR)/man
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@echo
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@echo "Build finished. The manual pages are in $(BUILDDIR)/man."
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|
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texinfo:
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$(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) $(BUILDDIR)/texinfo
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@echo
|
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@echo "Build finished. The Texinfo files are in $(BUILDDIR)/texinfo."
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||||
@echo "Run \`make' in that directory to run these through makeinfo" \
|
||||
"(use \`make info' here to do that automatically)."
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||||
|
||||
info:
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||||
$(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) $(BUILDDIR)/texinfo
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@echo "Running Texinfo files through makeinfo..."
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||||
make -C $(BUILDDIR)/texinfo info
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@echo "makeinfo finished; the Info files are in $(BUILDDIR)/texinfo."
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gettext:
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||||
$(SPHINXBUILD) -b gettext $(I18NSPHINXOPTS) $(BUILDDIR)/locale
|
||||
@echo
|
||||
@echo "Build finished. The message catalogs are in $(BUILDDIR)/locale."
|
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|
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changes:
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||||
$(SPHINXBUILD) -b changes $(ALLSPHINXOPTS) $(BUILDDIR)/changes
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||||
@echo
|
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@echo "The overview file is in $(BUILDDIR)/changes."
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linkcheck:
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$(SPHINXBUILD) -b linkcheck $(ALLSPHINXOPTS) $(BUILDDIR)/linkcheck
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@echo
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||||
@echo "Link check complete; look for any errors in the above output " \
|
||||
"or in $(BUILDDIR)/linkcheck/output.txt."
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doctest:
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||||
$(SPHINXBUILD) -b doctest $(ALLSPHINXOPTS) $(BUILDDIR)/doctest
|
||||
@echo "Testing of doctests in the sources finished, look at the " \
|
||||
"results in $(BUILDDIR)/doctest/output.txt."
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coverage:
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$(SPHINXBUILD) -b coverage $(ALLSPHINXOPTS) $(BUILDDIR)/coverage
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@echo "Testing of coverage in the sources finished, look at the " \
|
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"results in $(BUILDDIR)/coverage/python.txt."
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xml:
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$(SPHINXBUILD) -b xml $(ALLSPHINXOPTS) $(BUILDDIR)/xml
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@echo
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@echo "Build finished. The XML files are in $(BUILDDIR)/xml."
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pseudoxml:
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$(SPHINXBUILD) -b pseudoxml $(ALLSPHINXOPTS) $(BUILDDIR)/pseudoxml
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@echo
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@echo "Build finished. The pseudo-XML files are in $(BUILDDIR)/pseudoxml."
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deploy: html
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rsync -r _build/html/ /autohome/niels/public_html/mdevaluate/
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317
doc/conf.py
317
doc/conf.py
@ -1,317 +0,0 @@
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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#
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# mdevaluate documentation build configuration file, created by
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# sphinx-quickstart on Tue Nov 10 11:46:41 2015.
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#
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# This file is execfile()d with the current directory set to its
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# containing dir.
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#
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# Note that not all possible configuration values are present in this
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# autogenerated file.
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#
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# All configuration values have a default; values that are commented out
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# serve to show the default.
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import sys
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import os
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import shlex
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sys.path.insert(0, os.path.abspath('..'))
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import mdevaluate
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# If extensions (or modules to document with autodoc) are in another directory,
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# add these directories to sys.path here. If the directory is relative to the
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# documentation root, use os.path.abspath to make it absolute, like shown here.
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#sys.path.insert(0, os.path.abspath('.'))
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# -- General configuration ------------------------------------------------
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# If your documentation needs a minimal Sphinx version, state it here.
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#needs_sphinx = '1.0'
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# Add any Sphinx extension module names here, as strings. They can be
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# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
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# ones.
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extensions = [
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'sphinx.ext.autodoc',
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'sphinx.ext.doctest',
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'sphinx.ext.mathjax',
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'sphinx.ext.viewcode',
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'sphinx.ext.napoleon',
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'sphinx.ext.intersphinx',
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# 'sphinx.ext.autosummary',
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# 'sphinx.ext.inheritance_diagram',
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'sphinx_gallery.gen_gallery',
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'sphinxcontrib.github_ribbon'
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]
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# Add any paths that contain templates here, relative to this directory.
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templates_path = ['_templates']
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# The suffix(es) of source filenames.
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# You can specify multiple suffix as a list of string:
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# source_suffix = ['.rst', '.md']
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source_suffix = '.rst'
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# The encoding of source files.
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source_encoding = 'utf-8-sig'
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# The master toctree document.
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master_doc = 'index'
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# General information about the project.
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project = 'mdevaluate'
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copyright = '2017, Niels Müller'
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author = 'Niels Müller'
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# The version info for the project you're documenting, acts as replacement for
|
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# |version| and |release|, also used in various other places throughout the
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# built documents.
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#
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# The short X.Y version.
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version = mdevaluate.__version__
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# The full version, including alpha/beta/rc tags.
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release = mdevaluate.__version__
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# The language for content autogenerated by Sphinx. Refer to documentation
|
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# for a list of supported languages.
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#
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# This is also used if you do content translation via gettext catalogs.
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# Usually you set "language" from the command line for these cases.
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language = None
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# There are two options for replacing |today|: either, you set today to some
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# non-false value, then it is used:
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#today = ''
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# Else, today_fmt is used as the format for a strftime call.
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#today_fmt = '%B %d, %Y'
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# List of patterns, relative to source directory, that match files and
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# directories to ignore when looking for source files.
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exclude_patterns = ['_build']
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# The reST default role (used for this markup: `text`) to use for all
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# documents.
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#default_role = None
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# If true, '()' will be appended to :func: etc. cross-reference text.
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#add_function_parentheses = True
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# If true, the current module name will be prepended to all description
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# unit titles (such as .. function::).
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#add_module_names = True
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# If true, sectionauthor and moduleauthor directives will be shown in the
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# output. They are ignored by default.
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#show_authors = False
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# The name of the Pygments (syntax highlighting) style to use.
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pygments_style = 'sphinx'
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highlight_language = "python3"
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# A list of ignored prefixes for module index sorting.
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#modindex_common_prefix = []
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# If true, keep warnings as "system message" paragraphs in the built documents.
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#keep_warnings = False
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# If true, `todo` and `todoList` produce output, else they produce nothing.
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todo_include_todos = False
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# -- Options for HTML output ----------------------------------------------
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# The theme to use for HTML and HTML Help pages. See the documentation for
|
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# a list of builtin themes.
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html_theme = 'sphinx_rtd_theme'
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# Theme options are theme-specific and customize the look and feel of a theme
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# further. For a list of options available for each theme, see the
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# documentation.
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#html_theme_options = {}
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# Add any paths that contain custom themes here, relative to this directory.
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#html_theme_path = []
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# The name for this set of Sphinx documents. If None, it defaults to
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# "<project> v<release> documentation".
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#html_title = None
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# A shorter title for the navigation bar. Default is the same as html_title.
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#html_short_title = None
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# The name of an image file (relative to this directory) to place at the top
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# of the sidebar.
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#html_logo = None
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# The name of an image file (within the static path) to use as favicon of the
|
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# docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32
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# pixels large.
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#html_favicon = None
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# Add any paths that contain custom static files (such as style sheets) here,
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||||
# relative to this directory. They are copied after the builtin static files,
|
||||
# so a file named "default.css" will overwrite the builtin "default.css".
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html_static_path = ['_static']
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||||
# Add any extra paths that contain custom files (such as robots.txt or
|
||||
# .htaccess) here, relative to this directory. These files are copied
|
||||
# directly to the root of the documentation.
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||||
#html_extra_path = []
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||||
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||||
# If not '', a 'Last updated on:' timestamp is inserted at every page bottom,
|
||||
# using the given strftime format.
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||||
#html_last_updated_fmt = '%b %d, %Y'
|
||||
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||||
# If true, SmartyPants will be used to convert quotes and dashes to
|
||||
# typographically correct entities.
|
||||
#html_use_smartypants = True
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|
||||
# 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 <link> 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
|
||||
|
||||
# Language to be used for generating the HTML full-text search index.
|
||||
# Sphinx supports the following languages:
|
||||
# 'da', 'de', 'en', 'es', 'fi', 'fr', 'h', 'it', 'ja'
|
||||
# 'nl', 'no', 'pt', 'ro', 'r', 'sv', 'tr'
|
||||
#html_search_language = 'en'
|
||||
|
||||
# A dictionary with options for the search language support, empty by default.
|
||||
# Now only 'ja' uses this config value
|
||||
#html_search_options = {'type': 'default'}
|
||||
|
||||
# The name of a javascript file (relative to the configuration directory) that
|
||||
# implements a search results scorer. If empty, the default will be used.
|
||||
#html_search_scorer = 'scorer.js'
|
||||
|
||||
# Output file base name for HTML help builder.
|
||||
htmlhelp_basename = 'mdevaluatedoc'
|
||||
|
||||
# -- 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, 'mdevaluate.tex', 'mdevaluate Documentation',
|
||||
'mbartelm', '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 = [
|
||||
(master_doc, 'mdevaluate', 'mdevaluate Documentation',
|
||||
[author], 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 = [
|
||||
(master_doc, 'mdevaluate', 'mdevaluate Documentation',
|
||||
author, 'mdevaluate', '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
|
||||
|
||||
intersphinx_mapping = {
|
||||
'python': ('http://docs.python.org/3/', None),
|
||||
'numpy': ('http://docs.scipy.org/doc/numpy/', None),
|
||||
'ipython': ('http://ipython.org/ipython-doc/dev/', None),
|
||||
'scipy': ('http://docs.scipy.org/doc/scipy/reference/', None),
|
||||
}
|
||||
|
||||
sphinx_gallery_conf = {
|
||||
# path to your examples scripts
|
||||
'examples_dirs' : '../examples',
|
||||
# path where to save gallery generated examples
|
||||
'gallery_dirs' : 'gallery'}
|
||||
|
||||
|
||||
github_ribbon_repo = 'mdevaluate/mdevaluate'
|
||||
github_ribbon_color = 'green'
|
||||
@ -1,244 +0,0 @@
|
||||
|
||||
Contributing
|
||||
============
|
||||
|
||||
This document aims to lay out the basics of contributing code to the ``mdevaluate`` package.
|
||||
The code is managed through a git repository, hence this guides gives basic information on the usage of `git <https://git-scm.com>`_.
|
||||
Int this document the prefix ``$`` indicates commands which should be ran on a shell.
|
||||
For a brief 15 min interactive tutorial visit `try.github.org <https://try.gitbhub.org>`_.
|
||||
|
||||
|
||||
Let's start with a short introduction to the terminology.
|
||||
Python code is organized in *packages* and *modules*:
|
||||
|
||||
Modules:
|
||||
Any python file (e.g. ``test.py``) is called a module. A module can be imported (``import test``) an then used
|
||||
in other python code if in the python path, for example the working directory.
|
||||
In principle, importing a package means executing the code inside the file.
|
||||
All definitions, like variables or functions, are then available under the modules name.
|
||||
|
||||
Packages:
|
||||
Python modules can be grouped into packages. A python package is basically a folder,
|
||||
which contains at least one mandatory file ``__init__.py``. This file is the entry
|
||||
point into the module that is imported if the package is imported.
|
||||
All modules in the folder are treated as submodules, which can be accessed via
|
||||
a dot syntax, e.g. ``import package.test``. Packages can also contain sub packages.
|
||||
|
||||
A more `detailed explanation <https://docs.python.org/3/tutorial/modules.html>`_ can be found in the official python documentation.
|
||||
|
||||
Extending the documentation
|
||||
+++++++++++++++++++++++++++
|
||||
|
||||
One of the most important parts of software is its documentation.
|
||||
For modular packages like ``mdevaluate`` it's crucial to have a good coverage of the API,
|
||||
since users need to know which functions are provided and how they are used.
|
||||
To help others by extending the documentation is thereby a nice way of contributing to mdevaluate.
|
||||
|
||||
The documentation is generated with a third party tools named `Sphinx <http://www.sphinx-doc.org/en/stable/>`_.
|
||||
The contents of the documentation are based on the source code (for the reference guide)
|
||||
and documents written in the markup language *reStructuredText* (rst).
|
||||
The source of every page can be viewed in the browser through the *View page source* link in the upper right of the page.
|
||||
The name of the rst files can also be derived from the page URL.
|
||||
The rst files are placed in the ``doc`` directory of the repository.
|
||||
|
||||
Extending the documentation can be done in different ways, e.g.
|
||||
|
||||
- Correct, clarify or extend existing sections
|
||||
- Add new sections about the general use of mdevaluate
|
||||
- Add use cases to the special topics section.
|
||||
|
||||
To add a new sections to special topics, first create a new file for this guide in ``doc/special``.
|
||||
Then add the name of this file (without the .rst extension) to the toctree in the file ``special-topics.rst``.
|
||||
Now write the guide in the newly created file.
|
||||
|
||||
Building the docs
|
||||
-----------------
|
||||
|
||||
When you have made changes to the docs, first re-build them locally.
|
||||
You will need to have the ``sphinx`` python package installed and of course a working environment for ``mdevaluate``.
|
||||
When those requirements are fulfilled build the docs by:
|
||||
|
||||
1. Navigate to the ``doc`` directory
|
||||
2. Run ``make html`` in the shell
|
||||
3. View the produced html files in the browser: ``firefox _build/html/index.html``
|
||||
|
||||
Organization of the code
|
||||
++++++++++++++++++++++++
|
||||
|
||||
|
||||
|
||||
The code for the evaluation software is organized in two python packages:
|
||||
|
||||
- ``pygmx``: This package provides a python wrapper for the Gromacs library and
|
||||
thereby functionality to read file formats used within Gromacs.
|
||||
- ``mdevaluate``: This package provides functionality for evaluation of molecular
|
||||
dynamics simulations. It uses the ``pygmx`` package to read files, but is
|
||||
(in theory) not limited to Gromacs data.
|
||||
|
||||
Submodules
|
||||
----------
|
||||
|
||||
Below the content of the submodules of the package is described.
|
||||
|
||||
atoms.py
|
||||
........
|
||||
|
||||
Definition of the ``Atom`` class and related functions for atom selection and information.
|
||||
|
||||
autosave.py
|
||||
...........
|
||||
|
||||
Experimental functionality for automatic saving and loading of evaluated data,
|
||||
like correlation functions. For each function call a checksum is calculated
|
||||
from the input, which changes if the output of the function changes.
|
||||
|
||||
coordinates.py
|
||||
..............
|
||||
|
||||
Definition of the ``Coordinates`` class and ``CoordinatesMap`` for coordinates
|
||||
transformations and related functions.
|
||||
|
||||
correlation.py
|
||||
..............
|
||||
|
||||
Functionality to calculate correlation functions.
|
||||
|
||||
distribution.py
|
||||
...............
|
||||
|
||||
Functionality to calculate distribution functions.
|
||||
|
||||
reader.py
|
||||
.........
|
||||
|
||||
Defines reader classes that handle trajectory reading and caching.
|
||||
|
||||
utils.py
|
||||
........
|
||||
|
||||
A collection of utility functions.
|
||||
|
||||
Set up a development environment
|
||||
++++++++++++++++++++++++++++++++
|
||||
|
||||
.. code-block:: console
|
||||
|
||||
$ git clone https://github.com/mdevaluate/mdevaluate.git
|
||||
|
||||
Organization of the repository
|
||||
------------------------------
|
||||
|
||||
The repository is organized through git branches.
|
||||
At the moment there exist two branches in the remote repository: *master* and *dev*.
|
||||
|
||||
|
||||
Adding code to the repository
|
||||
+++++++++++++++++++++++++++++
|
||||
|
||||
All changes to the code are done in your local clone of the repository.
|
||||
If a feature is complete, or at least works, the code can be pushed to the remote,
|
||||
to make it accessible for others.
|
||||
|
||||
A standard work flow to submit new code is the following
|
||||
|
||||
1. Fork the main repository o github and clone your fork to your local machine.
|
||||
2. Create a new branch locally and apply the desired changes.
|
||||
3. If the master branch was updated, merge it into the local branch.
|
||||
4. Push the changes to github and create a pull request for your fork.
|
||||
|
||||
Pulling updates from remote
|
||||
---------------------------
|
||||
|
||||
Before working with the code, the latest updates should be pulled for the master branch
|
||||
|
||||
.. code-block:: console
|
||||
|
||||
$ git checkout master
|
||||
$ git pull
|
||||
|
||||
Create a new branch
|
||||
-------------------
|
||||
|
||||
Before changing any code, create a new branch in your local repository.
|
||||
This helps to keep an overview of all the changes and simplifies merging.
|
||||
To create a new branch locally enter the following commands
|
||||
|
||||
.. code-block:: console
|
||||
|
||||
$ git checkout master
|
||||
$ git branch my-feature
|
||||
$ git checkout my-feature
|
||||
|
||||
First switch to the master branch to make sure the new branch is based on it.
|
||||
Then create the new branch, called `my-feature` and switch to it.
|
||||
Now you can start making changes in the code.
|
||||
|
||||
Committing changes
|
||||
------------------
|
||||
|
||||
A bundle of changes in the code is called a *commit*.
|
||||
These changes can happen in different files and should be associated with each other.
|
||||
Let's assume, two files have been changed (``atoms.py`` and ``utils.py``).
|
||||
The command
|
||||
|
||||
.. code-block:: console
|
||||
|
||||
$ git diff atoms.py
|
||||
|
||||
will show you all changes that were made in the file since the latest commit.
|
||||
Before committing changes have to be *staged*, which is done by
|
||||
|
||||
.. code-block:: console
|
||||
|
||||
$ git add atoms.py utils.py
|
||||
|
||||
This my be repeated as often as necessary.
|
||||
When all changes for a commit are staged, it can actually be created
|
||||
|
||||
.. code-block:: console
|
||||
|
||||
$ git commit
|
||||
|
||||
This will open up an editor where a commit message has to be entered.
|
||||
After writing the commit message, save & close the file, which will create the commit.
|
||||
|
||||
Create Pullrequest
|
||||
------------------
|
||||
|
||||
When all changes are made and the new feature should be made public, you can open a new pull request on github.
|
||||
Most of the time, the master branch will have been updated, so first pull any updates
|
||||
|
||||
.. code-block:: console
|
||||
|
||||
$ git checkout master
|
||||
$ git pull
|
||||
|
||||
When the master branch is up to date, it can be merged into the feature branch
|
||||
|
||||
.. code-block:: console
|
||||
|
||||
$ git checkout my-feature
|
||||
$ git merge master
|
||||
|
||||
If no conflicting changes were made, merging works automatically.
|
||||
If for example the same line was modified in a commit in master and your commits, a merge conflict will occur.
|
||||
Git tells you which files have conflicts and asks you to resolve these.
|
||||
The respective lines will be marked with conflict-resolution markers in the files.
|
||||
The most basic way of resolving a conflict is by editing these files and choosing the appropriate version of the code.
|
||||
See the `git documentation <https://git-scm.com/book/en/v2/Git-Branching-Basic-Branching-and-Merging#Basic-Merge-Conflicts>`_ for an explanation.
|
||||
After resolving the conflict, the files need to be staged and the merge has to be committed
|
||||
|
||||
.. code-block:: console
|
||||
|
||||
$ git add utils.py
|
||||
$ git commit
|
||||
|
||||
The commit message will be generated automatically, indicating the merge.
|
||||
|
||||
After merging, the changes can be pushed to the remote
|
||||
|
||||
.. code-block:: console
|
||||
|
||||
$ git push
|
||||
|
||||
The new code is now available in the remote.
|
||||
@ -1,50 +0,0 @@
|
||||
Evaluation of dynamic properties
|
||||
================================
|
||||
|
||||
Dynamic properties like mean square displacement are calculated with the
|
||||
function :func:`mdevaluate.correlation.shifted_correlation`.
|
||||
This function takes a correlation function and calculates the averaged
|
||||
time series of it, by shifting a time interval over the trajectory.
|
||||
|
||||
::
|
||||
|
||||
from mdevaluate import correlation
|
||||
|
||||
time, msd_amim = correlation.shifted_correlation(correlation.msd, com_amim, average=True)
|
||||
plot(time,msd_amim)
|
||||
|
||||
The result of :func:`shifted_correlation` are two lists, the first one (``time``)
|
||||
contains the times of the frames that have been used for the correlation.
|
||||
The second list ``msd_amim`` is the correlation function at these times.
|
||||
If the keyword ``average=False`` is given, the correlation function for each shifted
|
||||
time window will be returned.
|
||||
|
||||
Arguments of ``shifted_correlation``
|
||||
------------------------------------
|
||||
|
||||
The function :func:`mdevaluate.correlation.shifted_correlation` accepts several keyword arguments.
|
||||
With those arguments, the calculation of the correlation function may be controlled in detail.
|
||||
The mathematical expression for a correlation function is the following:
|
||||
|
||||
.. math:: S(t) = \frac{1}{N} \sum_{i=1}^N C(f, R, t_i, t)
|
||||
|
||||
Here :math:`S(t)` denotes the correlation function at time t, :math:`R` are the coordinates of all atoms
|
||||
and :math:`t_i` are the onset times (:math:`N` is the number of onset times or time windows).
|
||||
Note that the outer sum and division by :math:`N` is only carried out if ``average=True``.
|
||||
The onset times are defined by the keywords ``segments`` and ``window``, with
|
||||
:math:`N = segments` and :math:`t_i = \frac{ (1 - window) \cdot t_{max}}{N} (i - 1)` with the total simulation time :math:`t_{max}`.
|
||||
As can be seen ``segments`` gives the number of onset times and ``window`` defines the part of the simulation time the correlation is calculated for,
|
||||
hence ``window - 1`` is the part of the simulation the onset times a distributed over.
|
||||
|
||||
|
||||
:math:`C(f, R, t_0, t)` is the function that actually correlates the function :math:`f`.
|
||||
For standard correlations the functions :math:`C(...)` and :math:`f` are defined as:
|
||||
|
||||
.. math:: C(f, R, t_0, t) = f(R(t_0), R(t_0 + t))
|
||||
|
||||
.. math:: f(r_0, r) = \langle s(r_0, r) \rangle
|
||||
|
||||
Here the brackets denote an ensemble average, small :math:`r` are coordinates of one frame and :math:`s(r_0, r)` is the value that is correlated,
|
||||
e.g. for the MSD :math:`s(r_0, r) = (r - r_0)^2`.
|
||||
|
||||
The function :math:`C(f, R, t_0, t)` is specified by the keyword ``correlation``, the function :math:`f(r_0, r)` is given by ``function``.
|
||||
@ -1,80 +0,0 @@
|
||||
General Hints for Python Programming
|
||||
====================================
|
||||
|
||||
This page collects some general hints for data centered programming with Python.
|
||||
Some resources for tutorials on the topics can be found here:
|
||||
|
||||
* http://www.scipy-lectures.org/
|
||||
* The `Python Data Science Handbook <https://jakevdp.github.io/PythonDataScienceHandbook/>`_, by Jake VanderPlas
|
||||
* PyCon-Talk on Numpy arrays: `Losing Your Loops, by Jake VanderPlas <https://www.youtube.com/watch?v=EEUXKG97YRw>`_
|
||||
|
||||
Programming Environments
|
||||
------------------------
|
||||
|
||||
There exist different environments for Python programming, each with their pros and cons.
|
||||
Some examples are:
|
||||
|
||||
* **IPython Console**: The most basic way to use Python is on the interactive console, the ipython console is a suffisticated Python console. After the mdevaluate module is loaded, ipython can be started with the command ``ipython``.
|
||||
* **Jupyter Notebook**: Provides a Mathematica-style notebook, which is accesed through a web browser. After the mdevaluate module is loaded a (local) notebook server can be started with the command ``jupyter-notebook``. See the help menu in the notebook for a short introduction and http://jupyter.org/ for a detailed user guide.
|
||||
* **Atom Editor**: When developing more complex code, like modules an editor comes in handy. Besides basic preinstalled editors (e.g. Gedit) the `atom editor <https://atom.io>`_ is a nice option. Recommended atpm packages for Python development are: language-python, autocomplete-python and linter-flake8.
|
||||
|
||||
Common Pitfalls
|
||||
---------------
|
||||
|
||||
* **For-Loops**: The biggest pitfall of data-intensive Python programming are ``for``-loops. Those loops perform bad in Python, but can be avoided in most cases through Numpy arrays, see the mentioned talk by Jake VdP.
|
||||
* **Non-Portable Code**: Most non-programmers tend to write complex scripts. It's always advisable to source out your code into seperate Python modules (i.e. seperate files) and split the code into reusable functions. Since these modules can be imported from any Python code, this will save time in the long run and often reduces errors.
|
||||
|
||||
|
||||
Pandas Dataframes
|
||||
-----------------
|
||||
|
||||
Most data in Mdevaluate is handled as Numpy arrays.
|
||||
For example the function :func:`~mdevaluate.correlation.shifted_correlation` returns a multidimensional array, which contains the time steps and the value of the correlation function.
|
||||
As pointed out above, those arrays a good for computation and can be used to plot data with, e.g. matplotlib.
|
||||
But often there is metadata associated with this data, for example the temperature or the specific subset of atoms that were analyzed.
|
||||
This is the point where **`Pandas dataframes <http://pandas.pydata.org/>`_** come in handy.
|
||||
Dataframes are most basically tables of samples, with named columns.
|
||||
The dataframe class allows easy acces of columns by label and complex operations, like grouping by columns or merging different datasets.
|
||||
|
||||
As an example say we have simulations at some temperatures and want to calculate the ISF and do a KWW-Fit for each of these trajectories.
|
||||
Details of the analysis will be explained at a later point of this document, thereby they will be omitted here::
|
||||
|
||||
import pandas
|
||||
datasets = []
|
||||
|
||||
for T in [250, 260, 270, 280, 290, 300]:
|
||||
# calculate the isf for this temperature
|
||||
t, Sqt = ...
|
||||
|
||||
# DataFrames can be created from dictionaries
|
||||
datasets.append(pandas.DataFrame({'time': t, 'Sqt': Sqt, 'T': T}))
|
||||
|
||||
# join the individual dataframes into one
|
||||
isf_data = pandas.concat(datasets)
|
||||
|
||||
# Now calculate the KWW fits for each temperature
|
||||
from scipy.optimize import curve_fit
|
||||
from mdevaluate.functions import kww
|
||||
kww_datasets = []
|
||||
# The isf data is grouped by temperature,
|
||||
# that is the loop iterates over all T values and the part of the data where isf_data['T'] == T
|
||||
for T, data in isf_data.groupby('T'):
|
||||
fit, cuv = curve_fit(kww, data['time'], data['Sqt'])
|
||||
# DataFrames can also be cerated from arrays and a defintion of columns
|
||||
df = pandas.DataFrame(fit, columns=['A', 'τ', 'β'])
|
||||
# columns can be added dynamically
|
||||
df['T'] = T
|
||||
kww_datasets.append(df)
|
||||
kww_data = pandas.concat(kww_datasets)
|
||||
|
||||
# We have two dataframes now, one with time series of the ISF at each temperature
|
||||
# and one with the fit parameters of the KWW for each temperature
|
||||
|
||||
# We can merge this data into one dataframe, by the overlapping columns (i.e. 'T' in this example)
|
||||
data = pandas.merge(isf_data, kww_data)
|
||||
# We can now compute the kww fit value of each sample point of the isf in one line:
|
||||
data['kww_fit'] = kww(data['time'], data['A'], data['τ'], data['β'])
|
||||
# And plot the data, resolved by temperature.
|
||||
for T, df in data.groupby('T'):
|
||||
plot(df['time'], df['Sqt'], 'o') # The actual correlation value
|
||||
plot(df['time'], df['kww_fit'], '-') # The kww fit
|
||||
@ -1,11 +0,0 @@
|
||||
|
||||
User Guide
|
||||
==========
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 2
|
||||
|
||||
loading
|
||||
static-evaluation
|
||||
dynamic-evaluation
|
||||
special-topics
|
||||
@ -1,29 +0,0 @@
|
||||
.. mdevaluate documentation master file, created by
|
||||
sphinx-quickstart on Tue Nov 10 11:46:41 2015.
|
||||
You can adapt this file completely to your liking, but it should at least
|
||||
contain the root `toctree` directive.
|
||||
|
||||
Documentation of mdevaluate
|
||||
===========================
|
||||
|
||||
A python package for evaluation of molecular dynamics simulation data.
|
||||
|
||||
Contents
|
||||
--------
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 1
|
||||
|
||||
installation
|
||||
general-hints
|
||||
guide
|
||||
gallery/index
|
||||
contributing
|
||||
modules
|
||||
|
||||
Indices and tables
|
||||
------------------
|
||||
|
||||
* :ref:`genindex`
|
||||
* :ref:`modindex`
|
||||
* :ref:`search`
|
||||
@ -1,44 +0,0 @@
|
||||
Installation
|
||||
============
|
||||
|
||||
Mdevaluate itself is a pure Python package and can be imported directly from the source directory, if needed.
|
||||
The Gromacs dependency pygmx has to be installed into the Python distribution,
|
||||
since parts are compiled with Cython.
|
||||
|
||||
Requirements
|
||||
------------
|
||||
|
||||
The package depends on some python packages that can all be installed via pip or conda:
|
||||
|
||||
- Python 3.5 (or higher)
|
||||
- NumPy
|
||||
- SciPy
|
||||
|
||||
|
||||
Install pygmx & mdevaluate
|
||||
---------------------------
|
||||
|
||||
To instal pygmx, first get the source from its repository, https://github.com/mdevaluate/pygmx.
|
||||
Installation instructions are given in the respective readme file.
|
||||
Two steps have to be performed:
|
||||
|
||||
1. Install Gromacs 2016
|
||||
2. Install pygmx
|
||||
|
||||
When this requirement is met, installing mdevaluate simply means getting the source code from the repository and running
|
||||
|
||||
python setup.py install
|
||||
|
||||
form within the source directory.
|
||||
|
||||
|
||||
Running Tests
|
||||
-------------
|
||||
|
||||
Some tests are included with the source that can be used too test the installation.
|
||||
The testsuite requires `pytest <https://pytest.org>`_.
|
||||
To run the test simply execute
|
||||
|
||||
pytest
|
||||
|
||||
in the source directory.
|
||||
115
doc/loading.rst
115
doc/loading.rst
@ -1,115 +0,0 @@
|
||||
Loading of simulation data
|
||||
==========================
|
||||
|
||||
Mdevaulate provides a convenient function :func:`mdevaluate.load_simulation`
|
||||
that loads a simulation more or less automatically.
|
||||
It takes a path as input and looks for all files it needs in this directory.
|
||||
|
||||
For information about the topology either a `tpr` or `gro` a file is read,
|
||||
where the former is the preferred choice.
|
||||
Trajectory data will be read from a xtc file.
|
||||
If the directory contains more than one file of any type, the desired file
|
||||
has to be specified with the appropriate keyword argument.
|
||||
For details see :func:`mdevaluate.open`.
|
||||
|
||||
The function will return a coordinates object, for the whole system.
|
||||
A subset of the system may be obtained directly from the coordinates object by
|
||||
calling its :func:`~mdevaluate.coordinates.Coordinates.subset` method.
|
||||
This function accepts the same input as :func:`mdevaluate.atoms.AtomSubset.subset`.
|
||||
A new feature that was introduced in the function is the possibility to chose
|
||||
atoms with regular expressions.
|
||||
|
||||
Example
|
||||
-------
|
||||
|
||||
The following code loads the example trajectory and selects a subset of all CW atoms.
|
||||
Since there are two CW atoms in each molecule (CW1 and CW2) a regular expression is
|
||||
used when selecting the subset.
|
||||
|
||||
::
|
||||
|
||||
import mdevaluate as md
|
||||
|
||||
trajectory = md.open('/data/niels/tutorial')
|
||||
CW_atoms = trajectory.subset(atom_name='CW.')
|
||||
|
||||
And that's it, now one can evaluate stuff for this subset of atoms.
|
||||
|
||||
Selecting a subset
|
||||
------------------
|
||||
|
||||
As shown in the example above it is often necessary to select a subset of the system for analysis.
|
||||
This can be a special group of atoms (e.g. all C atoms) or a whole residue for which the center of mass should be computed.
|
||||
Subsets are selected with the :func:`~mdevaluate.Coordinates.subset` method of Coordinates objects.
|
||||
|
||||
This method accepts four keyword arguments, with which the atom name, residue name and residue id or atom indices can be specified.
|
||||
The former two name arguments accept a regular expression which allows two include several different names in one subset.
|
||||
Some examples:
|
||||
|
||||
- All carbon atoms (which are named CW1, CT1, CA, ...): ``tr.subset(atom_name='C.*')``
|
||||
- Atoms NA1, NA2 and OW: ``tr.subset(atom_name='NA.|OW')``
|
||||
- All oxygen atoms of residue EG: ``tr.subset(atom_name='O.*', residue_name='EG')``
|
||||
|
||||
|
||||
Specifying data files
|
||||
---------------------
|
||||
|
||||
The above example only works if the directory contains exactly one tpr file and
|
||||
one xtc file.
|
||||
If your data files are located in subdirectories or multiple files of these types exist,
|
||||
they can be specified by the keywords ``topology`` and ``trajectory``.
|
||||
Those filenames can be a relative path to the simulation directory and can also make
|
||||
use of *shell globing*. For example::
|
||||
|
||||
traj = md.open('/path/to/sim', topology='atoms.gro', trajectory='out/traj_*.xtc')
|
||||
|
||||
Note that the topology can be specified as a gro file, with the limitation that
|
||||
only atom and residue names will be read from those files.
|
||||
Information about atom masses and charges for example will only be read from tpr files,
|
||||
therefore it is generally recommended to use the latter topologies.
|
||||
|
||||
The trajectory above is specified through a shell globing, meaning the ``*`` may be
|
||||
expanded to any string (without containing a forward slash).
|
||||
If more than one file exists which match this pattern an error will be raised,
|
||||
since the trajectory can not be identified clearly.
|
||||
|
||||
Caching of frames
|
||||
-----------------
|
||||
|
||||
One bottleneck in the analysis of MD data is the reading speed of the trajectory.
|
||||
In many cases frames will be needed repeatedly and hence the amount of time spend reading
|
||||
data from disk (or worse over the network) is huge.
|
||||
Therefore the mdevaluate package implements a simple caching mechanism, which holds
|
||||
on to a number of read frames.
|
||||
The downside if this is increased memory usage which may slow down the computation too.
|
||||
|
||||
Caching is done on the level of the trajectory readers, so that all ``Coordinate`` and
|
||||
``CoordinateMap`` objects working on the same trajectory will be sharing a cache.
|
||||
Caching has to be activated when opening a trajectory::
|
||||
|
||||
traj = md.open('/path/to/sim', cached=True)
|
||||
|
||||
The ``cached`` keyword takes either a boolean, a integer or None as input value.
|
||||
The value of ``cached`` controls the size of the cache and thereby the additional memory usage.
|
||||
Setting it to True will activate the caching with a maximum size of 128 frames,
|
||||
with an integer any other maximum size may be set.
|
||||
The special value ``None`` will set the cache size to infinite, so all frames will be cached.
|
||||
This will prevent the frames from being loaded twice but can also consume a whole lot of memory,
|
||||
since a single frame can easily take 1 MB of memory.
|
||||
|
||||
Clearing cached frames
|
||||
++++++++++++++++++++++
|
||||
|
||||
In some scenarios it may be advisable to free cached frames which are no longer needed.
|
||||
For this case the reader has a function ``clear_cache()``.
|
||||
The current state of the cache can be displayed with the ``cache_info`` property::
|
||||
|
||||
>>> traj.frames.cache_info
|
||||
CacheInfo(hits=12, misses=20, maxsize=128, currsize=20)
|
||||
>>> traj.frames.clear_cache()
|
||||
>>> traj.frames.cache_info
|
||||
CacheInfo(hits=0, misses=0, maxsize=128, currsize=0)
|
||||
|
||||
Clearing the cache when it is not needed anymore is advisable since this will help the
|
||||
Python interpreter to reuse the memory.
|
||||
|
||||
263
doc/make.bat
263
doc/make.bat
@ -1,263 +0,0 @@
|
||||
@ECHO OFF
|
||||
|
||||
REM Command file for Sphinx documentation
|
||||
|
||||
if "%SPHINXBUILD%" == "" (
|
||||
set SPHINXBUILD=sphinx-build
|
||||
)
|
||||
set BUILDDIR=_build
|
||||
set ALLSPHINXOPTS=-d %BUILDDIR%/doctrees %SPHINXOPTS% .
|
||||
set I18NSPHINXOPTS=%SPHINXOPTS% .
|
||||
if NOT "%PAPER%" == "" (
|
||||
set ALLSPHINXOPTS=-D latex_paper_size=%PAPER% %ALLSPHINXOPTS%
|
||||
set I18NSPHINXOPTS=-D latex_paper_size=%PAPER% %I18NSPHINXOPTS%
|
||||
)
|
||||
|
||||
if "%1" == "" goto help
|
||||
|
||||
if "%1" == "help" (
|
||||
:help
|
||||
echo.Please use `make ^<target^>` where ^<target^> is one of
|
||||
echo. html to make standalone HTML files
|
||||
echo. dirhtml to make HTML files named index.html in directories
|
||||
echo. singlehtml to make a single large HTML file
|
||||
echo. pickle to make pickle files
|
||||
echo. json to make JSON files
|
||||
echo. htmlhelp to make HTML files and a HTML help project
|
||||
echo. qthelp to make HTML files and a qthelp project
|
||||
echo. devhelp to make HTML files and a Devhelp project
|
||||
echo. epub to make an epub
|
||||
echo. latex to make LaTeX files, you can set PAPER=a4 or PAPER=letter
|
||||
echo. text to make text files
|
||||
echo. man to make manual pages
|
||||
echo. texinfo to make Texinfo files
|
||||
echo. gettext to make PO message catalogs
|
||||
echo. changes to make an overview over all changed/added/deprecated items
|
||||
echo. xml to make Docutils-native XML files
|
||||
echo. pseudoxml to make pseudoxml-XML files for display purposes
|
||||
echo. linkcheck to check all external links for integrity
|
||||
echo. doctest to run all doctests embedded in the documentation if enabled
|
||||
echo. coverage to run coverage check of the documentation if enabled
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "clean" (
|
||||
for /d %%i in (%BUILDDIR%\*) do rmdir /q /s %%i
|
||||
del /q /s %BUILDDIR%\*
|
||||
goto end
|
||||
)
|
||||
|
||||
|
||||
REM Check if sphinx-build is available and fallback to Python version if any
|
||||
%SPHINXBUILD% 2> nul
|
||||
if errorlevel 9009 goto sphinx_python
|
||||
goto sphinx_ok
|
||||
|
||||
:sphinx_python
|
||||
|
||||
set SPHINXBUILD=python -m sphinx.__init__
|
||||
%SPHINXBUILD% 2> nul
|
||||
if errorlevel 9009 (
|
||||
echo.
|
||||
echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
|
||||
echo.installed, then set the SPHINXBUILD environment variable to point
|
||||
echo.to the full path of the 'sphinx-build' executable. Alternatively you
|
||||
echo.may add the Sphinx directory to PATH.
|
||||
echo.
|
||||
echo.If you don't have Sphinx installed, grab it from
|
||||
echo.http://sphinx-doc.org/
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
:sphinx_ok
|
||||
|
||||
|
||||
if "%1" == "html" (
|
||||
%SPHINXBUILD% -b html %ALLSPHINXOPTS% %BUILDDIR%/html
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Build finished. The HTML pages are in %BUILDDIR%/html.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "dirhtml" (
|
||||
%SPHINXBUILD% -b dirhtml %ALLSPHINXOPTS% %BUILDDIR%/dirhtml
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Build finished. The HTML pages are in %BUILDDIR%/dirhtml.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "singlehtml" (
|
||||
%SPHINXBUILD% -b singlehtml %ALLSPHINXOPTS% %BUILDDIR%/singlehtml
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Build finished. The HTML pages are in %BUILDDIR%/singlehtml.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "pickle" (
|
||||
%SPHINXBUILD% -b pickle %ALLSPHINXOPTS% %BUILDDIR%/pickle
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Build finished; now you can process the pickle files.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "json" (
|
||||
%SPHINXBUILD% -b json %ALLSPHINXOPTS% %BUILDDIR%/json
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Build finished; now you can process the JSON files.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "htmlhelp" (
|
||||
%SPHINXBUILD% -b htmlhelp %ALLSPHINXOPTS% %BUILDDIR%/htmlhelp
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Build finished; now you can run HTML Help Workshop with the ^
|
||||
.hhp project file in %BUILDDIR%/htmlhelp.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "qthelp" (
|
||||
%SPHINXBUILD% -b qthelp %ALLSPHINXOPTS% %BUILDDIR%/qthelp
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Build finished; now you can run "qcollectiongenerator" with the ^
|
||||
.qhcp project file in %BUILDDIR%/qthelp, like this:
|
||||
echo.^> qcollectiongenerator %BUILDDIR%\qthelp\mdevaluate.qhcp
|
||||
echo.To view the help file:
|
||||
echo.^> assistant -collectionFile %BUILDDIR%\qthelp\mdevaluate.ghc
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "devhelp" (
|
||||
%SPHINXBUILD% -b devhelp %ALLSPHINXOPTS% %BUILDDIR%/devhelp
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Build finished.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "epub" (
|
||||
%SPHINXBUILD% -b epub %ALLSPHINXOPTS% %BUILDDIR%/epub
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Build finished. The epub file is in %BUILDDIR%/epub.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "latex" (
|
||||
%SPHINXBUILD% -b latex %ALLSPHINXOPTS% %BUILDDIR%/latex
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Build finished; the LaTeX files are in %BUILDDIR%/latex.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "latexpdf" (
|
||||
%SPHINXBUILD% -b latex %ALLSPHINXOPTS% %BUILDDIR%/latex
|
||||
cd %BUILDDIR%/latex
|
||||
make all-pdf
|
||||
cd %~dp0
|
||||
echo.
|
||||
echo.Build finished; the PDF files are in %BUILDDIR%/latex.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "latexpdfja" (
|
||||
%SPHINXBUILD% -b latex %ALLSPHINXOPTS% %BUILDDIR%/latex
|
||||
cd %BUILDDIR%/latex
|
||||
make all-pdf-ja
|
||||
cd %~dp0
|
||||
echo.
|
||||
echo.Build finished; the PDF files are in %BUILDDIR%/latex.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "text" (
|
||||
%SPHINXBUILD% -b text %ALLSPHINXOPTS% %BUILDDIR%/text
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Build finished. The text files are in %BUILDDIR%/text.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "man" (
|
||||
%SPHINXBUILD% -b man %ALLSPHINXOPTS% %BUILDDIR%/man
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Build finished. The manual pages are in %BUILDDIR%/man.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "texinfo" (
|
||||
%SPHINXBUILD% -b texinfo %ALLSPHINXOPTS% %BUILDDIR%/texinfo
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Build finished. The Texinfo files are in %BUILDDIR%/texinfo.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "gettext" (
|
||||
%SPHINXBUILD% -b gettext %I18NSPHINXOPTS% %BUILDDIR%/locale
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Build finished. The message catalogs are in %BUILDDIR%/locale.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "changes" (
|
||||
%SPHINXBUILD% -b changes %ALLSPHINXOPTS% %BUILDDIR%/changes
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.The overview file is in %BUILDDIR%/changes.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "linkcheck" (
|
||||
%SPHINXBUILD% -b linkcheck %ALLSPHINXOPTS% %BUILDDIR%/linkcheck
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Link check complete; look for any errors in the above output ^
|
||||
or in %BUILDDIR%/linkcheck/output.txt.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "doctest" (
|
||||
%SPHINXBUILD% -b doctest %ALLSPHINXOPTS% %BUILDDIR%/doctest
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Testing of doctests in the sources finished, look at the ^
|
||||
results in %BUILDDIR%/doctest/output.txt.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "coverage" (
|
||||
%SPHINXBUILD% -b coverage %ALLSPHINXOPTS% %BUILDDIR%/coverage
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Testing of coverage in the sources finished, look at the ^
|
||||
results in %BUILDDIR%/coverage/python.txt.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "xml" (
|
||||
%SPHINXBUILD% -b xml %ALLSPHINXOPTS% %BUILDDIR%/xml
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Build finished. The XML files are in %BUILDDIR%/xml.
|
||||
goto end
|
||||
)
|
||||
|
||||
if "%1" == "pseudoxml" (
|
||||
%SPHINXBUILD% -b pseudoxml %ALLSPHINXOPTS% %BUILDDIR%/pseudoxml
|
||||
if errorlevel 1 exit /b 1
|
||||
echo.
|
||||
echo.Build finished. The pseudo-XML files are in %BUILDDIR%/pseudoxml.
|
||||
goto end
|
||||
)
|
||||
|
||||
:end
|
||||
@ -1,83 +0,0 @@
|
||||
|
||||
Module contents
|
||||
---------------
|
||||
|
||||
.. automodule:: mdevaluate
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
mdevaluate.autosave
|
||||
...................
|
||||
|
||||
.. automodule:: mdevaluate.autosave
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
mdevaluate.atoms
|
||||
................
|
||||
|
||||
.. automodule:: mdevaluate.atoms
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
mdevaluate.coordinates
|
||||
......................
|
||||
|
||||
.. automodule:: mdevaluate.coordinates
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
mdevaluate.correlation
|
||||
......................
|
||||
|
||||
.. automodule:: mdevaluate.correlation
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
mdevaluate.distribution
|
||||
.......................
|
||||
|
||||
.. automodule:: mdevaluate.distribution
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
mdevaluate.evaluation
|
||||
.....................
|
||||
|
||||
mdevaluate.functions
|
||||
....................
|
||||
|
||||
.. automodule:: mdevaluate.functions
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
mdevaluate.pbc
|
||||
..............
|
||||
|
||||
.. automodule:: mdevaluate.pbc
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
mdevaluate.reader
|
||||
.....................
|
||||
|
||||
.. automodule:: mdevaluate.reader
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
mdevaluate.utils
|
||||
.....................
|
||||
|
||||
.. automodule:: mdevaluate.utils
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,9 +0,0 @@
|
||||
.. _reference-guide:
|
||||
|
||||
Reference Guide
|
||||
===============
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 4
|
||||
|
||||
mdevaluate
|
||||
@ -1,12 +0,0 @@
|
||||
|
||||
Special Topics
|
||||
==============
|
||||
|
||||
This part of the documentation describes advanced ways of the use of mdevaluate.
|
||||
|
||||
.. toctree::
|
||||
|
||||
special/autosave
|
||||
special/spatial
|
||||
special/overlap
|
||||
special/energies
|
||||
@ -1,93 +0,0 @@
|
||||
Automatic Saving of Analysis Data
|
||||
=================================
|
||||
|
||||
Mdevaluate provides a functionality to save the result of analysis functions automatically.
|
||||
The data is saved to a file after it was computed.
|
||||
If an analysis was done in the exact same way before, the result is loaded from this file.
|
||||
|
||||
This function may be activated through calling :func:`mdevaluate.autosave.enable`, which takes a directory as input.
|
||||
If this directory is a relative path (e.g. no trailing slash) the results will be saved in a location
|
||||
relative to the directory of the trajectory file.
|
||||
If the output files of your simulations are located in a subdirectory, like ``/path/to/sim/Output`` it is possible
|
||||
to specify the auto save location as ``../data`` such that the result files will be placed under ``/path/to/sim/data``.
|
||||
|
||||
At the moment the two functions which use this behavior are:
|
||||
|
||||
- :func:`~mdevaluate.correlation.shifted_correlation`
|
||||
- :func:`~mdevaluate.distribution.time_average`
|
||||
|
||||
Any other function can make use of the autosave mechanism by decorating it with :func:`mdevaluate.autosave.autosave_data`.
|
||||
|
||||
A full example
|
||||
--------------
|
||||
|
||||
This is how it works, for a detailed explanation see below::
|
||||
|
||||
import mdevaluate as md
|
||||
md.autosave.enable('data')
|
||||
water = md.open('/path/to/sim').subset(atom_name='OW')
|
||||
md.correlation.shifted_correlation(
|
||||
md.correlation.msd,
|
||||
water,
|
||||
description='test'
|
||||
)
|
||||
# The result will be saved to the file:
|
||||
# /path/to/sim/data/shifted_correlation_msd_OW_test.npz
|
||||
|
||||
Checksum of the Analysis Call
|
||||
-----------------------------
|
||||
|
||||
The autosave module calculates a checksum for each call of an analysis function,
|
||||
which is used to validate a present the data file.
|
||||
This way the result should only be loaded from file if the analysis is exactly the same.
|
||||
This includes the function code that is evaluated, so the result will be recomputed if any bit of the code changes.
|
||||
But there is always the possibility that checksums coincide accidentally,
|
||||
by chance or due to a bug in the code, which should be kept in mind when using this functionality.
|
||||
|
||||
Special Keyword Arguments
|
||||
-------------------------
|
||||
|
||||
The autosave module introduces two special keyword arguments to the decorated functions:
|
||||
|
||||
- ``autoload``: This prevents the loading of previously calculated data even if a valid file was found.
|
||||
- ``description``: A descriptive string of the specific analysis, see below.
|
||||
|
||||
Those keywords may be passed to those function (shifted_correlation, time_average) like any other keyword argument.
|
||||
If autosave was not enabled, they will be ignored.
|
||||
|
||||
File names and Analysis Descriptions
|
||||
------------------------------------
|
||||
|
||||
The evaluated data is saved to human readable files, whose name is derived from the function call
|
||||
and the automatic description of the subset.
|
||||
The latter one is assigned based on the ``atom_name`` and ``residue_name`` of the :func:`~mdevaluate.atoms.AtomSubset.subset` method.
|
||||
|
||||
In some cases this is not enough, for example if the same subset is analyzed spatially resolved,
|
||||
which would lead to identical filenames that would be overwritten.
|
||||
Therefore a more detailed description of each specific analysis call needs to be provided.
|
||||
For this reason the autosave module introduces the before mentioned keyword argument ``description``.
|
||||
The value of this keyword is appended to the filename and in addition if any of
|
||||
the other arguments of the function call has a attribute description, this will appended as well.
|
||||
For example this (pseudo) code will lead to the filename ``shifted_correlation_isf_OW_1-2nm_nice.npz``::
|
||||
|
||||
OW = traj.subset(atom_name='OW')
|
||||
|
||||
corr = subensemble_correlation(spatial_selector)
|
||||
corr.description = '1-2nm'
|
||||
|
||||
shifted_correlation(
|
||||
isf,
|
||||
OW,
|
||||
correlation=corr,
|
||||
description='nice'
|
||||
)
|
||||
|
||||
|
||||
Reusing the autosaved data
|
||||
--------------------------
|
||||
|
||||
The results of the functions are saved in NumPy's npz format, see :func:`numpy.savez`.
|
||||
If the result should be used in a different place, it can either be loaded with
|
||||
:func:`numpy.load` or :func:`mdevaluate.autosave.load_data`.
|
||||
The latter function will return the result of the function call directly, the former
|
||||
returns a dict with the keys ``checksum`` and ``data``, the latter yielding the results data.
|
||||
@ -1,18 +0,0 @@
|
||||
Gromacs Energy Files
|
||||
====================
|
||||
|
||||
It is possible to read the energy files (.edr) written out by Gromacs with mdevaluate.
|
||||
Those files contain thermodynamic properties of the system, like temperature or pressure.
|
||||
The exact contents of an energy file depend on the type of ensemble that was simulated,
|
||||
an NVT simulation's energy file for example will not contain information about the box size.
|
||||
|
||||
To open these files use the function :func:`mdevaluate.open_energy`, which takes the filename of an energy file.
|
||||
The types of energies stored in the file can be shown with the :attr:`types` attribute of the class :class:`~mdevaluate.reader.EnergyReader`,
|
||||
the :attr:`units` attribute gives the units of these energy types.
|
||||
The timesteps at which those energies were written out are accessible through the :attr:`~mdevaluate.reader.EnergyReader.time` property.
|
||||
The time series of one of these energies can be accessed through the named index, comparable to python dictionaries.
|
||||
::
|
||||
import mdevaluate as md
|
||||
edr = md.open_energy('/path/to/energy.edr')
|
||||
# plot the evolution of temperature
|
||||
plot(edr.time, edr['Temperature'])
|
||||
@ -1,76 +0,0 @@
|
||||
Computing the Overlap Function
|
||||
==============================
|
||||
|
||||
The overlap function is defined as the portion of particles of a given set,
|
||||
whose positions *overlap* after a given time :math:`t` with the reference configuration at :math:`t=0`.
|
||||
This is calculated as follows:
|
||||
The Initial positions define spheres of a given radius :math:`r` which then are used
|
||||
to test how many of the particles at a later time are found within those spheres.
|
||||
Normalized by the number of spheres this gives the correlation of the configurational overlap.
|
||||
|
||||
.. math::
|
||||
|
||||
Q(t) = \frac{1}{N} \left\langle \sum\limits_{i=1}^N n_i(t) \right\rangle
|
||||
|
||||
Where :math:`n_i(t)` defines the :math:`N` spheres, with :math:`n_i(t)=1` if a particle
|
||||
is found within this sphere at time :math:`t` and :math:`n_i(0) = 1` for :math:`1\leq i \leq N`.
|
||||
|
||||
Evaluation with mdevaluate
|
||||
--------------------------
|
||||
|
||||
Computation of the overlap requires the relatively expensive computation of next neighbor distances,
|
||||
which scales with the order of :math:`\mathcal{O}(N^2)`.
|
||||
There are more efficient ways for the solution of this problem, the one used here is
|
||||
the so called :class:`~scipy.spatial.cKDTree`.
|
||||
This is much more efficient and allows to compute the overlap relatively fast::
|
||||
|
||||
OW = md.open('/path/to/sim').subset(atom_name='OW')
|
||||
tree = md.coordinates.CoordinatesKDTree(OW)
|
||||
Qol = md.correlation.shifted_correlation(
|
||||
partial(md.correlation.overlap, crds_tree=tree, radius=0.11),
|
||||
OW
|
||||
)
|
||||
|
||||
As seen above, mdevaluate provides the function :func:`~mdevaluate.correlation.overlap`
|
||||
for this evaluation, which uses a special object of type :class:`~mdevaluate.coordinates.CoordinatesKDTree`
|
||||
for the neighbor search.
|
||||
The latter provides two features, necessary for the computation:
|
||||
First it computes a :class:`~scipy.spatial.cKDTree` for each necessary frame of the trajectory;
|
||||
second it caches those trees, since assembly of KDTrees is expensive.
|
||||
The size of the cache can be controlled with the keyword argument ``maxsize`` of the CoordinatesKDTree initialization.
|
||||
|
||||
Note that this class uses the C version (hence the lowercase C) rather than
|
||||
the pure Python version :class:`~scipy.spatial.KDTree` since the latter is significantly slower.
|
||||
The only downside is, that the C version had a memory leak before SciPy 0.17,
|
||||
but as long as a recent version of SciPy is used, this shouldn't be a problem.
|
||||
|
||||
Overlap of a Subsystem
|
||||
----------------------
|
||||
|
||||
In many cases the overlap of a subsystem, e.g. a spatial region, should be computed.
|
||||
This is done by selecting a subset of the initial configuration before defining the spheres.
|
||||
The overlap is then probed with the whole system.
|
||||
This has two benefits:
|
||||
|
||||
1. It yields the correct results
|
||||
2. The KDTree structures are smaller and thereby less computation and memory expensive
|
||||
|
||||
An example of a spatial resolved analysis, where ``OW`` is loaded as above::
|
||||
|
||||
selector = partial(
|
||||
md.coordinates.spatial_selector,
|
||||
transform=md.coordinates.spherical_radius,
|
||||
rmin=1.0,
|
||||
rmax=1.5
|
||||
)
|
||||
tree = md.coordinates.CoordinatesKDTree(OW, selector=selector)
|
||||
Qol = md.correlation.shifted_correlation(
|
||||
partial(md.correlation.overlap, crds_tree=tree, radius=0.11),
|
||||
OW
|
||||
)
|
||||
|
||||
This computes the overlap of OW atoms in the region :math:`1.0 \leq r \leq 1.5`.
|
||||
This method can of course be used to probe the overlap of any subsystem, which is selected by the given selector function.
|
||||
It should return a viable index for a (m, 3) sized NumPy array when called with original frame of size (N, 3)::
|
||||
|
||||
subset = frame[selector(frame)]
|
||||
@ -1,38 +0,0 @@
|
||||
Spatial Resolved Analysis
|
||||
=========================
|
||||
|
||||
This section describes how spatially resolved correlation can be analyzed with mdevaluate.
|
||||
This guide assumes that the variable ``traj`` holds a trajectory where the subset of atoms that should be analyzed are selected.
|
||||
For example::
|
||||
|
||||
traj = md.open('/path/to/sim', cached=1000).subset(atom_name='OW')
|
||||
|
||||
Which would load a simulation from the directory ``/path/to/sim`` and select all ``OW`` atoms.
|
||||
Note that for this use case, the caching is quite useful since it enables us to iterate over spatial regions
|
||||
without significant time penalty.
|
||||
Moving on let's calculate the ISF of water oxygens with spherical radius between 0.5 and 0.7 nm::
|
||||
|
||||
from functools import partial
|
||||
func = partial(md.correlation.isf, q=22.7)
|
||||
selector = partial(
|
||||
md.coordinates.spatial_selector,
|
||||
transform=md.coordinates.spherical_radius,
|
||||
rmin=0.5, rmax=0.7
|
||||
)
|
||||
t, S = md.correlation.shifted_correlation(
|
||||
func, traj,
|
||||
correlation=md.correlation.subensemble_correlation(selector)
|
||||
)
|
||||
|
||||
To explain how this works, let's go through the code from bottom to top.
|
||||
The spatial filtering is done inside the shifted_correlation by the function
|
||||
:func:`mdevaluate.correlation.subensemble_correlation`.
|
||||
This function takes a selector function as argument that should take a frame as input
|
||||
and return the selection of the coordinates that should be selected.
|
||||
A new selection is taken for the starting frame of each shifted time segment.
|
||||
|
||||
In this case the selection is done with the function :func:`mdevaluate.coordinates.spatial_selector`.
|
||||
This function takes four arguments, the first being the frame of coordinates which is handed by :func:`subensemble_correlation`.
|
||||
The second argument is a transformation function, which transforms the input coordinates to the coordinate which will be filtered,
|
||||
in this case the spherical radius.
|
||||
The two last arguments define the minimum and maximum value of this quantity.
|
||||
@ -1,76 +0,0 @@
|
||||
|
||||
Evaluation of static properties
|
||||
===============================
|
||||
|
||||
.. note::
|
||||
All examples in this section assume, that the packages has been imported and a trajectory was loaded::
|
||||
|
||||
import mdevaluate.distribution as dist
|
||||
|
||||
coords = mdevaluate.open('/path/to/simulation')
|
||||
|
||||
Static properties of the system, like density distribution or pair correlation function,
|
||||
can be evaluated with the :mod:`mdevaluate.distribution` module.
|
||||
It provides the function :func:`mdevaluate.distribution.time_average`
|
||||
that computes the average of a property over the whole trajectory.
|
||||
An example call of this function is::
|
||||
|
||||
tetra = dist.time_average(dist.tetrahedral_order, coords)
|
||||
|
||||
This will calculate the average of the tetrahedral order parameter for each atom.
|
||||
The first argument of :func:`time_average` is a function that takes one argument.
|
||||
It will be called for each frame in the trajectory and the output of this function
|
||||
is than averaged over all these frames.
|
||||
|
||||
Slicing of the trajectory
|
||||
-------------------------
|
||||
|
||||
In most cases averaging each frame of the trajectory is not necessary,
|
||||
since the conformation of the atoms doesn't change significantly between two frames.
|
||||
Hence it is sufficient to skip some frames without suffering significant statistics.
|
||||
The exact amount of frames which can be skipped before the statistics suffer depends strongly
|
||||
on the calculated property, therefore it has to be chosen manually.
|
||||
For this purpose the Coordinates objects can be sliced like any python list::
|
||||
|
||||
tetra = dist.time_average(dist.tetrahedral_order, coords[1000::50])
|
||||
|
||||
This makes it possible to skip a number of frames at the start (or end) and with every step.
|
||||
The above call would start with frame 1000 of the trajectory and evaluate each 50th frame until the end.
|
||||
Since the number of frames read and evaluated is reduced by about a factor of 50, the computational cost will decrease accordingly.
|
||||
|
||||
Calculating distributions
|
||||
-------------------------
|
||||
|
||||
In many cases the static distributions of a property is of interest.
|
||||
For example, the tetrahedral order parameter is often wanted as a distribution.
|
||||
This can too be calculated with ``time_average`` but the bins of the distribution have to be specified::
|
||||
|
||||
from functools import partial
|
||||
func = partial(dist.tetrahedral_order_distribution, bins=np.linspace(-3, 1, 401)
|
||||
tetra_dist = dist.time_average(func, coords)
|
||||
|
||||
The bins (which are ultimately used with the function :func:`numpy.histogram`) are specified
|
||||
by partially evaluating the evaluation function with :func:`functools.partial`.
|
||||
See the documentation of :func:`numpy.histogram` for details on bin specification.
|
||||
|
||||
.. note::
|
||||
If :func:`numpy.histogram` is used with :func:`time_average` the bins have to be given explicitly.
|
||||
When not specified, the bins will be chosen automatically for each call of ``histogram`` leading to
|
||||
different bins for each frame, hence an incorrect average.
|
||||
|
||||
Advanced evaluations
|
||||
--------------------
|
||||
|
||||
The function that will be evaluated by ``time_average`` can return numpy arrays of arbitrary shape.
|
||||
It is for example possible to calculate the distribution of a property for several subsets of the system at once::
|
||||
|
||||
def subset_tetra(frame, bins):
|
||||
tetra = dist.tetrahedral_order(frame)
|
||||
return array([np.histogram(tetra[0::2], bins=bins),
|
||||
np.histogram(tetra[1::2], bins=bins),])
|
||||
|
||||
func = partial(subset, bins=np.linspace(-1,1,201))
|
||||
tetra_subdist = dist.time_average(func, coords)
|
||||
|
||||
In this example the tetrahedral order parameter is first calculated for each atom of the system.
|
||||
Then the distribution is calculated for two subsets, containing atoms (0, 2, 4, 6, ...) and (1, 3, 5, 7, ...).
|
||||
@ -1,2 +0,0 @@
|
||||
Example Gallery
|
||||
===============
|
||||
@ -1,47 +0,0 @@
|
||||
r"""
|
||||
Four-Point susceptibility
|
||||
=========================
|
||||
|
||||
The dynamic four-point susceptibility :math:`\chi_4(t)` is a measure for heterogenous dynamics. [Berthier]_
|
||||
It can be calculated from the variance of the incoherent intermediate scattering function
|
||||
:math:`F_q(t)`.
|
||||
|
||||
.. math::
|
||||
\chi_4 (t) = N\cdot\left( \left\langle F_q^2(t) \right\rangle - \left\langle F_q(t) \right\rangle^2 \right)
|
||||
|
||||
This is astraight forward calculation in mdevaluate.
|
||||
First calculate the ISF without time average and then take the variance along the first axis of this data.
|
||||
Note that this quantity requires good statistics, hence it is adviced to use a small time window
|
||||
and a sufficient number of segments for the analysis.
|
||||
Another way to reduce scatter is to smooth the data with a running mean,
|
||||
calling :func:`~mdevaluate.utils.runningmean` as shown below.
|
||||
|
||||
.. [Berthier] http://link.aps.org/doi/10.1103/Physics.4.42
|
||||
"""
|
||||
|
||||
from functools import partial
|
||||
import matplotlib.pyplot as plt
|
||||
import mdevaluate as md
|
||||
import tudplot
|
||||
|
||||
OW = md.open('/data/niels/sim/water/bulk/260K', trajectory='out/*.xtc').subset(atom_name='OW')
|
||||
|
||||
t, Fqt = md.correlation.shifted_correlation(
|
||||
partial(md.correlation.isf, q=22.7),
|
||||
OW,
|
||||
average=False,
|
||||
window=0.2,
|
||||
skip=0.1,
|
||||
segments=20
|
||||
)
|
||||
chi4 = len(OW[0]) * Fqt.var(axis=0)
|
||||
|
||||
tudplot.activate()
|
||||
|
||||
plt.plot(t, chi4, 'h', label=r'$\chi_4$')
|
||||
plt.plot(t[2:-2], md.utils.moving_average(chi4, 5), '-', label='smoothed')
|
||||
|
||||
plt.semilogx()
|
||||
plt.xlabel('time / ps')
|
||||
plt.ylabel('$\\chi_4$')
|
||||
plt.legend(loc='best')
|
||||
@ -1,30 +0,0 @@
|
||||
"""
|
||||
Calculating the ISF of Water
|
||||
=======================================================
|
||||
|
||||
In this example the ISF of water oxygens is calculated for a bulk simulation.
|
||||
Additionally a KWW function is fitted to the results.
|
||||
"""
|
||||
from functools import partial
|
||||
import matplotlib.pyplot as plt
|
||||
from scipy.optimize import curve_fit
|
||||
import mdevaluate as md
|
||||
import tudplot
|
||||
|
||||
OW = md.open('/data/niels/sim/water/bulk/260K', trajectory='out/*.xtc').subset(atom_name='OW')
|
||||
t, S = md.correlation.shifted_correlation(
|
||||
partial(md.correlation.isf, q=22.7),
|
||||
OW,
|
||||
average=True
|
||||
)
|
||||
# Only include data-points of the alpha-relaxation for the fit
|
||||
mask = t > 3e-1
|
||||
fit, cov = curve_fit(md.functions.kww, t[mask], S[mask])
|
||||
tau = md.functions.kww_1e(*fit)
|
||||
|
||||
tudplot.activate()
|
||||
plt.figure()
|
||||
plt.plot(t, S, '.', label='ISF of Bulk Water')
|
||||
plt.plot(t, md.functions.kww(t, *fit), '-', label=r'KWW, $\tau$={:.2f}ps'.format(tau))
|
||||
plt.xscale('log')
|
||||
plt.legend()
|
||||
@ -1,121 +0,0 @@
|
||||
"""
|
||||
Spatially resolved analysis in a cylindrical pore
|
||||
=======================================================
|
||||
|
||||
Calculate the spatially resolved ISF inside a cylindrical neutral water pore
|
||||
In this case the bins describe the shortest distance of an oxygen atom to any wall atom
|
||||
"""
|
||||
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
import mdevaluate as md
|
||||
import tudplot
|
||||
from scipy import spatial
|
||||
from scipy.optimize import curve_fit
|
||||
|
||||
#trajectory with index file
|
||||
#TODO eine allgemeinere stelle?
|
||||
traj = md.open('/data/robin/sim/nvt/12kwater/240_r25_0_NVT',
|
||||
trajectory='nojump.xtc', index_file='indexSL.ndx',topology='*.gro')
|
||||
#Liquid oxygens
|
||||
LO = traj.subset(indices= traj.atoms.indices['LH2O'])
|
||||
#Solid oxygens
|
||||
SO = traj.subset(indices= traj.atoms.indices['SH2O'])
|
||||
#Solid oxygens and bonded hydrogens
|
||||
SW = traj.subset(residue_id = SO.atom_subset.residue_ids)
|
||||
|
||||
#TODO die folgenden beiden zusammen sind nochmal deutlich schneller als
|
||||
#md.atom.distance_to_atoms, kannst du entweder in irgendeiner weise einbauen
|
||||
#oder hier lassen, man muss aber auf thickness achten, dass das sinn macht
|
||||
#adds periodic layers of the atoms
|
||||
def pbc_points(points, box_vector, thickness=0, index=False, inclusive=True):
|
||||
coordinates = np.copy(points)%box_vector
|
||||
allcoordinates = np.copy(coordinates)
|
||||
indices = np.tile(np.arange(len(points)),(27))
|
||||
for x in range(-1, 2, 1):
|
||||
for y in range(-1, 2, 1):
|
||||
for z in range(-1, 2, 1):
|
||||
vv = np.array([x, y, z], dtype=float)
|
||||
if not (vv == 0).all() :
|
||||
allcoordinates = np.concatenate((allcoordinates, coordinates + vv*box_vector), axis=0)
|
||||
|
||||
if thickness != 0:
|
||||
mask = np.all(allcoordinates < box_vector+thickness, axis=1)
|
||||
allcoordinates = allcoordinates[mask]
|
||||
indices = indices[mask]
|
||||
mask = np.all(allcoordinates > -thickness, axis=1)
|
||||
allcoordinates = allcoordinates[mask]
|
||||
indices = indices[mask]
|
||||
if not inclusive:
|
||||
allcoordinates = allcoordinates[len(points):]
|
||||
indices = indices[len(points):]
|
||||
if index:
|
||||
return (allcoordinates, indices)
|
||||
return allcoordinates
|
||||
|
||||
#fast calculation of shortest distance from one subset to another, uses pbc_points
|
||||
def distance_to_atoms(ref, observed_atoms, box=None, thickness=0.5):
|
||||
if box is not None:
|
||||
start_coords = np.copy(observed_atoms)%box
|
||||
all_frame_coords = pbc_points(ref, box, thickness = thickness)
|
||||
else:
|
||||
start_coords = np.copy(observed_atoms)
|
||||
all_frame_coords = np.copy(ref)
|
||||
|
||||
tree = spatial.cKDTree(all_frame_coords)
|
||||
first_neighbors = tree.query(start_coords)[0]
|
||||
return first_neighbors
|
||||
|
||||
#this is used to reduce the number of wall atoms to those relevant, speeds up the rest
|
||||
dist = distance_to_atoms(LO[0], SW[0], np.diag(LO[0].box))
|
||||
wall_atoms = SW.atom_subset.indices[0]
|
||||
wall_atoms = wall_atoms[dist < 0.35]
|
||||
SW = traj.subset(indices = wall_atoms)
|
||||
|
||||
from functools import partial
|
||||
func = partial(md.correlation.isf, q=22.7)
|
||||
|
||||
#selector function to choose liquid oxygens with a certain distance to wall atoms
|
||||
def selector_func(coords, lindices, windices, dmin, dmax):
|
||||
lcoords = coords[lindices]
|
||||
wcoords = coords[windices]
|
||||
dist = distance_to_atoms(wcoords, lcoords,box=np.diag(coords.box))
|
||||
#radial distance to pore center to ignore molecules that entered the wall
|
||||
rad = np.sum((lcoords[:,:2]-np.diag(coords.box)[:2]/2)**2,axis=1)**.5
|
||||
return lindices[(dist >= dmin) & (dist < dmax) & (rad < 2.7)]
|
||||
|
||||
#calculate the shifted correlation for several bins
|
||||
#bin positions are roughly the average of the limits
|
||||
bins = np.array([0.15,0.2,0.3,0.4,0.5,0.8,1.0,1.4,1.8,2.3])
|
||||
binpos = (bins[1:]+bins[:-1])/2
|
||||
S = np.empty(len(bins)-1, dtype='object')
|
||||
for i in range(len(bins)-1):
|
||||
selector = partial(selector_func,lindices=LO.atom_subset.indices[0],
|
||||
windices=SW.atom_subset.indices[0],dmin=bins[i],
|
||||
dmax = bins[i+1])
|
||||
t, S[i] = md.correlation.shifted_correlation(
|
||||
func, traj,segments=50, skip=0.1,average=True,
|
||||
correlation=md.correlation.subensemble_correlation(selector),
|
||||
description=str(bins[i])+','+str(bins[i+1]))
|
||||
|
||||
taus = np.zeros(len(S))
|
||||
tudplot.activate()
|
||||
plt.figure()
|
||||
for i,s in enumerate(S):
|
||||
pl = plt.plot(t, s, '.', label='d = ' + str(binpos[i]) + ' nm')
|
||||
#only includes the relevant data for 1/e fitting
|
||||
mask = s < 0.6
|
||||
fit, cov = curve_fit(md.functions.kww, t[mask], s[mask],
|
||||
p0=[1.0,t[t>1/np.e][-1],0.5])
|
||||
taus[i] = md.functions.kww_1e(*fit)
|
||||
plt.plot(t, md.functions.kww(t, *fit), c=pl[0].get_color())
|
||||
plt.xscale('log')
|
||||
plt.legend()
|
||||
#plt.show()
|
||||
|
||||
tudplot.activate()
|
||||
plt.figure()
|
||||
plt.plot(binpos, taus,'.',label=r'$\tau$(d)')
|
||||
plt.yscale('log')
|
||||
plt.legend()
|
||||
#plt.show()
|
||||
@ -1,17 +0,0 @@
|
||||
"""
|
||||
Plotting the Temperature from an Energy File
|
||||
============================================
|
||||
|
||||
This example reads an Gromacs energy file and plots the evolultion and mean of the temperature.
|
||||
"""
|
||||
|
||||
from matplotlib import pyplot as plt
|
||||
import mdevaluate as md
|
||||
import tudplot
|
||||
|
||||
tudplot.activate()
|
||||
|
||||
edr = md.open_energy('/data/niels/sim/water/bulk/300K/out/energy_water1000bulk300.edr')
|
||||
T = edr['Temperature']
|
||||
plt.plot(edr.time, T)
|
||||
plt.plot(edr.time[[0, -1]], [T.mean(), T.mean()])
|
||||
Loading…
Reference in New Issue
Block a user