Package: pyJac
pyJacThis utility creates source code to calculate the Jacobian matrix
analytically for a chemical reaction mechanism.DocumentationThe full documentation for pyJac can be found athttp://slackha.github.io/pyJac/.User GroupFurther support can be found at ouruser
group, or byopening an
issueon our github repo.InstallationDetailed installation instructions can be found in thefull
documentation. The easiest way to
install pyJac is viaconda. You can install to your environment with> conda install -c slackha pyjacpyJac can also be installed from PyPI using pip:pip install pyjacor, using the downloaded source code, installed as a Python module:> python setup.py installUsagepyJac can be run as a python module:> python -m pyjac [options]The generated source code is placed within theout(by default)
directory, which is created if it doesn’t exist initially. See the
documentation or usepython pyjac-hfor the full list of options.TheoryTheory, derivations, validation and performance testing can be found in
the paper fully describing version 1.0.2 of pyJac:https://niemeyer-research-group.github.io/pyJac-paper/, now published
viahttps://doi.org/10.1016/j.cpc.2017.02.004and available openly via`arXiv:1605.03262[physics.comp-ph]<https://arxiv.org/abs/1605.03262>`__.LicensepyJac is released under the MIT license; see theLICENSEfor
details.If you use this package as part of a scholarly publication, please seeCITATION.mdfor the appropriate citation(s).ContributingWe welcome contributions to pyJac! Please see the guide to making
contributions in theCONTRIBUTING.mdfile.Code of ConductIn order to have a more open and welcoming community, pyJac adheres to a
code of conduct adapted from theContributor
Covenantcode of conduct.Please adhere to this code of conduct in any interactions you have in
the pyJac community. It is strictly enforced on all official pyJac
repositories, websites, and resources. If you encounter someone
violating these terms, please let a maintainer
([@kyleniemeyer](https://github.com/kyleniemeyer) or
[@arghdos](https://github.com/arghdos), via email atslackha@googlegroups.com) know and we will address it as soon as
possible.AuthorsCreated byKyle Niemeyer(kyle.niemeyer@gmail.com) and Nicholas Curtis (arghdos@gmail.com)Change LogAll notable changes to this project will be documented in this file.The format is based onKeep a Changelogand this project adheres toSemantic
Versioning.[1.0.6] - 2018-02-21AddedDOI for 1.0.4FixedSyntax errors in readme.mdConda install instructions in install.mdCorrected TRange columns in parserMinor documentation fixesAddedAdd check to reactions to test that all species existDuplicate warning from falloff->chemically-activated TROE reactions
for zero-parametersAdd handling of non-unity default third body efficiencyChangedBump internal version to 1.0.5.c[1.0.5.b0] - 2017-06-02AddedAdded usergroup info to README and documentationFixedChangedNow strip whitespace from mechanism file lines prior to parsing
keywordsRemovedRemoved plotting scripts specific to first paper on pyJac1.0.4- 2017-04-18AddedAdds Travis config for automatic PyPI and conda buildsAdds minimal unittest test suite for module importsAdds code of conductChangedChanged README back to Markdown for simplicityUpdated citation instructions1.0.3- 2017-04-01FixedFix for SRI Falloff functions with non-default third bodies (issue
#12)Fixed removal of jac/rate lists before libgen of functional_testerFixed pywrap module importChangedIssue warning in Cantera parsing if the installed version doesn’t
have access to species thermo properties.AddedAdded significantly more documentation and examples for data
ordering, the state vector / Jacobian, and using the python interface1.0.2- 2017-01-18AddedAdded CHANGELOGAdded documentation for libgen / pywrap featuresChangedMinor compilation fixes for including OpenMPUpdated github links to point to SLACKHA / Niemeyer Research GroupDeprecatedShared library creation for CUDA disabled, as CUDA does not allow
linkage of SO’s into another CUDA kernelFixedExplicitly conserve mass in PaSRMinor path fixesDivision by zero in some TROE parameter cases1.0.1- 2016-05-25AddedAdded GPU macros, e.g., THREAD_ID, GRID_SIZEChangedMuch better handling of removal of files created during testingFixedBugfix that generates data.bin files correctly from .npy files for
performance testing (important)Explicit setting of OpenMP # threads for performance testing1.0- 2016-05-07AddedpyJac is now a Python packagepyJac can now create a static/shared library for a mechanism (for
external linkage)Added documentationAdded examplesChangedHandles CUDA compilation better via Cythonpointers are now restricted where appropriatebetter Python3 compatibilityFixedother minor bugfixes0.9.1-beta- 2015-10-29ChangedImplemented the strict mass conservation formulationUpdated CUDA implementation such that it is testable vs. pyJac
c-version (and Cantera where applicable)More robust build folder managementMore robust mapping for strict mass conservation0.9-beta - 2015-10-02AddedFirst working / tested version of pyJacCitation of pyJacIf you use pyJac in a scholarly article, please cite it directly asKyle E. Niemeyer and Nicholas J. Curtis (2017). pyJac v1.0.4
[Software]. Zenodo.https://doi.org/10.5281/zenodo.######A BibTeX entry for LaTeX users isBibTeX entry:@misc{pyJac,
    author ={Kyle E Niemeyer and Nicholas J Curtis},
    year = 2017,
    title ={{pyJac}v1.0.4},
    doi ={10.5281/zenodo.######},
    url ={https://github.com/slackha/pyJac},}In both cases, please update the entry with the version used. The DOI
for the latest version can be found in the badge at the top. If you
would like to cite a specific, older version, the DOIs for each release
are:v1.0.4:10.5281/zenodo.555950v1.0.3:10.5281/zenodo.439682v1.0.2:10.5281/zenodo.251144