{ "info": { "author": "pyMOR developers", "author_email": "pymor-dev@listserv.uni-muenster.de", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: Science/Research", "License :: OSI Approved :: BSD License", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Topic :: Scientific/Engineering :: Mathematics" ], "description": "pyMOR - Model Order Reduction with Python\n=========================================\n\npyMOR is a software library for building model order\nreduction applications with the Python programming language. Implemented\nalgorithms include reduced basis methods for parametric linear and non-linear\nproblems, as well as system-theoretic methods such as balanced truncation or\nIRKA. All algorithms in pyMOR are formulated in terms of abstract interfaces\nfor seamless integration with external PDE solver packages. Moreover, pure\nPython implementations of finite element and finite volume discretizations\nusing the NumPy/SciPy scientific computing stack are\nprovided for getting started quickly.\n\n[![Docs](https://readthedocs.org/projects/pymor/badge/?version=latest)](https://pymor.readthedocs.org)\n[![DOI](https://zenodo.org/badge/9220688.svg)](https://zenodo.org/badge/latestdoi/9220688)\n[![Build Status](https://travis-ci.org/pymor/pymor.png?branch=master)](https://travis-ci.org/pymor/pymor)\n\n\nLicense\n-------\n\nCopyright 2013-2018 pyMOR developers and contributors. All rights reserved.\n\nRedistribution and use in source and binary forms, with or without modification, are permitted provided that the\nfollowing conditions are met:\n\n* Redistributions of source code must retain the above copyright notice, this list of conditions and the following\n disclaimer.\n* Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following\n disclaimer in the documentation and/or other materials provided with the distribution.\n\nTHIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES,\nINCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\nDISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,\nSPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR\nSERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,\nWHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF\nTHIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n\n\nThe following files contain source code originating from other open source software projects:\n\n* docs/source/pymordocstring.py (sphinxcontrib-napoleon)\n* src/pymor/algorithms/genericsolvers.py (SciPy)\n\nSee these files for more information.\n\n\nCiting\n------\n\nIf you use pyMOR for academic work, please consider citing our\n[publication](https://epubs.siam.org/doi/abs/10.1137/15M1026614):\n\n\tR. Milk, S. Rave, F. Schindler\n\tpyMOR - Generic Algorithms and Interfaces for Model Order Reduction\n\tSIAM J. Sci. Comput., 38(5), pp. S194-S216\n\n\n\nInstallation via pip\n--------------------\n\nWe recommend installation of pyMOR in a [virtual environment](https://virtualenv.pypa.io/en/latest/>).\n\npyMOR can easily be installed with the [pip](https://pip.pypa.io/en/stable/)\ncommand:\n\n pip install --upgrade pip # make sure that pip is reasonably new\n pip install pymor[full]\n\nThis will install the latest release of pyMOR on your system with most optional\ndependencies.\nFor Linux we provide binary wheels, so no further system packages should\nbe required. Use\n\n pip install pymor\n\nfor an installation with minimal dependencies.\nThere are some optional packages not included with `pymor[full]`\nbecause they need additional setup on your system:\n\n # for support of MPI distributed models and parallelization of\n # greedy algorithms (requires MPI development headers and a C compiler)\n pip install mpi4py\n\n # dense matrix equation solver for system-theoretic MOR methods,\n # required for H-infinity norm calculation (requires OpenBLAS headers and a Fortran compiler)\n pip install slycot\n\n # sparse matrix equation solver for system-theoretic MOR methods\n # (other backends available)\n open https://www.mpi-magdeburg.mpg.de/projects/mess\n # download and install pymess wheel for your architecture\n\nIf you are not operating in a virtual environment, you can pass the optional `--user`\nargument to pip. pyMOR will then only be installed for your\nlocal user, not requiring administrator privileges.\n\nTo install the latest development version of pyMOR, execute\n\n pip install git+https://github.com/pymor/pymor#egg=pymor[full]\n\nwhich will require that the [git](https://git-scm.com/) version control system is\ninstalled on your system.\n\nFrom time to time, the master branch of pyMOR undergoes major changes and things\nmight break (this is usually announced on our\n[mailing list](http://listserv.uni-muenster.de/mailman/listinfo/pymor-dev)),\nso you might prefer to install pyMOR from the current release branch:\n\n pip install git+https://github.com/pymor/pymor@0.5.x#egg=pymor[full]\n\nRelease branches will always stay stable and will only receive bugfix commits\nafter the corresponding release has been made.\n\n\nDocumentation\n-------------\n\nDocumentation is available online at [Read the Docs](https://pymor.readthedocs.org/)\nor you can build it yourself from inside the root directory of the pyMOR source tree\nby executing:\n\n make doc\n\nThis will generate HTML documentation in `docs/_build/html`.\n\n\nExternal PDE solvers\n--------------------\n\npyMOR has been designed with easy integration of external PDE solvers\nin mind.\n\nA basic approach is to use the solver only to generate high-dimensional\nsystem matrices which are then read by pyMOR from disk (`pymor.discretizers.disk`).\nAnother possibility is to steer the solver via an appropriate network\nprotocol.\n\nWhenever possible, we recommend to recompile the solver as a\nPython extension module which gives pyMOR direct access to the solver without\nany communication overhead. A basic example using\n[pybindgen](https://github.com/gjcarneiro/pybindgen) can be found in\n`src/pymordemos/minimal_cpp_demo`. A more elaborate nonlinear example\nusing [Boost.Python](http://www.boost.org/) can be found\n[here](https://github.com/pymor/dune-burgers-demo). Moreover,\nwe provide bindings for the following solver libraries:\n\n* [FEniCS](http://fenicsproject.org)\n\n MPI-compatible wrapper classes for dolfin linear algebra data structures are\n shipped with pyMOR (`pymor.bindings.fenics`).\n For an example see `pymordemos.thermalbock`, `pymordemos.thermalblock_simple`.\n\n* [deal.II](https://dealii.org)\n\n Python bindings and pyMOR wrapper classes can be found\n [here](https://github.com/pymor/pymor-deal.II).\n\n* [NGSolve](https://ngsolve.org)\n\n Wrapper classes for the NGSolve finite element library are shipped with pyMOR\n (`pymor.bindings.ngsolve`).\n For an example see `pymordemos.thermalblock_simple`.\n\n\nDo not hesitate to contact\n[us](http://listserv.uni-muenster.de/mailman/listinfo/pymor-dev) if you\nneed help with the integration of your PDE solver.\n\n\nSetting up an Environment for pyMOR Development\n-----------------------------------------------\n\nIf you already installed a pyMOR release version, please uninstall it\n\n pip uninstall pyMOR\n\nThen, clone the pyMOR git repository using\n\n git clone https://github.com/pymor/pymor $PYMOR_SOURCE_DIR\n cd $PYMOR_SOURCE_DIR\n\nand, optionally, switch to the branch you are interested in, e.g.\n\n git checkout 0.5.x\n\nThen, make an editable installation of pyMOR with\n\n pip install -e .\n\nand pull in all optional dependencies by using\n\n pip install -r requirements-optional.txt\n\n\nTests\n-----\n\npyMOR uses [pytest](https://pytest.org/) for unit testing. To run the test suite,\nsimply execute `make test` in the base directory of the pyMOR repository. This\nwill also create a test coverage report which can be found in the `htmlcov`\ndirectory. Alternatively, you can run `make full-test` which will also enable\n[pyflakes](https://pypi.python.org/pypi/pyflakes) and\n[pep8](https://www.python.org/dev/peps/pep-0008/) checks.\n\nAll tests are contained within the `src/pymortests` directory and can be run\nindividually by executing `py.test src/pymortests/the_module.py`.\n\n\nContact\n-------\n\nShould you have any questions regarding pyMOR or wish to contribute,\ndo not hestitate to contact us via our development mailing list:\n\n\n\n\n", "description_content_type": "text/markdown", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "http://pymor.org", "keywords": "", "license": "LICENSE.txt", "maintainer": "Rene Milk", "maintainer_email": "rene.milk@wwu.de", "name": "pymor", "package_url": "https://pypi.org/project/pymor/", "platform": "", "project_url": "https://pypi.org/project/pymor/", "project_urls": { "Homepage": "http://pymor.org" }, "release_url": 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