{ "info": { "author": "Kevin Thornton", "author_email": "krthornt@uci.edu", "bugtrack_url": null, "classifiers": [ "Intended Audience :: Science/Research", "License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)", "Topic :: Scientific/Engineering :: Bio-Informatics" ], "description": "fwdpy11\n*************************\n\nThis is the README for fwdpy11_, which is a Python package for forward-time population genetic simulation. It uses\nfwdpp_ as its C++ back-end.\n\n\n.. image:: https://anaconda.org/bioconda/fwdpy11/badges/license.svg\n :target: https://anaconda.org/bioconda/fwdpy11\n\n.. image:: https://anaconda.org/bioconda/fwdpy11/badges/installer/conda.svg\n :target: https://conda.anaconda.org/bioconda\n\n.. image:: https://anaconda.org/bioconda/fwdpy11/badges/version.svg \n\t:target: https://anaconda.org/bioconda/fwdpy11\n\n.. image:: https://anaconda.org/bioconda/fwdpy11/badges/platforms.svg \n :target: https://anaconda.org/bioconda/fwdpy11\n\n\nBuild status\n-----------------------\n\nMaster:\n\n.. image:: https://travis-ci.org/molpopgen/fwdpy11.svg?branch=master\n :target: https://travis-ci.org/molpopgen/fwdpy11\n\n.. image:: https://circleci.com/gh/molpopgen/fwdpy11/tree/master.svg?style=svg\n :target: https://circleci.com/gh/molpopgen/fwdpy11/tree/master\n\nDevelopment: \n\n.. image:: https://travis-ci.org/molpopgen/fwdpy11.svg?branch=dev\n :target: https://travis-ci.org/molpopgen/fwdpy11\n\n.. image:: https://circleci.com/gh/molpopgen/fwdpy11/tree/dev.svg?style=svg\n :target: https://circleci.com/gh/molpopgen/fwdpy11/tree/dev\n\nManual\n-----------------------\n\nLatest/master:\n\n.. image:: https://readthedocs.org/projects/fwdpy11/badge/?version=latest\n\t:target: http://fwdpy11.readthedocs.io/en/latest/?badge=latest\n\nDevelopment branch:\n\n.. image:: https://readthedocs.org/projects/fwdpy11/badge/?version=dev\n\t:target: http://fwdpy11.readthedocs.io/en/dev/?badge=dev\n\n\n\nFeatures\n-----------------------\n\n* Picklable population objects\n* Parallel computation via multiprocessing_ or concurrent.futures_.\n* Custom temporal samplers to analyze populations *during* a simulation may be written in pure Python.\n \nDependencies\n-----------------------\n\nThe following must be present on your system:\n\n* GSL_. This is a C library. It is available via `conda`. fwdpy11 requires version 2.3 or greater.\n* pybind11_. This should be installed `conda` as appropriate for your system, or via your system's package manager or\n manually. See note below.\n* cmake_. This should be installed by `conda` or your favorite package manager.\n\nfwdpy11_ also uses fwdpp_, which is included as a submodule.\n\n.. note::\n\n The C++ modules are built using cmake_, which requires that pybind11_'s cmake macros are visible.\n Installing pybind11_ via `pip` does **not** install the macros. However, installs using `conda`, \n apt-get, or manual installation from source will install both the Python module and the cmake macros.\n\nLicense\n-----------------------\n\nGPLv3 or later (See COPYING)\n\nSuppored Python version\n-----------------------\n\nfwdpy11 is written for Python 3. We will not modify the package to be compatible with Python 2.7.\n\n\nInstallation\n---------------------------------\n\nBuilding from the git repository:\n\n.. code-block:: bash\n\n git submodule init\n git submodule update\n python setup.py build_ext -i\n python -m unittest discover tests\n\nUsing pip on OS X and Linux (or pip3 as appropriate for your system):\n\n.. code-block:: bash\n\n pip install --upgrade fwdpy11\n\nIt is possible that the cmake macros to detect the GSL can fail to detect the correct version. Issues like this are a\nbasic weakness of cmake. I've seen this in conda environments, where the macro prefers the system version over the\nnewer version in the environment. To \"fix\" this, give it a hint:\n\n.. code-block:: bash\n\n GSL_ROOT_DIR=/path/to/gsl python3 setup.py build_ext -i\n\nOS X\n==================================\n\nOn Apple's OS X, we strongly encourage that you use conda with the clang-4.0 compiler packages:\n\n.. code-block:: bash\n\n conda install clang_osx_64 clangxx_osx-64\n\nInstalling these packages will mean that you can get away from the relatively old versions of these compilers that ship\nwith Xcode. However, you do need to add the following flag when building the package:\n\n.. code-block:: bash\n\n CONDA_BUILD_SYSROOT=/ python3 setup.py build_ext -i\n\nDo the same for a `pip install` from the source directory.\n\nCaution\n==================================\n\nWe use the GitHub \"release_\" mechanism to make stable versions available. However, GitHub releases to not include the\nsub-modules, meaning that the releases themselves cannot be used for installation. (A related irony is that the Zenodo\nDOI for the releases are somewhat meaningless.)\n\nTo install a specific release:\n\n1. Use pip (see above). This is the recommended approach if you do not use conda.\n2. Install from bioconda. This is the recommended approach.\n3. Clone the repo, checkout the release, and update submodules:\n\n.. code-block:: bash\n\n git clone http://github.com/molpopgen/fwdpy11\n cd fwdpy11\n git submodule init\n git submodule update\n\nThe latter method is probably the least appealing.\n\nWe have a strict policy of putting releases on PyPi and bioconda_. If there is a release on PyPi but not on bioconda_,\nthen that is because we identified a bug and pushed a new release before the bioconda_ build happend. It happens.\nThat's life.\n\nEnabling code profiling\n-------------------------------------------------------------------\n\nBy default, fwdpy11 is compiled with aggressive optimizations to help reduce the library size. One side effect\nis that it becomes impossible to accurately profile the code. To override these defaults:\n\n.. code-block:: bash\n\n python setup.py build_ext -i --enable-profiling\n\n.. note::\n\n The package should not be installed with profiling enabled. This method of building\n is for developers who need to accurately profile the C++ back-end. Also note that\n only the main package is affected. Building the unit test modules is not affected.\n\nEnabling debugging symbols in the C++ code\n------------------------------------------------------------------\n\n.. code-block:: bash\n\n python setup.py build_ext -i --debug\n\nDebug mode disables all compiler optimizations, allows C-like assertions, and generated debug symbols.\n\n.. note::\n Never install the package compiled in debug mode! First, things will run much more slowly. \n Second, triggering an assertion will cause the Python interpreter to crash. These assertions\n exist as a brute-force method to help developers quickly identify bugs.\n\nEnabling assertions in the C++ code\n------------------------------------------------------------------\n\nThe fwdpp library code uses C's assert macros in several places. These are disabled by default. However, it can be useful to\nenable them when hacking the code. To do so, you must manually set your compiler flags with cmake:\n\n.. code-block:: bash\n \n cmake . -DCMAKE_CXX_FLAGS=\"-UNDEBUG -O2 -g\"\n\nWhen compiling this way, fwdpy11 makes some extra checks that will throw `RuntimeError` if they fail. The fwdpp_ back\nend also makes extra checks. If those fail, `abort` will be called, which will crash the Python interpreter. 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