Forward-time population genetic simulation in Python
The following must be present on your system:
- GSL. This is a C library. It is available via conda. fwdpy11 requires version 2.3 or greater.
- pybind11. This should be installed conda as appropriate for your system, or via your system’s package manager or manually. See note below.
- cmake. This should be installed by conda or your favorite package manager.
GPLv3 or later (See COPYING)
Suppored Python version
fwdpy11 is written for Python 3. We will not modify the package to be compatible with Python 2.7.
Building from the git repository:
git submodule init git submodule update python setup.py build_ext -i python -m unittest discover tests
Using pip on macOS and Linux (or pip3 as appropriate for your system):
pip install --upgrade fwdpy11
It is possible that the cmake macros to detect the GSL can fail to detect the correct version. Issues like this are a basic weakness of cmake. I’ve seen this in conda environments, where the macro prefers the system version over the newer version in the environment. To “fix” this, give it a hint:
GSL_ROOT_DIR=/path/to/gsl python3 setup.py build_ext -i
On Apple’s macOS, we strongly encourage that you use conda with their compiler packages:
conda install clang_osx-64 clangxx_osx-64
Installing these packages will mean that you can get away from the relatively old versions of these compilers that ship with Xcode. However, you do need to add the following flag when building the package:
On macOS versions prior to “Mojave”:
CONDA_BUILD_SYSROOT=/ python3 setup.py build_ext -i
For later versions, you may omit the environment variable prefix.
Do the same for a pip install from the source directory.
We have heard positive reports of using fwdpy11 on Windows 10 with the Ubuntu subsystem installed. For such a system, you may use a Linux conda installer and then install fwdpy11 via bioconda.
The developers do not have access to this platform, but we are keen to hear of any issues.
We use the GitHub “release” mechanism to make stable versions available. However, GitHub releases to not include the sub-modules, meaning that the releases themselves cannot be used for installation. (A related irony is that the Zenodo DOI for the releases are somewhat meaningless.)
To install a specific release:
- Use pip (see above). This is the recommended approach if you do not use conda.
- Install from bioconda. This is the recommended approach.
- Clone the repo, checkout the release, and update submodules:
git clone http://github.com/molpopgen/fwdpy11 cd fwdpy11 git submodule init git submodule update
The latter method is probably the least appealing.
We have a strict policy of putting releases on PyPi and bioconda. If there is a release on PyPi but not on bioconda, then that is because we identified a bug and pushed a new release before the bioconda build happend. It happens. That’s life.
Enabling code profiling
By default, fwdpy11 is compiled with aggressive optimizations to help reduce the library size. One side effect is that it becomes impossible to accurately profile the code. To override these defaults:
python setup.py build_ext -i --enable-profiling
The package should not be installed with profiling enabled. This method of building is for developers who need to accurately profile the C++ back-end. Also note that only the main package is affected. Building the unit test modules is not affected.
Enabling debugging symbols in the C++ code
python setup.py build_ext -i --debug
Debug mode disables all compiler optimizations, allows C-like assertions, and generated debug symbols.
Never install the package compiled in debug mode! First, things will run much more slowly. Second, triggering an assertion will cause the Python interpreter to crash. These assertions exist as a brute-force method to help developers quickly identify bugs.
Enabling assertions in the C++ code
The fwdpp library code uses C’s assert macros in several places. These are disabled by default. However, it can be useful to enable them when hacking the code. To do so, you must manually set your compiler flags with cmake:
cmake . -DCMAKE_CXX_FLAGS="-UNDEBUG -O2 -g"
When compiling this way, fwdpy11 makes some extra checks that will throw RuntimeError if they fail. The fwdpp back end also makes extra checks. If those fail, abort will be called, which will crash the Python interpreter. Thus, compiling with this option is a “serious debugging mode only” option.
Enabling aggressive debugging of C++ STL templates using GCC
Use the following flags to enable an “extreme” debugging mode of the C++ standard template library:
CXXFLAGS="-D_GLIBCXX_CONCEPT_CHECKS -D_GLIBCXX_DEBUG -D_GLIBCXX_DEBUG_PEDANTIC" \ CPPFLAGS="-D_GLIBCXX_CONCEPT_CHECKS -D_GLIBCXX_DEBUG -D_GLIBCXX_DEBUG_PEDANTIC" python3 setup.py build_ext -i
fwdpy11 is available through bioconda for Linux and for macOS:
conda install -c bioconda fwdpy11
Release history Release notifications | RSS feed
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size fwdpy11-0.7.1.tar.gz (1.8 MB)||File type Source||Python version None||Upload date||Hashes View|