{ "info": { "author": "Henry Schreiner", "author_email": "hschrein@cern.ch", "bugtrack_url": null, "classifiers": [ "Development Status :: 5 - Production/Stable", "Intended Audience :: Science/Research", "License :: OSI Approved :: GNU General Public License v3 (GPLv3)", "Natural Language :: English", "Operating System :: Unix", "Programming Language :: C++", "Programming Language :: Python", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Topic :: Scientific/Engineering :: Physics" ], "description": "GooFit for Python\n-----------------\n\nGooFit is a highly parallel fitting framework originally designed for High Energy Physics.\n\nInstallation basics\n===================\n\nThis package can be installed with pip, but uses SciKit-Build, and is build, fully optimized, on your system. Because of this, there are a few caveats when running a pip install. Make sure you have SciKit-Build (``pip install scikit-build``) before you attempt an install. Also, if you don't have a recent version of CMake (3.8 or better recommended), also run ``pip install cmake``. When you build, you should also use pip's ``-v`` flag, so that you can see it build (and observe the\nconfiguration options). Otherwise, you might wait a very long time without output (especially if CUDA was found).\n\n\nInstallation: pip\n=================\n\nUsing pip 10+::\n\n pip install -v goofit\n\nUsing pip < 10::\n\n pip install scikit-build\n pip install -v goofit\n\n\nGooFit will automatically look for CUDA, and build in GPU mode if it finds CUDA. You can pick a specific version by passing through a CMake option (see below), or by setting an environment variable, `GOOFIT_DEVICE` before building. You may want to build with OpenMP as a backend to avoid using your GPU, or you might want the CPP version if you are using Anaconda on macOS. Here are the three common backends::\n\n GOOFIT_DEVICE=CUDA pip install -v goofit\n GOOFIT_DEVICE=OMP pip install -v goofit\n GOOFIT_DEVICE=CPP pip install -v goofit\n\nIf you want to send arbitrary commands to CMake through PIP, you will need to pass each option through, starting with a ``--`` option. Pip will try to reuse the built version if you do not pass options, but will rebuild if you pass options, so this works for a rebuild, unlike the lines above. This is how you would do this to set OMP as the backend:\n\n pip install -v goofit --install-option=\"--\" --install-option=\"-DGOOFIT_DEVICE=OMP\"\n\n\nInstallation: local\n===================\n\nIf you want to add PDFs to GooFit, or use GooFit pacakges, you should be working in a local directory using git. In the following example, I'm assuming you've set up SSH keys with GitHub; you can use https instead if you prefer by changing the URL to ``https://github.com/GooFit/GooFit.git``::\n\n git clone --recursive git@github.com:GooFit/GooFit.git\n cd goofit\n\nPipenv\n~~~~~~\n\nYou can set up a quick environment using pipenv::\n\n pipenv install --dev\n\nThen activate that environment::\n\n pipenv shell\n\nLocal pip\n~~~~~~~~~\n\nThe normal install here works, though as usual you should include verbose output::\n\n pip install -v .\n\n\nYou can pass through options to the build command, for example::\n\n pip install -v . --install-options=\"--\" --install-options=\"-DGOOFIT_PACKAGES=OFF\"\n\n\nBuilding a source package from git\n==================================\n\nFor developers only:\n\nTo make a source package, start with a clean (such as new) git GooFit package with all submodules checked out::\n\n git clone --branch=master --recursive --depth=10 git@github.com:GooFit/GooFit.git\n cd 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