GooFit fitting package
Project description
GooFit is a highly parallel fitting framework originally designed for High Energy Physics.
Installation
This 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 configuration options). Otherwise, you might wait a very long time without output (especially if CUDA was found).
In practice, this looks like this:
pip install scikit-build cmake pip install -v goofit
Building a source package from git
For developers:
To make a source package, start with a clean (such as new) git GooFit package with all submodules checked out:
git clone --branch=master --recursive --depth=10 git@github.com:GooFit/GooFit.git cd goofit python setup.py sdist twine upload dist/*
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file goofit-2.1.0.dev2.tar.gz.
File metadata
- Download URL: goofit-2.1.0.dev2.tar.gz
- Upload date:
- Size: 6.0 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | ad695be4da5b1a86a32786b114f4d0362cc6f77c70def8f77b1f8f79791b73dc |
|
| MD5 | ad554b90e0c22e458f7c9e8cecd403ef |
|
| BLAKE2b-256 | 46de397f24f9b88922d6a83bd79928b0c5d4a2d5a97655c43cb695de14cd21b0 |
