Metadata-Version: 2.1
Name: TFPWA
Version: 0.1.3
Summary: Partial Wave Analysis program using Tensorflow
Home-page: https://github.com/jiangyi15/tf-pwa
Author: Yi Jiang
Author-email: jiangyi15@mails.ucas.ac.cn
License: MIT
Project-URL: Documentation, https://tf-pwa.readthedocs.io/en/latest
Project-URL: Source, https://github.com/jiangyi15/tf-pwa
Project-URL: Tracker, https://github.com/jiangyi15/tf-pwa/issues
Description: # A Partial Wave Analysis program using Tensorflow
        
        [![Documentation build status](https://readthedocs.org/projects/tf-pwa/badge/?version=latest)](https://tf-pwa.readthedocs.io)
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        [![conda cloud](https://anaconda.org/jiangyi15/tf-pwa/badges/version.svg)](https://anaconda.org/jiangyi15/tf-pwa)
        [![pypi](https://img.shields.io/pypi/v/TFPWA)](https://pypi.org/project/TFPWA/)
        [![license](https://anaconda.org/jiangyi15/tf-pwa/badges/license.svg)](https://choosealicense.com/licenses/mit/)
        <br>
        [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/jiangyi15/tf-pwa/HEAD)
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        This is a package and application for partial wave analysis (PWA) using
        TensorFlow. By using simple configuration file (and some scripts), PWA can be
        done fast and automatically.
        
        ## Install
        
        Get the packages using
        
        ```
        git clone https://github.com/jiangyi15/tf-pwa
        ```
        
        The dependencies can be installed by `conda` or `pip`.
        
        ### conda (recommended)
        
        When using conda, you don't need to install CUDA for TensorFlow specially.
        
        1. Get miniconda for python3 from
           [miniconda3](https://docs.conda.io/en/latest/miniconda.html) and install it.
        
        2. Install requirements
        
        ```
        conda install --file requirements-min.txt
        ```
        
        3. The following command can be used to set environment variables of Python.
           (Use `--no-deps` to make sure that no PyPI package will be installed. Using
           `-e`, so it can be updated by `git pull` directly.)
        
        ```
        python -m pip install -e . --no-deps
        ```
        
        4. (option) There are some option packages, such as `uproot` for reading root
           file. It can be installed as
        
        ```
        conda install uproot -c conda-forge
        ```
        
        <details><summary>
        ### conda channel (experimental)
        </summary><p>
        
        A pre-built conda package (Linux only) is also provided, just run following
        command to install it.
        
        ```
        conda config --add channels jiangyi15
        conda install tf-pwa
        ```
        
        </p></details>
        
        <details><summary>
        ### pip
        </summary><p>
        When using `pip`, you will need to install CUDA to use GPU. Just run the
        following command :
        
        ```bash
        python3 -m pip install -e .
        ```
        
        To contribute to the project, please also install additional developer tools
        with:
        
        ```bash
        python3 -m pip install -e .[dev]
        ```
        
        </p></details>
        
        ## Scripts
        
        ### fit.py
        
        simple fit scripts, decay structure is described in `config.yml`, here `[]`
        means options.
        
        ```
        python fit.py [--config config.yml]  [--init_params init_params.json]
        ```
        
        fit parameters will save in final_params.json, figure can be found in
        `figure/`.
        
        ### state_cache.sh
        
        script for cache state, using the latest \*\_params.json file as parameters and
        cache newer files in `path` (the default is `trash/`).
        
        ```
        ./state_cache.sh [path]
        ```
        
        ## Documents
        
        See [tf-pwa.rtfd.io](http://tf-pwa.readthedocs.io) for more information.
        
        Autodoc using sphinx-doc, need sphinx-doc
        
        ```
        python setup.py build_sphinx
        ```
        
        Then, the documents can be found in build/sphinx/index.html.
        
        Documents cna also build with `Makefile` in `docs` as
        
        ```
        cd docs && make html
        ```
        
        Then, the documents can be found in docs/\_build/html.
        
        ## Dependencies
        
        tensorflow or tensorflow-gpu >= 2.0.0
        
        sympy : symbolic expression
        
        PyYAML : config.yml file
        
        matplotlib : plot
        
        scipy : fit
        
Keywords: HEP,PWA,particle physics,physics
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: gpu
Provides-Extra: minuit
Provides-Extra: root
Provides-Extra: vis
Provides-Extra: doc
Provides-Extra: test
Provides-Extra: dev
Provides-Extra: all
