Metadata-Version: 2.1
Name: pdfflow
Version: 0.9rc0
Summary: PDF interpolation with Tensorflow
Home-page: https://github.com/N3PDF/pdfflow
Author: S.Carrazza, J.Cruz-Martinez, M.Rossi
Author-email: stefano.carrazza@cern.ch, juan.cruz@mi.infn.it, marco.rossi5@unimi.it
License: UNKNOWN
Description: ![pytest](https://github.com/N3PDF/pdfflow/workflows/pytest/badge.svg) [![DOI](https://zenodo.org/badge/238731330.svg)](https://zenodo.org/badge/latestdoi/238731330)
        
        # PDFflow
        
        PDFflow is parton distribution function interpolation library written in Python and based on the [TensorFlow](https://www.tensorflow.org/) framework. It is developed with a focus on speed and efficiency, enabling researchers to perform very expensive calculation as quick and easy as possible.
        
        The key features of PDFflow is the possibility to query PDF sets on GPU accelerators.
        
        ## Documentation
        
        [https://pdfflow.readthedocs.io/en/latest](https://pdfflow.readthedocs.io/en/latest)
        
        ## Installation
        
        The package can be installed with pip:
        ```
        python3 -m pip install pdfflow
        ```
        
        as well as with `conda`, from the `conda-forge` channel:
        ```
        conda install pdfflow -c conda-forge
        ```
        
        If you prefer a manual installation just use:
        ```
        python setup.py install
        ```
        or if you are planning to extend or develop code just use:
        ```
        python setup.py develop
        ```
        
        ## Examples
        
        There are some examples in the `benchmarks` folder.
        
        ## Citation policy
        
        If you use the package pelase cite the following paper and zenodo references:
        - https://doi.org/10.5281/zenodo.3964190
        - https://arxiv.org/abs/20xx.xxxxx
        
Platform: UNKNOWN
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: docs
