Metadata-Version: 2.1
Name: vegasflow
Version: 1.0
Summary: Monte Carlo integration with Tensorflow
Home-page: https://github.com/N3PDF/VegasFlow
Author: S.Carrazza, J.Cruz-Martinez
Author-email: stefano.carrazza@cern.ch, juan.cruz@mi.infn.it
License: UNKNOWN
Description: [![Tests](https://github.com/N3PDF/vegasflow/workflows/pytest/badge.svg)](https://github.com/N3PDF/vegasflow/actions?query=workflow%3A%22pytest%22)
        [![Documentation Status](https://readthedocs.org/projects/vegasflow/badge/?version=latest)](https://vegasflow.readthedocs.io/en/latest/?badge=latest)
        
        # VegasFlow
        
        VegasFlow is a Monte Carlo integration 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.
        
        Some of the key features of VegasFlow are:
        - Integrates efficiently high dimensional functions on single (multi-threading) and multi CPU, single and multi GPU, many GPUs or clusters.
        
        - Compatible with Python, C, C++ or Fortran.
        
        - Implementation of different Monte Carlo algorithms.
        
        
        
        ## Documentation
        
        [https://vegasflow.readthedocs.io/en/latest](https://vegasflow.readthedocs.io/en/latest)
        
        
        ## Installation
        
        The package can be installed with pip:
        ```
        python3 -m pip install vegasflow
        ```
        
        as well as with `conda`, from the `conda-forge` channel:
        ```
        conda install vegasflow -c conda-forge
        ```
        
        If you prefer a manual installation just use:
        ```
        pip install vegasflow
        ```
        or if you are planning to extend or develop code just use:
        ```
        python setup.py develop
        ```
        
        ## Examples
        
        There are some examples in the `examples/` folder.
        
        ## Citation policy
        
        If you use the theta package please cite the following  paper and zenodo references:
        - Zenodo
        - arXiv:
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: >=3.6,<3.8
Description-Content-Type: text/markdown
Provides-Extra: benchmark
Provides-Extra: examples
Provides-Extra: docs
