Metadata-Version: 2.1
Name: modopt
Version: 1.5.1
Summary: Modular Optimisation tools for soliving inverse problems.
Home-page: https://github.com/cea-cosmic/modopt
Author: Samuel Farrens
Author-email: samuel.farrens@cea.fr
License: MIT
Description: # ModOpt
        
        <img width=400 src="docs/source/modopt_logo.png">
        
        | Usage | Development | Release |
        | ----- | ----------- | ------- |
        | [![docs](https://img.shields.io/badge/docs-Sphinx-blue)](https://cea-cosmic.github.io/ModOpt/) | [![build](https://github.com/CEA-COSMIC/modopt/workflows/CI/badge.svg)](https://github.com/CEA-COSMIC/modopt/actions?query=workflow%3ACI) | [![release](https://img.shields.io/github/v/release/CEA-COSMIC/modopt)](https://github.com/CEA-COSMIC/modopt/releases/latest) |
        | [![license](https://img.shields.io/github/license/CEA-COSMIC/modopt)](https://github.com/CEA-COSMIC/modopt/blob/master/LICENCE.txt) | [![deploy](https://github.com/CEA-COSMIC/modopt/workflows/CD/badge.svg)](https://github.com/CEA-COSMIC/modopt/actions?query=workflow%3ACD) | [![pypi](https://img.shields.io/pypi/v/modopt)](https://pypi.org/project/modopt/) |
        | [![wemake-python-styleguide](https://img.shields.io/badge/style-wemake-000000.svg)](https://github.com/wemake-services/wemake-python-styleguide) | [![codecov](https://codecov.io/gh/CEA-COSMIC/modopt/branch/master/graph/badge.svg?token=XHJIQXV7AX)](https://codecov.io/gh/CEA-COSMIC/modopt) | [![python](https://img.shields.io/pypi/pyversions/modopt)](https://www.python.org/downloads/source/) |
        | [![contribute](https://img.shields.io/badge/contribute-read-lightgrey)](https://github.com/CEA-COSMIC/modopt/blob/master/CONTRIBUTING.md) | [![CodeFactor](https://www.codefactor.io/repository/github/CEA-COSMIC/modopt/badge)](https://www.codefactor.io/repository/github/CEA-COSMIC/modopt) | |
        | [![coc](https://img.shields.io/badge/conduct-read-lightgrey)](https://github.com/CEA-COSMIC/modopt/blob/master/CODE_OF_CONDUCT.md) | [![Updates](https://pyup.io/repos/github/CEA-COSMIC/modopt/shield.svg)](https://pyup.io/repos/github/CEA-COSMIC/ModOpt/) | |
        
        ModOpt is a series of **Modular Optimisation** tools for solving inverse problems.
        
        See [documentation](https://CEA-COSMIC.github.io/ModOpt/) for more details.
        
        ## Installation
        
        To install using `pip` run the following command:
        
        ```bash
          $ pip install modopt
        ```
        
        To clone the ModOpt repository from GitHub run the following command:
        
        ```bash
          $ git clone https://github.com/CEA-COSMIC/ModOpt.git
        ```
        
        ## Dependencies
        
        All packages required by ModOpt should be installed automatically. Optional packages, however, will need to be installed manually.
        
        ### Required Packages
        
        In order to run the code in this repository the following packages must be
        installed:
        
        * [Python](https://www.python.org/) [> 3.6]
        * [importlib_metadata](https://importlib-metadata.readthedocs.io/en/latest/) [==3.7.0]
        * [Numpy](http://www.numpy.org/) [==1.19.5]
        * [Scipy](http://www.scipy.org/) [==1.5.4]
        * [Progressbar 2](https://progressbar-2.readthedocs.io/) [==3.53.1]
        
        ### Optional Packages
        
        The following packages can optionally be installed to add extra functionality:
        
        * [Astropy](http://www.astropy.org/)
        * [Matplotlib](http://matplotlib.org/)
        * [Scikit-Image](https://scikit-image.org/)
        * [Scikit-Learn](https://scikit-learn.org/)
        * [Termcolor](https://pypi.python.org/pypi/termcolor)
        
        For (partial) GPU compliance the following packages can also be installed.
        Note that none of these are required for running on a CPU.
        
        * [CuPy](https://cupy.dev/)
        * [Torch](https://pytorch.org/)
        * [TensorFlow](https://www.tensorflow.org/)
        
        ## Citation
        
        If you use ModOpt in a scientific publication, we would appreciate citations to the following paper:
        
        [PySAP: Python Sparse Data Analysis Package for multidisciplinary image processing](https://www.sciencedirect.com/science/article/pii/S2213133720300561), S. Farrens et al., Astronomy and Computing 32, 2020
        
        The BibTeX citation is the following:
        ```
        @Article{farrens2020pysap,
          title={{PySAP: Python Sparse Data Analysis Package for multidisciplinary image processing}},
          author={Farrens, S and Grigis, A and El Gueddari, L and Ramzi, Z and Chaithya, GR and Starck, S and Sarthou, B and Cherkaoui, H and Ciuciu, P and Starck, J-L},
          journal={Astronomy and Computing},
          volume={32},
          pages={100402},
          year={2020},
          publisher={Elsevier}
        }
        ```
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: develop
