Usage	Development	Release

ModOpt is a series of Modular Optimisation tools for solving inverse problems.

See documentation for more details.

To install using pip run the following command:

  $ pip install modopt

To clone the ModOpt repository from GitHub run the following command:

  $ git clone https://github.com/CEA-COSMIC/ModOpt.git

All packages required by ModOpt should be installed automatically. Optional packages, however, will need to be installed manually.

In order to run the code in this repository the following packages must be installed:

• Python [> 3.6]
• importlib_metadata [==3.7.0]
• Numpy [==1.19.5]
• Scipy [==1.5.4]
• Progressbar 2 [==3.53.1]

The following packages can optionally be installed to add extra functionality:

• Astropy
• Matplotlib
• Scikit-Image
• Scikit-Learn
• 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
• Torch
• TensorFlow

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, 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}
}