Benchopt is a package to simplify and make more transparent and reproducible the comparisons of optimization algorithms. This benchmark is dedicated for MRI reconstruction using pysap-mri and modopt in cartesian and non-cartesian setting.

$$\min_{w} f(X, w)$$

where $n$ (or n_samples) stands for the number of samples, $p$ (or n_features) stands for the number of features and

$$X \in \mathbb{R}^{n \times p} \ , \quad w \in \mathbb{R}^p$$

This benchmark can be run using the following commands:

$ pip install -U benchopt
$ git clone https://github.com/ndpooja/bechopt_pysap_mri
$ benchopt run bechopt_pysap_mri

Apart from the problem, options can be passed to benchopt run, to restrict the benchmarks to some solvers or datasets, e.g.:

$ benchopt run bechopt_pysap_mri -s solver1 -d dataset2 --max-runs 10 --n-repetitions 10

Use benchopt run -h for more details about these options, or visit https://benchopt.github.io/api.html.