docs: make readme more detailed

README.rst

@@ -1,10 +1,8 @@
-Benchmark repository for SLOPE
+Benchmark Repository for SLOPE
 ==============================
 
 |Build Status| |Python 3.6+|
 
-This repository is based on the work of Johan Larsson, Quentin Klopfenstein, Mathurin Massias and Jonas Wallin at https://github.com/Klopfe/benchmark_slope.
-
 This repository is dedicated to regression with the Sorted L-One Penalized Estimation (SLOPE) estimator which consists in solving the following program:
 
 $$ \\min_{\\beta} \\, \\tfrac{1}{2n} \\Vert y - X\\beta \\Vert^2_2 + J(\\beta, \\lambda) $$
@@ -18,27 +16,72 @@ with $\\lambda_1 \\geq \\lambda_2 \\geq ... \\geq \\lambda_p$ and $\|\\beta_{(1)
 We note $n$ (or n_samples) the number of samples and $p$ (or n_features) the number of features.
 We also have that $X\\in \\mathbb{R}^{n\\times p}$ and $y\\in \\mathbb{R}^n$.
 
-Install
---------
+Installling Benchopt
+--------------------
 
-This benchmark can be run using the following commands:
+This benchmark relies on benchopt, a generic framework for running numerical benchmarks.
+The recommended way to use benchopt is within a conda environment. So, begin by creating and activating
+a new conda environment and install benchopt in it:
 
 .. code-block::
 
+   $ conda create -n benchopt python
+   $ conda activate benchopt
    $ pip install -U benchopt
+
+Installing the Benchmark
+------------------------
+
+To install the benchmark, clone this repository and move to its folder:
+
+.. code-block::
+
    $ git clone https://github.com/benchopt/benchmark_slope
-   $ benchopt install ./benchmark_slope
-   $ benchopt run ./benchmark_slope  --config example_config
+   $ cd benchmark_slope/
+
+To install the dependencies for the solvers and datasets for the benchmark,
+first make sure that you have activated the conda environment where benchopt is
+installed. Then, you can either install all the dependencies with:
+
+.. code-block::
+
+   $ benchopt install .
+
+Or you can install only a subset of solvers by specifying them with the ``-s`` option.
+
+.. code-block::
+   $ benchopt install . -s sortedl1 -d libsvm
+
+Running the Benchmark
+---------------------
 
-Apart from the problem, options can be passed to `benchopt run`, to restrict the benchmarks to some solvers or datasets, e.g.:
+To run the benchmark, simply use the `benchopt run` command:
 
 .. code-block::
 
-	$ benchopt run ./benchmark_slope -s PGD -d simulated --max-runs 10 --n-repetitions 5
+	$ benchopt run .
 
-Use `benchopt run -h` for more details about these options, or visit https://benchopt.github.io/cli.html.
+By default, all solvers and datasets are run. You can restrict the benchmark to some solvers or datasets, e.g.:
+
+.. code-block::
+
+	$ benchopt run -s PGD[prox=prox_fast_stack] -d libsvm[dataset=real-sim,standardize=True]
+
+You can also specify a YAML configuration file to set the parameters of the benchmark.
+An example config is provided in <example_config.yml>.
+
+.. code-block::
+
+	$ benchopt run --config example_config.yml .
+
+Use `benchopt run -h` for more details about these options, or visit https://benchopt.github.io/api.html.
 
 .. |Build Status| image:: https://github.com/benchopt/benchmark_slope/workflows/Tests/badge.svg
    :target: https://github.com/benchopt/benchmark_slope/actions
 .. |Python 3.6+| image:: https://img.shields.io/badge/python-3.6%2B-blue
    :target: https://www.python.org/downloads/release/python-360/
+
+Acknowledgments
+---------------
+
+This repository is based on the work of Johan Larsson, Quentin Klopfenstein, Mathurin Massias and Jonas Wallin at https://github.com/Klopfe/benchmark_slope.