Updated README and requirements

README.rst

@@ -12,13 +12,85 @@
 Graphs in *Pycsou-gsp* are instances from the class ``pygsp.graphs.Graph`` from the `pygsp <https://github.com/epfl-lts2/pygsp>`_ library for graph signal processing with Python. 
 
 Content
--------
+=======
 
-The package is organised as follows:
+The package, named `pycgsp <https://pypi.org/project/pycgsp>`_, is organised as follows:
 
-1. The subpackage ``pycsou_gsp.linop`` implements the following common graph linear operators:
+1. The subpackage ``pycgsp.linop`` implements the following common graph linear operators:
 
    * Graph convolution operators: ``GraphConvolution``
    * Graph differential operators: ``GraphLaplacian``, ``GraphGradient``, ``GeneralisedGraphLaplacian``.
 
-2. The subpackage ``pycsou_gsp.tesselation`` provides routines for generating graphs from discrete tessellations of continuous manifolds such as the sphere. 
+2. The subpackage ``pycgsp.tesselation`` provides routines for generating graphs from discrete tessellations of continuous manifolds such as the sphere. 
+
+Installation
+============
+
+Pycsou-gsp requires Python 3.6 or greater. It is developed and tested on x86_64 systems running MacOS and Linux.
+
+
+Dependencies
+------------
+
+Before installing Pycsou-gsp, make sure that the base package `Pycsou <https://github.com/matthieumeo/pycsou>`_ is correctly installed on your machine.
+Installation instructions for Pycsou are available at `that link <https://matthieumeo.github.io/pycsou/html/general/install.html>`_.
+
+The package extra dependencies are listed in the files ``requirements.txt`` and ``requirements-conda.txt``.
+It is recommended to install those extra dependencies using `Miniconda <https://conda.io/miniconda.html>`_ or
+`Anaconda <https://www.anaconda.com/download/#linux>`_. This
+is not just a pure stylistic choice but comes with some *hidden* advantages, such as the linking to
+``Intel MKL`` library (a highly optimized BLAS library created by Intel).
+
+.. code-block:: bash
+
+   >> conda install --channel=conda-forge --file=requirements-conda.txt
+
+
+Quick Install
+-------------
+
+Pycsou-gsp is also available on `Pypi <https://pypi.org/project/pycsou-gsp/>`_. You can hence install it very simply via the command:
+
+.. code-block:: bash
+
+   >> pip install pycsou-gsp
+
+If you have previously activated your conda environment ``pip`` will install Pycsou in said environment.
+Otherwise it will install it in your ``base`` environment together with the various dependencies obtained from the file ``requirements.txt``.
+
+
+Developer Install
+------------------
+
+It is also possible to install Pycsou-gsp from the source for developers:
+
+
+.. code-block:: bash
+
+   >> git clone https://github.com/matthieumeo/pycsou-gsp
+   >> cd <repository_dir>/
+   >> pip install -e .
+
+The package documentation can be generated with:
+
+.. code-block:: bash
+
+   >> conda install sphinx=='2.1.*'            \
+                    sphinx_rtd_theme=='0.4.*'
+   >> python3 setup.py build_sphinx
+
+You can verify that the installation was successful by running the package doctests:
+
+.. code-block:: bash
+
+   >> python3 test.py
+
+
+Cite
+====
+
+For citing this package, please see: http://doi.org/10.5281/zenodo.4486431
+
+
+
+

requirements.txt

@@ -1,6 +1,6 @@
 pygsp == 0.5.1
 healpy >= 1.14.*
-pycsou >= 1.0.*
+pycsou >= 1.0.5
 numpy >= 1.10
 scipy >= 1.5.*
 matplotlib >= 3.3.*