Merge pull request #501 from VChristiaens/master

Updated README

README.rst

@@ -191,33 +191,12 @@ also install the optional dependencies listed below.
 
 Optional dependencies
 ^^^^^^^^^^^^^^^^^^^^^
+The following dependencies are not automatically installed upon installation of ``VIP`` but may significantly improve your experience:
 
-The following dependencies are not automatically installed upon installation of
- ``VIP`` but may significantly improve your experience:
-
-``VIP`` contains a class ``vip_hci.fits.ds9`` that enables, through ``pyds9``,
-the interaction with a DS9 window (displaying numpy arrays, controlling the
-display options, etc). ``pyds9`` is an optional requirement and must be
-installed from the latest development version:
-
-.. code-block:: bash
-
-    $ pip install git+git://github.com/ericmandel/pyds9.git#egg=pyds9
-
-Also, you can install the Intel Math Kernel Library (``mkl``) optimizations
-(provided that you have a recent version of ``conda``) or ``openblas``
-libraries. Either of them can be installed with ``conda install``. This is
-recommended along with ``OpenCV`` for maximum speed on ``VIP`` computations.
-
-``VIP`` offers the possibility of computing SVDs on GPU by using ``CuPy``
-(starting from version 0.8.0) or ``PyTorch`` (from version 0.9.2). These remain
-as optional requirements, to be installed by the user, as well as a proper CUDA
-environment (and a decent GPU card).
-
-Finally, bad pixel correction routines can be optimised with ``Numba``, which 
-converts some Python code, particularly ``NumPy``, into fast machine code. A 
-factor up to ~50x times speed improvement can be obtained on large images 
-compared to NumPy. Numba can be installed with ``conda install numba``.
+- ``VIP`` contains a class ``vip_hci.vip_ds9`` that enables, through ``pyds9``, the interaction with a DS9 window (displaying numpy arrays, controlling the display options, etc). To enable this feature, ``pyds9`` must be installed from the latest development version: ``pip install git+git://github.com/ericmandel/pyds9.git#egg=pyds9``
+- Also, you can install the Intel Math Kernel Library (``mkl``) optimizations (provided that you have a recent version of ``conda``) or ``openblas`` libraries. Either of them can be installed with ``conda install``. This is recommended along with ``OpenCV`` for maximum speed on ``VIP`` computations.
+- ``VIP`` offers the possibility of computing SVDs on GPU by using ``CuPy`` (starting from version 0.8.0) or ``PyTorch`` (from version 0.9.2). These remain as optional requirements, to be installed by the user, as well as a proper CUDA environment (and a decent GPU card).
+- Finally, bad pixel correction routines can be optimised with ``Numba``, which  converts some Python code, particularly ``NumPy``, into fast machine code. A factor up to ~50x times speed improvement can be obtained on large images compared to NumPy. Numba can be installed with ``conda install numba``.
 
 
 Loading VIP
@@ -265,4 +244,4 @@ In addition, if you use one of the following modules, please also cite:
 - pca: `Amara and Quanz (2012) <https://ui.adsabs.harvard.edu/abs/2012MNRAS.427..948A/abstract>`_ and `Soummer et al. (2012) <https://ui.adsabs.harvard.edu/abs/2012ApJ...755L..28S/abstract>`_;
 
 
-Note: The `specfit <https://github.com/VChristiaens/specfit>`_ module, previously part of VIP, has now been moved to a separate GitHub repository.
+Note: The ``specfit`` module, previously part of VIP, has now been moved to a separate `GitHub repository <https://github.com/VChristiaens/special>`_.