Release cleanup

MANIFEST.in

@@ -3,4 +3,3 @@ include develop.txt
 include docs/requirements.txt
 include README.rst
 include LICENSE.txt
-include docs/source/modopt_logo.png

README.md

@@ -1,6 +1,6 @@
 # ModOpt
 
-<img width=400 src="docs/source/modopt_logo.png">
+<img width=400 src="https://raw.githubusercontent.com/CEA-COSMIC/ModOpt/master/docs/source/modopt_logo.png">
 
 | Usage | Development | Release |
 | ----- | ----------- | ------- |

develop.txt

@@ -1,4 +1,5 @@
 coverage>=5.5
+flake8<4
 nose>=1.3.7
 pytest>=6.2.2
 pytest-cov>=2.11.1

docs/requirements.txt

@@ -1,7 +1,8 @@
 jupyter==1.0.0
+myst-parser==0.16.0
 nbsphinx==0.8.7
 nbsphinx-link==1.3.0
 numpydoc==1.1.0
-sphinx==4.3.0
+sphinx==4.3.1
 sphinxcontrib-bibtex==2.4.1
-sphinxawesome-theme==3.2.0
+sphinxawesome-theme==3.2.1

docs/source/about.rst

@@ -15,6 +15,8 @@ Contributors
 
 You can find a |link-to-contributors|.
 
+|CS_LOGO| |NS_LOGO|
+
 .. |link-to-cosmic| raw:: html
 
   <a href="http://cosmic.cosmostat.org/" target="_blank">COSMIC</a>
@@ -38,11 +40,12 @@ You can find a |link-to-contributors|.
   <a href="https://github.com/CEA-COSMIC/ModOpt/graphs/contributors"
   target="_blank">list of ModOpt contributors here</a>
 
-
-.. image:: cosmostat_logo.jpg
-  :width: 300
+.. |CS_LOGO| image:: cosmostat_logo.jpg
+  :width: 45%
   :alt: CosmoStat Logo
+  :target: http://www.cosmostat.org/
 
-.. image:: neurospin_logo.png
-  :width: 300
+.. |NS_LOGO| image:: neurospin_logo.png
+  :width: 45%
   :alt: NeuroSpin Logo
+  :target: https://joliot.cea.fr/drf/joliot/en/Pages/research_entities/NeuroSpin.aspx

docs/source/conf.py

@@ -41,6 +41,7 @@
     'sphinx.ext.viewcode',
     'sphinxawesome_theme',
     'sphinxcontrib.bibtex',
+    'myst_parser',
     'nbsphinx',
     'nbsphinx_link',
     'numpydoc',
@@ -95,12 +96,25 @@
 html_theme_options = {
     "nav_include_hidden": True,
     "show_nav": True,
-    "show_breadcrumbs": False,
-    "breadcrumbs_separator": "/"
+    "show_breadcrumbs": True,
+    "breadcrumbs_separator": "/",
+    "show_prev_next": True,
+    "show_scrolltop": True,
+
 }
 html_collapsible_definitions = True
-
-
+html_awesome_headerlinks = True
+html_logo = 'modopt_logo.jpg'
+html_permalinks_icon = (
+    '<svg xmlns="http://www.w3.org/2000/svg" '
+    'viewBox="0 0 24 24">'
+    '<path d="M3.9 12c0-1.71 1.39-3.1 '
+    "3.1-3.1h4V7H7c-2.76 0-5 2.24-5 5s2.24 "
+    "5 5 5h4v-1.9H7c-1.71 0-3.1-1.39-3.1-3.1zM8 "
+    "13h8v-2H8v2zm9-6h-4v1.9h4c1.71 0 3.1 1.39 3.1 "
+    "3.1s-1.39 3.1-3.1 3.1h-4V17h4c2.76 0 5-2.24 "
+    '5-5s-2.24-5-5-5z"/></svg>'
+)
 # The name for this set of Sphinx documents.  If None, it defaults to
 # "<project> v<release> documentation".
 html_title = '{0} v{1}'.format(project, version)
@@ -216,12 +230,25 @@ def add_notebooks(nb_path='../../notebooks'):
     'python': ('http://docs.python.org/3', None),
     'numpy': ('https://numpy.org/doc/stable/', None),
     'scipy': ('https://docs.scipy.org/doc/scipy/reference', None),
+    'progressbar': ('https://progressbar-2.readthedocs.io/en/latest/', None),
     'matplotlib': ('https://matplotlib.org', None),
     'astropy': ('http://docs.astropy.org/en/latest/', None),
     'cupy': ('https://docs-cupy.chainer.org/en/stable/', None),
     'torch': ('https://pytorch.org/docs/stable/', None),
+    'sklearn': (
+        'http://scikit-learn.org/stable',
+        (None, './_intersphinx/sklearn-objects.inv')
+    ),
+    'tensorflow': (
+        'https://www.tensorflow.org/api_docs/python',
+        (
+            'https://github.com/GPflow/tensorflow-intersphinx/'
+            + 'raw/master/tf2_py_objects.inv')
+    )
+
 }
 
 # -- BibTeX Setting  ----------------------------------------------
 
 bibtex_bibfiles = ['refs.bib', 'my_ref.bib']
+bibtex_default_style = 'alpha'

docs/source/contributing.rst

@@ -1,9 +1,16 @@
 Contributing
 ============
 
-Read our `Contribution Guidelines <https://github.com/cea-cosmic/modopt/blob/master/CONTRIBUTING.md>`_
+Read our |link-to-contrib|.
 for details on how to contribute to the development of this package.
 
-All contributors are kindly asked to adhere to the
-`Code of Conduct <https://github.com/cea-cosmic/modopt/blob/master/CODE_OF_CONDUCT.md>`_
+All contributors are kindly asked to adhere to the |link-to-conduct|
 at all times to ensure a safe and inclusive environment for everyone.
+
+.. |link-to-contrib| raw:: html
+
+  <a href="https://github.com/cea-cosmic/modopt/blob/master/CONTRIBUTING.md" target="_blank">Contribution Guidelines</a>
+
+.. |link-to-conduct| raw:: html
+
+  <a href="https://github.com/cea-cosmic/modopt/blob/master/CODE_OF_CONDUCT.md" target="_blank">Code of Conduct</a>

docs/source/dependencies.rst

@@ -11,7 +11,7 @@ Required Packages
 
 In order to use ModOpt the following packages must be installed:
 
-* |link-to-python| ``[> 3.6]``
+* |link-to-python| ``[>= 3.6]``
 * |link-to-metadata| ``[>=3.7.0]``
 * |link-to-numpy| ``[>=1.19.5]``
 * |link-to-scipy| ``[>=1.5.4]``

docs/source/index.rst

@@ -7,13 +7,15 @@ ModOpt Documentation
 ======================
 
 .. image:: modopt_logo.png
+  :width: 100%
+  :alt: ModOpt logo
 
 .. Include table of contents
 .. include:: toc.rst
 
 :Author: Samuel Farrens `(samuel.farrens@cea.fr) <samuel.farrens@cea.fr>`_
-:Version: 1.5.1
-:Release Date: 22/04/2021
+:Version: 1.6.0
+:Release Date: 17/12/2021
 :Repository: |link-to-repo|
 
 .. |link-to-repo| raw:: html

docs/source/refs.bib

@@ -65,6 +65,22 @@ @article{condat2013
   doi = {10.1007/s10957-012-0245-9}
 }
 
+@ARTICLE{defazio2014,
+       author = {{Defazio}, Aaron and {Bach}, Francis and {Lacoste-Julien}, Simon},
+        title = "{SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives}",
+      journal = {arXiv e-prints},
+     keywords = {Computer Science - Machine Learning, Mathematics - Optimization and Control, Statistics - Machine Learning},
+         year = 2014,
+        month = jul,
+          eid = {arXiv:1407.0202},
+        pages = {arXiv:1407.0202},
+archivePrefix = {arXiv},
+       eprint = {1407.0202},
+ primaryClass = {cs.LG},
+       adsurl = {https://ui.adsabs.harvard.edu/abs/2014arXiv1407.0202D},
+      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+}
+
 @ARTICLE{figueiredo2014,
   author = {Figueiredo, Mario A.~T. and Nowak, Robert D.},
   title = {Sparse Estimation with Strongly Correlated Variables using Ordered Weighted L1 Regularization},
@@ -145,6 +161,22 @@ @ARTICLE{raguet2011
   adsnote = {Provided by the SAO/NASA Astrophysics Data System}
 }
 
+@ARTICLE{ruder2017,
+       author = {{Ruder}, Sebastian},
+        title = "{An overview of gradient descent optimization algorithms}",
+      journal = {arXiv e-prints},
+     keywords = {Computer Science - Machine Learning},
+         year = 2016,
+        month = sep,
+          eid = {arXiv:1609.04747},
+        pages = {arXiv:1609.04747},
+archivePrefix = {arXiv},
+       eprint = {1609.04747},
+ primaryClass = {cs.LG},
+       adsurl = {https://ui.adsabs.harvard.edu/abs/2016arXiv160904747R},
+      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+}
+
 @book{starck2010,
   place={Cambridge},
   title={Sparse Image and Signal Processing: Wavelets, Curvelets, Morphological Diversity},
@@ -175,22 +207,3 @@ @article{zou2005
   journal = {Journal of the Royal Statistical Society Series B},
   doi = {10.1111/j.1467-9868.2005.00527.x}
 }
-
-@article{ruder2017,
-	title = {An overview of gradient descent optimization algorithms},
-	url = {http://arxiv.org/abs/1609.04747},
-	journaltitle = {{arXiv}:1609.04747 [cs]},
-	author = {Ruder, Sebastian},
-	urldate = {2021-12-09},
-	date = {2017-06-15},
-	langid = {english},
-	eprinttype = {arxiv},
-	eprint = {1609.04747},
-}
-
-@article{defazio2014,
-	title = {{SAGA}: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives},
-	pages = {15},
-	author = {Defazio, Aaron and Bach, Francis and Lacoste-Julien, Simon},
-	langid = {english},
-}

docs/source/z_ref.rst

@@ -2,4 +2,3 @@ References
 ==========
 
 .. bibliography:: refs.bib
-   :style: alpha

modopt/base/backend.py

@@ -49,26 +49,26 @@
 def get_backend(backend):
     """Get backend.
 
-    Returns the backend module for input specified by string
+    Returns the backend module for input specified by string.
 
     Parameters
     ----------
     backend: str
-        String holding the backend name. One of `tensorflow`,
-        `numpy` or `cupy`.
+        String holding the backend name. One of ``'tensorflow'``,
+        ``'numpy'`` or ``'cupy'``.
 
     Returns
     -------
     tuple
         Returns the module for carrying out calculations and the actual backend
         that was reverted towards. If the right libraries are not installed,
-        the function warns and reverts to `numpy` backend
+        the function warns and reverts to the ``'numpy'`` backend.
     """
     if backend not in LIBRARIES.keys() or LIBRARIES[backend] is None:
         msg = (
             '{0} backend not possible, please ensure that '
             + 'the optional libraries are installed.\n'
-            + 'Reverting to numpy'
+            + 'Reverting to numpy.'
         )
         warn(msg.format(backend))
         backend = 'numpy'
@@ -83,7 +83,7 @@ def get_array_module(input_data):
 
     Parameters
     ----------
-    input_data : numpy.ndarray or cupy.ndarray
+    input_data : numpy.ndarray, cupy.ndarray or tf.experimental.numpy.ndarray
         Input data array
 
     Returns
@@ -104,16 +104,16 @@ def get_array_module(input_data):
 def change_backend(input_data, backend='cupy'):
     """Move data to device.
 
-    This method changes the backend of an array
-    This can be used to copy data to GPU or to CPU
+    This method changes the backend of an array. This can be used to copy data
+    to GPU or to CPU.
 
     Parameters
     ----------
-    input_data : numpy.ndarray or cupy.ndarray
+    input_data : numpy.ndarray, cupy.ndarray or tf.experimental.numpy.ndarray
         Input data array to be moved
     backend: str, optional
-        The backend to use, one among `tensorflow`, `cupy` and
-        `numpy`. Default is `cupy`.
+        The backend to use, one among ``'tensorflow'``, ``'cupy'`` and
+        ``'numpy'``. Default is ``'cupy'``.
 
     Returns
     -------
@@ -131,12 +131,12 @@ def change_backend(input_data, backend='cupy'):
 def move_to_cpu(input_data):
     """Move data to CPU.
 
-    This method moves data from GPU to CPU.
-    It returns the same data if it is already on CPU.
+    This method moves data from GPU to CPU. It returns the same data if it is
+    already on CPU.
 
     Parameters
     ----------
-    input_data : cupy.ndarray
+    input_data : cupy.ndarray or tf.experimental.numpy.ndarray
         Input data array to be moved
 
     Returns

modopt/base/np_adjust.py

@@ -144,6 +144,7 @@ def pad2d(input_data, padding):
     See Also
     --------
     numpy.pad : base function
+
     """
     input_data = np.array(input_data)
 
@@ -169,7 +170,7 @@ def pad2d(input_data, padding):
 def ftr(input_data):
     """Fancy transpose right.
 
-    Apply fancy_transpose() to data with roll=1.
+    Apply ``fancy_transpose`` to data with ``roll=1``.
 
     Parameters
     ----------
@@ -192,7 +193,7 @@ def ftr(input_data):
 def ftl(input_data):
     """Fancy transpose left.
 
-    Apply fancy_transpose() to data with roll=-1.
+    Apply ``fancy_transpose`` to data with ``roll=-1``.
 
     Parameters
     ----------

modopt/base/observable.py

@@ -85,7 +85,7 @@ def notify_observers(self, signal, **kwargs):
         ----------
         signal : str
             A valid signal
-        kwargs : dict
+        **kwargs : dict
             The parameters that will be sent to the observers
 
         Returns
@@ -191,9 +191,9 @@ class MetricObserver(object):
         Metric function with this precise signature func(test, ref)
     mapping : dict
         Define the mapping between the iterate variable and the metric
-        keyword: {'x_new':'name_var_1', 'y_new':'name_var_2'}. To cancel
+        keyword: ``{'x_new':'name_var_1', 'y_new':'name_var_2'}``. To cancel
         the need of a variable, the dict value should be None:
-        'y_new':None.
+        ``'y_new': None``.
     cst_kwargs : dict
         Keywords arguments of constant argument for the metric computation
     early_stopping : bool