Update Documentation

Clean up project

docs/source/conf.py

@@ -104,7 +104,7 @@ autodoc_inherit_docstrings = False
 # https://sphinx-themes.org/
 html_theme = "sphinx_rtd_theme"
 
-html_logo = "_static/img/horizontal-lockup.png"
+html_logo = "_static/img/logo.png"
 
 html_theme_options = {
     "logo_only": True,
@@ -168,8 +168,8 @@ latex_documents = [
 
 # One entry per manual page. List of tuples
 # (source start file, name, description, authors, manual section).
-man_pages = [(master_doc, "ProtoTorch", "ProtoTorch Documentation", [author],
-              1)]
+man_pages = [(master_doc, "ProtoTorch Models",
+              "ProtoTorch Models Plugin Documentation", [author], 1)]
 
 # -- Options for Texinfo output -------------------------------------------
 
@@ -179,19 +179,22 @@ man_pages = [(master_doc, "ProtoTorch", "ProtoTorch Documentation", [author],
 texinfo_documents = [
     (
         master_doc,
-        "prototorch",
-        "ProtoTorch Documentation",
+        "prototorch models",
+        "ProtoTorch Models Plugin Documentation",
         author,
-        "prototorch",
-        "Prototype-based machine learning in PyTorch.",
+        "prototorch models",
+        "Prototype-based machine learning Models in ProtoTorch.",
         "Miscellaneous",
     ),
 ]
 
 # Example configuration for intersphinx: refer to the Python standard library.
 intersphinx_mapping = {
-    "python": ("https://docs.python.org/", None),
-    "numpy": ("https://docs.scipy.org/doc/numpy/", None),
+    "python": ("https://docs.python.org/3/", None),
+    "numpy": ("https://numpy.org/doc/stable/", None),
+    "torch": ('https://pytorch.org/docs/stable/', None),
+    "pytorch_lightning":
+    ("https://pytorch-lightning.readthedocs.io/en/stable/", None),
 }
 
 # -- Options for Epub output ----------------------------------------------

docs/source/custom.rst

@@ -0,0 +1,9 @@
+.. Customize the Models
+
+Abstract Models
+========================================
+.. autoclass:: prototorch.models.abstract.AbstractPrototypeModel
+   :members:
+
+.. autoclass:: prototorch.models.abstract.PrototypeImageModel
+   :members:

docs/source/index.rst

@@ -1,25 +1,40 @@
 .. ProtoTorch Models documentation master file
-   You can adapt this file completely to your liking, but it should at least
-   contain the root `toctree` directive.
 
-About ProtoTorch Models
-========================
+ProtoTorch Models Plugins
+========================================
+.. toctree::
+   :hidden:
+   :maxdepth: 3
+
+   self
+   tutorial.ipynb
 
 .. toctree::
    :hidden:
    :maxdepth: 3
-   :caption: Contents:
+   :caption: Library
 
-   self
-   models
-   tutorial.ipynb
+   library
 
+.. toctree::
+   :hidden:
+   :maxdepth: 3
+   :caption: Customize
+
+   custom
+
+About
+-----------------------------------------
 `Prototorch Models <https://github.com/si-cim/prototorch_models>`_ is a Plugin
 for `Prototorch <https://github.com/si-cim/prototorch>`_. It implements common
 prototype-based Machine Learning algorithms using `PyTorch-Lightning
 <https://www.pytorchlightning.ai/>`_.
 
-Indices
-=======
-* :ref:`genindex`
-* :ref:`modindex`
+Library
+-----------------------------------------
+Prototorch Models delivers many application ready models.
+These models have been published in the past and have been adapted to the Prototorch library.
+
+Customizable
+-----------------------------------------
+Prototorch Models also contains the building blocks to build own models with PyTorch-Lightning and Prototorch.

docs/source/library.rst

@@ -1,27 +1,35 @@
 .. Available Models
 
-Available Models
+Models
 ========================================
 
 Unsupervised Methods
 -----------------------------------------
-.. autoclass:: prototorch.models.knn.KNN
+.. autoclass:: prototorch.models.unsupervised.KNN
    :members:
 
-.. autoclass:: prototorch.models.neural_gas.NeuralGas
+.. autoclass:: prototorch.models.unsupervised.NeuralGas
    :members:
 
 
 Classical Learning Vector Quantization
 -----------------------------------------
-Original LVQ models. Implementations use GLVQ structure as shown in [Sato&Yamada].
+Original LVQ models by Kohonen.
+These heuristic algorithms do not use gradient descent.
 
 .. autoclass:: prototorch.models.glvq.LVQ1
    :members:
-
 .. autoclass:: prototorch.models.glvq.LVQ21
    :members:
 
+It is also possible to use the GLVQ structure as shown in [Sato&Yamada].
+This allows the use of gradient descent methods.
+
+.. autoclass:: prototorch.models.glvq.GLVQ1
+   :members:
+.. autoclass:: prototorch.models.glvq.GLVQ21
+   :members:
+
 Generalized Learning Vector Quantization
 -----------------------------------------
 
@@ -43,10 +51,17 @@ Generalized Learning Vector Quantization
 .. autoclass:: prototorch.models.glvq.LVQMLN
    :members:
 
-CBC
+Classification by Component
 -----------------------------------------
 .. autoclass:: prototorch.models.cbc.CBC
    :members:
 
 .. autoclass:: prototorch.models.cbc.ImageCBC
-   :members:
+   :members:
+
+Visualization
+========================================
+
+.. automodule:: prototorch.models.vis
+   :members:
+   :undoc-members: