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-rwxr-xr-xsrc/python/doc/conf.py1
-rw-r--r--src/python/doc/index.rst5
-rw-r--r--src/python/doc/representations.rst48
-rw-r--r--src/python/doc/representations_sum.inc14
4 files changed, 68 insertions, 0 deletions
diff --git a/src/python/doc/conf.py b/src/python/doc/conf.py
index e4c718c3..64d9cba1 100755
--- a/src/python/doc/conf.py
+++ b/src/python/doc/conf.py
@@ -39,6 +39,7 @@ extensions = [
'sphinx.ext.mathjax',
'sphinx.ext.ifconfig',
'sphinx.ext.viewcode',
+ 'sphinx.ext.napoleon',
'sphinxcontrib.bibtex',
]
diff --git a/src/python/doc/index.rst b/src/python/doc/index.rst
index 8f27da0d..1ef08096 100644
--- a/src/python/doc/index.rst
+++ b/src/python/doc/index.rst
@@ -78,6 +78,11 @@ Wasserstein distance
.. include:: wasserstein_distance_sum.inc
+Persistence representations
+===========================
+
+.. include:: representations_sum.inc
+
Persistence graphical tools
===========================
diff --git a/src/python/doc/representations.rst b/src/python/doc/representations.rst
new file mode 100644
index 00000000..a137a035
--- /dev/null
+++ b/src/python/doc/representations.rst
@@ -0,0 +1,48 @@
+:orphan:
+
+.. To get rid of WARNING: document isn't included in any toctree
+
+======================
+Representations manual
+======================
+
+.. include:: representations_sum.inc
+
+This module, originally named sklearn_tda, aims at bridging the gap between persistence diagrams and machine learning tools, in particular scikit-learn. It provides tools, using the scikit-learn standard interface, to compute distances and kernels on diagrams, and to convert diagrams into vectors.
+
+A diagram is represented as a numpy array of shape (n,2), as can be obtained from `SimplexTree.persistence_intervals_in_dimension` for instance. Points at infinity are represented as a numpy array of shape (n,1), storing only the birth time.
+
+A small example is provided
+
+.. only:: builder_html
+
+ * :download:`diagram_vectorizations_distances_kernels.py <../example/diagram_vectorizations_distances_kernels.py>`
+
+
+Preprocessing
+-------------
+.. automodule:: gudhi.representations.preprocessing
+ :members:
+ :special-members:
+ :show-inheritance:
+
+Vector methods
+--------------
+.. automodule:: gudhi.representations.vector_methods
+ :members:
+ :special-members:
+ :show-inheritance:
+
+Kernel methods
+--------------
+.. automodule:: gudhi.representations.kernel_methods
+ :members:
+ :special-members:
+ :show-inheritance:
+
+Metrics
+-------
+.. automodule:: gudhi.representations.metrics
+ :members:
+ :special-members:
+ :show-inheritance:
diff --git a/src/python/doc/representations_sum.inc b/src/python/doc/representations_sum.inc
new file mode 100644
index 00000000..7b167a17
--- /dev/null
+++ b/src/python/doc/representations_sum.inc
@@ -0,0 +1,14 @@
+.. table::
+ :widths: 30 50 20
+
+ +------------------------------------------------------------------+----------------------------------------------------------------+-----------------------------------------------+
+ | .. figure:: | Vectorizations, distances and kernels that work on persistence | :Author: Mathieu Carrière |
+ | ../../doc/Persistence_representations/average_landscape.png | diagrams, compatible with scikit-learn. | |
+ | | | :Introduced in: GUDHI 3.1.0 |
+ | | | |
+ | | | :Copyright: MIT |
+ | | | |
+ | | | :Requires: scikit-learn |
+ +------------------------------------------------------------------+----------------------------------------------------------------+-----------------------------------------------+
+ | * :doc:`representations` |
+ +------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------+