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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: |