tangles.separations.finding
===========================

.. currentmodule:: tangles.separations.finding

.. automodule:: tangles.separations.finding


   .. rubric:: Classes

   .. toctree::
      :hidden:

      tangles.separations.finding.OrderFuncDerivative

   .. list-table::
      :widths: 50 50

      * - :class:`OrderFuncDerivative`
        - Abstract Base Class for use with the minimize cut method


   .. rubric:: Functions

   .. toctree::
      :hidden:

      tangles.separations.finding.add_all_corners_of_features
      tangles.separations.finding.min_S_T_cut
      tangles.separations.finding.minimize_cut
      tangles.separations.finding.nodal_domains
      tangles.separations.finding.pca_features
      tangles.separations.finding.random_features
      tangles.separations.finding.spectral_features
      tangles.separations.finding.spectral_features_splitted

   .. list-table::
      :widths: 50 50

      * - :func:`add_all_corners_of_features`
        - Calculates the four corners of every pair of features from an input array
      * - :func:`min_S_T_cut`
        - Search a minimal weight `S`-`T`-cut in the graph with adjacency matrix `A`
      * - :func:`minimize_cut`
        - Find a locally minimal cut in a graph starting with the cut specified by `starting_feature`
      * - :func:`nodal_domains`
        - Calculate the nodal domains of a function from the vertices of the graph with adjacency matrix `A` to the real numbers
      * - :func:`pca_features`
        - Generate features using a method inspired by Principal Component Analysis (PCA)
      * - :func:`random_features`
        - Generates an array of features randomly
      * - :func:`spectral_features`
        - Compute spectral bipartitions directly by computing eigenvectors of the complete graph
      * - :func:`spectral_features_splitted`
        - Compute spectral bipartitions of a graph after splitting into connected components