# scipy.cluster.hierarchy.correspond

scipy.cluster.hierarchy.correspond(Z, Y)

  Check for correspondence between linkage and condensed distance matrices.

  They must have the same number of original observations for the check to succeed.

  This function is useful as a sanity check in algorithms that make extensive use of linkage and distance matrices that must correspond to the same set of original observations.

  Parameters
    Z array_like

      The linkage matrix to check for correspondence.

    Y array_like

      The condensed distance matrix to check for correspondence.

  Returns
    b bool

      A boolean indicating whether the linkage matrix and distance matrix could possibly correspond to one another.

  See also

  `linkage`

    for a description of what a linkage matrix is.

  Examples

      >>> from scipy.cluster.hierarchy import ward, correspond
      >>> from scipy.spatial.distance import pdist

  This method can be used to check if a given linkage matrix `Z` has been obtained from the application of a cluster method over a dataset `X`:

      >>> X = [[0, 0], [0, 1], [1, 0],
      ...      [0, 4], [0, 3], [1, 4],
      ...      [4, 0], [3, 0], [4, 1],
      ...      [4, 4], [3, 4], [4, 3]]
      >>> X_condensed = pdist(X)
      >>> Z = ward(X_condensed)

  Here, we can compare `Z` and `X` (in condensed form):

      >>> correspond(Z, X_condensed)
      True

scipy.cluster.hierarchy.is_monotonic scipy.cluster.hierarchy.num_obs_linkage