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.
- Z : array_like
The linkage matrix to check for correspondence.
- Y : array_like
The condensed distance matrix to check for correspondence.
- b : bool
A boolean indicating whether the linkage matrix and distance matrix could possibly correspond to one another.
- for a description of what a linkage matrix is.
>>> 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
Zhas been obtained from the application of a cluster method over a dataset
>>> 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
X(in condensed form):
>>> correspond(Z, X_condensed) True