scipy.cluster.hierarchy.correspond#
- scipy.cluster.hierarchy.correspond(Z, Y)[source]#
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:
- Zarray_like
The linkage matrix to check for correspondence.
- Yarray_like
The condensed distance matrix to check for correspondence.
- Returns:
- bbool
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 datasetX
:>>> 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
andX
(in condensed form):>>> correspond(Z, X_condensed) True