scipy tutorial - Baustatik-Info-Server

SciPy Reference Guide, Release 0.8.dev
maxdists(Z)
Returns the maximum distance between any cluster for each non-singleton cluster.
Arguments
Returns
• Z
[ndarray] The hierarchical clustering encoded as a matrix. See linkage for more
information.
• MD : ndarray A (n-1) sized numpy array of doubles; MD[i] represents the maximum
distance between any cluster (including singletons) below and including the node with
index i. More specifically, MD[i] = Z[Q(i)-n, 2].max() where Q(i) is the set
of all node indices below and including node i.
maxinconsts(Z, R)
Returns the maximum inconsistency coefficient for each non-singleton cluster and its descendents.
Arguments
Returns
• Z
• R
[ndarray] The hierarchical clustering encoded as a matrix. See linkage for more
information.
[ndarray] The inconsistency matrix.
• MI
[ndarray] A monotonic (n-1)-sized numpy array of doubles.
median(y)
Performs median/WPGMC linkage. See linkage for more information on the return structure and algorithm.
The following are common calling conventions:
1.Z = median(y)
Performs median/WPGMC linkage on the condensed distance matrix y. See linkage for more information
on the return structure and algorithm.
2.Z = median(X)
Performs median/WPGMC linkage on the observation matrix X using Euclidean distance as the distance
metric. See linkage for more information on the return structure and algorithm.
Parameters
Q
[ndarray] A condensed or redundant distance matrix. A condensed distance matrix is a
flat array containing the upper triangular of the distance matrix. This is the form that
pdist returns. Alternatively, a collection of m observation vectors in n dimensions may
be passed as a m by n array.
144 Chapter 3. Reference