scipy.cluster.hierarchy.maxRstat¶
-
scipy.cluster.hierarchy.
maxRstat
(Z, R, i)[source]¶ Return the maximum statistic for each non-singleton cluster and its children.
- Parameters
- Zarray_like
The hierarchical clustering encoded as a matrix. See
linkage
for more information.- Rarray_like
The inconsistency matrix.
- iint
The column of R to use as the statistic.
- Returns
- MRndarray
Calculates the maximum statistic for the i’th column of the inconsistency matrix R for each non-singleton cluster node.
MR[j]
is the maximum overR[Q(j)-n, i]
, whereQ(j)
the set of all node ids corresponding to nodes below and includingj
.
See also
linkage
for a description of what a linkage matrix is.
inconsistent
for the creation of a inconsistency matrix.
Examples
>>> from scipy.cluster.hierarchy import median, inconsistent, maxRstat >>> from scipy.spatial.distance import pdist
Given a data set
X
, we can apply a clustering method to obtain a linkage matrixZ
.scipy.cluster.hierarchy.inconsistent
can be also used to obtain the inconsistency matrixR
associated to this clustering process:>>> 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]]
>>> Z = median(pdist(X)) >>> R = inconsistent(Z) >>> R array([[1. , 0. , 1. , 0. ], [1. , 0. , 1. , 0. ], [1. , 0. , 1. , 0. ], [1. , 0. , 1. , 0. ], [1.05901699, 0.08346263, 2. , 0.70710678], [1.05901699, 0.08346263, 2. , 0.70710678], [1.05901699, 0.08346263, 2. , 0.70710678], [1.05901699, 0.08346263, 2. , 0.70710678], [1.74535599, 1.08655358, 3. , 1.15470054], [1.91202266, 1.37522872, 3. , 1.15470054], [3.25 , 0.25 , 3. , 0. ]])
scipy.cluster.hierarchy.maxRstat
can be used to compute the maximum value of each column ofR
, for each non-singleton cluster and its children:>>> maxRstat(Z, R, 0) array([1. , 1. , 1. , 1. , 1.05901699, 1.05901699, 1.05901699, 1.05901699, 1.74535599, 1.91202266, 3.25 ]) >>> maxRstat(Z, R, 1) array([0. , 0. , 0. , 0. , 0.08346263, 0.08346263, 0.08346263, 0.08346263, 1.08655358, 1.37522872, 1.37522872]) >>> maxRstat(Z, R, 3) array([0. , 0. , 0. , 0. , 0.70710678, 0.70710678, 0.70710678, 0.70710678, 1.15470054, 1.15470054, 1.15470054])