scipy.cluster.hierarchy.leaders¶

scipy.cluster.hierarchy.
leaders
(Z, T)[source]¶ Returns the root nodes in a hierarchical clustering.
Returns the root nodes in a hierarchical clustering corresponding to a cut defined by a flat cluster assignment vector
T
. See thefcluster
function for more information on the format ofT
.For each flat cluster \(j\) of the \(k\) flat clusters represented in the nsized flat cluster assignment vector
T
, this function finds the lowest cluster node \(i\) in the linkage tree Z such that: leaf descendents belong only to flat cluster j
(i.e.
T[p]==j
for all \(p\) in \(S(i)\) where \(S(i)\) is the set of leaf ids of leaf nodes descendent with cluster node \(i\))  there does not exist a leaf that is not descendent with
\(i\) that also belongs to cluster \(j\)
(i.e.
T[q]!=j
for all \(q\) not in \(S(i)\)). If this condition is violated,T
is not a valid cluster assignment vector, and an exception will be thrown.
Parameters: Z : ndarray
The hierarchical clustering encoded as a matrix. See
linkage
for more information.T : ndarray
The flat cluster assignment vector.
Returns: L : ndarray
The leader linkage node id’s stored as a kelement 1D array where
k
is the number of flat clusters found inT
.L[j]=i
is the linkage cluster node id that is the leader of flat cluster with id M[j]. Ifi < n
,i
corresponds to an original observation, otherwise it corresponds to a nonsingleton cluster.For example: if
L[3]=2
andM[3]=8
, the flat cluster with id 8’s leader is linkage node 2.M : ndarray
The leader linkage node id’s stored as a kelement 1D array where
k
is the number of flat clusters found inT
. This allows the set of flat cluster ids to be any arbitrary set ofk
integers. leaf descendents belong only to flat cluster j
(i.e.