def clustercentroids(self, clusterid=None, method='a', transpose=0):
"""Calculate the cluster centroids and return a tuple (cdata, cmask).
The centroid is defined as either the mean or the median over all elements
for each dimension.
- data : nrows x ncolumns array containing the expression data
- mask : nrows x ncolumns array of integers, showing which data are
missing. If mask[i][j]==0, then data[i][j] is missing.
- transpose: if equal to 0, gene (row) clusters are considered;
if equal to 1, microarray (column) clusters are considered.
- clusterid: array containing the cluster number for each gene or
microarray. The cluster number should be non-negative.
- method : specifies how the centroid is calculated:
method=='a': arithmetic mean over each dimension. (default)
method=='m': median over each dimension.
Return values:
- cdata : 2D array containing the cluster centroids. If transpose==0,
then the dimensions of cdata are nclusters x ncolumns. If
transpose==1, then the dimensions of cdata are
nrows x nclusters.
- cmask : 2D array of integers describing which elements in cdata,
if any, are missing.
"""
return clustercentroids(self.data, self.mask, clusterid, method,
transpose)
def clustercentroids(self, clusterid=None, method='a', transpose=0):
"""Calculate the cluster centroids and return a tuple (cdata, cmask).
The centroid is defined as either the mean or the median over all
elements for each dimension.
Arguments:
- data : nrows x ncolumns array containing the expression data
- mask : nrows x ncolumns array of integers, showing which data
are missing. If mask[i][j]==0, then data[i][j] is missing.
- transpose: if equal to 0, gene (row) clusters are considered;
if equal to 1, microarray (column) clusters are considered.
- clusterid: array containing the cluster number for each gene or
microarray. The cluster number should be non-negative.
- method : specifies how the centroid is calculated:
- method=='a': arithmetic mean over each dimension. (default)
- method=='m': median over each dimension.
Return values:
- cdata : 2D array containing the cluster centroids. If transpose==0,
then the dimensions of cdata are nclusters x ncolumns. If
transpose==1, then the dimensions of cdata are nrows x nclusters.
- cmask : 2D array of integers describing which elements in cdata,
if any, are missing.
"""
return clustercentroids(self.data, self.mask, clusterid, method,
transpose)