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)