NAME: CLUST_WTS1 PURPOSE: This function computes the weights (the cluster centers) of an M-column, N-row array, where M is the number of variables and N is the number of observations or samples. The result is an M-column, N_CLUSTERS-row array of cluster centers. mModified to include CGPROGRESSBAR my Mort Canty (2013) CATEGORY: Statistics CALLING SEQUENCE: Result = Clust_wts(Array) INPUTS: Array: An M-column, N-row array of type float or double. KEYWORD PARAMETERS: DOUBLE: If set to a non-zero value, computations are done in double precision arithmetic. N_CLUSTERS: Use this keyword to specify the number of cluster centers. The default is to compute N cluster centers. N_ITERATIONS: Use this keyword to specify the number of iterations in computing the cluster centers. The default is to use 20 iterations. VARIABLE_WTS: An M-element vector of variable weights. The elements of this vector are used to give greater or lesser importance to each variable (each column) in determining the cluster centers. The default is to give all variables equal weighting using a value of 1.0. EXAMPLE: See the documentation for CLUSTER. REFERENCE: CLUSTER ANALYSIS (Third Edition) Brian S. Everitt ISBN 0-340-58479-3 MODIFICATION HISTORY: Written by: GGS, RSI, June 1996 Adapted from an algorithm written by Robb Habbersett of Los Alamos National Laboratory.