import java.text.*;
import com.imsl.stat.*;
import com.imsl.math.PrintMatrix;

public class DiscriminantAnalysisEx1 {
    public static void main(String args[]) throws Exception {
        double[][] xorig = {
            {1.0, 5.1, 3.5, 1.4, .2},
            {1.0, 4.9, 3.0, 1.4, .2},
            {1.0, 4.7, 3.2, 1.3, .2},
            {1.0, 4.6, 3.1, 1.5, .2},
            {1.0, 5.0, 3.6, 1.4, .2},
            {1.0, 5.4, 3.9, 1.7, .4},
            {1.0, 4.6, 3.4, 1.4, .3},
            {1.0, 5.0, 3.4, 1.5, .2},
            {1.0, 4.4, 2.9, 1.4, .2},
            {1.0, 4.9, 3.1, 1.5, .1},
            {1.0, 5.4, 3.7, 1.5, .2},
            {1.0, 4.8, 3.4, 1.6, .2},
            {1.0, 4.8, 3.0, 1.4, .1},
            {1.0, 4.3, 3.0, 1.1, .1},
            {1.0, 5.8, 4.0, 1.2, .2},
            {1.0, 5.7, 4.4, 1.5, .4},
            {1.0, 5.4, 3.9, 1.3, .4},
            {1.0, 5.1, 3.5, 1.4, .3},
            {1.0, 5.7, 3.8, 1.7, .3},
            {1.0, 5.1, 3.8, 1.5, .3},
            {1.0, 5.4, 3.4, 1.7, .2},
            {1.0, 5.1, 3.7, 1.5, .4},
            {1.0, 4.6, 3.6, 1.0, .2},
            {1.0, 5.1, 3.3, 1.7, .5},
            {1.0, 4.8, 3.4, 1.9, .2},
            {1.0, 5.0, 3.0, 1.6, .2},
            {1.0, 5.0, 3.4, 1.6, .4},
            {1.0, 5.2, 3.5, 1.5, .2},
            {1.0, 5.2, 3.4, 1.4, .2},
            {1.0, 4.7, 3.2, 1.6, .2},
            {1.0, 4.8, 3.1, 1.6, .2},
            {1.0, 5.4, 3.4, 1.5, .4},
            {1.0, 5.2, 4.1, 1.5, .1},
            {1.0, 5.5, 4.2, 1.4, .2},
            {1.0, 4.9, 3.1, 1.5, .2},
            {1.0, 5.0, 3.2, 1.2, .2},
            {1.0, 5.5, 3.5, 1.3, .2},
            {1.0, 4.9, 3.6, 1.4, .1},
            {1.0, 4.4, 3.0, 1.3, .2},
            {1.0, 5.1, 3.4, 1.5, .2},
            {1.0, 5.0, 3.5, 1.3, .3},
            {1.0, 4.5, 2.3, 1.3, .3},
            {1.0, 4.4, 3.2, 1.3, .2},
            {1.0, 5.0, 3.5, 1.6, .6},
            {1.0, 5.1, 3.8, 1.9, .4},
            {1.0, 4.8, 3.0, 1.4, .3},
            {1.0, 5.1, 3.8, 1.6, .2},
            {1.0, 4.6, 3.2, 1.4, .2},
            {1.0, 5.3, 3.7, 1.5, .2},
            {1.0, 5.0, 3.3, 1.4, .2},
            {2.0, 7.0, 3.2, 4.7, 1.4},
            {2.0, 6.4, 3.2, 4.5, 1.5},
            {2.0, 6.9, 3.1, 4.9, 1.5},
            {2.0, 5.5, 2.3, 4.0, 1.3},
            {2.0, 6.5, 2.8, 4.6, 1.5},
            {2.0, 5.7, 2.8, 4.5, 1.3},
            {2.0, 6.3, 3.3, 4.7, 1.6},
            {2.0, 4.9, 2.4, 3.3, 1.0},
            {2.0, 6.6, 2.9, 4.6, 1.3},
            {2.0, 5.2, 2.7, 3.9, 1.4},
            {2.0, 5.0, 2.0, 3.5, 1.0},
            {2.0, 5.9, 3.0, 4.2, 1.5},
            {2.0, 6.0, 2.2, 4.0, 1.0},
            {2.0, 6.1, 2.9, 4.7, 1.4},
            {2.0, 5.6, 2.9, 3.6, 1.3},
            {2.0, 6.7, 3.1, 4.4, 1.4},
            {2.0, 5.6, 3.0, 4.5, 1.5},
            {2.0, 5.8, 2.7, 4.1, 1.0},
            {2.0, 6.2, 2.2, 4.5, 1.5},
            {2.0, 5.6, 2.5, 3.9, 1.1},
            {2.0, 5.9, 3.2, 4.8, 1.8},
            {2.0, 6.1, 2.8, 4.0, 1.3},
            {2.0, 6.3, 2.5, 4.9, 1.5},
            {2.0, 6.1, 2.8, 4.7, 1.2},
            {2.0, 6.4, 2.9, 4.3, 1.3},
            {2.0, 6.6, 3.0, 4.4, 1.4},
            {2.0, 6.8, 2.8, 4.8, 1.4},
            {2.0, 6.7, 3.0, 5.0, 1.7},
            {2.0, 6.0, 2.9, 4.5, 1.5},
            {2.0, 5.7, 2.6, 3.5, 1.0},
            {2.0, 5.5, 2.4, 3.8, 1.1},
            {2.0, 5.5, 2.4, 3.7, 1.0},
            {2.0, 5.8, 2.7, 3.9, 1.2},
            {2.0, 6.0, 2.7, 5.1, 1.6},
            {2.0, 5.4, 3.0, 4.5, 1.5},
            {2.0, 6.0, 3.4, 4.5, 1.6},
            {2.0, 6.7, 3.1, 4.7, 1.5},
            {2.0, 6.3, 2.3, 4.4, 1.3},
            {2.0, 5.6, 3.0, 4.1, 1.3},
            {2.0, 5.5, 2.5, 4.0, 1.3},
            {2.0, 5.5, 2.6, 4.4, 1.2},
            {2.0, 6.1, 3.0, 4.6, 1.4},
            {2.0, 5.8, 2.6, 4.0, 1.2},
            {2.0, 5.0, 2.3, 3.3, 1.0},
            {2.0, 5.6, 2.7, 4.2, 1.3},
            {2.0, 5.7, 3.0, 4.2, 1.2},
            {2.0, 5.7, 2.9, 4.2, 1.3},
            {2.0, 6.2, 2.9, 4.3, 1.3},
            {2.0, 5.1, 2.5, 3.0, 1.1},
            {2.0, 5.7, 2.8, 4.1, 1.3},
            {3.0, 6.3, 3.3, 6.0, 2.5},
            {3.0, 5.8, 2.7, 5.1, 1.9},
            {3.0, 7.1, 3.0, 5.9, 2.1},
            {3.0, 6.3, 2.9, 5.6, 1.8},
            {3.0, 6.5, 3.0, 5.8, 2.2},
            {3.0, 7.6, 3.0, 6.6, 2.1},
            {3.0, 4.9, 2.5, 4.5, 1.7},
            {3.0, 7.3, 2.9, 6.3, 1.8},
            {3.0, 6.7, 2.5, 5.8, 1.8},
            {3.0, 7.2, 3.6, 6.1, 2.5},
            {3.0, 6.5, 3.2, 5.1, 2.0},
            {3.0, 6.4, 2.7, 5.3, 1.9},
            {3.0, 6.8, 3.0, 5.5, 2.1},
            {3.0, 5.7, 2.5, 5.0, 2.0},
            {3.0, 5.8, 2.8, 5.1, 2.4},
            {3.0, 6.4, 3.2, 5.3, 2.3},
            {3.0, 6.5, 3.0, 5.5, 1.8},
            {3.0, 7.7, 3.8, 6.7, 2.2},
            {3.0, 7.7, 2.6, 6.9, 2.3},
            {3.0, 6.0, 2.2, 5.0, 1.5},
            {3.0, 6.9, 3.2, 5.7, 2.3},
            {3.0, 5.6, 2.8, 4.9, 2.0},
            {3.0, 7.7, 2.8, 6.7, 2.0},
            {3.0, 6.3, 2.7, 4.9, 1.8},
            {3.0, 6.7, 3.3, 5.7, 2.1},
            {3.0, 7.2, 3.2, 6.0, 1.8},
            {3.0, 6.2, 2.8, 4.8, 1.8},
            {3.0, 6.1, 3.0, 4.9, 1.8},
            {3.0, 6.4, 2.8, 5.6, 2.1},
            {3.0, 7.2, 3.0, 5.8, 1.6},
            {3.0, 7.4, 2.8, 6.1, 1.9},
            {3.0, 7.9, 3.8, 6.4, 2.0},
            {3.0, 6.4, 2.8, 5.6, 2.2},
            {3.0, 6.3, 2.8, 5.1, 1.5},
            {3.0, 6.1, 2.6, 5.6, 1.4},
            {3.0, 7.7, 3.0, 6.1, 2.3},
            {3.0, 6.3, 3.4, 5.6, 2.4},
            {3.0, 6.4, 3.1, 5.5, 1.8},
            {3.0, 6.0, 3.0, 4.8, 1.8},
            {3.0, 6.9, 3.1, 5.4, 2.1},
            {3.0, 6.7, 3.1, 5.6, 2.4},
            {3.0, 6.9, 3.1, 5.1, 2.3},
            {3.0, 5.8, 2.7, 5.1, 1.9},
            {3.0, 6.8, 3.2, 5.9, 2.3},
            {3.0, 6.7, 3.3, 5.7, 2.5},
            {3.0, 6.7, 3.0, 5.2, 2.3},
            {3.0, 6.3, 2.5, 5.0, 1.9},
            {3.0, 6.5, 3.0, 5.2, 2.0},
            {3.0, 6.2, 3.4, 5.4, 2.3},
            {3.0, 5.9, 3.0, 5.1, 1.8}};
            int i, j, jj, k;
            int ipermu[] = {2, 3, 4, 5, 1};
            double temp;
            double x[][];

            x = new double[xorig.length][xorig[0].length];

            for (i = 0; i< xorig.length; i++) {
                for (j = 1; j < xorig[0].length; j++) {
                    x[i][j-1] = xorig[i][j];
                }               
            }
            for (i = 0; i< xorig.length; i++) {
                x[i][4] = xorig[i][0];
            }
            
            int nvar = x[0].length -1;
            
            DiscriminantAnalysis da = new DiscriminantAnalysis(nvar, 3);
            da.setCovarianceComputation(da.POOLED);
            da.setClassificationMethod(da.RECLASSIFICATION);
            da.update(x);
            new PrintMatrix("Xmean are:  ").print(da.getMeans());
            new PrintMatrix("Coef:  ").print(da.getCoefficients());
            new PrintMatrix("Counts: ").print(da.getGroupCounts());
            new PrintMatrix("Stats: ").print(da.getStatistics());
            new PrintMatrix("ClassMembership: ").print(da.getClassMembership());
            new PrintMatrix("ClassTable: ").print(da.getClassTable()); 
            double cov[][][] = da.getCovariance();
            for (i= 0; i<cov.length;i++) {
                 new PrintMatrix("Covariance Matrix "+i+" : ").print(cov[i]);
            }
            new PrintMatrix("Prior : ").print(da.getPrior());
            new PrintMatrix("PROB: ").print(da.getProbability());
            new PrintMatrix("MAHALANOBIS: ").print(da.getMahalanobis());
            System.out.println("nrmiss = " + da.getNRowsMissing()); 
    }

}