Example usage for org.apache.commons.math3.linear RealMatrix toString

Introduction

In this page you can find the example usage for org.apache.commons.math3.linear RealMatrix toString.

Prototype

public String toString() 

Source Link

Document

Returns a string representation of the object.

Usage

From source file:edu.oregonstate.eecs.mcplan.ml.KulisLowRankKernelLearner.java

/**
 * @param args/*w  w w .ja v a  2s . com*/
 */
public static void main(final String[] args) {
    final RandomGenerator rng = new MersenneTwister(42);
    final int d = 2;
    final double u = 5.0;
    final double ell = 7.0;
    final double gamma = 1.0;
    final ArrayList<RealVector> X = new ArrayList<RealVector>();
    final RealMatrix A0 = MatrixUtils.createRealIdentityMatrix(d);

    for (final int w : new int[] { 0, 5 }) {
        for (final int h : new int[] { 0, 5 }) {
            for (int x = -1; x <= 1; ++x) {
                for (int y = -1; y <= 1; ++y) {
                    X.add(new ArrayRealVector(new double[] { x + w, y + h }));
                }
            }
        }
    }

    final ArrayList<int[]> S = new ArrayList<int[]>();
    S.add(new int[] { 4, 31 }); // Must link diagonally
    final ArrayList<int[]> D = new ArrayList<int[]>();
    D.add(new int[] { 4, 13 });
    D.add(new int[] { 22, 31 });
    D.add(new int[] { 13, 22 }); // Cannot link vertically

    final KulisLowRankKernelLearner itml = new KulisLowRankKernelLearner(X, S, D, u, ell, A0, gamma, rng);
    itml.run();

    final RealMatrix A = itml.A();

    System.out.println(A0.toString());

    for (final int[] c : S) {
        final RealVector diff = X.get(c[0]).subtract(X.get(c[1]));
        System.out.println(diff.dotProduct(A0.operate(diff)));
    }
    for (final int[] c : D) {
        final RealVector diff = X.get(c[0]).subtract(X.get(c[1]));
        System.out.println(diff.dotProduct(A0.operate(diff)));
    }

    System.out.println(A.toString());

    for (final int[] c : S) {
        final RealVector diff = X.get(c[0]).subtract(X.get(c[1]));
        System.out.println(diff.dotProduct(A.operate(diff)));
    }
    for (final int[] c : D) {
        final RealVector diff = X.get(c[0]).subtract(X.get(c[1]));
        System.out.println(diff.dotProduct(A.operate(diff)));
    }

    //      int i = 0;
    //      for( final int w : new int[] { 0, 5 } ) {
    //         for( final int h : new int[] { 0, 5 } ) {
    //            for( int x = -1; x <= 1; ++x ) {
    //               for( int y = -1; y <= 1; ++y ) {
    //                  System.out.println( itml.A().operate( X.get( i++ ) ) );
    //               }
    //            }
    //         }
    //      }
}

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From source file:edu.oregonstate.eecs.mcplan.ml.InformationTheoreticMetricLearner.java

/**
 * @param args//from  ww w . j a va2s .c o  m
 */
public static void main(final String[] args) {
    final RandomGenerator rng = new MersenneTwister(42);
    final int d = 2;
    final double u = 5.0;
    final double ell = 7.0;
    final double gamma = 1.0;
    final ArrayList<RealVector> X = new ArrayList<RealVector>();
    final RealMatrix A0 = MatrixUtils.createRealIdentityMatrix(d);

    for (final int w : new int[] { 0, 5 }) {
        for (final int h : new int[] { 0, 50 }) {
            for (int x = -1; x <= 1; ++x) {
                for (int y = -1; y <= 1; ++y) {
                    X.add(new ArrayRealVector(new double[] { x + w, y + h }));
                }
            }
        }
    }

    final ArrayList<int[]> S = new ArrayList<int[]>();
    S.add(new int[] { 4, 12 }); // Must link diagonally
    S.add(new int[] { 21, 31 });
    final ArrayList<double[]> Sd = new ArrayList<double[]>();
    for (final int[] s : S) {
        final double[] a = X.get(s[0]).subtract(X.get(s[1])).toArray();
        Sd.add(a);
    }

    final ArrayList<int[]> D = new ArrayList<int[]>();
    D.add(new int[] { 5, 23 });
    D.add(new int[] { 13, 32 }); // Cannot link vertically
    final ArrayList<double[]> Dd = new ArrayList<double[]>();
    for (final int[] dd : D) {
        final double[] a = X.get(dd[0]).subtract(X.get(dd[1])).toArray();
        Dd.add(a);
    }

    final InformationTheoreticMetricLearner itml = new InformationTheoreticMetricLearner(Sd, Dd, u, ell, A0,
            gamma, rng);
    itml.run();

    final RealMatrix A = itml.A();

    System.out.println(A0.toString());

    for (final int[] c : S) {
        final RealVector diff = X.get(c[0]).subtract(X.get(c[1]));
        System.out.println(diff.dotProduct(A0.operate(diff)));
    }
    for (final int[] c : D) {
        final RealVector diff = X.get(c[0]).subtract(X.get(c[1]));
        System.out.println(diff.dotProduct(A0.operate(diff)));
    }

    System.out.println(A.toString());

    for (final int[] c : S) {
        final RealVector diff = X.get(c[0]).subtract(X.get(c[1]));
        System.out.println(diff.dotProduct(A.operate(diff)));
    }
    for (final int[] c : D) {
        final RealVector diff = X.get(c[0]).subtract(X.get(c[1]));
        System.out.println(diff.dotProduct(A.operate(diff)));
    }

    //      int i = 0;
    //      for( final int w : new int[] { 0, 5 } ) {
    //         for( final int h : new int[] { 0, 5 } ) {
    //            for( int x = -1; x <= 1; ++x ) {
    //               for( int y = -1; y <= 1; ++y ) {
    //                  System.out.println( itml.A().operate( X.get( i++ ) ) );
    //               }
    //            }
    //         }
    //      }
}

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