Examples with DoubleMatrix2D cern.colt.matrix.DoubleMatrix2D used on opensource projects

Example 31 with DoubleMatrix2D

use of cern.colt.matrix.DoubleMatrix2D in project tdq-studio-se by Talend.

the class TestMatrix2D method doubleTest23.

/**
 */
public static void doubleTest23(int runs, int size, double nonZeroFraction, boolean dense) {
    System.out.println("\n\n");
    System.out.println("initializing...");
    DoubleMatrix2D A, LU, I, Inv;
    DoubleMatrix1D b, solved;
    double mean = 5.0;
    double stdDev = 3.0;
    cern.jet.random.Normal random = new cern.jet.random.Normal(mean, stdDev, new cern.jet.random.engine.MersenneTwister());
    System.out.println("sampling...");
    double value = 2;
    if (dense)
        A = Factory2D.dense.sample(size, size, value, nonZeroFraction);
    else
        A = Factory2D.sparse.sample(size, size, value, nonZeroFraction);
    b = A.like1D(size).assign(1);
    // A.assign(random);
    // A.assign(F.rint); // round
    System.out.println("generating invertible matrix...");
    Property.generateNonSingular(A);
    // I = Factory2D.identity(size);
    LU = A.like();
    solved = b.like();
    // Inv = Factory2D.make(size,size);
    LUDecompositionQuick lu = new LUDecompositionQuick();
    System.out.println("benchmarking assignment...");
    cern.colt.Timer timer = new cern.colt.Timer().start();
    LU.assign(A);
    solved.assign(b);
    timer.stop().display();
    LU.assign(A);
    lu.decompose(LU);
    System.out.println("benchmarking LU...");
    timer.reset().start();
    for (int i = runs; --i >= 0; ) {
        solved.assign(b);
        // Inv.assign(I);
        // lu.decompose(LU);
        lu.solve(solved);
    // lu.solve(Inv);
    }
    timer.stop().display();
    // System.out.println("A="+A);
    // System.out.println("LU="+LU);
    // System.out.println("U="+lu.getU());
    // System.out.println("L="+lu.getL());
    System.out.println("done.");
}

Example 32 with DoubleMatrix2D

use of cern.colt.matrix.DoubleMatrix2D in project tdq-studio-se by Talend.

the class TestMatrix2D method doubleTest7.

/**
 */
public static void doubleTest7() {
    int rows = 4;
    // make a 4*5 matrix
    int columns = 5;
    DoubleMatrix2D master = Factory2D.ascending(rows, columns);
    // master.assign(1); // set all cells to 1
    System.out.println("\n" + master);
    // master.viewPart(2,0,2,3).assign(2); // set [2,1] .. [3,3] to 2
    // System.out.println("\n"+master);
    int[] rowIndexes = { 0, 1, 3, 0 };
    int[] columnIndexes = { 0, 2 };
    DoubleMatrix2D view1 = master.viewSelection(rowIndexes, columnIndexes);
    System.out.println("view1=" + view1);
    DoubleMatrix2D view2 = view1.viewPart(0, 0, 2, 2);
    System.out.println("view2=" + view2);
    view2.assign(-1);
    System.out.println("master replaced" + master);
    System.out.println("flip1 replaced" + view1);
    System.out.println("flip2 replaced" + view2);
}

Example 33 with DoubleMatrix2D

use of cern.colt.matrix.DoubleMatrix2D in project tdq-studio-se by Talend.

the class TestMatrix2D method doubleTest27.

/**
 */
public static void doubleTest27() {
    System.out.println("\n\n");
    System.out.println("initializing...");
    int rows = 51;
    int columns = 10;
    double[][] trainingSet = new double[columns][rows];
    for (int i = columns; --i >= 0; ) trainingSet[i][i] = 2.0;
    int patternIndex = 0;
    int unitIndex = 0;
    DoubleMatrix2D patternMatrix = null;
    DoubleMatrix2D transposeMatrix = null;
    DoubleMatrix2D QMatrix = null;
    DoubleMatrix2D inverseQMatrix = null;
    DoubleMatrix2D pseudoInverseMatrix = null;
    DoubleMatrix2D weightMatrix = null;
    // form a matrix with the columns as training vectors
    patternMatrix = DoubleFactory2D.dense.make(rows, columns);
    // copy the patterns into the matrix
    for (patternIndex = 0; patternIndex < columns; patternIndex++) {
        for (unitIndex = 0; unitIndex < rows; unitIndex++) {
            patternMatrix.setQuick(unitIndex, patternIndex, trainingSet[patternIndex][unitIndex]);
        }
    }
    transposeMatrix = Algebra.DEFAULT.transpose(patternMatrix);
    QMatrix = Algebra.DEFAULT.mult(transposeMatrix, patternMatrix);
    inverseQMatrix = Algebra.DEFAULT.inverse(QMatrix);
    pseudoInverseMatrix = Algebra.DEFAULT.mult(inverseQMatrix, transposeMatrix);
    weightMatrix = Algebra.DEFAULT.mult(patternMatrix, pseudoInverseMatrix);
    System.out.println("done.");
}

Example 34 with DoubleMatrix2D

use of cern.colt.matrix.DoubleMatrix2D in project tdq-studio-se by Talend.

the class TestMatrix2D method testLU.

/**
 */
public static void testLU() {
    double[][] vals = { { -0.074683, 0.321248, -0.014656, 0.286586, 0 }, { -0.344852, -0.16278, 0.173711, 0.00064, 0 }, { -0.181924, -0.092926, 0.184153, 0.177966, 1 }, { -0.166829, -0.10321, 0.582301, 0.142583, 0 }, { 0, -0.112952, -0.04932, -0.700157, 0 }, { 0, 0, 0, 0, 0 } };
    // see values below...
    DoubleMatrix2D H = new DenseDoubleMatrix2D(vals);
    System.out.println("\nHplus=" + H.viewDice().zMult(H, null));
    DoubleMatrix2D Hplus = Algebra.DEFAULT.inverse(H.viewDice().zMult(H, null)).zMult(H.viewDice(), null);
    Hplus.assign(cern.jet.math.Functions.round(1.0E-10));
    System.out.println("\nHplus=" + Hplus);
/*
DoubleMatrix2D HtH = new DenseDoubleMatrix2D( 5, 5 );
DoubleMatrix2D Hplus = new DenseDoubleMatrix2D( 5, 6 );
LUDecompositionQuick LUD = new LUDecompositionQuick();
		//H.zMult( H, HtH, 1, 0, true, false );
		//DoubleMatrix2D res = Algebra.DEFAULT.inverse(HtH).zMult(H,null,1,0,false,true);
		LUD.decompose( HtH );
		// first fill Hplus with the transpose of H...
		for (int i = 0; i < 6; i++ ) {
			for ( int j = 0; j < 5; j++ ) {
				Hplus.set( j, i, H.get( i, j ) );
			}
		}
		LUD.solve( Hplus );

		DoubleMatrix2D perm = Algebra.DEFAULT.permute(Hplus, null,LUD.getPivot());
		DoubleMatrix2D inv = Algebra.DEFAULT.inverse(HtH);//.zMult(H,null,1,0,false,true);
		*/
// in matlab...
// Hplus = inv(H' * H) * H'
// System.out.println("\nLU="+LUD);
// System.out.println("\nHplus="+Hplus);
// System.out.println("\nperm="+perm);
// System.out.println("\ninv="+inv);
// System.out.println("\nres="+res);
}

Example 35 with DoubleMatrix2D

use of cern.colt.matrix.DoubleMatrix2D in project tdq-studio-se by Talend.

the class SmpBlas method dgemv.

public void dgemv(final boolean transposeA, final double alpha, DoubleMatrix2D A, final DoubleMatrix1D x, final double beta, DoubleMatrix1D y) {
    /*
	split A, as follows:
	
			x x
			x
			x
	A
	xxx     x y
	xxx     x
	---     -
	xxx     x
	xxx     x
	---     -
	xxx     x

	*/
    if (transposeA) {
        dgemv(false, alpha, A.viewDice(), x, beta, y);
        return;
    }
    int m = A.rows();
    int n = A.columns();
    long flops = 2L * m * n;
    // each thread should process at least 30000 flops
    int noOfTasks = (int) Math.min(flops / 30000, this.maxThreads);
    int width = A.rows();
    noOfTasks = Math.min(width, noOfTasks);
    if (noOfTasks < 2) {
        // parallelization doesn't pay off (too much start up overhead)
        seqBlas.dgemv(transposeA, alpha, A, x, beta, y);
        return;
    }
    // set up concurrent tasks
    int span = width / noOfTasks;
    final FJTask[] subTasks = new FJTask[noOfTasks];
    for (int i = 0; i < noOfTasks; i++) {
        final int offset = i * span;
        // last span may be a bit larger
        if (i == noOfTasks - 1)
            span = width - span * i;
        // split A along rows into blocks
        final DoubleMatrix2D AA = A.viewPart(offset, 0, span, n);
        final DoubleMatrix1D yy = y.viewPart(offset, span);
        subTasks[i] = new FJTask() {

            public void run() {
                seqBlas.dgemv(transposeA, alpha, AA, x, beta, yy);
            // System.out.println("Hello "+offset);
            }
        };
    }
    // run tasks and wait for completion
    try {
        this.smp.taskGroup.invoke(new FJTask() {

            public void run() {
                coInvoke(subTasks);
            }
        });
    } catch (InterruptedException exc) {
    }
}