Examples with Algebra cern.colt.matrix.linalg.Algebra used on opensource projects

Example 16 with Algebra

use of cern.colt.matrix.linalg.Algebra in project tetrad by cmu-phil.

the class Ricf method lik.

private double lik(DoubleMatrix2D K, DoubleMatrix2D S, int n, int k) {
    Algebra algebra = new Algebra();
    DoubleMatrix2D SK = algebra.mult(S, K);
    return (algebra.trace(SK) - Math.log(algebra.det(SK)) - k) * n;
}

Example 17 with Algebra

use of cern.colt.matrix.linalg.Algebra in project tetrad by cmu-phil.

the class Glasso method fatmul.

// s = vv * x, or s12 = Theta.1 * Theta.12
private void fatmul(int it, int n, DoubleMatrix2D vv, DoubleMatrix1D x, DoubleMatrix1D s, DoubleMatrix1D z, int[] m) {
    double fac = 0.2;
    // z consists of the nonzero entries of x. m indexes these. If there are enough zeroes in x,
    // use the simpler multiplication method.
    int l = 0;
    for (int j = 0; j < n; j++) {
        if (x.get(j) == 0.0)
            continue;
        l = l + 1;
        m[l] = j;
    }
    if (l < (int) (fac * n)) {
        int[] indices = new int[l];
        for (int i = 0; i < indices.length; i++) indices[i] = i;
        if (it == 1) {
            for (int j = 0; j < n; j++) {
                if (Thread.currentThread().isInterrupted()) {
                    break;
                }
                double dotProduct = 0.0;
                for (int i = 0; i < l; i++) {
                    // dotProduct += vv.get(m[i], j) * z.get(j);
                    dotProduct += vv.get(m[i], j) * x.get(m[j]);
                }
                s.set(j, dotProduct);
            }
        } else {
            for (int j = 0; j < n; j++) {
                if (Thread.currentThread().isInterrupted()) {
                    break;
                }
                double dotProduct = 0.0;
                for (int i = 0; i < l; i++) {
                    dotProduct += vv.get(m[i], j) * x.get(m[j]);
                }
                s.set(j, s.get(j) - dotProduct);
            }
        }
    } else if (it == 1) {
        s.assign(new Algebra().mult(vv, x));
    } else {
        s.assign(new Algebra().mult(vv, x), PlusMult.plusMult(-1));
    }
    return;
}

Example 18 with Algebra

use of cern.colt.matrix.linalg.Algebra in project tetrad by cmu-phil.

the class IndTestFisherZGeneralizedInverse method isIndependent.

/**
 * Determines whether variable x is independent of variable y given a list of conditioning variables z.
 *
 * @param xVar the one variable being compared.
 * @param yVar the second variable being compared.
 * @param z    the list of conditioning variables.
 * @return true iff x _||_ y | z.
 * @throws RuntimeException if a matrix singularity is encountered.
 */
public boolean isIndependent(Node xVar, Node yVar, List<Node> z) {
    if (z == null) {
        throw new NullPointerException();
    }
    for (Node node : z) {
        if (node == null) {
            throw new NullPointerException();
        }
    }
    int size = z.size();
    int[] zCols = new int[size];
    int xIndex = getVariables().indexOf(xVar);
    int yIndex = getVariables().indexOf(yVar);
    for (int i = 0; i < z.size(); i++) {
        zCols[i] = getVariables().indexOf(z.get(i));
    }
    int[] zRows = new int[data.rows()];
    for (int i = 0; i < data.rows(); i++) {
        zRows[i] = i;
    }
    DoubleMatrix2D Z = data.viewSelection(zRows, zCols);
    DoubleMatrix1D x = data.viewColumn(xIndex);
    DoubleMatrix1D y = data.viewColumn(yIndex);
    DoubleMatrix2D Zt = new Algebra().transpose(Z);
    DoubleMatrix2D ZtZ = new Algebra().mult(Zt, Z);
    TetradMatrix _ZtZ = new TetradMatrix(ZtZ.toArray());
    TetradMatrix ginverse = _ZtZ.inverse();
    DoubleMatrix2D G = new DenseDoubleMatrix2D(ginverse.toArray());
    DoubleMatrix2D Zt2 = Zt.like();
    Zt2.assign(Zt);
    DoubleMatrix2D GZt = new Algebra().mult(G, Zt2);
    DoubleMatrix1D b_x = new Algebra().mult(GZt, x);
    DoubleMatrix1D b_y = new Algebra().mult(GZt, y);
    DoubleMatrix1D xPred = new Algebra().mult(Z, b_x);
    DoubleMatrix1D yPred = new Algebra().mult(Z, b_y);
    DoubleMatrix1D xRes = xPred.copy().assign(x, Functions.minus);
    DoubleMatrix1D yRes = yPred.copy().assign(y, Functions.minus);
    // Note that r will be NaN if either xRes or yRes is constant.
    double r = StatUtils.correlation(xRes.toArray(), yRes.toArray());
    if (Double.isNaN(thresh)) {
        this.thresh = cutoffGaussian();
    }
    if (Double.isNaN(r)) {
        if (verbose) {
            TetradLogger.getInstance().log("independencies", SearchLogUtils.independenceFactMsg(xVar, yVar, z, getPValue()));
        }
        return true;
    }
    if (r > 1)
        r = 1;
    if (r < -1)
        r = -1;
    this.fishersZ = Math.sqrt(sampleSize() - z.size() - 3.0) * 0.5 * (Math.log(1.0 + r) - Math.log(1.0 - r));
    if (Double.isNaN(this.fishersZ)) {
        throw new IllegalArgumentException("The Fisher's Z " + "score for independence fact " + xVar + " _||_ " + yVar + " | " + z + " is undefined.");
    }
    boolean indFisher = true;
    // if(Math.abs(fishersZ) > 1.96) indFisher = false; //Two sided with alpha = 0.05
    if (Math.abs(fishersZ) > thresh) {
        // Two sided
        indFisher = false;
    }
    if (verbose) {
        if (indFisher) {
            TetradLogger.getInstance().log("independencies", SearchLogUtils.independenceFactMsg(xVar, yVar, z, getPValue()));
        } else {
            TetradLogger.getInstance().log("independencies", SearchLogUtils.independenceFactMsg(xVar, yVar, z, getPValue()));
        }
    }
    return indFisher;
}