Examples with DoubleMatrix1D cern.colt.matrix.DoubleMatrix1D used on opensource projects

Example 1 with DoubleMatrix1D

use of cern.colt.matrix.DoubleMatrix1D in project tetrad by cmu-phil.

the class IndTestMixedMultipleTTest method multiLL.

private double multiLL(DoubleMatrix2D coeffs, Node dep, List<Node> indep) {
    DoubleMatrix2D indepData = factory2D.make(internalData.subsetColumns(indep).getDoubleData().toArray());
    List<Node> depList = new ArrayList<>();
    depList.add(dep);
    DoubleMatrix2D depData = factory2D.make(internalData.subsetColumns(depList).getDoubleData().toArray());
    int N = indepData.rows();
    DoubleMatrix2D probs = Algebra.DEFAULT.mult(factory2D.appendColumns(factory2D.make(N, 1, 1.0), indepData), coeffs);
    probs = factory2D.appendColumns(factory2D.make(indepData.rows(), 1, 1.0), probs).assign(Functions.exp);
    double ll = 0;
    for (int i = 0; i < N; i++) {
        DoubleMatrix1D curRow = probs.viewRow(i);
        curRow.assign(Functions.div(curRow.zSum()));
        ll += Math.log(curRow.get((int) depData.get(i, 0)));
    }
    return ll;
}

Example 2 with DoubleMatrix1D

use of cern.colt.matrix.DoubleMatrix1D in project tetrad by cmu-phil.

the class IndTestRegressionAD method determines.

// ==========================PRIVATE METHODS============================//
// /**
// * Return the p-value of the last calculated independence fact.
// *
// * @return this p-value.  When accessed through the IndependenceChecker
// *         interface, this p-value should only be considered to be a
// *         relative strength.
// */
// private double getRelativeStrength() {
// 
// // precondition:  pdf is the most recently used partial
// // correlation distribution function, and storedR is the most
// // recently calculated partial correlation.
// return 2.0 * Integrator.getArea(npdf, Math.abs(storedR), 9.0, 100);
// }
// /**
// * Computes that value x such that P(abs(N(0,1) > x) < alpha.  Note that
// * this is a two sided test of the null hypothesis that the Fisher's Z
// * value, which is distributed as N(0,1) is not equal to 0.0.
// */
// private double cutoffGaussian() {
// npdf = new NormalPdf();
// final double upperBound = 9.0;
// final double delta = 0.001;
// //        double alpha = this.alpha/2.0;    //Two sided test
// return CutoffFinder.getCutoff(npdf, upperBound, alpha, delta);
// }
// private int sampleSize() {
// return data.rows();
// }
public boolean determines(List<Node> zList, Node xVar) {
    if (zList == null) {
        throw new NullPointerException();
    }
    for (Node node : zList) {
        if (node == null) {
            throw new NullPointerException();
        }
    }
    int size = zList.size();
    int[] zCols = new int[size];
    int xIndex = getVariables().indexOf(xVar);
    for (int i = 0; i < zList.size(); i++) {
        zCols[i] = getVariables().indexOf(zList.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);
    DoubleMatrix2D Zt = new Algebra().transpose(Z);
    DoubleMatrix2D ZtZ = new Algebra().mult(Zt, Z);
    DoubleMatrix2D G = new DenseDoubleMatrix2D(new TetradMatrix(ZtZ.toArray()).inverse().toArray());
    // Bug in Colt? Need to make a copy before multiplying to avoid
    // a ClassCastException.
    DoubleMatrix2D Zt2 = Zt.like();
    Zt2.assign(Zt);
    DoubleMatrix2D GZt = new Algebra().mult(G, Zt2);
    DoubleMatrix1D b_x = new Algebra().mult(GZt, x);
    DoubleMatrix1D xPred = new Algebra().mult(Z, b_x);
    DoubleMatrix1D xRes = xPred.copy().assign(x, Functions.minus);
    double SSE = xRes.aggregate(Functions.plus, Functions.square);
    boolean determined = SSE < 0.0001;
    if (determined) {
        StringBuilder sb = new StringBuilder();
        sb.append("Determination found: ").append(xVar).append(" is determined by {");
        for (int i = 0; i < zList.size(); i++) {
            sb.append(zList.get(i));
            if (i < zList.size() - 1) {
                sb.append(", ");
            }
        }
        sb.append("}");
        TetradLogger.getInstance().log("independencies", sb.toString());
    }
    return determined;
}

Example 3 with DoubleMatrix1D

use of cern.colt.matrix.DoubleMatrix1D in project tetrad by cmu-phil.

the class IndTestFisherZGeneralizedInverse method determines.

public boolean determines(List<Node> zList, Node xVar) {
    if (zList == null) {
        throw new NullPointerException();
    }
    if (zList.isEmpty()) {
        return false;
    }
    for (Node node : zList) {
        if (node == null) {
            throw new NullPointerException();
        }
    }
    int size = zList.size();
    int[] zCols = new int[size];
    int xIndex = getVariables().indexOf(xVar);
    for (int i = 0; i < zList.size(); i++) {
        zCols[i] = getVariables().indexOf(zList.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);
    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 G = MatrixUtils.ginverse(ZtZ);
    DoubleMatrix2D Zt2 = Zt.copy();
    DoubleMatrix2D GZt = new Algebra().mult(G, Zt2);
    DoubleMatrix1D b_x = new Algebra().mult(GZt, x);
    DoubleMatrix1D xPred = new Algebra().mult(Z, b_x);
    DoubleMatrix1D xRes = xPred.copy().assign(x, Functions.minus);
    double SSE = xRes.aggregate(Functions.plus, Functions.square);
    double variance = SSE / (data.rows() - (zList.size() + 1));
    // ChiSquare chiSquare = new ChiSquare(data.rows(),
    // PersistentRandomUtil.getInstance().getEngine());
    // 
    // double p = chiSquare.cdf(sum);
    // boolean determined = p < 1 - getAlternativePenalty();
    // 
    boolean determined = variance < getAlpha();
    if (determined) {
        StringBuilder sb = new StringBuilder();
        sb.append("Determination found: ").append(xVar).append(" is determined by {");
        for (int i = 0; i < zList.size(); i++) {
            sb.append(zList.get(i));
            if (i < zList.size() - 1) {
                sb.append(", ");
            }
        }
        sb.append("}");
        // sb.append(" p = ").append(nf.format(p));
        sb.append(" SSE = ").append(nf.format(SSE));
        TetradLogger.getInstance().log("independencies", sb.toString());
        System.out.println(sb);
    }
    return determined;
}

Example 4 with DoubleMatrix1D

use of cern.colt.matrix.DoubleMatrix1D in project tetrad by cmu-phil.

the class Ricf method ricf.

// =============================PUBLIC METHODS=========================//
public RicfResult ricf(SemGraph mag, ICovarianceMatrix covMatrix, double tolerance) {
    mag.setShowErrorTerms(false);
    DoubleFactory2D factory = DoubleFactory2D.dense;
    Algebra algebra = new Algebra();
    DoubleMatrix2D S = new DenseDoubleMatrix2D(covMatrix.getMatrix().toArray());
    int p = covMatrix.getDimension();
    if (p == 1) {
        return new RicfResult(S, S, null, null, 1, Double.NaN, covMatrix);
    }
    List<Node> nodes = new ArrayList<>();
    for (String name : covMatrix.getVariableNames()) {
        nodes.add(mag.getNode(name));
    }
    DoubleMatrix2D omega = factory.diagonal(factory.diagonal(S));
    DoubleMatrix2D B = factory.identity(p);
    int[] ug = ugNodes(mag, nodes);
    int[] ugComp = complement(p, ug);
    if (ug.length > 0) {
        List<Node> _ugNodes = new LinkedList<>();
        for (int i : ug) {
            _ugNodes.add(nodes.get(i));
        }
        Graph ugGraph = mag.subgraph(_ugNodes);
        ICovarianceMatrix ugCov = covMatrix.getSubmatrix(ug);
        DoubleMatrix2D lambdaInv = fitConGraph(ugGraph, ugCov, p + 1, tolerance).shat;
        omega.viewSelection(ug, ug).assign(lambdaInv);
    }
    // Prepare lists of parents and spouses.
    int[][] pars = parentIndices(p, mag, nodes);
    int[][] spo = spouseIndices(p, mag, nodes);
    int i = 0;
    double _diff;
    while (true) {
        i++;
        DoubleMatrix2D omegaOld = omega.copy();
        DoubleMatrix2D bOld = B.copy();
        for (int _v = 0; _v < p; _v++) {
            // Exclude the UG part.
            if (Arrays.binarySearch(ug, _v) >= 0) {
                continue;
            }
            int[] v = new int[] { _v };
            int[] vcomp = complement(p, v);
            int[] all = range(0, p - 1);
            int[] parv = pars[_v];
            int[] spov = spo[_v];
            DoubleMatrix2D a6 = B.viewSelection(v, parv);
            if (spov.length == 0) {
                if (parv.length != 0) {
                    if (i == 1) {
                        DoubleMatrix2D a1 = S.viewSelection(parv, parv);
                        DoubleMatrix2D a2 = S.viewSelection(v, parv);
                        DoubleMatrix2D a3 = algebra.inverse(a1);
                        DoubleMatrix2D a4 = algebra.mult(a2, a3);
                        a4.assign(Mult.mult(-1));
                        a6.assign(a4);
                        DoubleMatrix2D a7 = S.viewSelection(parv, v);
                        DoubleMatrix2D a9 = algebra.mult(a6, a7);
                        DoubleMatrix2D a8 = S.viewSelection(v, v);
                        DoubleMatrix2D a8b = omega.viewSelection(v, v);
                        a8b.assign(a8);
                        omega.viewSelection(v, v).assign(a9, PlusMult.plusMult(1));
                    }
                }
            } else {
                if (parv.length != 0) {
                    DoubleMatrix2D oInv = new DenseDoubleMatrix2D(p, p);
                    DoubleMatrix2D a2 = omega.viewSelection(vcomp, vcomp);
                    DoubleMatrix2D a3 = algebra.inverse(a2);
                    oInv.viewSelection(vcomp, vcomp).assign(a3);
                    DoubleMatrix2D Z = algebra.mult(oInv.viewSelection(spov, vcomp), B.viewSelection(vcomp, all));
                    int lpa = parv.length;
                    int lspo = spov.length;
                    // Build XX
                    DoubleMatrix2D XX = new DenseDoubleMatrix2D(lpa + lspo, lpa + lspo);
                    int[] range1 = range(0, lpa - 1);
                    int[] range2 = range(lpa, lpa + lspo - 1);
                    // Upper left quadrant
                    XX.viewSelection(range1, range1).assign(S.viewSelection(parv, parv));
                    // Upper right quadrant
                    DoubleMatrix2D a11 = algebra.mult(S.viewSelection(parv, all), algebra.transpose(Z));
                    XX.viewSelection(range1, range2).assign(a11);
                    // Lower left quadrant
                    DoubleMatrix2D a12 = XX.viewSelection(range2, range1);
                    DoubleMatrix2D a13 = algebra.transpose(XX.viewSelection(range1, range2));
                    a12.assign(a13);
                    // Lower right quadrant
                    DoubleMatrix2D a14 = XX.viewSelection(range2, range2);
                    DoubleMatrix2D a15 = algebra.mult(Z, S);
                    DoubleMatrix2D a16 = algebra.mult(a15, algebra.transpose(Z));
                    a14.assign(a16);
                    // Build XY
                    DoubleMatrix1D YX = new DenseDoubleMatrix1D(lpa + lspo);
                    DoubleMatrix1D a17 = YX.viewSelection(range1);
                    DoubleMatrix1D a18 = S.viewSelection(v, parv).viewRow(0);
                    a17.assign(a18);
                    DoubleMatrix1D a19 = YX.viewSelection(range2);
                    DoubleMatrix2D a20 = S.viewSelection(v, all);
                    DoubleMatrix1D a21 = algebra.mult(a20, algebra.transpose(Z)).viewRow(0);
                    a19.assign(a21);
                    // Temp
                    DoubleMatrix2D a22 = algebra.inverse(XX);
                    DoubleMatrix1D temp = algebra.mult(algebra.transpose(a22), YX);
                    // Assign to b.
                    DoubleMatrix1D a23 = a6.viewRow(0);
                    DoubleMatrix1D a24 = temp.viewSelection(range1);
                    a23.assign(a24);
                    a23.assign(Mult.mult(-1));
                    // Assign to omega.
                    omega.viewSelection(v, spov).viewRow(0).assign(temp.viewSelection(range2));
                    omega.viewSelection(spov, v).viewColumn(0).assign(temp.viewSelection(range2));
                    // Variance.
                    double tempVar = S.get(_v, _v) - algebra.mult(temp, YX);
                    DoubleMatrix2D a27 = omega.viewSelection(v, spov);
                    DoubleMatrix2D a28 = oInv.viewSelection(spov, spov);
                    DoubleMatrix2D a29 = omega.viewSelection(spov, v).copy();
                    DoubleMatrix2D a30 = algebra.mult(a27, a28);
                    DoubleMatrix2D a31 = algebra.mult(a30, a29);
                    omega.viewSelection(v, v).assign(tempVar);
                    omega.viewSelection(v, v).assign(a31, PlusMult.plusMult(1));
                } else {
                    DoubleMatrix2D oInv = new DenseDoubleMatrix2D(p, p);
                    DoubleMatrix2D a2 = omega.viewSelection(vcomp, vcomp);
                    DoubleMatrix2D a3 = algebra.inverse(a2);
                    oInv.viewSelection(vcomp, vcomp).assign(a3);
                    // System.out.println("O.inv = " + oInv);
                    DoubleMatrix2D a4 = oInv.viewSelection(spov, vcomp);
                    DoubleMatrix2D a5 = B.viewSelection(vcomp, all);
                    DoubleMatrix2D Z = algebra.mult(a4, a5);
                    // System.out.println("Z = " + Z);
                    // Build XX
                    DoubleMatrix2D XX = algebra.mult(algebra.mult(Z, S), Z.viewDice());
                    // System.out.println("XX = " + XX);
                    // Build XY
                    DoubleMatrix2D a20 = S.viewSelection(v, all);
                    DoubleMatrix1D YX = algebra.mult(a20, Z.viewDice()).viewRow(0);
                    // System.out.println("YX = " + YX);
                    // Temp
                    DoubleMatrix2D a22 = algebra.inverse(XX);
                    DoubleMatrix1D a23 = algebra.mult(algebra.transpose(a22), YX);
                    // Assign to omega.
                    DoubleMatrix1D a24 = omega.viewSelection(v, spov).viewRow(0);
                    a24.assign(a23);
                    DoubleMatrix1D a25 = omega.viewSelection(spov, v).viewColumn(0);
                    a25.assign(a23);
                    // System.out.println("Omega 2 " + omega);
                    // Variance.
                    double tempVar = S.get(_v, _v) - algebra.mult(a24, YX);
                    // System.out.println("tempVar = " + tempVar);
                    DoubleMatrix2D a27 = omega.viewSelection(v, spov);
                    DoubleMatrix2D a28 = oInv.viewSelection(spov, spov);
                    DoubleMatrix2D a29 = omega.viewSelection(spov, v).copy();
                    DoubleMatrix2D a30 = algebra.mult(a27, a28);
                    DoubleMatrix2D a31 = algebra.mult(a30, a29);
                    omega.set(_v, _v, tempVar + a31.get(0, 0));
                // System.out.println("Omega final " + omega);
                }
            }
        }
        DoubleMatrix2D a32 = omega.copy();
        a32.assign(omegaOld, PlusMult.plusMult(-1));
        double diff1 = algebra.norm1(a32);
        DoubleMatrix2D a33 = B.copy();
        a33.assign(bOld, PlusMult.plusMult(-1));
        double diff2 = algebra.norm1(a32);
        double diff = diff1 + diff2;
        _diff = diff;
        if (diff < tolerance)
            break;
    }
    DoubleMatrix2D a34 = algebra.inverse(B);
    DoubleMatrix2D a35 = algebra.inverse(B.viewDice());
    DoubleMatrix2D sigmahat = algebra.mult(algebra.mult(a34, omega), a35);
    DoubleMatrix2D lambdahat = omega.copy();
    DoubleMatrix2D a36 = lambdahat.viewSelection(ugComp, ugComp);
    a36.assign(factory.make(ugComp.length, ugComp.length, 0.0));
    DoubleMatrix2D omegahat = omega.copy();
    DoubleMatrix2D a37 = omegahat.viewSelection(ug, ug);
    a37.assign(factory.make(ug.length, ug.length, 0.0));
    DoubleMatrix2D bhat = B.copy();
    return new RicfResult(sigmahat, lambdahat, bhat, omegahat, i, _diff, covMatrix);
}

Example 5 with DoubleMatrix1D

use of cern.colt.matrix.DoubleMatrix1D in project tetrad by cmu-phil.

the class MGM method nonSmoothValue.

/**
 * Calculates penalty term of objective function
 *
 * @param parIn
 * @return
 */
public double nonSmoothValue(DoubleMatrix1D parIn) {
    // DoubleMatrix1D tlam = lambda.copy().assign(Functions.mult(t));
    // Dimension checked in constructor
    // par is a copy so we can update it
    MGMParams par = new MGMParams(parIn, p, lsum);
    // penbeta = t(1).*(wv(1:p)'*wv(1:p));
    // betascale=zeros(size(beta));
    // betascale=max(0,1-penbeta./abs(beta));
    DoubleMatrix2D weightMat = alg.multOuter(weights, weights, null);
    // int p = xDat.columns();
    // weight beta
    // betaw = (wv(1:p)'*wv(1:p)).*abs(beta);
    // betanorms=sum(betaw(:));
    DoubleMatrix2D betaWeight = weightMat.viewPart(0, 0, p, p);
    DoubleMatrix2D absBeta = par.beta.copy().assign(Functions.abs);
    double betaNorms = absBeta.assign(betaWeight, Functions.mult).zSum();
    /*
        thetanorms=0;
        for s=1:p
            for j=1:q
                tempvec=theta(Lsums(j)+1:Lsums(j+1),s);
                thetanorms=thetanorms+(wv(s)*wv(p+j))*norm(tempvec);
            end
        end
        */
    double thetaNorms = 0;
    for (int i = 0; i < p; i++) {
        if (Thread.currentThread().isInterrupted()) {
            break;
        }
        for (int j = 0; j < lcumsum.length - 1; j++) {
            if (Thread.currentThread().isInterrupted()) {
                break;
            }
            DoubleMatrix1D tempVec = par.theta.viewColumn(i).viewPart(lcumsum[j], l[j]);
            thetaNorms += weightMat.get(i, p + j) * Math.sqrt(alg.norm2(tempVec));
        }
    }
    /*
        for r=1:q
            for j=1:q
                if r<j
                    tempmat=phi(Lsums(r)+1:Lsums(r+1),Lsums(j)+1:Lsums(j+1));
                    tempmat=max(0,1-t(3)*(wv(p+r)*wv(p+j))/norm(tempmat))*tempmat; % Lj by 2*Lr
                    phinorms=phinorms+(wv(p+r)*wv(p+j))*norm(tempmat,'fro');
                    phi( Lsums(r)+1:Lsums(r+1),Lsums(j)+1:Lsums(j+1) )=tempmat;
                end
            end
        end
         */
    double phiNorms = 0;
    for (int i = 0; i < lcumsum.length - 1; i++) {
        if (Thread.currentThread().isInterrupted()) {
            break;
        }
        for (int j = i + 1; j < lcumsum.length - 1; j++) {
            if (Thread.currentThread().isInterrupted()) {
                break;
            }
            DoubleMatrix2D tempMat = par.phi.viewPart(lcumsum[i], lcumsum[j], l[i], l[j]);
            phiNorms += weightMat.get(p + i, p + j) * alg.normF(tempMat);
        }
    }
    return lambda.get(0) * betaNorms + lambda.get(1) * thetaNorms + lambda.get(2) * phiNorms;
}