Examples with DenseDoubleMatrix1D cern.colt.matrix.impl.DenseDoubleMatrix1D used on opensource projects

Example 11 with DenseDoubleMatrix1D

use of cern.colt.matrix.impl.DenseDoubleMatrix1D in project tetrad by cmu-phil.

the class Ricf method ricf2.

/**
 * same as above but takes a Graph instead of a SemGraph *
 */
public RicfResult ricf2(Graph 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 12 with DenseDoubleMatrix1D

use of cern.colt.matrix.impl.DenseDoubleMatrix1D in project tetrad by cmu-phil.

the class Glasso method search.

public Result search() {
    int niter = 0;
    double eps = 1.0e-7;
    int n = getN();
    DoubleMatrix2D ss = getSs();
    boolean approximateAlgorithm = isIa();
    boolean warmStart = isIs();
    boolean itr = isItr();
    boolean pen = isIpen();
    double thr = getThr();
    // System.out.println(ss);
    Rho rho = getRho();
    DoubleMatrix2D ww = new DenseDoubleMatrix2D(n, n);
    DoubleMatrix2D wwi = new DenseDoubleMatrix2D(n, n);
    double dlx;
    double del;
    int nm1 = n - 1;
    DoubleMatrix2D vv = new DenseDoubleMatrix2D(nm1, nm1);
    DoubleMatrix2D xs = null;
    if (!approximateAlgorithm) {
        xs = new DenseDoubleMatrix2D(nm1, n);
    }
    DoubleMatrix1D s = new DenseDoubleMatrix1D(nm1);
    DoubleMatrix1D so = new DenseDoubleMatrix1D(nm1);
    DoubleMatrix1D x = new DenseDoubleMatrix1D(n - 1);
    DoubleMatrix1D ws;
    DoubleMatrix1D z = new DenseDoubleMatrix1D(nm1);
    int[] mm = new int[nm1];
    DoubleMatrix1D ro = new DenseDoubleMatrix1D(nm1);
    // shr warmStart sum(abs(offdiagonal(ss))).
    double shr = 0.0;
    for (int j = 0; j < n; j++) {
        for (int k = 0; k < n; k++) {
            if (j == k)
                continue;
            shr += Math.abs(ss.get(j, k));
        }
    }
    // (penalized if necessary).
    if (shr == 0.0) {
        for (int j = 0; j < n; j++) {
            if (Thread.currentThread().isInterrupted()) {
                break;
            }
            if (!pen) {
                ww.set(j, j, ss.get(j, j));
            } else {
                ww.set(j, j, ss.get(j, j) + rho.get(j, j));
            }
            wwi.set(j, j, 1.0 / Math.max(ww.get(j, j), eps));
        }
        return new Result(ww, wwi, niter, Double.NaN);
    }
    shr = getThr() * shr / nm1;
    if (approximateAlgorithm) {
        if (!warmStart) {
            zero(wwi);
        }
        for (int m = 0; m < n; m++) {
            System.out.println("m = " + m);
            // This sets up vv, s, and r--i.e., W.11, s.12, and r.12.
            setup(m, n, ss, rho, ss, vv, s, ro);
            // This sets up x.12--i.e. theta.12.
            int l = -1;
            for (int j = 0; j < n; j++) {
                if (Thread.currentThread().isInterrupted()) {
                    break;
                }
                if (j == m)
                    continue;
                l = l + 1;
                x.set(l, wwi.get(j, m));
            }
            lasso(ro, nm1, vv, s, shr / n, x, z, mm);
            l = -1;
            for (int j = 0; j < n; j++) {
                if (Thread.currentThread().isInterrupted()) {
                    break;
                }
                if (j == m)
                    continue;
                l = l + 1;
                wwi.set(j, m, x.get(l));
            }
        }
        niter = 1;
        return new Result(ww, wwi, niter, Double.NaN);
    }
    if (!warmStart) {
        ww.assign(ss);
        if (xs != null) {
            zero(xs);
        }
    } else {
        for (int j = 0; j < n; j++) {
            double xjj = -wwi.get(j, j);
            // System.out.println("xjj = " + xjj);
            int l = -1;
            for (int k = 0; k < n; k++) {
                if (Thread.currentThread().isInterrupted()) {
                    break;
                }
                if (k == j)
                    continue;
                l = l + 1;
                xs.set(l, j, wwi.get(k, j) / xjj);
            }
        }
    }
    for (int j = 0; j < n; j++) {
        if (pen) {
            ww.set(j, j, ss.get(j, j) + rho.get(j, j));
        } else {
            ww.set(j, j, ss.get(j, j));
        // System.out.println(ww);
        }
    }
    niter = 0;
    while (true) {
        dlx = 0.0;
        for (int m = 0; m < n; m++) {
            if (itr) {
                System.out.println("Outer loop = " + m);
            }
            x = xs.viewColumn(m);
            // System.out.println(x);
            // System.out.println();
            ws = ww.viewColumn(m);
            // This sets up vv, s, and ro--i.e., W.11, s.12, and r.12.
            setup(m, n, ss, rho, ww, vv, s, ro);
            so.assign(s);
            // System.out.println("ww = " + ww);
            // This updates s and x--the estimated correlation matrix and the reduced form of the
            // estimated inverse covariance.
            lasso(ro, nm1, vv, s, shr / sum_abs(vv), x, z, mm);
            // lasso(ro,nm1,vv,s,thr/sum_abs(vv),x,z,mm);
            int l = -1;
            for (int j = 0; j < n; j++) {
                if (Thread.currentThread().isInterrupted()) {
                    break;
                }
                if (j == m)
                    continue;
                l = l + 1;
                ww.set(j, m, so.get(l) - s.get(l));
                ww.set(m, j, ww.get(j, m));
            }
            dlx = Math.max(dlx, sum_abs_diff(ww.viewColumn(m), ws));
            // xs(:,m)=x
            xs.viewColumn(m).assign(x);
        }
        niter = niter + 1;
        if (niter < getMaxit())
            break;
        if (dlx < shr)
            break;
    }
    del = dlx / nm1;
    inv(n, ww, xs, wwi);
    return new Result(ww, wwi, niter, del);
}