Examples with ICovarianceMatrix edu.cmu.tetrad.data.ICovarianceMatrix used on opensource projects

Example 6 with ICovarianceMatrix

use of edu.cmu.tetrad.data.ICovarianceMatrix in project tetrad by cmu-phil.

the class IndTestFisherZD method indTestSubset.

// ==========================PUBLIC METHODS=============================//
/**
 * Creates a new independence test instance for a subset of the variables.
 */
public IndependenceTest indTestSubset(List<Node> vars) {
    if (vars.isEmpty()) {
        throw new IllegalArgumentException("Subset may not be empty.");
    }
    for (Node var : vars) {
        if (!variables.contains(var)) {
            throw new IllegalArgumentException("All vars must be original vars");
        }
    }
    int[] indices = new int[vars.size()];
    for (int i = 0; i < indices.length; i++) {
        indices[i] = indexMap.get(vars.get(i));
    }
    ICovarianceMatrix newCovMatrix = covMatrix.getSubmatrix(indices);
    double alphaNew = getAlpha();
    return new IndTestFisherZD(newCovMatrix, alphaNew);
}

Example 7 with ICovarianceMatrix

use of edu.cmu.tetrad.data.ICovarianceMatrix 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 8 with ICovarianceMatrix

use of edu.cmu.tetrad.data.ICovarianceMatrix in project tetrad by cmu-phil.

the class CovCellEditor method getCellEditor.

public TableCellEditor getCellEditor(int row, int col) {
    CovMatrixTable covMatrixTable = (CovMatrixTable) getModel();
    covCellEditor.setRed(false);
    if (row >= 4 && col >= 1) {
        java.util.List<String> varNames = covMatrixTable.getCovMatrix().getVariableNames();
        java.util.List<String> selectedVarNames = covMatrixTable.getCovMatrix().getSelectedVariableNames();
        ICovarianceMatrix subMatrix = covMatrixTable.getCovMatrix().getSubmatrix(selectedVarNames);
        if (selectedVarNames.contains(varNames.get(row - 4)) && selectedVarNames.contains(varNames.get(col - 1))) {
            if (!MatrixUtils.isPositiveDefinite(subMatrix.getMatrix())) {
                // covCellEditor.setRed(!covMatrixTable.isEditingMatrixPositiveDefinite());
                covCellEditor.setRed(true);
            }
        }
    }
    return covCellEditor;
}

Example 9 with ICovarianceMatrix

use of edu.cmu.tetrad.data.ICovarianceMatrix in project tetrad by cmu-phil.

the class CovCellEditor method getCellRenderer.

public TableCellRenderer getCellRenderer(int row, int col) {
    CovMatrixTable covMatrixTable = (CovMatrixTable) getModel();
    if (covMatrixTable.getColumnCount() <= 200) {
        java.util.List<String> varNames = covMatrixTable.getCovMatrix().getVariableNames();
        java.util.List<String> selectedVarNames = covMatrixTable.getCovMatrix().getSelectedVariableNames();
        ICovarianceMatrix subMatrix = covMatrixTable.getCovMatrix().getSubmatrix(selectedVarNames);
        covCellEditor.setRed(false);
        covCellRenderer.setPositiveDefinite(true);
        if (row >= 4 && row - 4 < varNames.size() && col >= 1 && col - 1 < varNames.size()) {
            if (selectedVarNames.contains(varNames.get(row - 4)) && selectedVarNames.contains(varNames.get(col - 1))) {
                if (!MatrixUtils.isPositiveDefinite(subMatrix.getMatrix())) {
                    // covCellEditor.setRed(!covMatrixTable.isEditingMatrixPositiveDefinite());
                    covCellEditor.setRed(true);
                    covCellRenderer.setPositiveDefinite(false);
                }
            }
        }
    }
    // covMatrixTable.isEditingMatrixPositiveDefinite());
    return covCellRenderer;
}

Example 10 with ICovarianceMatrix

use of edu.cmu.tetrad.data.ICovarianceMatrix in project tetrad by cmu-phil.

the class CovCellEditor method updateSelection.

private void updateSelection() {
    ListSelectionModel rowSelectionModel = getSelectionModel();
    ListSelectionModel colSelectionModel = getColumnModel().getSelectionModel();
    CovMatrixTable covMatrixTable = (CovMatrixTable) getModel();
    ICovarianceMatrix covMatrix = covMatrixTable.getCovMatrix();
    covMatrix.clearSelection();
    for (int i = 0; i < covMatrix.getDimension(); i++) {
        Node variable = covMatrix.getVariables().get(i);
        if (colSelectionModel.isSelectedIndex(i + 1)) {
            covMatrix.select(variable);
        }
        if (rowSelectionModel.isSelectedIndex(i + 4)) {
            covMatrix.select(variable);
        }
    }
    for (int i = -1; i < covMatrix.getDimension(); i++) {
        for (int j = -1; j < covMatrix.getDimension(); j++) {
            covMatrixTable.fireTableCellUpdated(i + 4, j + 1);
        }
    }
    firePropertyChange("modelChanged", null, null);
}