Examples with PrimitiveDenseStore org.ojalgo.matrix.store.PrimitiveDenseStore used on opensource projects

Example 46 with PrimitiveDenseStore

use of org.ojalgo.matrix.store.PrimitiveDenseStore in project ojAlgo by optimatika.

the class GaussianField method getDistribution.

public Normal1D getDistribution(final boolean cleanCovariances, final K... evaluationPoint) {
    final MatrixStore<Double> tmpRegCoef = this.getRegressionCoefficients(evaluationPoint);
    final MatrixStore<Double> tmpM1 = this.getM1(evaluationPoint);
    final MatrixStore<Double> tmpM2differenses = this.getM2differenses();
    final PrimitiveDenseStore tmpLocations = FACTORY.makeZero(tmpM1.countRows(), tmpM1.countColumns());
    tmpLocations.fillMatching(tmpM1, ADD, tmpRegCoef.multiply(tmpM2differenses));
    final MatrixStore<Double> tmpC11 = this.getC11(evaluationPoint);
    final MatrixStore<Double> tmpC21 = this.getC21(evaluationPoint);
    final PrimitiveDenseStore tmpCovariances = FACTORY.makeZero(tmpC11.countRows(), tmpC11.countColumns());
    tmpCovariances.fillMatching(tmpC11, SUBTRACT, tmpRegCoef.multiply(tmpC21));
    if (cleanCovariances) {
        final Eigenvalue<Double> tmpEvD = Eigenvalue.PRIMITIVE.make(true);
        tmpEvD.decompose(tmpCovariances);
        final MatrixStore<Double> tmpV = tmpEvD.getV();
        final PhysicalStore<Double> tmpD = tmpEvD.getD().copy();
        final double tmpLargest = tmpD.doubleValue(0, 0);
        final double tmpLimit = PrimitiveFunction.MAX.invoke(PrimitiveMath.MACHINE_EPSILON * tmpLargest, 1E-12);
        final int tmpLength = (int) Math.min(tmpD.countRows(), tmpD.countColumns());
        for (int ij = 0; ij < tmpLength; ij++) {
            if (tmpD.doubleValue(ij, ij) < tmpLimit) {
                tmpD.set(ij, ij, tmpLimit);
            }
        }
        tmpCovariances.fillMatching(tmpV.multiply(tmpD).multiply(tmpV.logical().transpose().get()));
    }
    return new Normal1D(tmpLocations, tmpCovariances);
}

Example 47 with PrimitiveDenseStore

use of org.ojalgo.matrix.store.PrimitiveDenseStore in project ojAlgo by optimatika.

the class GaussianField method getC21.

MatrixStore<Double> getC21(final K[] args) {
    final List<ComparableToDouble<K>> tmpObservations = this.getObservations();
    final int tmpRowDim = tmpObservations.size();
    final int tmpColDim = args.length;
    final PrimitiveDenseStore retVal = FACTORY.makeZero(tmpRowDim, tmpColDim);
    for (int j = 0; j < tmpColDim; j++) {
        for (int i = 0; i < tmpRowDim; i++) {
            retVal.set(i, j, myCovarianceFunction.invoke(tmpObservations.get(i).key, args[j]));
        }
    }
    return retVal;
}

Example 48 with PrimitiveDenseStore

use of org.ojalgo.matrix.store.PrimitiveDenseStore in project ojAlgo by optimatika.

the class GaussianField method getM2.

MatrixStore<Double> getM2() {
    final List<ComparableToDouble<K>> tmpObservations = this.getObservations();
    final int tmpSize = tmpObservations.size();
    final PrimitiveDenseStore retVal = FACTORY.makeZero(tmpSize, 1);
    for (int i = 0; i < tmpSize; i++) {
        retVal.set(i, 0, myMeanFunction.invoke(tmpObservations.get(i).key));
    }
    return retVal;
}

Example 49 with PrimitiveDenseStore

use of org.ojalgo.matrix.store.PrimitiveDenseStore in project ojAlgo by optimatika.

the class AbstractSolver method leastSquares.

static void leastSquares(final Access2D<?> body, final Access1D<?> rhs, final PhysicalStore<?> solution) {
    final PrimitiveDenseStore tmpTranspBody = PrimitiveDenseStore.FACTORY.transpose(body);
    final int tmpCountRows = (int) tmpTranspBody.countRows();
    final PrimitiveDenseStore tmpBody = PrimitiveDenseStore.FACTORY.makeZero(tmpCountRows, tmpCountRows);
    tmpTranspBody.multiply(tmpTranspBody.transpose(), tmpBody);
    final PrimitiveDenseStore tmpRHS = PrimitiveDenseStore.FACTORY.makeZero(tmpCountRows, solution.countColumns());
    tmpTranspBody.multiply((Access1D<Double>) rhs, tmpRHS);
    switch(tmpCountRows) {
        case 1:
            AbstractSolver.full1X1(tmpBody, tmpRHS, solution);
            break;
        case 2:
            AbstractSolver.symmetric2X2(tmpBody, tmpRHS, solution);
            break;
        case 3:
            AbstractSolver.symmetric3X3(tmpBody, tmpRHS, solution);
            break;
        case 4:
            AbstractSolver.symmetric4X4(tmpBody, tmpRHS, solution);
            break;
        case 5:
            AbstractSolver.symmetric5X5(tmpBody, tmpRHS, solution);
            break;
        default:
            throw new IllegalArgumentException();
    }
}

Example 50 with PrimitiveDenseStore

use of org.ojalgo.matrix.store.PrimitiveDenseStore in project ojAlgo by optimatika.

the class ConvexProblems method testP20081014.

/**
 * <p>
 * I'm trying to solve some quadratic programming systems using version 24. The ActiveSetSolver does not
 * always converge to a solution, but throws an exception, "Matrix is singular" (The exception is thrown
 * by org.ojalgo.matrix.jama.LUDecomposition). The thing is that if I run Matlabs quadprog method on the
 * exact same system, a solution is found without problems. Here is the code that produces the exception:
 * </p>
 * <p>
 * 2015-02-21: Extended the test case with a few alternatives using ExpressionsBasedModel. Numerically
 * difficult problem as the formulation includes both large and very small parameters (like 1000000000 and
 * -7.646043242556307E-15).
 * </p>
 */
@Test
public void testP20081014() {
    final PhysicalStore.Factory<Double, PrimitiveDenseStore> tmpFactory = PrimitiveDenseStore.FACTORY;
    final PrimitiveDenseStore[] tmpSystem = new PrimitiveDenseStore[6];
    // {[AE], [BE], [Q], [C], [AI], [BI]}
    tmpSystem[0] = tmpFactory.rows(new double[][] { { -0.0729971273939726, -0.31619624199405116, -0.14365990081105298, -3.4914813388431334E-15, 0.9963066090106673, 0.9989967493404447, 1.0, 0.0, 0.0 }, { -2.5486810808521023E-16, 3.6687950405257466, 3.2047109656515507, 1.0, 0.08586699506600544, 0.04478275122437895, 0.0, 1.0, 0.0 }, // AE
    { -7.646043242556307E-15, -107.21808503782593, -97.434268076846, 30.0, -11.54276933307617, 7.647488207332634, 0.0, 0, 1.0 } });
    // BE
    tmpSystem[1] = tmpFactory.rows(new double[][] { { 10.461669614447484 }, { -0.5328532701990767 }, { 15.782527136201711 } });
    final PrimitiveDenseStore tmpQ = tmpFactory.makeEye(9, 9);
    tmpQ.set(3, 3, 10);
    tmpQ.set(4, 4, 10);
    tmpQ.set(5, 5, 10);
    tmpQ.set(6, 6, 1000000000);
    tmpQ.set(7, 7, 1000000000);
    tmpQ.set(8, 8, 1000000000);
    // Q
    tmpSystem[2] = tmpQ;
    // C
    tmpSystem[3] = tmpFactory.rows(new double[][] { { 0 }, { 0 }, { 0 }, { -1 }, { -1 }, { -1 }, { 0 }, { 0 }, { 0 } });
    final double[][] tmpAI = new double[18][9];
    for (int i = 0; i < 9; i++) {
        tmpAI[i][i] = 1;
        tmpAI[i + 9][i] = -1;
    }
    // AI
    tmpSystem[4] = tmpFactory.rows(tmpAI);
    tmpSystem[5] = tmpFactory.rows(new double[][] { { 0 }, { 0.0175 }, { 0.0175 }, { 5 }, { 5 }, { 5 }, { 100000 }, { 100000 }, { 100000 }, { 0 }, { 0.0175 }, { 0.0175 }, { 5 }, { 5 }, { 5 }, { 100000 }, { 100000 }, // BI
    { 100000 } });
    final PrimitiveDenseStore tmpMatlabSolution = tmpFactory.columns(new double[] { 0.00000000000000, -0.01750000000000, -0.01750000000000, 0.88830035195990, 4.56989525276369, 5.00000000000000, 0.90562154243124, -1.91718419629399, 0.06390614020590 });
    // Compare to MatLab using 3 digits and 6 decimal places
    final NumberContext tmpAccuracy = NumberContext.getGeneral(3, 6);
    ConvexProblems.builAndTestModel(tmpSystem, tmpMatlabSolution, tmpAccuracy, false);
}