Examples with Normal org.ojalgo.random.Normal used on opensource projects

Example 1 with Normal

use of org.ojalgo.random.Normal in project ojAlgo by optimatika.

the class GaussianProcess method getDistribution.

public Normal getDistribution(final double evaluationPoint) {
    final Normal1D tmpVal = this.getDistribution(new Double[] { evaluationPoint });
    final double tmpLocation = tmpVal.getExpected().doubleValue(0);
    final double tmpScale = tmpVal.getStandardDeviation().doubleValue(0);
    return new Normal(tmpLocation, tmpScale);
}

Example 2 with Normal

use of org.ojalgo.random.Normal in project ojAlgo by optimatika.

the class GaussianProcess method step.

@Override
protected double step(final double currentValue, final double stepSize, final double normalisedRandomIncrement) {
    final Normal tmpDistr = this.getDistribution(stepSize);
    final double retVal = (normalisedRandomIncrement * tmpDistr.getStandardDeviation()) + tmpDistr.getExpected();
    this.addObservation(this.getObservations().last().key + stepSize, retVal);
    return retVal;
}

Example 3 with Normal

use of org.ojalgo.random.Normal in project ojAlgo by optimatika.

the class DecompositionProblems method testP20160419.

/**
 * A user reported problems related to calculating the pseudoinverse for large (2000x2000) matrices.
 */
@Test
@Tag("slow")
public void testP20160419() {
    final PrimitiveDenseStore tmpOrg = PrimitiveDenseStore.FACTORY.makeFilled(2000, 2000, new Normal());
    final SingularValue<Double> tmpRaw = new RawSingularValue();
    try {
        final MatrixStore<Double> tmpInv = tmpRaw.invert(tmpOrg);
        TestUtils.assertEquals(tmpOrg, tmpOrg.multiply(tmpInv).multiply(tmpOrg), NumberContext.getGeneral(6, 6));
    } catch (final RecoverableCondition exception) {
        exception.printStackTrace();
    }
}

Example 4 with Normal

use of org.ojalgo.random.Normal in project ojAlgo by optimatika.

the class GeometricBrownianMotionTest method testLogNormal.

@Test
@Tag("unstable")
public void testLogNormal() {
    final int tmpPeriods = 10000;
    final double tmpFactoryExpected = 1.05;
    final double tmpFactoryStdDev = PrimitiveFunction.ABS.invoke(new Normal(0.0, (tmpFactoryExpected - ONE)).doubleValue());
    final Normal tmpFactoryDistr = new Normal(tmpFactoryExpected, tmpFactoryStdDev);
    TestUtils.assertEquals("Factory Expected", tmpFactoryExpected, tmpFactoryDistr.getExpected(), 1E-14 / PrimitiveMath.THREE);
    TestUtils.assertEquals("Factory Std Dev", tmpFactoryStdDev, tmpFactoryDistr.getStandardDeviation(), 1E-14 / PrimitiveMath.THREE);
    final Primitive64Array tmpRawValues = Primitive64Array.make(tmpPeriods + 1);
    tmpRawValues.data[0] = ONE;
    for (int t = 1; t < tmpRawValues.count(); t++) {
        tmpRawValues.data[t] = tmpRawValues.data[t - 1] * tmpFactoryDistr.doubleValue();
    }
    final Primitive64Array tmpQuotient = Primitive64Array.make(tmpPeriods);
    final Primitive64Array tmpLogDiffs = Primitive64Array.make(tmpPeriods);
    for (int t = 0; t < tmpPeriods; t++) {
        tmpQuotient.data[t] = tmpRawValues.data[t + 1] / tmpRawValues.data[t];
        tmpLogDiffs.data[t] = PrimitiveFunction.LOG.invoke(tmpRawValues.data[t + 1]) - PrimitiveFunction.LOG.invoke(tmpRawValues.data[t]);
    }
    final SampleSet tmpQuotientSet = SampleSet.wrap(tmpQuotient);
    final SampleSet tmpLogDiffsSet = SampleSet.wrap(tmpLogDiffs);
    final GeometricBrownianMotion tmpProcess = GeometricBrownianMotion.estimate(tmpRawValues, ONE);
    final Normal tmpQuotienDistr = new Normal(tmpQuotientSet.getMean(), tmpQuotientSet.getStandardDeviation());
    final LogNormal tmpLogDiffDistr = new LogNormal(tmpLogDiffsSet.getMean(), tmpLogDiffsSet.getStandardDeviation());
    final LogNormal tmpProcessDistr = tmpProcess.getDistribution(ONE);
    TestUtils.assertEquals("Expected", tmpLogDiffDistr.getExpected(), tmpProcessDistr.getExpected(), 1E-14 / PrimitiveMath.THREE);
    TestUtils.assertEquals("Geometric Mean", tmpLogDiffDistr.getGeometricMean(), tmpProcessDistr.getGeometricMean(), 1E-14 / PrimitiveMath.THREE);
    TestUtils.assertEquals("Geometric Standard Deviation", tmpLogDiffDistr.getGeometricStandardDeviation(), tmpProcessDistr.getGeometricStandardDeviation(), 1E-14 / PrimitiveMath.THREE);
    TestUtils.assertEquals("Standard Deviation", tmpLogDiffDistr.getStandardDeviation(), tmpProcessDistr.getStandardDeviation(), 1E-14 / PrimitiveMath.THREE);
    TestUtils.assertEquals("Variance", tmpLogDiffDistr.getVariance(), tmpProcessDistr.getVariance(), 1E-14 / PrimitiveMath.THREE);
    double tmpFactoryVal = tmpFactoryDistr.getExpected();
    double tmpQuotienVal = tmpQuotienDistr.getExpected();
    double tmpLogDiffVal = tmpLogDiffDistr.getExpected();
    double tmpProcessVal = tmpProcessDistr.getExpected();
    double tmpGeometrVal = tmpProcessDistr.getGeometricMean();
    if (RandomProcessTests.DEBUG) {
        this.logDebug("Expected", tmpFactoryVal, tmpQuotienVal, tmpLogDiffVal, tmpProcessVal, tmpGeometrVal);
    }
    final double tmpDeltaExpected = (1E-14 / THREE) * THOUSAND * THOUSAND * THOUSAND * HUNDRED;
    TestUtils.assertEquals(tmpQuotienVal, tmpLogDiffVal, tmpDeltaExpected);
    TestUtils.assertEquals(tmpQuotienVal, tmpProcessVal, tmpDeltaExpected);
    TestUtils.assertEquals(true, tmpGeometrVal <= tmpProcessVal);
    tmpFactoryVal = tmpFactoryDistr.getStandardDeviation();
    tmpQuotienVal = tmpQuotienDistr.getStandardDeviation();
    tmpLogDiffVal = tmpLogDiffDistr.getStandardDeviation();
    tmpProcessVal = tmpProcessDistr.getStandardDeviation();
    tmpGeometrVal = tmpProcessDistr.getGeometricStandardDeviation();
    if (RandomProcessTests.DEBUG) {
        this.logDebug("Std Dev", tmpFactoryVal, tmpQuotienVal, tmpLogDiffVal, tmpProcessVal, tmpGeometrVal);
    }
    final double tmpDeltaStdDev = (1E-14 / THREE) * THOUSAND * THOUSAND * THOUSAND * THOUSAND;
    TestUtils.assertEquals(tmpQuotienVal, tmpLogDiffVal, tmpDeltaStdDev);
    TestUtils.assertEquals(tmpQuotienVal, tmpProcessVal, tmpDeltaStdDev);
    tmpFactoryVal = tmpFactoryDistr.getVariance();
    tmpQuotienVal = tmpQuotienDistr.getVariance();
    tmpLogDiffVal = tmpLogDiffDistr.getVariance();
    tmpProcessVal = tmpProcessDistr.getVariance();
    tmpGeometrVal = tmpProcessDistr.getGeometricStandardDeviation() * tmpLogDiffDistr.getGeometricStandardDeviation();
    if (RandomProcessTests.DEBUG) {
        this.logDebug("Var", tmpFactoryVal, tmpQuotienVal, tmpLogDiffVal, tmpProcessVal, tmpGeometrVal);
    }
    final double tmpDeltaVar = (1E-14 / THREE) * THOUSAND * THOUSAND * THOUSAND * HUNDRED;
    TestUtils.assertEquals(tmpQuotienVal, tmpLogDiffVal, tmpDeltaVar);
    TestUtils.assertEquals(tmpQuotienVal, tmpProcessVal, tmpDeltaVar);
    tmpFactoryVal = tmpRawValues.data[tmpPeriods];
    tmpQuotienVal = PrimitiveFunction.POW.invoke(tmpQuotienDistr.getExpected(), tmpPeriods);
    tmpLogDiffVal = PrimitiveFunction.POW.invoke(tmpLogDiffDistr.getExpected(), tmpPeriods);
    tmpProcessVal = tmpProcess.getExpected(tmpPeriods);
    tmpGeometrVal = PrimitiveFunction.POW.invoke(tmpProcessDistr.getGeometricMean(), tmpPeriods);
    if (RandomProcessTests.DEBUG) {
        this.logDebug("Final Value", tmpFactoryVal, tmpQuotienVal, tmpLogDiffVal, tmpProcessVal, tmpGeometrVal);
    }
    final double tmpDeltaFinal = (1E-14 / THREE) * THOUSAND;
    TestUtils.assertEquals(ONE, tmpGeometrVal / tmpFactoryVal, tmpDeltaFinal);
}

Example 5 with Normal

use of org.ojalgo.random.Normal in project ojAlgo by optimatika.

the class DesignCase method testRandomUnderdetermined.

@Test
public void testRandomUnderdetermined() {
    final PhysicalStore<Double> tmpA = PrimitiveDenseStore.FACTORY.makeFilled(3, 9, new Normal());
    final PhysicalStore<Double> tmpB = PrimitiveDenseStore.FACTORY.makeFilled(3, 1, new Normal());
    final QR<Double> tmpQR = QR.PRIMITIVE.make(tmpA);
    tmpQR.setFullSize(false);
    tmpQR.decompose(tmpA);
    final PhysicalStore<Double> tmpX = tmpQR.getSolution(tmpB).copy();
    // BasicLogger.debug("Straigt X: " + tmpX.toString());
    tmpB.modifyMatching(PrimitiveFunction.SUBTRACT, tmpA.multiply(tmpX));
// BasicLogger.debug("Residual B: " + tmpB.toString());
}