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

Example 6 with RawStore

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

the class RawLDL method doSolve.

private MatrixStore<Double> doSolve(final Collectable<Double, ? super PhysicalStore<Double>> rhs, final PhysicalStore<Double> preallocated) {
    rhs.supplyTo(preallocated);
    final RawStore tmpBody = this.getRawInPlaceStore();
    preallocated.substituteForwards(tmpBody, true, false, false);
    for (int i = 0; i < preallocated.countRows(); i++) {
        preallocated.modifyRow(i, 0, DIVIDE.second(tmpBody.doubleValue(i, i)));
    }
    preallocated.substituteBackwards(tmpBody, true, true, false);
    return preallocated;
}

Example 7 with RawStore

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

the class RawLDL method decompose.

public boolean decompose(final Access2D.Collectable<Double, ? super PhysicalStore<Double>> matrix) {
    final double[][] retVal = this.reset(matrix, false);
    final RawStore tmpRawInPlaceStore = this.getRawInPlaceStore();
    matrix.supplyTo(tmpRawInPlaceStore);
    return this.doDecompose(retVal, tmpRawInPlaceStore);
}

Example 8 with RawStore

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

the class RawLU method doGetInverse.

private MatrixStore<Double> doGetInverse(final PhysicalStore<Double> preallocated) {
    final int[] tmpPivotOrder = myPivot.getOrder();
    final int tmpRowDim = this.getRowDim();
    for (int i = 0; i < tmpRowDim; i++) {
        preallocated.set(i, tmpPivotOrder[i], ONE);
    }
    final RawStore tmpBody = this.getRawInPlaceStore();
    preallocated.substituteForwards(tmpBody, true, false, !myPivot.isModified());
    preallocated.substituteBackwards(tmpBody, false, false, false);
    return preallocated;
}

Example 9 with RawStore

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

the class ConvexProblems method testP20140522.

/**
 * I’ve been using the QuadraticSolver for a while, and suddenly stumbled over an unexpected failure to
 * solve a problem. The solution state was APPROXIMATE and the solution was not correct. I tested the same
 * system with another QP-solver and got the result I expected. I then condensed the problem as much as I
 * could and made a test out of it (see below). To my surprise the test sometimes fails and sometimes
 * passes(!). I’ve been running this test (alone) in TestNG. I’m using Ojalgo v35 and Java 1.7.55. The Q
 * matrix is positive definite.
 *
 * @see "http://bugzilla.optimatika.se/show_bug.cgi?id=210"
 */
@Test
public void testP20140522() {
    final double[][] q = new double[][] { { 49.0, 31.0, 17.0, 6.0 }, { 31.0, 25.0, 13.0, 5.0 }, { 17.0, 13.0, 11.0, 3.5 }, { 6.0, 5.0, 3.5, 4.0 } };
    final RawStore JamaQ = RawStore.FACTORY.rows(q);
    final double[] c = new double[] { 195.0, 59.0, -1.8, -11.7 };
    final RawStore JamaC = RawStore.FACTORY.columns(c);
    final double[][] ai = new double[][] { { 1.0, 0.0, 0.0, 0.0 }, { -1.0, 0.0, 0.0, 0.0 }, { 1.0, 1.0, 0.0, 0.0 }, { -1.0, -1.0, 0.0, 0.0 }, { 1.0, 1.0, 1.0, 0.0 }, { -1.0, -1.0, -1.0, 0.0 }, { 0.1, 0.0, 0.0, 0.0 }, { 0.01, 0.0, 0.0, 0.0 }, { 0.18, 0.1, 0.0, 0.0 }, { -0.01, 0.0, 0.0, 0.0 }, { -0.183, -0.1, 0.0, 0.0 }, { 0.0283, 0.01, 0.0, 0.0 }, { 0.25, 0.183, 0.1, 0.0 } };
    final RawStore JamaAI = RawStore.FACTORY.rows(ai);
    final double[] bi = new double[] { 0.13, 0.87, 0.18, 0.82, 0.23, 0.77, -0.04, 99.67, -0.06, 100.33, 1.06, 99.62, -0.08 };
    final RawStore JamaBI = RawStore.FACTORY.columns(bi);
    Optimisation.Result result = null;
    try {
        final ConvexSolver.Builder qsBuilder = new ConvexSolver.Builder(JamaQ, JamaC);
        qsBuilder.inequalities(JamaAI, JamaBI);
        final ConvexSolver qSolver = qsBuilder.build();
        // qSolver.options.debug(ConvexSolver.class);
        result = qSolver.solve();
        OptimisationConvexTests.assertDirectAndIterativeEquals(qsBuilder, null);
    } catch (final Exception e) {
        e.printStackTrace();
        assert false;
    }
    final CompoundFunction<Double> tmpObj = CompoundFunction.makePrimitive(JamaQ.multiply(0.5), JamaC.multiply(-1.0));
    TestUtils.assertEquals(State.OPTIMAL, result.getState());
    final int numElm = (int) result.count();
    final double[] expectedSolution = new double[] { -0.4, 0.12, -0.0196, -2.45785 };
    tmpObj.invoke(Access1D.wrap(expectedSolution));
    tmpObj.invoke(Access1D.asPrimitive1D(result));
    JamaBI.subtract(JamaAI.multiply(PrimitiveDenseStore.FACTORY.columns(expectedSolution)));
    JamaBI.subtract(JamaAI.multiply(PrimitiveDenseStore.FACTORY.columns(result)));
    for (int i = 0; i < numElm; i++) {
        TestUtils.assertEquals(expectedSolution[i], result.doubleValue(i), 1e-4);
    }
}

Example 10 with RawStore

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

the class P20150809 method buildModel.

static ConvexSolver buildModel(final boolean identity, final boolean addDummyConstraints) {
    if (OptimisationConvexTests.DEBUG) {
        if (!identity && !addDummyConstraints) {
            System.out.println("Zero Q matrix and no constraints -------------------------!");
        } else if (!identity) {
            System.out.println("Zero Q matrix and constraints -------------------------!");
        } else if (!addDummyConstraints) {
            System.out.println("Identity Q matrix and no constraints -------------------------!");
        } else {
            System.out.println("Identity Q matrix and  constraints -------------------------!");
        }
    }
    final double[] C = new double[] { 0.12, -0.05, 0.08, 0.07 };
    final RawStore cov = new RawStore(4, 4);
    if (identity) {
        for (int i = 0; i < 4; i++) {
            cov.set(i, i, 1.0);
        }
    }
    final RawStore linPart = new RawStore(C, 4);
    ConvexSolver.Builder builder = ConvexSolver.getBuilder(cov, linPart);
    if (addDummyConstraints) {
        final RawStore ineq = RawStore.FACTORY.rows(new double[][] { { -1.0, 0.0, 0.0, 0.0 }, { 0.0, -1.0, 0.0, 0.0 }, { 0.0, 0.0, -1.0, 0.0 }, { 0.0, 0.0, 0.0, -1.0 }, { 1.0, 0.0, 0.0, 0.0 }, { 0.0, 1.0, 0.0, 0.0 }, { 0.0, 0.0, 1.0, 0.0 }, { 0.0, 0.0, 0.0, 1.0 } });
        final RawStore coeff = RawStore.FACTORY.columns(new double[][] { { 99999, 99999, 99999, 99999, 99999, 99999, 99999, 99999 } });
        builder = builder.inequalities(ineq, coeff);
    }
    final Optimisation.Options opts = new Optimisation.Options();
    opts.iterations_abort = 10000;
    opts.iterations_suffice = 100;
    if (OptimisationConvexTests.DEBUG) {
        opts.debug(ConvexSolver.class);
    }
    return builder.build(opts);
}