Examples with Matrix org.apache.ignite.ml.math.Matrix used on opensource projects

Example 6 with Matrix

use of org.apache.ignite.ml.math.Matrix in project ignite by apache.

the class EigenDecomposition method orthes.

/** */
private Matrix orthes(Matrix matrix) {
    // Working storage for nonsymmetric algorithm.
    Vector ort = likeVector(matrix);
    Matrix hessenBerg = like(matrix).assign(matrix);
    //  This is derived from the Algol procedures orthes and ortran,
    //  by Martin and Wilkinson, Handbook for Auto. Comp.,
    //  Vol.ii-Linear Algebra, and the corresponding
    //  Fortran subroutines in EISPACK.
    int low = 0;
    int high = n - 1;
    for (int m = low + 1; m <= high - 1; m++) {
        // Scale column.
        Vector hCol = hessenBerg.viewColumn(m - 1).viewPart(m, high - m + 1);
        double scale = hCol.kNorm(1);
        if (scale != 0.0) {
            // Compute Householder transformation.
            ort.viewPart(m, high - m + 1).map(hCol, Functions.plusMult(1 / scale));
            double h = ort.viewPart(m, high - m + 1).getLengthSquared();
            double g = Math.sqrt(h);
            if (ort.getX(m) > 0)
                g = -g;
            h -= ort.getX(m) * g;
            ort.setX(m, ort.getX(m) - g);
            // Apply Householder similarity transformation
            // H = (I-u*u'/h)*H*(I-u*u')/h)
            Vector ortPiece = ort.viewPart(m, high - m + 1);
            for (int j = m; j < n; j++) {
                double f = ortPiece.dot(hessenBerg.viewColumn(j).viewPart(m, high - m + 1)) / h;
                hessenBerg.viewColumn(j).viewPart(m, high - m + 1).map(ortPiece, Functions.plusMult(-f));
            }
            for (int i = 0; i <= high; i++) {
                double f = ortPiece.dot(hessenBerg.viewRow(i).viewPart(m, high - m + 1)) / h;
                hessenBerg.viewRow(i).viewPart(m, high - m + 1).map(ortPiece, Functions.plusMult(-f));
            }
            ort.setX(m, scale * ort.getX(m));
            hessenBerg.setX(m, m - 1, scale * g);
        }
    }
    // Accumulate transformations (Algol's ortran).
    v.assign(0);
    v.viewDiagonal().assign(1);
    for (int m = high - 1; m >= low + 1; m--) {
        if (hessenBerg.getX(m, m - 1) != 0.0) {
            ort.viewPart(m + 1, high - m).assign(hessenBerg.viewColumn(m - 1).viewPart(m + 1, high - m));
            for (int j = m; j <= high; j++) {
                double g = ort.viewPart(m, high - m + 1).dot(v.viewColumn(j).viewPart(m, high - m + 1));
                // Double division avoids possible underflow
                g = g / ort.getX(m) / hessenBerg.getX(m, m - 1);
                v.viewColumn(j).viewPart(m, high - m + 1).map(ort.viewPart(m, high - m + 1), Functions.plusMult(g));
            }
        }
    }
    return hessenBerg;
}

Example 7 with Matrix

use of org.apache.ignite.ml.math.Matrix in project ignite by apache.

the class PivotedMatrixViewConstructorTest method basicTest.

/** */
@Test
public void basicTest() {
    Matrix m = new DenseLocalOnHeapMatrix(2, 2);
    int[] pivot = new int[] { 0, 1 };
    PivotedMatrixView view = new PivotedMatrixView(m, pivot);
    assertEquals("Rows in view.", m.rowSize(), view.rowSize());
    assertEquals("Cols in view.", m.columnSize(), view.columnSize());
    assertTrue("Row pivot array in view.", Arrays.equals(pivot, view.rowPivot()));
    assertTrue("Col pivot array in view.", Arrays.equals(pivot, view.columnPivot()));
    Assert.assertEquals("Base matrix in view.", m, view.getBaseMatrix());
    assertEquals("Row pivot value in view.", 0, view.rowPivot(0));
    assertEquals("Col pivot value in view.", 0, view.columnPivot(0));
    assertEquals("Row unpivot value in view.", 0, view.rowUnpivot(0));
    assertEquals("Col unpivot value in view.", 0, view.columnUnpivot(0));
    Matrix swap = view.swap(1, 1);
    for (int row = 0; row < view.rowSize(); row++) for (int col = 0; col < view.columnSize(); col++) assertEquals("Unexpected swap value set at (" + row + "," + col + ").", view.get(row, col), swap.get(row, col), 0d);
    //noinspection EqualsWithItself
    assertTrue("View is expected to be equal to self.", view.equals(view));
    //noinspection ObjectEqualsNull
    assertFalse("View is expected to be not equal to null.", view.equals(null));
}

Example 8 with Matrix

use of org.apache.ignite.ml.math.Matrix in project ignite by apache.

the class PivotedMatrixViewConstructorTest method pivotTest.

/** */
private void pivotTest(Matrix parent, int[] pivot) {
    for (int row = 0; row < parent.rowSize(); row++) for (int col = 0; col < parent.columnSize(); col++) parent.set(row, col, row * parent.columnSize() + col + 1);
    Matrix view = new PivotedMatrixView(parent, pivot);
    int rows = parent.rowSize();
    int cols = parent.columnSize();
    assertEquals("Rows in view.", rows, view.rowSize());
    assertEquals("Cols in view.", cols, view.columnSize());
    for (int row = 0; row < rows; row++) for (int col = 0; col < cols; col++) assertEquals("Unexpected value at " + row + "x" + col, parent.get(pivot[row], pivot[col]), view.get(row, col), 0d);
    int min = rows < cols ? rows : cols;
    for (int idx = 0; idx < min; idx++) view.set(idx, idx, 0d);
    for (int idx = 0; idx < min; idx++) assertEquals("Unexpected value set at " + idx, 0d, parent.get(pivot[idx], pivot[idx]), 0d);
}

Example 9 with Matrix

use of org.apache.ignite.ml.math.Matrix in project ignite by apache.

the class MatrixImplementationsTest method testPlus.

/** */
@Test
public void testPlus() {
    consumeSampleMatrix((m, desc) -> {
        if (readOnly(m))
            return;
        double[][] data = fillAndReturn(m);
        double plusVal = Math.random();
        Matrix plus = m.plus(plusVal);
        for (int i = 0; i < m.rowSize(); i++) for (int j = 0; j < m.columnSize(); j++) assertEquals("Unexpected value for " + desc + " at (" + i + "," + j + ")", data[i][j] + plusVal, plus.get(i, j), 0d);
    });
}

Example 10 with Matrix

use of org.apache.ignite.ml.math.Matrix in project ignite by apache.

the class MatrixImplementationFixtures method consumeSampleMatrix.

/** */
void consumeSampleMatrix(BiConsumer<Matrix, String> consumer) {
    for (Supplier<Iterable<Matrix>> fixtureSupplier : suppliers) {
        final Iterable<Matrix> fixture = fixtureSupplier.get();
        for (Matrix matrix : fixture) {
            consumer.accept(matrix, fixture.toString());
            matrix.destroy();
        }
    }
}