Examples with GMatrix javax.vecmath.GMatrix used on opensource projects

Example 1 with GMatrix

use of javax.vecmath.GMatrix in project bb4-common by bb4.

the class ConjugateGradientSolver method solve.

/**
 * Find a solution or return the initial guess if something goes wrong.
 * @param initialGuess the initial guess for the solution x, x0
 * @return solution vector
 */
public GVector solve(GVector initialGuess) {
    GVector x = new GVector(initialGuess);
    GVector tempv = new GVector(initialGuess);
    tempv.mul(matrix, initialGuess);
    GVector bb = new GVector(b);
    bb.sub(tempv);
    GVector r = new GVector(bb);
    GVector p = new GVector(r);
    GVector xnew = new GVector(p);
    GVector rnew = new GVector(p);
    GVector pnew = new GVector(p);
    GVector matrixMultp = new GVector(p);
    GMatrix matrixInverse = new GMatrix(matrix);
    matrixInverse.invert();
    double error, norm;
    int iteration = 0;
    do {
        matrixMultp.mul(matrix, p);
        double lambda = (r.dot(p) / p.dot(matrixMultp));
        xnew.scaleAdd(lambda, p, x);
        rnew.scaleAdd(-lambda, matrixMultp, r);
        double alpha = -(rnew.dot(matrixMultp) / p.dot(matrixMultp));
        pnew.scaleAdd(alpha, p, rnew);
        p.set(pnew);
        r.set(rnew);
        // System.out.println("the residual = "+r.toString());
        x.set(xnew);
        // error = Math.abs(r.dot(r)); // wrong way to compute norm
        rnew.mul(r, matrixInverse);
        norm = rnew.dot(r);
        error = norm * norm;
        // System.out.println("xi = "+x.toString());
        iteration++;
    // System.out.println("The error for iteration " + iteration + " is : " + error );
    } while (error > eps && iteration < maxIterations);
    if (error > eps || Double.isNaN(error) || Double.isInfinite(error)) {
        // something went wrong
        throw new IllegalStateException("Unable to converge on a solution. Error = " + error);
    // return initialGuess;
    }
    return xnew;
}

Example 2 with GMatrix

use of javax.vecmath.GMatrix in project bb4-common by bb4.

the class ConjugateGradientSolverTest method solve3by4System.

/* didn't work. typo?
    @Test
    public void solveSimple3by3System() {

        GMatrix A = new GMatrix(3, 3, new double[] {
                5, 4, -1,
                0, 10, -3,
                0, 0, 1
        });
        GVector b = new GVector(new double[] {0, 11, 3});

        solver = new ConjugateGradientSolver(A, b);

        GVector solution = solver.solve();

        System.out.println("Solution = "+ solution);
        GVector expectedSolution = new GVector(new double[] {-1, 2, 3});

        assertTrue("Unexpected solution:" + solution,
                LinearUtil.appxVectorsEqual(expectedSolution, solution, 0.0000001));
    }*/
// Conjugant gradient can only be applied to square matrices
@Test(expected = MismatchedSizeException.class)
public void solve3by4System() {
    GMatrix A = new GMatrix(3, 4, new double[] { 2, 2, -1, 1, 1, 1, 1, 1, 2, -2, 2, 3 });
    GVector b = new GVector(new double[] { 11, 4, 7 });
    solver = new ConjugateGradientSolver(A, b);
    solver.solve();
}

Example 3 with GMatrix

use of javax.vecmath.GMatrix in project imageio-ext by geosolutions-it.

the class NetCDFCFExperiment method Resampler.

private WritableRaster Resampler(final Array latData, final Array lonData, final int imageWidth, final int imageHeight, final int polyDegree, final Array data, final float fillValue) {
    final Index latIndex = latData.getIndex();
    final Index lonIndex = lonData.getIndex();
    final int numCoeffs = (polyDegree + 1) * (polyDegree + 2) / 2;
    final int XOFFSET = 0;
    final int YOFFSET = 1;
    final int stepX = 2;
    final int stepY = 2;
    int numNeededPoints = 0;
    for (int xi = 0; xi < imageWidth; xi += stepX) {
        for (int yi = 0; yi < imageHeight; yi += stepY) {
            numNeededPoints++;
        }
    }
    computeMatrixExtremes(latData, lonData, imageWidth, imageHeight, latIndex, lonIndex);
    float[] destCoords = new float[2 * numNeededPoints];
    float[] srcCoords = new float[2 * numNeededPoints];
    /*
         * Copy source and destination coordinates into float arrays. The
         * destination coordinates are scaled in order to gets values similar to
         * source coordinates (values will be identical if all "real world"
         * coordinates are grid indices multiplied by a constant).
         */
    int offset = 0;
    for (int yi = 0; yi < imageHeight; yi += stepY) {
        for (int xi = 0; xi < imageWidth; xi += stepX) {
            srcCoords[offset] = xi;
            srcCoords[offset + 1] = yi;
            destCoords[offset] = (float) ((lonData.getFloat(lonIndex.set(xi)) - this.xmin) / this.periodX);
            destCoords[offset + 1] = (float) ((this.ymax - latData.getFloat(latIndex.set(yi))) / this.periodY);
            // destCoords[offset + 1] = ((latData.getFloat(latIndex.set(yi)) - this.ymin) / this.periodY);
            offset += 2;
        }
    }
    GMatrix A = new GMatrix(numNeededPoints, numCoeffs);
    for (int coord = 0; coord < numNeededPoints; coord++) {
        int var = 0;
        for (int i = 0; i <= polyDegree; i++) {
            for (int j = 0; j <= i; j++) {
                double value = Math.pow(destCoords[2 * coord + XOFFSET], (double) (i - j)) * Math.pow(destCoords[2 * coord + YOFFSET], (double) j);
                A.setElement(coord, var++, value);
            }
        }
    }
    GMatrix AtAi = new GMatrix(numCoeffs, numCoeffs);
    GMatrix Ap = new GMatrix(numCoeffs, numNeededPoints);
    AtAi.mulTransposeLeft(A, A);
    AtAi.invert();
    Ap.mulTransposeRight(AtAi, A);
    GMatrix xVector = new GMatrix(numNeededPoints, 1);
    GMatrix yVector = new GMatrix(numNeededPoints, 1);
    for (int idx = 0; idx < numNeededPoints; idx++) {
        xVector.setElement(idx, 0, srcCoords[2 * idx + XOFFSET]);
        yVector.setElement(idx, 0, srcCoords[2 * idx + YOFFSET]);
    }
    GMatrix xCoeffsG = new GMatrix(numCoeffs, 1);
    GMatrix yCoeffsG = new GMatrix(numCoeffs, 1);
    xCoeffsG.mul(Ap, xVector);
    yCoeffsG.mul(Ap, yVector);
    float[] xCoeffs = new float[numCoeffs];
    float[] yCoeffs = new float[numCoeffs];
    for (int ii = 0; ii < numCoeffs; ii++) {
        xCoeffs[ii] = new Double(xCoeffsG.getElement(ii, 0)).floatValue();
        yCoeffs[ii] = new Double(yCoeffsG.getElement(ii, 0)).floatValue();
    }
    WritableRaster outDataCube;
    WritableRandomIter iteratorDataCube;
    SampleModel outSampleModel = RasterFactory.createBandedSampleModel(// data type
    DataBuffer.TYPE_FLOAT, // width
    imageWidth, // height
    imageHeight, // num bands
    1);
    outDataCube = Raster.createWritableRaster(outSampleModel, null);
    iteratorDataCube = RandomIterFactory.createWritable(outDataCube, null);
    // Transfering data in the WritableRaster structure
    Index indexInputVar = data.getIndex();
    for (int jj = 0; jj < outDataCube.getNumBands(); jj++) {
        for (int kk = 0; kk < outDataCube.getWidth(); kk++) {
            for (int ll = 0; ll < outDataCube.getHeight(); ll++) {
                iteratorDataCube.setSample(kk, ll, jj, data.getFloat(indexInputVar.set(ll, kk)));
            }
        }
    }
    WritableRaster target = RasterFactory.createWritableRaster(outSampleModel, null);
    for (int bi = 0; bi < outDataCube.getNumBands(); bi++) {
        for (int yi = 0; yi < imageHeight; yi++) {
            for (int xi = 0; xi < imageWidth; xi++) {
                float[] dstCoords = new float[2];
                GMatrix regressionVec = new GMatrix(numCoeffs, 1);
                int var = 0;
                for (int i = 0; i <= polyDegree; i++) {
                    for (int j = 0; j <= i; j++) {
                        double value = Math.pow(xi, (double) (i - j)) * Math.pow(yi, (double) j);
                        regressionVec.setElement(var++, 0, value);
                    }
                }
                GMatrix xG = new GMatrix(1, 1);
                GMatrix yG = new GMatrix(1, 1);
                xG.mulTransposeLeft(regressionVec, xCoeffsG);
                yG.mulTransposeLeft(regressionVec, yCoeffsG);
                int X = (int) Math.round(xG.getElement(0, 0));
                int Y = (int) Math.round(yG.getElement(0, 0));
                if (X >= 0 && Y >= 0 && X < imageWidth && Y < imageHeight) {
                    target.setSample(xi, yi, bi, outDataCube.getSampleFloat(X, Y, bi));
                } else {
                    // TODO: Change with fillvalue
                    // target.setSample(xi, yi, bi, Float.NaN);
                    target.setSample(xi, yi, bi, fillValue);
                }
            }
        }
    }
    return target;
}

Example 4 with GMatrix

use of javax.vecmath.GMatrix in project bb4-common by bb4.

the class ConjugateGradientSolverTest method solveSimple2by2System.

@Test
public void solveSimple2by2System() {
    GMatrix A = new GMatrix(2, 2, new double[] { 4, 1, 1, 3 });
    GVector b = new GVector(new double[] { 1, 2 });
    solver = new ConjugateGradientSolver(A, b);
    GVector solution = solver.solve();
    System.out.println("Solution = " + solution);
    GVector expectedSolution = new GVector(new double[] { 1.0 / 11.0, 7.0 / 11.0 });
    assertTrue("Unexpected solution:" + solution, LinearUtil.appxVectorsEqual(expectedSolution, solution, 0.000001));
}

Example 5 with GMatrix

use of javax.vecmath.GMatrix in project imageio-ext by geosolutions-it.

the class HOPSConverter method Resampler.

private WritableRaster Resampler(final Array latData, final Array lonData, final int imageWidth, final int imageHeight, final int polyDegree, final Array data, final float fillValue) {
    final Index latIndex = latData.getIndex();
    final Index lonIndex = lonData.getIndex();
    final int numCoeffs = (polyDegree + 1) * (polyDegree + 2) / 2;
    final int XOFFSET = 0;
    final int YOFFSET = 1;
    final int stepX = 2;
    final int stepY = 2;
    int numNeededPoints = 0;
    for (int xi = 0; xi < imageWidth; xi += stepX) {
        for (int yi = 0; yi < imageHeight; yi += stepY) {
            numNeededPoints++;
        }
    }
    computeMatrixExtremes(latData, lonData, imageWidth, imageHeight, latIndex, lonIndex);
    float[] destCoords = new float[2 * numNeededPoints];
    float[] srcCoords = new float[2 * numNeededPoints];
    /*
         * Copy source and destination coordinates into float arrays. The
         * destination coordinates are scaled in order to gets values similar to
         * source coordinates (values will be identical if all "real world"
         * coordinates are grid indices multiplied by a constant).
         */
    int offset = 0;
    for (int yi = 0; yi < imageHeight; yi += stepY) {
        for (int xi = 0; xi < imageWidth; xi += stepX) {
            srcCoords[offset] = xi;
            srcCoords[offset + 1] = yi;
            destCoords[offset] = (float) ((lonData.getFloat(lonIndex.set(xi)) - this.xmin) / this.periodX);
            destCoords[offset + 1] = (float) ((this.ymax - latData.getFloat(latIndex.set(yi))) / this.periodY);
            // destCoords[offset + 1] = ((latData.getFloat(latIndex.set(yi)) - this.ymin) / this.periodY);
            offset += 2;
        }
    }
    GMatrix A = new GMatrix(numNeededPoints, numCoeffs);
    for (int coord = 0; coord < numNeededPoints; coord++) {
        int var = 0;
        for (int i = 0; i <= polyDegree; i++) {
            for (int j = 0; j <= i; j++) {
                double value = Math.pow(destCoords[2 * coord + XOFFSET], (double) (i - j)) * Math.pow(destCoords[2 * coord + YOFFSET], (double) j);
                A.setElement(coord, var++, value);
            }
        }
    }
    GMatrix AtAi = new GMatrix(numCoeffs, numCoeffs);
    GMatrix Ap = new GMatrix(numCoeffs, numNeededPoints);
    AtAi.mulTransposeLeft(A, A);
    AtAi.invert();
    Ap.mulTransposeRight(AtAi, A);
    GMatrix xVector = new GMatrix(numNeededPoints, 1);
    GMatrix yVector = new GMatrix(numNeededPoints, 1);
    for (int idx = 0; idx < numNeededPoints; idx++) {
        xVector.setElement(idx, 0, srcCoords[2 * idx + XOFFSET]);
        yVector.setElement(idx, 0, srcCoords[2 * idx + YOFFSET]);
    }
    GMatrix xCoeffsG = new GMatrix(numCoeffs, 1);
    GMatrix yCoeffsG = new GMatrix(numCoeffs, 1);
    xCoeffsG.mul(Ap, xVector);
    yCoeffsG.mul(Ap, yVector);
    float[] xCoeffs = new float[numCoeffs];
    float[] yCoeffs = new float[numCoeffs];
    for (int ii = 0; ii < numCoeffs; ii++) {
        xCoeffs[ii] = new Double(xCoeffsG.getElement(ii, 0)).floatValue();
        yCoeffs[ii] = new Double(yCoeffsG.getElement(ii, 0)).floatValue();
    }
    WritableRaster outDataCube;
    WritableRandomIter iteratorDataCube;
    SampleModel outSampleModel = RasterFactory.createBandedSampleModel(// data type
    DataBuffer.TYPE_FLOAT, // width
    imageWidth, // height
    imageHeight, // num bands
    1);
    outDataCube = Raster.createWritableRaster(outSampleModel, null);
    iteratorDataCube = RandomIterFactory.createWritable(outDataCube, null);
    // Transfering data in the WritableRaster structure
    Index indexInputVar = data.getIndex();
    for (int jj = 0; jj < outDataCube.getNumBands(); jj++) {
        for (int kk = 0; kk < outDataCube.getWidth(); kk++) {
            for (int ll = 0; ll < outDataCube.getHeight(); ll++) {
                iteratorDataCube.setSample(kk, ll, jj, data.getFloat(indexInputVar.set(ll, kk)));
            }
        }
    }
    WritableRaster target = RasterFactory.createWritableRaster(outSampleModel, null);
    for (int bi = 0; bi < outDataCube.getNumBands(); bi++) {
        for (int yi = 0; yi < imageHeight; yi++) {
            for (int xi = 0; xi < imageWidth; xi++) {
                float[] dstCoords = new float[2];
                GMatrix regressionVec = new GMatrix(numCoeffs, 1);
                int var = 0;
                for (int i = 0; i <= polyDegree; i++) {
                    for (int j = 0; j <= i; j++) {
                        double value = Math.pow(xi, (double) (i - j)) * Math.pow(yi, (double) j);
                        regressionVec.setElement(var++, 0, value);
                    }
                }
                GMatrix xG = new GMatrix(1, 1);
                GMatrix yG = new GMatrix(1, 1);
                xG.mulTransposeLeft(regressionVec, xCoeffsG);
                yG.mulTransposeLeft(regressionVec, yCoeffsG);
                int X = (int) Math.round(xG.getElement(0, 0));
                int Y = (int) Math.round(yG.getElement(0, 0));
                if (X >= 0 && Y >= 0 && X < imageWidth && Y < imageHeight) {
                    target.setSample(xi, yi, bi, outDataCube.getSampleFloat(X, Y, bi));
                } else {
                    // TODO: Change with fillvalue
                    // target.setSample(xi, yi, bi, Float.NaN);
                    target.setSample(xi, yi, bi, fillValue);
                }
            }
        }
    }
    return target;
}