for(double value : X.getRow(rowId)) { xData.put(componentId++, value);
public static RealMatrix createHankelMatrix(RealMatrix data, int windowSize) { int n = data.getRowDimension(); int m = data.getColumnDimension(); int k = n - windowSize + 1; RealMatrix res = MatrixUtils.createRealMatrix(k, m * windowSize); double[] buffer = {}; for (int i = 0; i < n; ++i) { double[] row = data.getRow(i); buffer = ArrayUtils.addAll(buffer, row); if (i >= windowSize - 1) { RealMatrix mat = MatrixUtils.createRowRealMatrix(buffer); res.setRowMatrix(i - windowSize + 1, mat); buffer = ArrayUtils.subarray(buffer, m, buffer.length); } } return res; }
double[] row = r.getRow(0); traceS += row[i]; System.arraycopy(row, 0, bigS[i], 0, nSamples); //NOPMD
public static RealMatrix clipLower(RealMatrix m, double lowerBound){ // TODO see if you really need to modify m or just return a modified copy of m //process the matrix row by row, each row gets processed in parallel // TODO See if you can directly parallelize on the entire matrix not row by row // OPEN implement using Arrays.parallelSetAll Method? int nrOfRows = m.getRowDimension(); for(int i = 0; i < nrOfRows; i++){ // TODO move the declaration outside the for loop double[] currRow = m.getRow(i); double[] newRow = Arrays.stream(currRow) .parallel() .map((number) -> (number < lowerBound) ? lowerBound : number) .toArray(); m.setRow(i, newRow); } return m; }
for (int i = 0; i < nR; ++i) { final double[] grad = weightedJacobian.getRow(i); final double weight = residualsWeights[i]; final double residual = currentResiduals[i];
RealMatrix cInv = cdSolver.getInverse(); RealMatrix r = rx.multiply(cInv).multiply(mXTW); double[] row = r.getRow(0); sTrace += row[i]; System.arraycopy(row, 0, bigS[i], 0, nSamples);
public void estimateMean(RealMatrix x){ VectorialMean m = new VectorialMean(dimensions); for(int i=0;i<x.getRowDimension();i++){ m.increment(x.getRow(i)); } initialMean = new Array2DRowRealMatrix(m.getResult()); }
for (int i = 0; i < nR; ++i) { final double[] grad = weightedJacobian.getRow(i); final double weight = residualsWeights[i]; final double residual = currentResiduals[i];
RealMatrix arzneg = selectColumns(arz, MathArrays.copyOf(arReverseIndex, mu)); RealMatrix arnorms = sqrt(sumRows(square(arzneg))); final int[] idxnorms = sortedIndices(arnorms.getRow(0)); final RealMatrix arnormsSorted = selectColumns(arnorms, idxnorms); final int[] idxReverse = reverse(idxnorms);
RealMatrix arzneg = selectColumns(arz, MathArrays.copyOf(arReverseIndex, mu)); RealMatrix arnorms = sqrt(sumRows(square(arzneg))); final int[] idxnorms = sortedIndices(arnorms.getRow(0)); final RealMatrix arnormsSorted = selectColumns(arnorms, idxnorms); final int[] idxReverse = reverse(idxnorms);
RealMatrix result = MatrixUtils.createRealMatrix(a).multiply(MatrixUtils.createRealMatrix(b)); double[] array = result.getRow(0);
public TetradVector getRow(int i) { if (zeroDimension()) { return new TetradVector(columns()); } return new TetradVector(apacheData.getRow(i)); }
@Test public void testTransposeTimesSelf() { FastByIDMap<float[]> M = new FastByIDMap<float[]>(); M.put(1L, new float[] {4.0f, -1.0f, -5.0f}); M.put(2L, new float[] {2.0f, 0.0f, 3.0f}); RealMatrix MTM = MatrixUtils.transposeTimesSelf(M); assertArrayEquals(new double[]{20.0, -4.0, -14.0}, MTM.getRow(0)); assertArrayEquals(new double[]{-4.0, 1.0, 5.0}, MTM.getRow(1)); assertArrayEquals(new double[]{-14.0, 5.0, 34.0}, MTM.getRow(2)); }
private Pair<double[], double[]> calculatePixelLookupTable(DicomImageElement dicomImage) { double deltaI = dicomImage.getSliceGeometry().getVoxelSpacingArray()[0]; double deltaJ = dicomImage.getSliceGeometry().getVoxelSpacingArray()[1]; double[] rowDirection = dicomImage.getSliceGeometry().getRowArray(); double[] columnDirection = dicomImage.getSliceGeometry().getColumnArray(); double[] position = dicomImage.getSliceGeometry().getTLHCArray(); // DICOM C.7.6.2.1 Equation C.7.6.2.1-1. double[][] m = { { rowDirection[0] * deltaI, columnDirection[0] * deltaJ, 0, position[0] }, { rowDirection[1] * deltaI, columnDirection[1] * deltaJ, 0, position[1] }, { rowDirection[2] * deltaI, columnDirection[2] * deltaJ, 0, position[2] }, { 0, 0, 0, 1 } }; RealMatrix matrix = MatrixUtils.createRealMatrix(m); double[] x = new double[dicomImage.getImage().width()]; // column index to the image plane. for (int i = 0; i < dicomImage.getImage().width(); i++) { x[i] = matrix.multiply(MatrixUtils.createColumnRealMatrix(new double[] { i, 0, 0, 1 })).getRow(0)[0]; } double[] y = new double[dicomImage.getImage().height()]; // row index to the image plane for (int j = 0; j < dicomImage.getImage().height(); j++) { y[j] = matrix.multiply(MatrixUtils.createColumnRealMatrix(new double[] { 0, j, 0, 1 })).getRow(1)[0]; } return new Pair<>(x, y); }
for (int i = 0; i < nR; ++i) { final double[] grad = weightedJacobian.getRow(i); final double weight = residualsWeights[i]; final double residual = currentResiduals[i];
for (int i = 0; i < nR; ++i) { final double[] grad = weightedJacobian.getRow(i); final double weight = residualsWeights[i]; final double residual = currentResiduals[i];
for (int i = 0; i < nR; ++i) { final double[] grad = weightedJacobian.getRow(i); final double weight = residualsWeights[i]; final double residual = currentResiduals[i];
RealMatrix arzneg = selectColumns(arz, MathArrays.copyOf(arReverseIndex, mu)); RealMatrix arnorms = sqrt(sumRows(square(arzneg))); final int[] idxnorms = sortedIndices(arnorms.getRow(0)); final RealMatrix arnormsSorted = selectColumns(arnorms, idxnorms); final int[] idxReverse = reverse(idxnorms);
RealMatrix arzneg = selectColumns(arz, MathArrays.copyOf(arReverseIndex, mu)); RealMatrix arnorms = sqrt(sumRows(square(arzneg))); final int[] idxnorms = sortedIndices(arnorms.getRow(0)); final RealMatrix arnormsSorted = selectColumns(arnorms, idxnorms); final int[] idxReverse = reverse(idxnorms);
RealMatrix arzneg = selectColumns(arz, MathArrays.copyOf(arReverseIndex, mu)); RealMatrix arnorms = sqrt(sumRows(square(arzneg))); final int[] idxnorms = sortedIndices(arnorms.getRow(0)); final RealMatrix arnormsSorted = selectColumns(arnorms, idxnorms); final int[] idxReverse = reverse(idxnorms);