public void setDouble(double value, int row, int column) { matrix.setQuick(row, column, value); }
public void setDouble(double value, int row, int column) { matrix.setQuick(row, column, value); }
public void setDouble(double value, long row, long column) { matrix.setQuick(MathUtil.longToInt(row), MathUtil.longToInt(column), value); }
public void setDouble(double value, long row, long column) { matrix.setQuick(MathUtil.longToInt(row), MathUtil.longToInt(column), value); }
for (int z = 0; z < qz.length; z++) { double r = qz[z] * v; piz.setQuick(iidx, z, piz.getQuick(iidx, z) + r);
private static DoubleMatrix2D getGt(final DenseDoubleMatrix2D p, final DenseDoubleMatrix2D q, double lambda) { final int K = p.columns(); DenseDoubleMatrix2D A1 = new DenseDoubleMatrix2D(K, K); q.zMult(q, A1, 1.0, 0.0, true, false); for (int k = 0; k < K; k++) { A1.setQuick(k, k, lambda + A1.getQuick(k, k)); } EigenvalueDecomposition eig = new EigenvalueDecomposition(A1); DoubleMatrix1D d = eig.getRealEigenvalues(); DoubleMatrix2D gt = eig.getV(); for (int k = 0; k < K; k++) { double a = sqrt(d.get(k)); gt.viewColumn(k).assign(x -> a * x); } return gt; }
q.zMult(q, A1P, 1.0, 0.0, true, false); for (int k = 0; k < K; k++) { A1P.setQuick(k, k, lambda + A1P.getQuick(k, k));