public static void mult(DMatrixSparseCSC A, DMatrixRMaj B, DMatrixRMaj C)
{
C.zero();
// C(i,j) = sum_k A(i,k) * B(k,j)
for (int k = 0; k < A.numCols; k++)
{
int idx0 = A.col_idx[k];
int idx1 = A.col_idx[k + 1];
for (int indexA = idx0; indexA < idx1; indexA++)
{
int i = A.nz_rows[indexA];
double valueA = A.nz_values[indexA];
int indexB = k * B.numCols;
int indexC = i * C.numCols;
int end = indexB + B.numCols;
// for (int j = 0; j < B.numCols; j++) {
while (indexB < end)
{
C.data[indexC++] += valueA * B.data[indexB++];
}
}
}
}
/**
* Creates a zeros matrix only if A does not already exist. If it does exist it will fill
* the lower triangular portion with zeros.
*/
public static DMatrixRMaj checkZerosLT(DMatrixRMaj A, int numRows, int numCols)
{
if (A == null)
{
return(new DMatrixRMaj(numRows, numCols));
}
else if (numRows != A.numRows || numCols != A.numCols)
{
A.reshape(numRows, numCols);
A.zero();
}
else
{
for (int i = 0; i < A.numRows; i++)
{
int index = i * A.numCols;
int end = index + Math.Min(i, A.numCols);
while (index < end)
{
A.data[index++] = 0;
}
}
}
return(A);
}
public static DMatrixRMaj ensureZeros(DMatrixRMaj A, int numRows, int numCols)
{
if (A == null)
{
return(new DMatrixRMaj(numRows, numCols));
}
A.reshape(numRows, numCols);
A.zero();
return(A);
}
public static DMatrixRMaj checkZeros(DMatrixRMaj A, int numRows, int numCols)
{
if (A == null)
{
return(new DMatrixRMaj(numRows, numCols));
}
else if (numRows != A.numRows || numCols != A.numCols)
{
throw new ArgumentException("Input is not " + numRows + " x " + numCols + " matrix");
}
else
{
A.zero();
}
return(A);
}
private void solveEigenvectorDuplicateEigenvalue(double real, int first, bool isTriangle)
{
double scale = Math.Abs(real);
if (scale == 0)
{
scale = 1;
}
eigenvectorTemp.reshape(N, 1, false);
eigenvectorTemp.zero();
if (first > 0)
{
if (isTriangle)
{
solveUsingTriangle(real, first, eigenvectorTemp);
}
else
{
solveWithLU(real, first, eigenvectorTemp);
}
}
eigenvectorTemp.reshape(N, 1, false);
for (int i = first; i < N; i++)
{
Complex_F64 c = _implicit.eigenvalues[N - i - 1];
if (c.isReal() && Math.Abs(c.real - real) / scale < 100.0 * UtilEjml.EPS)
{
eigenvectorTemp.data[i] = 1;
DMatrixRMaj v = new DMatrixRMaj(N, 1);
CommonOps_DDRM.multTransA(Q, eigenvectorTemp, v);
eigenvectors[N - i - 1] = v;
NormOps_DDRM.normalizeF(v);
eigenvectorTemp.data[i] = 0;
}
}
}
