public static void squareConjugate(CMatrixRMaj mat)
{
int index = 2;
int rowStride = mat.getRowStride();
int indexEnd = rowStride;
for (int i = 0;
i < mat.numRows;
i++, index += (i + 1) * 2, indexEnd += rowStride)
{
mat.data[index - 1] = -mat.data[index - 1];
int indexOther = (i + 1) * rowStride + i * 2;
for (; index < indexEnd; index += 2, indexOther += rowStride)
{
float real = mat.data[index];
float img = mat.data[index + 1];
mat.data[index] = mat.data[indexOther];
mat.data[index + 1] = -mat.data[indexOther + 1];
mat.data[indexOther] = real;
mat.data[indexOther + 1] = -img;
}
}
}
//@Override
public override void invert(CMatrixRMaj A_inv)
{
float[] vv = decomp._getVV();
CMatrixRMaj LU = decomp.getLU();
if (A_inv.numCols != LU.numCols || A_inv.numRows != LU.numRows)
{
throw new ArgumentException("Unexpected matrix dimension");
}
int n = A.numCols;
float[] dataInv = A_inv.data;
int strideAinv = A_inv.getRowStride();
for (int j = 0; j < n; j++)
{
// don't need to change inv into an identity matrix before hand
Array.Clear(vv, 0, n * 2);
vv[j * 2] = 1;
vv[j * 2 + 1] = 0;
decomp._solveVectorInternal(vv);
// for( int i = 0; i < n; i++ ) dataInv[i* n +j] = vv[i];
int index = j * 2;
for (int i = 0; i < n; i++, index += strideAinv)
{
dataInv[index] = vv[i * 2];
dataInv[index + 1] = vv[i * 2 + 1];
}
}
}
/**
* Computes the quality of a triangular matrix, where the quality of a matrix
* is defined in {@link LinearSolverDense#quality()}. In
* this situation the quality is the magnitude of the product of
* each diagonal element divided by the magnitude of the largest diagonal element.
* If all diagonal elements are zero then zero is returned.
*
* @return the quality of the system.
*/
public static float qualityTriangular(CMatrixRMaj T)
{
int N = Math.Min(T.numRows, T.numCols);
float max = elementDiagMaxMagnitude2(T);
if (max == 0.0f)
{
return(0.0f);
}
max = (float)Math.Sqrt(max);
int rowStride = T.getRowStride();
float qualityR = 1.0f;
float qualityI = 0.0f;
for (int i = 0; i < N; i++)
{
int index = i * rowStride + i * 2;
float real = T.data[index] / max;
float imaginary = T.data[index] / max;
float r = qualityR * real - qualityI * imaginary;
float img = qualityR * imaginary + real * qualityI;
qualityR = r;
qualityI = img;
}
return((float)Math.Sqrt(qualityR * qualityR + qualityI * qualityI));
}
/**
* Sets all the diagonal elements equal to one and everything else equal to zero.
* If this is a square matrix then it will be an identity matrix.
*
* @param mat A square matrix.
*/
public static void setIdentity(CMatrixRMaj mat)
{
int width = mat.numRows < mat.numCols ? mat.numRows : mat.numCols;
Array.Clear(mat.data, 0, mat.getDataLength());
int index = 0;
int stride = mat.getRowStride();
for (int i = 0; i < width; i++, index += stride + 2)
{
mat.data[index] = 1;
}
}
/**
* A straight forward transpose. Good for small non-square matrices.
*
* @param A Original matrix. Not modified.
* @param A_tran Transposed matrix. Modified.
*/
public static void standard(CMatrixRMaj A, CMatrixRMaj A_tran)
{
int index = 0;
int rowStrideTran = A_tran.getRowStride();
int rowStride = A.getRowStride();
for (int i = 0; i < A_tran.numRows; i++)
{
int index2 = i * 2;
int end = index + rowStrideTran;
while (index < end)
{
A_tran.data[index++] = A.data[index2];
A_tran.data[index++] = A.data[index2 + 1];
index2 += rowStride;
}
}
}
//@Override
public override void solve(CMatrixRMaj b, CMatrixRMaj x)
{
if (b.numCols != x.numCols || b.numRows != numRows || x.numRows != numCols)
{
throw new ArgumentException("Unexpected matrix size");
}
int bnumCols = b.numCols;
int bstride = b.getRowStride();
float[] dataB = b.data;
float[] dataX = x.data;
float[] vv = decomp._getVV();
// for( int j = 0; j < numCols; j++ ) {
// for( int i = 0; i < this.numCols; i++ ) vv[i] = dataB[i*numCols+j];
// decomp._solveVectorInternal(vv);
// for( int i = 0; i < this.numCols; i++ ) dataX[i*numCols+j] = vv[i];
// }
for (int j = 0; j < bnumCols; j++)
{
int index = j * 2;
for (int i = 0; i < numRows; i++, index += bstride)
{
vv[i * 2] = dataB[index];
vv[i * 2 + 1] = dataB[index + 1];
}
decomp._solveVectorInternal(vv);
index = j * 2;
for (int i = 0; i < numRows; i++, index += bstride)
{
dataX[index] = vv[i * 2];
dataX[index + 1] = vv[i * 2 + 1];
}
}
}
/**
* <p>
* Returns the magnitude squared of the complex element along the diagonal with the largest magnitude<br>
* <br>
* Max{ |a<sub>ij</sub>|^2 } for all i and j<br>
* </p>
*
* @param a A matrix. Not modified.
* @return The max magnitude squared
*/
public static float elementDiagMaxMagnitude2(CMatrixRMaj a)
{
int size = Math.Min(a.numRows, a.numCols);
int rowStride = a.getRowStride();
float max = 0;
for (int i = 0; i < size; i++)
{
int index = i * rowStride + i * 2;
float real = a.data[index];
float imaginary = a.data[index + 1];
float m = real * real + imaginary * imaginary;
if (m > max)
{
max = m;
}
}
return(max);
}
