/**
* Computes the householder vector used in QR decomposition.
*
* u = x / max(x)
* u(0) = u(0) + |u|
* u = u / u(0)
*
* @param x Input vector. Unmodified.
* @return The found householder reflector vector
*/
public static CMatrixRMaj householderVector(CMatrixRMaj x)
{
CMatrixRMaj u = (CMatrixRMaj)x.copy();
float max = CommonOps_CDRM.elementMaxAbs(u);
CommonOps_CDRM.elementDivide(u, max, 0, u);
float nx = NormOps_CDRM.normF(u);
Complex_F32 c = new Complex_F32();
u.get(0, 0, c);
float realTau, imagTau;
if (c.getMagnitude() == 0)
{
realTau = nx;
imagTau = 0;
}
else
{
realTau = c.real / c.getMagnitude() * nx;
imagTau = c.imaginary / c.getMagnitude() * nx;
}
u.set(0, 0, c.real + realTau, c.imaginary + imagTau);
CommonOps_CDRM.elementDivide(u, u.getReal(0, 0), u.getImag(0, 0), u);
return(u);
}
/**
* <p>
* Creates an identity matrix of the specified size.<br>
* <br>
* a<sub>ij</sub> = 0+0i if i ≠ j<br>
* a<sub>ij</sub> = 1+0i if i = j<br>
* </p>
*
* @param width The width and height of the identity matrix.
* @return A new instance of an identity matrix.
*/
public static CMatrixRMaj identity(int width)
{
CMatrixRMaj A = new CMatrixRMaj(width, width);
for (int i = 0; i < width; i++)
{
A.set(i, i, 1, 0);
}
return(A);
}
/**
* <p>
* Creates a matrix with diagonal elements set to 1 and the rest 0.<br>
* <br>
* a<sub>ij</sub> = 0+0i if i ≠ j<br>
* a<sub>ij</sub> = 1+0i if i = j<br>
* </p>
*
* @param width The width of the identity matrix.
* @param height The height of the identity matrix.
* @return A new instance of an identity matrix.
*/
public static CMatrixRMaj identity(int width, int height)
{
CMatrixRMaj A = new CMatrixRMaj(width, height);
int m = Math.Min(width, height);
for (int i = 0; i < m; i++)
{
A.set(i, i, 1, 0);
}
return(A);
}
/**
* <p>Performs an "in-place" conjugate transpose.</p>
*
* @see #transpose(CMatrixRMaj)
*
* @param mat The matrix that is to be transposed. Modified.
*/
public static void transposeConjugate(CMatrixRMaj mat)
{
if (mat.numCols == mat.numRows)
{
TransposeAlgs_CDRM.squareConjugate(mat);
}
else
{
CMatrixRMaj b = new CMatrixRMaj(mat.numCols, mat.numRows);
transposeConjugate(mat, b);
mat.reshape(b.numRows, b.numCols);
mat.set(b);
}
}
/**
* Assigns the provided square matrix to be a random Hermitian matrix with elements from min to max value.
*
* @param A The matrix that is to be modified. Must be square. Modified.
* @param min Minimum value an element can have.
* @param max Maximum value an element can have.
* @param rand Random number generator.
*/
public static void fillHermitian(CMatrixRMaj A, float min, float max, IMersenneTwister rand)
{
if (A.numRows != A.numCols)
{
throw new ArgumentException("A must be a square matrix");
}
float range = max - min;
int length = A.numRows;
for (int i = 0; i < length; i++)
{
A.set(i, i, rand.NextFloat() * range + min, 0);
for (int j = i + 1; j < length; j++)
{
float real = rand.NextFloat() * range + min;
float imaginary = rand.NextFloat() * range + min;
A.set(i, j, real, imaginary);
A.set(j, i, real, -imaginary);
}
}
}
/**
* <p>
* Creates a new square matrix whose diagonal elements are specified by data and all
* the other elements are zero.<br>
* <br>
* a<sub>ij</sub> = 0 if i ≤ j<br>
* a<sub>ij</sub> = diag[i] if i = j<br>
* </p>
*
* @param data Contains the values of the diagonal elements of the resulting matrix.
* @return A new complex matrix.
*/
public static CMatrixRMaj diag(float[] data)
{
if (data.Length % 2 == 1)
{
throw new ArgumentException("must be an even number of arguments");
}
int N = data.Length / 2;
CMatrixRMaj m = new CMatrixRMaj(N, N);
int index = 0;
for (int i = 0; i < N; i++)
{
m.set(i, i, data[index++], data[index++]);
}
return(m);
}
public override /**/ double quality()
{
return(SpecializedOps_CDRM.qualityTriangular(R));
}
/**
* Solves for X using the QR decomposition.
*
* @param B A matrix that is n by m. Not modified.
* @param X An n by m matrix where the solution is written to. Modified.
*/
//@Override
public override void solve(CMatrixRMaj B, CMatrixRMaj X)
{
if (X.numRows != numCols)
{
throw new ArgumentException("Unexpected dimensions for X");
}
else if (B.numRows != numRows || B.numCols != X.numCols)
{
throw new ArgumentException("Unexpected dimensions for B");
}
int BnumCols = B.numCols;
Y.reshape(numRows, 1);
Z.reshape(numRows, 1);
// solve each column one by one
for (int colB = 0; colB < BnumCols; colB++)
{
// make a copy of this column in the vector
for (int i = 0; i < numRows; i++)
{
int indexB = B.getIndex(i, colB);
Y.data[i * 2] = B.data[indexB];
Y.data[i * 2 + 1] = B.data[indexB + 1];
}
// Solve Qa=b
// a = Q'b
CommonOps_CDRM.mult(Qt, Y, Z);
// solve for Rx = b using the standard upper triangular solver
TriangularSolver_CDRM.solveU(R.data, Z.data, numCols);
// save the results
for (int i = 0; i < numCols; i++)
{
X.set(i, colB, Z.data[i * 2], Z.data[i * 2 + 1]);
}
}
}
