/// <summary>
/// Multiplies two matrices and updates another with the result. <c>c = alpha*op(a)*op(b) + beta*c</c>
/// </summary>
/// <param name="transposeA">How to transpose the <paramref name="a"/> matrix.</param>
/// <param name="transposeB">How to transpose the <paramref name="b"/> matrix.</param>
/// <param name="alpha">The value to scale <paramref name="a"/> matrix.</param>
/// <param name="a">The a matrix.</param>
/// <param name="rowsA">The number of rows in the <paramref name="a"/> matrix.</param>
/// <param name="columnsA">The number of columns in the <paramref name="a"/> matrix.</param>
/// <param name="b">The b matrix</param>
/// <param name="rowsB">The number of rows in the <paramref name="b"/> matrix.</param>
/// <param name="columnsB">The number of columns in the <paramref name="b"/> matrix.</param>
/// <param name="beta">The value to scale the <paramref name="c"/> matrix.</param>
/// <param name="c">The c matrix.</param>
public virtual void MatrixMultiplyWithUpdate(Transpose transposeA, Transpose transposeB, Complex alpha, Complex[] a, int rowsA, int columnsA, Complex[] b, int rowsB, int columnsB, Complex beta, Complex[] c)
{
int m; // The number of rows of matrix op(A) and of the matrix C.
int n; // The number of columns of matrix op(B) and of the matrix C.
int k; // The number of columns of matrix op(A) and the rows of the matrix op(B).
// First check some basic requirement on the parameters of the matrix multiplication.
if (a == null)
{
throw new ArgumentNullException("a");
}
if (b == null)
{
throw new ArgumentNullException("b");
}
if ((int) transposeA > 111 && (int) transposeB > 111)
{
if (rowsA != columnsB)
{
throw new ArgumentOutOfRangeException();
}
if (columnsA*rowsB != c.Length)
{
throw new ArgumentOutOfRangeException();
}
m = columnsA;
n = rowsB;
k = rowsA;
}
else if ((int) transposeA > 111)
{
if (rowsA != rowsB)
{
throw new ArgumentOutOfRangeException();
}
if (columnsA*columnsB != c.Length)
{
throw new ArgumentOutOfRangeException();
}
m = columnsA;
n = columnsB;
k = rowsA;
}
else if ((int) transposeB > 111)
{
if (columnsA != columnsB)
{
throw new ArgumentOutOfRangeException();
}
if (rowsA*rowsB != c.Length)
{
throw new ArgumentOutOfRangeException();
}
m = rowsA;
n = rowsB;
k = columnsA;
}
else
{
if (columnsA != rowsB)
{
throw new ArgumentOutOfRangeException();
}
if (rowsA*columnsB != c.Length)
{
throw new ArgumentOutOfRangeException();
}
m = rowsA;
n = columnsB;
k = columnsA;
}
if (alpha.IsZero() && beta.IsZero())
{
Array.Clear(c, 0, c.Length);
return;
}
// Check whether we will be overwriting any of our inputs and make copies if necessary.
// TODO - we can don't have to allocate a completely new matrix when x or y point to the same memory
// as result, we can do it on a row wise basis. We should investigate this.
Complex[] adata;
if (ReferenceEquals(a, c))
{
adata = (Complex[]) a.Clone();
}
else
{
adata = a;
}
Complex[] bdata;
if (ReferenceEquals(b, c))
{
bdata = (Complex[]) b.Clone();
}
else
{
bdata = b;
}
if (beta.IsZero())
{
Array.Clear(c, 0, c.Length);
}
else if (!beta.IsOne())
{
Control.LinearAlgebraProvider.ScaleArray(beta, c, c);
}
if (alpha.IsZero())
{
return;
}
CacheObliviousMatrixMultiply(transposeA, transposeB, alpha, adata, 0, 0, bdata, 0, 0, c, 0, 0, m, n, k, m, n, k, true);
}
/// <summary>
/// Multiples two matrices. <c>result = x * y</c>
/// </summary>
/// <param name="x">The x matrix.</param>
/// <param name="rowsX">The number of rows in the x matrix.</param>
/// <param name="columnsX">The number of columns in the x matrix.</param>
/// <param name="y">The y matrix.</param>
/// <param name="rowsY">The number of rows in the y matrix.</param>
/// <param name="columnsY">The number of columns in the y matrix.</param>
/// <param name="result">Where to store the result of the multiplication.</param>
/// <remarks>This is a simplified version of the BLAS GEMM routine with alpha
/// set to 1.0 and beta set to 0.0, and x and y are not transposed.</remarks>
public virtual void MatrixMultiply(Complex[] x, int rowsX, int columnsX, Complex[] y, int rowsY, int columnsY, Complex[] result)
{
// First check some basic requirement on the parameters of the matrix multiplication.
if (x == null)
{
throw new ArgumentNullException("x");
}
if (y == null)
{
throw new ArgumentNullException("y");
}
if (result == null)
{
throw new ArgumentNullException("result");
}
if (rowsX*columnsX != x.Length)
{
throw new ArgumentException("x.Length != xRows * xColumns");
}
if (rowsY*columnsY != y.Length)
{
throw new ArgumentException("y.Length != yRows * yColumns");
}
if (columnsX != rowsY)
{
throw new ArgumentException("xColumns != yRows");
}
if (rowsX*columnsY != result.Length)
{
throw new ArgumentException("xRows * yColumns != result.Length");
}
// Check whether we will be overwriting any of our inputs and make copies if necessary.
// TODO - we can don't have to allocate a completely new matrix when x or y point to the same memory
// as result, we can do it on a row wise basis. We should investigate this.
Complex[] xdata;
if (ReferenceEquals(x, result))
{
xdata = (Complex[]) x.Clone();
}
else
{
xdata = x;
}
Complex[] ydata;
if (ReferenceEquals(y, result))
{
ydata = (Complex[]) y.Clone();
}
else
{
ydata = y;
}
MatrixMultiplyWithUpdate(Transpose.DontTranspose, Transpose.DontTranspose, Complex.One, xdata, rowsX, columnsX, ydata, rowsY, columnsY, Complex.Zero, result);
}
