private static SVDRec svdLAS2(SMat A)
{
int ibeta, it, irnd, machep, negep, n, steps, nsig, neig;
double kappa = 1e-6;
double[] las2end = new double[2] { -1.0e-30, 1.0e-30 };
double[] ritz, bnd;
double[][] wptr = new double[10][];
svdResetCounters();
int dimensions = A.rows;
if (A.cols < dimensions) dimensions = A.cols;
int iterations = dimensions;
// Check parameters
if (check_parameters(A, dimensions, iterations, las2end[0], las2end[1]) > 0) return null;
// If A is wide, the SVD is computed on its transpose for speed.
bool transpose = false;
if (A.cols >= A.rows * 1.2)
{
//Console.WriteLine("TRANSPOSING THE MATRIX FOR SPEED\n");
transpose = true;
A = svdTransposeS(A);
}
n = A.cols;
// Compute machine precision
ibeta = it = irnd = machep = negep = 0;
machar(ref ibeta, ref it, ref irnd, ref machep, ref negep);
eps1 = eps * Math.Sqrt((double)n);
reps = Math.Sqrt(eps);
eps34 = reps * Math.Sqrt(reps);
//Console.WriteLine("Machine precision {0} {1} {2} {3} {4}", ibeta, it, irnd, machep, negep);
// Allocate temporary space.
wptr[0] = new double[n];
for (int i = 0; i < n; ++i) wptr[0][i] = 0.0;
wptr[1] = new double[n];
wptr[2] = new double[n];
wptr[3] = new double[n];
wptr[4] = new double[n];
wptr[5] = new double[n];
wptr[6] = new double[iterations];
wptr[7] = new double[iterations];
wptr[8] = new double[iterations];
wptr[9] = new double[iterations + 1];
ritz = new double[iterations + 1];
for (int i = 0; i < iterations + 1; ++i) ritz[0] = 0.0;
bnd = new double[iterations + 1];
for (int i = 0; i < iterations + 1; ++i) bnd[0] = 0.0;
LanStore = new double[iterations + MAXLL][];
for (int i = 0; i < iterations + MAXLL; ++i)
{
LanStore[i] = null;
}
OPBTemp = new double[A.rows];
// Actually run the lanczos thing:
neig = 0;
steps = lanso(A, iterations, dimensions, las2end[0], las2end[1], ritz, bnd, wptr, ref neig, n);
//Console.WriteLine("NUMBER OF LANCZOS STEPS {0}", steps + 1);
//Console.WriteLine("RITZ VALUES STABILIZED = RANK {0}", neig);
kappa = svd_dmax(Math.Abs(kappa), eps34);
SVDRec R = new SVDRec();
R.d = dimensions;
DMat Tmp1 = new DMat();
Tmp1.rows = R.d;
Tmp1.cols = A.rows;
Tmp1.value = new double[Tmp1.rows][];
for (int mm = 0; mm < Tmp1.rows; ++mm)
{
Tmp1.value[mm] = new double[Tmp1.cols];
for (int j = 0; j < Tmp1.cols; ++j)
{
Tmp1.value[mm][j] = 0.0;
}
}
R.Ut = Tmp1;
R.S = new double[R.d];
for (int k = 0; k < R.d; ++k)
{
R.S[k] = 0.0;
}
DMat Tmp2 = new DMat();
Tmp2.rows = R.d;
Tmp2.cols = A.cols;
Tmp2.value = new double[Tmp2.rows][];
for (int mm = 0; mm < Tmp2.rows; ++mm)
{
Tmp2.value[mm] = new double[Tmp2.cols];
for (int j = 0; j < Tmp2.cols; ++j)
{
Tmp2.value[mm][j] = 0.0;
}
}
R.Vt = Tmp2;
nsig = ritvec(n, A, R, kappa, ritz, bnd, wptr[6], wptr[9], wptr[5], steps, neig);
// This swaps and transposes the singular matrices if A was transposed.
if (transpose)
{
DMat T;
T = R.Ut;
R.Ut = R.Vt;
R.Vt = T;
}
return R;
}
private static void svdWriteDenseMatrix(DMat D, string filename)
{
using (FileStream stream = new FileStream(filename, FileMode.Create))
{
using (BinaryWriter writer = new BinaryWriter(stream))
{
writer.Write(System.Net.IPAddress.HostToNetworkOrder(D.rows));
writer.Write(System.Net.IPAddress.HostToNetworkOrder(D.cols));
for (int k = 0; k < D.rows; ++k)
{
for (int j = 0; j < D.cols; ++j)
{
float buf = (float)(D.value[k][j]);
byte[] b = BitConverter.GetBytes(buf);
int x = BitConverter.ToInt32(b, 0);
writer.Write(System.Net.IPAddress.HostToNetworkOrder(x));
}
}
writer.Flush();
writer.Close();
}
stream.Close();
}
}