static int MatDecompose(cv.Mat m, out cv.Mat lum, out int[] perm)
{
// Crout's LU decomposition for matrix determinant and inverse
// stores combined lower & upper in lum[][]
// stores row permuations into perm[]
// returns +1 or -1 according to even or odd number of row permutations
// lower gets dummy 1.0s on diagonal (0.0s above)
// upper gets lum values on diagonal (0.0s below)
int toggle = +1; // even (+1) or odd (-1) row permutatuions
int n = m.Rows;
// make a copy of m[][] into result lum[][]
lum = m.Clone();
// make perm[]
perm = new int[n];
for (int i = 0; i < n; ++i)
{
perm[i] = i;
}
for (int j = 0; j < n - 1; ++j) // process by column. note n-1
{
double max = Math.Abs(lum.At <double>(j, j));
int piv = j;
for (int i = j + 1; i < n; ++i) // find pivot index
{
double xij = Math.Abs(lum.At <double>(i, j));
if (xij > max)
{
max = xij;
piv = i;
}
} // i
if (piv != j)
{
cv.Mat tmp = lum.Row(piv).Clone(); // swap rows j, piv
lum.Row(j).CopyTo(lum.Row(piv));
tmp.CopyTo(lum.Row(j));
int t = perm[piv]; // swap perm elements
perm[piv] = perm[j];
perm[j] = t;
toggle = -toggle;
}
double xjj = lum.At <double>(j, j);
if (xjj != 0.0)
{
for (int i = j + 1; i < n; ++i)
{
double xij = lum.At <double>(i, j) / xjj;
lum.Set <double>(i, j, xij);
for (int k = j + 1; k < n; ++k)
{
lum.Set <double>(i, k, lum.At <double>(i, k) - xij * lum.At <double>(j, k));
}
}
}
}
return(toggle); // for determinant
}
