Comments (3)
This will not be part of CSparse.NET and as @epsi1on pointed out, computing the inverse of a sparse matrix isn't a good idea. If you need to compute the inverse explicitly, use one of the factorizations, for example SparseLU
:
using CSparse;
using CSparse.Double.Factorization;
using CSparse.Storage;
using System;
public static class CSparseExtensions
{
public static CompressedColumnStorage<double> Inverse(
this CompressedColumnStorage<double> A)
{
int size = A.RowCount;
if (A.ColumnCount != size)
{
throw new ArgumentException("Matrix must be square.");
}
var lu = SparseLU.Create(A, ColumnOrdering.MinimumDegreeAtPlusA, 1.0);
var b = new double[size];
var x = new double[size];
// Result will most likely be dense. I use a sparse storage here
// just for simplicity.
var inverse = new CoordinateStorage<double>(size, size, size * size);
for (int i = 0; i < size; i++)
{
b[i] = 1.0;
lu.Solve(b, x);
for (int j = 0; j < size; j++)
{
inverse.At(j, i, x[j]);
}
b[i] = 0.0;
}
return Converter.ToCompressedColumnStorage(inverse);
}
}
from csparse.net.
I think the inverse of a sparse matrix can be a dense matrix, so you maybe need to convert your sparse matrix to a dense matrix and then use a dense matrix library (like Math.NET) for inverting.
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👍
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