package edu.emory.mathcs.csparsej.tfloat;
import edu.emory.mathcs.csparsej.tfloat.Scs_common.Scs;
import edu.emory.mathcs.csparsej.tfloat.Scs_common.Scsn;
import edu.emory.mathcs.csparsej.tfloat.Scs_common.Scss;
/**
* Solve Ax=b using sparse LU factorization.
*
* @author Piotr Wendykier (piotr.wendykier@gmail.com)
*
*/
public class Scs_lusol {
/**
* Solves Ax=b, where A is square and nonsingular. b overwritten with
* solution. Partial pivoting if tol = 1.f
*
* @param order
* ordering method to use (0 to 3)
* @param A
* column-compressed matrix
* @param b
* size n, b on input, x on output
* @param tol
* partial pivoting tolerance
* @return true if successful, false on error
*/
public static boolean cs_lusol(int order, Scs A, float[] b, float tol) {
float[] x;
Scss S;
Scsn N;
int n;
boolean ok;
if (!Scs_util.CS_CSC(A) || b == null)
return (false); /* check inputs */
n = A.n;
S = Scs_sqr.cs_sqr(order, A, false); /* ordering and symbolic analysis */
N = Scs_lu.cs_lu(A, S, tol); /* numeric LU factorization */
x = new float[n]; /* get workspace */
ok = (S != null && N != null);
if (ok) {
Scs_ipvec.cs_ipvec(N.pinv, b, x, n); /* x = b(p) */
Scs_lsolve.cs_lsolve(N.L, x); /* x = L\x */
Scs_usolve.cs_usolve(N.U, x); /* x = U\x */
Scs_ipvec.cs_ipvec(S.q, x, b, n); /* b(q) = x */
}
return (ok);
}
}