package edu.emory.mathcs.csparsej.tdouble;
import edu.emory.mathcs.csparsej.tdouble.Dcs_common.Dcs;
import edu.emory.mathcs.csparsej.tdouble.Dcs_common.Dcss;
/**
* Symbolic Cholesky ordering and analysis.
*
* @author Piotr Wendykier (piotr.wendykier@gmail.com)
*
*/
public class Dcs_schol {
/**
* Ordering and symbolic analysis for a Cholesky factorization.
*
* @param order
* ordering option (0 or 1)
* @param A
* column-compressed matrix
* @return symbolic analysis for Cholesky, null on error
*/
public static Dcss cs_schol(int order, Dcs A) {
int n, c[], post[], P[];
Dcs C;
Dcss S;
if (!Dcs_util.CS_CSC(A))
return (null); /* check inputs */
n = A.n;
S = new Dcss(); /* allocate result S */
P = Dcs_amd.cs_amd(order, A); /* P = amd(A+A'), or natural */
S.pinv = Dcs_pinv.cs_pinv(P, n); /* find inverse permutation */
if (order != 0 && S.pinv == null)
return null;
C = Dcs_symperm.cs_symperm(A, S.pinv, false); /* C = spones(triu(A(P,P))) */
S.parent = Dcs_etree.cs_etree(C, false); /* find etree of C */
post = Dcs_post.cs_post(S.parent, n); /* postorder the etree */
c = Dcs_counts.cs_counts(C, S.parent, post, false); /* find column counts of chol(C) */
S.cp = new int[n + 1]; /* allocate result S.cp */
S.unz = S.lnz = Dcs_cumsum.cs_cumsum(S.cp, c, n); /* find column pointers for L */
return ((S.lnz >= 0) ? S : null);
}
}