jiangchengfeiyi-xiaochengxu/node_modules/mathjs/lib/esm/function/algebra/sparse/csSymperm.js
2025-01-02 11:13:50 +08:00

93 lines
2.7 KiB
JavaScript

// Copyright (c) 2006-2024, Timothy A. Davis, All Rights Reserved.
// SPDX-License-Identifier: LGPL-2.1+
// https://github.com/DrTimothyAldenDavis/SuiteSparse/tree/dev/CSparse/Source
import { csCumsum } from './csCumsum.js';
import { factory } from '../../../utils/factory.js';
var name = 'csSymperm';
var dependencies = ['conj', 'SparseMatrix'];
export var createCsSymperm = /* #__PURE__ */factory(name, dependencies, _ref => {
var {
conj,
SparseMatrix
} = _ref;
/**
* Computes the symmetric permutation of matrix A accessing only
* the upper triangular part of A.
*
* C = P * A * P'
*
* @param {Matrix} a The A matrix
* @param {Array} pinv The inverse of permutation vector
* @param {boolean} values Process matrix values (true)
*
* @return {Matrix} The C matrix, C = P * A * P'
*/
return function csSymperm(a, pinv, values) {
// A matrix arrays
var avalues = a._values;
var aindex = a._index;
var aptr = a._ptr;
var asize = a._size;
// columns
var n = asize[1];
// C matrix arrays
var cvalues = values && avalues ? [] : null;
var cindex = []; // (nz)
var cptr = []; // (n + 1)
// variables
var i, i2, j, j2, p, p0, p1;
// create workspace vector
var w = []; // (n)
// count entries in each column of C
for (j = 0; j < n; j++) {
// column j of A is column j2 of C
j2 = pinv ? pinv[j] : j;
// loop values in column j
for (p0 = aptr[j], p1 = aptr[j + 1], p = p0; p < p1; p++) {
// row
i = aindex[p];
// skip lower triangular part of A
if (i > j) {
continue;
}
// row i of A is row i2 of C
i2 = pinv ? pinv[i] : i;
// column count of C
w[Math.max(i2, j2)]++;
}
}
// compute column pointers of C
csCumsum(cptr, w, n);
// loop columns
for (j = 0; j < n; j++) {
// column j of A is column j2 of C
j2 = pinv ? pinv[j] : j;
// loop values in column j
for (p0 = aptr[j], p1 = aptr[j + 1], p = p0; p < p1; p++) {
// row
i = aindex[p];
// skip lower triangular part of A
if (i > j) {
continue;
}
// row i of A is row i2 of C
i2 = pinv ? pinv[i] : i;
// C index for column j2
var q = w[Math.max(i2, j2)]++;
// update C index for entry q
cindex[q] = Math.min(i2, j2);
// check we need to process values
if (cvalues) {
cvalues[q] = i2 <= j2 ? avalues[p] : conj(avalues[p]);
}
}
}
// return C matrix
return new SparseMatrix({
values: cvalues,
index: cindex,
ptr: cptr,
size: [n, n]
});
};
});