feat:node-modules

node_modules/mathjs/lib/esm/function/algebra/sparse/csSymperm.js

@@ -0,0 +1,93 @@
+// 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]
+    });
+  };
+});