simple-squiggle/node_modules/mathjs/lib/cjs/function/algebra/sparse/csSpsolve.js

96 lines
3.0 KiB
JavaScript

"use strict";
Object.defineProperty(exports, "__esModule", {
value: true
});
exports.createCsSpsolve = void 0;
var _csReach = require("./csReach.js");
var _factory = require("../../../utils/factory.js");
var name = 'csSpsolve';
var dependencies = ['divideScalar', 'multiply', 'subtract'];
var createCsSpsolve = /* #__PURE__ */(0, _factory.factory)(name, dependencies, function (_ref) {
var divideScalar = _ref.divideScalar,
multiply = _ref.multiply,
subtract = _ref.subtract;
/**
* The function csSpsolve() computes the solution to G * x = bk, where bk is the
* kth column of B. When lo is true, the function assumes G = L is lower triangular with the
* diagonal entry as the first entry in each column. When lo is true, the function assumes G = U
* is upper triangular with the diagonal entry as the last entry in each column.
*
* @param {Matrix} g The G matrix
* @param {Matrix} b The B matrix
* @param {Number} k The kth column in B
* @param {Array} xi The nonzero pattern xi[top] .. xi[n - 1], an array of size = 2 * n
* The first n entries is the nonzero pattern, the last n entries is the stack
* @param {Array} x The soluton to the linear system G * x = b
* @param {Array} pinv The inverse row permutation vector, must be null for L * x = b
* @param {boolean} lo The lower (true) upper triangular (false) flag
*
* @return {Number} The index for the nonzero pattern
*
* Reference: http://faculty.cse.tamu.edu/davis/publications.html
*/
return function csSpsolve(g, b, k, xi, x, pinv, lo) {
// g arrays
var gvalues = g._values;
var gindex = g._index;
var gptr = g._ptr;
var gsize = g._size; // columns
var n = gsize[1]; // b arrays
var bvalues = b._values;
var bindex = b._index;
var bptr = b._ptr; // vars
var p, p0, p1, q; // xi[top..n-1] = csReach(B(:,k))
var top = (0, _csReach.csReach)(g, b, k, xi, pinv); // clear x
for (p = top; p < n; p++) {
x[xi[p]] = 0;
} // scatter b
for (p0 = bptr[k], p1 = bptr[k + 1], p = p0; p < p1; p++) {
x[bindex[p]] = bvalues[p];
} // loop columns
for (var px = top; px < n; px++) {
// x array index for px
var j = xi[px]; // apply permutation vector (U x = b), j maps to column J of G
var J = pinv ? pinv[j] : j; // check column J is empty
if (J < 0) {
continue;
} // column value indeces in G, p0 <= p < p1
p0 = gptr[J];
p1 = gptr[J + 1]; // x(j) /= G(j,j)
x[j] = divideScalar(x[j], gvalues[lo ? p0 : p1 - 1]); // first entry L(j,j)
p = lo ? p0 + 1 : p0;
q = lo ? p1 : p1 - 1; // loop
for (; p < q; p++) {
// row
var i = gindex[p]; // x(i) -= G(i,j) * x(j)
x[i] = subtract(x[i], multiply(gvalues[p], x[j]));
}
} // return top of stack
return top;
};
});
exports.createCsSpsolve = createCsSpsolve;