simple-squiggle/node_modules/mathjs/lib/cjs/function/matrix/det.js

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"use strict";
Object.defineProperty(exports, "__esModule", {
value: true
});
exports.createDet = void 0;
var _is = require("../../utils/is.js");
var _object = require("../../utils/object.js");
var _string = require("../../utils/string.js");
var _factory = require("../../utils/factory.js");
var name = 'det';
var dependencies = ['typed', 'matrix', 'subtract', 'multiply', 'unaryMinus', 'lup'];
var createDet = /* #__PURE__ */(0, _factory.factory)(name, dependencies, function (_ref) {
var typed = _ref.typed,
matrix = _ref.matrix,
subtract = _ref.subtract,
multiply = _ref.multiply,
unaryMinus = _ref.unaryMinus,
lup = _ref.lup;
/**
* Calculate the determinant of a matrix.
*
* Syntax:
*
* math.det(x)
*
* Examples:
*
* math.det([[1, 2], [3, 4]]) // returns -2
*
* const A = [
* [-2, 2, 3],
* [-1, 1, 3],
* [2, 0, -1]
* ]
* math.det(A) // returns 6
*
* See also:
*
* inv
*
* @param {Array | Matrix} x A matrix
* @return {number} The determinant of `x`
*/
return typed(name, {
any: function any(x) {
return (0, _object.clone)(x);
},
'Array | Matrix': function det(x) {
var size;
if ((0, _is.isMatrix)(x)) {
size = x.size();
} else if (Array.isArray(x)) {
x = matrix(x);
size = x.size();
} else {
// a scalar
size = [];
}
switch (size.length) {
case 0:
// scalar
return (0, _object.clone)(x);
case 1:
// vector
if (size[0] === 1) {
return (0, _object.clone)(x.valueOf()[0]);
} else {
throw new RangeError('Matrix must be square ' + '(size: ' + (0, _string.format)(size) + ')');
}
case 2:
{
// two dimensional array
var rows = size[0];
var cols = size[1];
if (rows === cols) {
return _det(x.clone().valueOf(), rows, cols);
} else {
throw new RangeError('Matrix must be square ' + '(size: ' + (0, _string.format)(size) + ')');
}
}
default:
// multi dimensional array
throw new RangeError('Matrix must be two dimensional ' + '(size: ' + (0, _string.format)(size) + ')');
}
}
});
/**
* Calculate the determinant of a matrix
* @param {Array[]} matrix A square, two dimensional matrix
* @param {number} rows Number of rows of the matrix (zero-based)
* @param {number} cols Number of columns of the matrix (zero-based)
* @returns {number} det
* @private
*/
function _det(matrix, rows, cols) {
if (rows === 1) {
// this is a 1 x 1 matrix
return (0, _object.clone)(matrix[0][0]);
} else if (rows === 2) {
// this is a 2 x 2 matrix
// the determinant of [a11,a12;a21,a22] is det = a11*a22-a21*a12
return subtract(multiply(matrix[0][0], matrix[1][1]), multiply(matrix[1][0], matrix[0][1]));
} else {
// Compute the LU decomposition
var decomp = lup(matrix); // The determinant is the product of the diagonal entries of U (and those of L, but they are all 1)
var det = decomp.U[0][0];
for (var _i = 1; _i < rows; _i++) {
det = multiply(det, decomp.U[_i][_i]);
} // The determinant will be multiplied by 1 or -1 depending on the parity of the permutation matrix.
// This can be determined by counting the cycles. This is roughly a linear time algorithm.
var evenCycles = 0;
var i = 0;
var visited = [];
while (true) {
while (visited[i]) {
i++;
}
if (i >= rows) break;
var j = i;
var cycleLen = 0;
while (!visited[decomp.p[j]]) {
visited[decomp.p[j]] = true;
j = decomp.p[j];
cycleLen++;
}
if (cycleLen % 2 === 0) {
evenCycles++;
}
}
return evenCycles % 2 === 0 ? det : unaryMinus(det);
}
}
});
exports.createDet = createDet;