(function(){science = {version: "1.7.0"}; // semver science.ascending = function(a, b) { return a - b; }; // Euler's constant. science.EULER = .5772156649015329; // Compute exp(x) - 1 accurately for small x. science.expm1 = function(x) { return (x < 1e-5 && x > -1e-5) ? x + .5 * x * x : Math.exp(x) - 1; }; science.functor = function(v) { return typeof v === "function" ? v : function() { return v; }; }; // Based on: // http://www.johndcook.com/blog/2010/06/02/whats-so-hard-about-finding-a-hypotenuse/ science.hypot = function(x, y) { x = Math.abs(x); y = Math.abs(y); var max, min; if (x > y) { max = x; min = y; } else { max = y; min = x; } var r = min / max; return max * Math.sqrt(1 + r * r); }; science.quadratic = function() { var complex = false; function quadratic(a, b, c) { var d = b * b - 4 * a * c; if (d > 0) { d = Math.sqrt(d) / (2 * a); return complex ? [{r: -b - d, i: 0}, {r: -b + d, i: 0}] : [-b - d, -b + d]; } else if (d === 0) { d = -b / (2 * a); return complex ? [{r: d, i: 0}] : [d]; } else { if (complex) { d = Math.sqrt(-d) / (2 * a); return [ {r: -b, i: -d}, {r: -b, i: d} ]; } return []; } } quadratic.complex = function(x) { if (!arguments.length) return complex; complex = x; return quadratic; }; return quadratic; }; // Constructs a multi-dimensional array filled with zeroes. science.zeroes = function(n) { var i = -1, a = []; if (arguments.length === 1) while (++i < n) a[i] = 0; else while (++i < n) a[i] = science.zeroes.apply( this, Array.prototype.slice.call(arguments, 1)); return a; }; science.vector = {}; science.vector.cross = function(a, b) { // TODO how to handle non-3D vectors? // TODO handle 7D vectors? return [ a[1] * b[2] - a[2] * b[1], a[2] * b[0] - a[0] * b[2], a[0] * b[1] - a[1] * b[0] ]; }; science.vector.dot = function(a, b) { var s = 0, i = -1, n = Math.min(a.length, b.length); while (++i < n) s += a[i] * b[i]; return s; }; science.vector.length = function(p) { return Math.sqrt(science.vector.dot(p, p)); }; science.vector.normalize = function(p) { var length = science.vector.length(p); return p.map(function(d) { return d / length; }); }; // 4x4 matrix determinant. science.vector.determinant = function(matrix) { var m = matrix[0].concat(matrix[1]).concat(matrix[2]).concat(matrix[3]); return ( m[12] * m[9] * m[6] * m[3] - m[8] * m[13] * m[6] * m[3] - m[12] * m[5] * m[10] * m[3] + m[4] * m[13] * m[10] * m[3] + m[8] * m[5] * m[14] * m[3] - m[4] * m[9] * m[14] * m[3] - m[12] * m[9] * m[2] * m[7] + m[8] * m[13] * m[2] * m[7] + m[12] * m[1] * m[10] * m[7] - m[0] * m[13] * m[10] * m[7] - m[8] * m[1] * m[14] * m[7] + m[0] * m[9] * m[14] * m[7] + m[12] * m[5] * m[2] * m[11] - m[4] * m[13] * m[2] * m[11] - m[12] * m[1] * m[6] * m[11] + m[0] * m[13] * m[6] * m[11] + m[4] * m[1] * m[14] * m[11] - m[0] * m[5] * m[14] * m[11] - m[8] * m[5] * m[2] * m[15] + m[4] * m[9] * m[2] * m[15] + m[8] * m[1] * m[6] * m[15] - m[0] * m[9] * m[6] * m[15] - m[4] * m[1] * m[10] * m[15] + m[0] * m[5] * m[10] * m[15]); }; // Performs in-place Gauss-Jordan elimination. // // Based on Jarno Elonen's Python version (public domain): // http://elonen.iki.fi/code/misc-notes/python-gaussj/index.html science.vector.gaussjordan = function(m, eps) { if (!eps) eps = 1e-10; var h = m.length, w = m[0].length, y = -1, y2, x; while (++y < h) { var maxrow = y; // Find max pivot. y2 = y; while (++y2 < h) { if (Math.abs(m[y2][y]) > Math.abs(m[maxrow][y])) maxrow = y2; } // Swap. var tmp = m[y]; m[y] = m[maxrow]; m[maxrow] = tmp; // Singular? if (Math.abs(m[y][y]) <= eps) return false; // Eliminate column y. y2 = y; while (++y2 < h) { var c = m[y2][y] / m[y][y]; x = y - 1; while (++x < w) { m[y2][x] -= m[y][x] * c; } } } // Backsubstitute. y = h; while (--y >= 0) { var c = m[y][y]; y2 = -1; while (++y2 < y) { x = w; while (--x >= y) { m[y2][x] -= m[y][x] * m[y2][y] / c; } } m[y][y] /= c; // Normalize row y. x = h - 1; while (++x < w) { m[y][x] /= c; } } return true; }; // Find matrix inverse using Gauss-Jordan. science.vector.inverse = function(m) { var n = m.length i = -1; // Check if the matrix is square. if (n !== m[0].length) return; // Augment with identity matrix I to get AI. m = m.map(function(row, i) { var identity = new Array(n), j = -1; while (++j < n) identity[j] = i === j ? 1 : 0; return row.concat(identity); }); // Compute IA^-1. science.vector.gaussjordan(m); // Remove identity matrix I to get A^-1. while (++i < n) { m[i] = m[i].slice(n); } return m; }; science.vector.multiply = function(a, b) { var m = a.length, n = b[0].length, p = b.length, i = -1, j, k; if (p !== a[0].length) throw {"error": "columns(a) != rows(b); " + a[0].length + " != " + p}; var ab = new Array(m); while (++i < m) { ab[i] = new Array(n); j = -1; while(++j < n) { var s = 0; k = -1; while (++k < p) s += a[i][k] * b[k][j]; ab[i][j] = s; } } return ab; }; science.vector.transpose = function(a) { var m = a.length, n = a[0].length, i = -1, j, b = new Array(n); while (++i < n) { b[i] = new Array(m); j = -1; while (++j < m) b[i][j] = a[j][i]; } return b; }; })()