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Update science.js to 1.7.0: fix science.stats.kde.
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‎lib/science/science.js‎

Lines changed: 221 additions & 1 deletion
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@@ -1,5 +1,225 @@
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(function(){science = {version: "0.0.1"}; // semver
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(function(){science = {version: "1.7.0"}; // semver
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science.ascending = function(a, b) {
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return a - b;
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};
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// Euler's constant.
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science.EULER = .5772156649015329;
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// Compute exp(x) - 1 accurately for small x.
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science.expm1 = function(x) {
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return (x < 1e-5 && x > -1e-5) ? x + .5 * x * x : Math.exp(x) - 1;
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};
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science.functor = function(v) {
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return typeof v === "function" ? v : function() { return v; };
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};
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// Based on:
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// http://www.johndcook.com/blog/2010/06/02/whats-so-hard-about-finding-a-hypotenuse/
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science.hypot = function(x, y) {
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x = Math.abs(x);
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y = Math.abs(y);
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var max,
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min;
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if (x > y) { max = x; min = y; }
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else { max = y; min = x; }
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var r = min / max;
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return max * Math.sqrt(1 + r * r);
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};
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science.quadratic = function() {
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var complex = false;
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function quadratic(a, b, c) {
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var d = b * b - 4 * a * c;
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if (d > 0) {
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d = Math.sqrt(d) / (2 * a);
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return complex
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? [{r: -b - d, i: 0}, {r: -b + d, i: 0}]
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: [-b - d, -b + d];
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} else if (d === 0) {
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d = -b / (2 * a);
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return complex ? [{r: d, i: 0}] : [d];
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} else {
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if (complex) {
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d = Math.sqrt(-d) / (2 * a);
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return [
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{r: -b, i: -d},
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{r: -b, i: d}
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];
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}
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return [];
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}
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}
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quadratic.complex = function(x) {
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if (!arguments.length) return complex;
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complex = x;
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return quadratic;
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};
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return quadratic;
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};
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// Constructs a multi-dimensional array filled with zeroes.
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science.zeroes = function(n) {
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var i = -1,
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a = [];
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if (arguments.length === 1)
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while (++i < n)
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a[i] = 0;
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else
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while (++i < n)
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a[i] = science.zeroes.apply(
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this, Array.prototype.slice.call(arguments, 1));
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return a;
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};
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science.vector = {};
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science.vector.cross = function(a, b) {
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// TODO how to handle non-3D vectors?
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// TODO handle 7D vectors?
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return [
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a[1] * b[2] - a[2] * b[1],
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a[2] * b[0] - a[0] * b[2],
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a[0] * b[1] - a[1] * b[0]
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];
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};
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science.vector.dot = function(a, b) {
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var s = 0,
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i = -1,
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n = Math.min(a.length, b.length);
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while (++i < n) s += a[i] * b[i];
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return s;
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};
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science.vector.length = function(p) {
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return Math.sqrt(science.vector.dot(p, p));
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};
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science.vector.normalize = function(p) {
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var length = science.vector.length(p);
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return p.map(function(d) { return d / length; });
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};
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// 4x4 matrix determinant.
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science.vector.determinant = function(matrix) {
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var m = matrix[0].concat(matrix[1]).concat(matrix[2]).concat(matrix[3]);
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return (
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m[12] * m[9] * m[6] * m[3] - m[8] * m[13] * m[6] * m[3] -
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m[12] * m[5] * m[10] * m[3] + m[4] * m[13] * m[10] * m[3] +
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m[8] * m[5] * m[14] * m[3] - m[4] * m[9] * m[14] * m[3] -
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m[12] * m[9] * m[2] * m[7] + m[8] * m[13] * m[2] * m[7] +
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m[12] * m[1] * m[10] * m[7] - m[0] * m[13] * m[10] * m[7] -
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m[8] * m[1] * m[14] * m[7] + m[0] * m[9] * m[14] * m[7] +
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m[12] * m[5] * m[2] * m[11] - m[4] * m[13] * m[2] * m[11] -
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m[12] * m[1] * m[6] * m[11] + m[0] * m[13] * m[6] * m[11] +
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m[4] * m[1] * m[14] * m[11] - m[0] * m[5] * m[14] * m[11] -
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m[8] * m[5] * m[2] * m[15] + m[4] * m[9] * m[2] * m[15] +
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m[8] * m[1] * m[6] * m[15] - m[0] * m[9] * m[6] * m[15] -
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m[4] * m[1] * m[10] * m[15] + m[0] * m[5] * m[10] * m[15]);
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};
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// Performs in-place Gauss-Jordan elimination.
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//
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// Based on Jarno Elonen's Python version (public domain):
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// http://elonen.iki.fi/code/misc-notes/python-gaussj/index.html
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science.vector.gaussjordan = function(m, eps) {
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if (!eps) eps = 1e-10;
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var h = m.length,
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w = m[0].length,
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y = -1,
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y2,
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x;
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while (++y < h) {
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var maxrow = y;
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// Find max pivot.
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y2 = y; while (++y2 < h) {
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if (Math.abs(m[y2][y]) > Math.abs(m[maxrow][y]))
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maxrow = y2;
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}
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// Swap.
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var tmp = m[y];
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m[y] = m[maxrow];
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m[maxrow] = tmp;
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// Singular?
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if (Math.abs(m[y][y]) <= eps) return false;
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// Eliminate column y.
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y2 = y; while (++y2 < h) {
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var c = m[y2][y] / m[y][y];
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x = y - 1; while (++x < w) {
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m[y2][x] -= m[y][x] * c;
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}
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}
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}
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// Backsubstitute.
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y = h; while (--y >= 0) {
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var c = m[y][y];
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y2 = -1; while (++y2 < y) {
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x = w; while (--x >= y) {
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m[y2][x] -= m[y][x] * m[y2][y] / c;
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}
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}
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m[y][y] /= c;
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// Normalize row y.
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x = h - 1; while (++x < w) {
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m[y][x] /= c;
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}
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}
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return true;
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};
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// Find matrix inverse using Gauss-Jordan.
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science.vector.inverse = function(m) {
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var n = m.length
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i = -1;
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// Check if the matrix is square.
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if (n !== m[0].length) return;
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// Augment with identity matrix I to get AI.
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m = m.map(function(row, i) {
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var identity = new Array(n),
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j = -1;
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while (++j < n) identity[j] = i === j ? 1 : 0;
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return row.concat(identity);
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});
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// Compute IA^-1.
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science.vector.gaussjordan(m);
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// Remove identity matrix I to get A^-1.
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while (++i < n) {
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m[i] = m[i].slice(n);
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}
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return m;
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};
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science.vector.multiply = function(a, b) {
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var m = a.length,
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n = b[0].length,
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p = b.length,
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i = -1,
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j,
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k;
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if (p !== a[0].length) throw {"error": "columns(a) != rows(b); " + a[0].length + " != " + p};
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var ab = new Array(m);
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while (++i < m) {
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ab[i] = new Array(n);
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j = -1; while(++j < n) {
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var s = 0;
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k = -1; while (++k < p) s += a[i][k] * b[k][j];
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ab[i][j] = s;
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}
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}
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return ab;
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};
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science.vector.transpose = function(a) {
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var m = a.length,
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n = a[0].length,
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i = -1,
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j,
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b = new Array(n);
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while (++i < n) {
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b[i] = new Array(m);
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j = -1; while (++j < m) b[i][j] = a[j][i];
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}
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return b;
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};
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})()

‎lib/science/science.lin.js‎

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(function(){science.lin = {};
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/**
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* Solves tridiagonal systems of linear equations.
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*
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* Source: http://en.wikipedia.org/wiki/Tridiagonal_matrix_algorithm
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*
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* @param {number[]} a
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* @param {number[]} b
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* @param {number[]} c
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* @param {number[]} d
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* @param {number[]} x
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* @param {number} n
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*/
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science.lin.tridag = function(a, b, c, d, x, n) {
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var i,
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m;
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for (i = 1; i < n; i++) {
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m = a[i] / b[i - 1];
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b[i] -= m * c[i - 1];
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d[i] -= m * d[i - 1];
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}
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x[n - 1] = d[n - 1] / b[n - 1];
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for (i = n - 2; i >= 0; i--) {
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x[i] = (d[i] - c[i] * x[i + 1]) / b[i];
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}
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};
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})()

‎lib/science/science.lin.min.js‎

Lines changed: 1 addition & 0 deletions
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‎lib/science/science.min.js‎

Lines changed: 1 addition & 1 deletion
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