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regression.js
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regression.js
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/**
* @license
*
* Regression.JS - Regression functions for javascript
* http://tom-alexander.github.com/regression-js/
*
* copyright(c) 2013 Tom Alexander
* Licensed under the MIT license.
*
**/
;(function() {
'use strict';
var gaussianElimination = function(a, o) {
var i = 0, j = 0, k = 0, maxrow = 0, tmp = 0, n = a.length - 1, x = new Array(o);
for (i = 0; i < n; i++) {
maxrow = i;
for (j = i + 1; j < n; j++) {
if (Math.abs(a[i][j]) > Math.abs(a[i][maxrow]))
maxrow = j;
}
for (k = i; k < n + 1; k++) {
tmp = a[k][i];
a[k][i] = a[k][maxrow];
a[k][maxrow] = tmp;
}
for (j = i + 1; j < n; j++) {
for (k = n; k >= i; k--) {
a[k][j] -= a[k][i] * a[i][j] / a[i][i];
}
}
}
for (j = n - 1; j >= 0; j--) {
tmp = 0;
for (k = j + 1; k < n; k++)
tmp += a[k][j] * x[k];
x[j] = (a[n][j] - tmp) / a[j][j];
}
return (x);
};
var methods = {
linear: function(data) {
var sum = [0, 0, 0, 0, 0], n = 0, results = [];
for (; n < data.length; n++) {
if (data[n][1] != null) {
sum[0] += data[n][0];
sum[1] += data[n][1];
sum[2] += data[n][0] * data[n][0];
sum[3] += data[n][0] * data[n][1];
sum[4] += data[n][1] * data[n][1];
}
}
var gradient = (n * sum[3] - sum[0] * sum[1]) / (n * sum[2] - sum[0] * sum[0]);
var intercept = (sum[1] / n) - (gradient * sum[0]) / n;
// var correlation = (n * sum[3] - sum[0] * sum[1]) / Math.sqrt((n * sum[2] - sum[0] * sum[0]) * (n * sum[4] - sum[1] * sum[1]));
for (var i = 0, len = data.length; i < len; i++) {
var coordinate = [data[i][0], data[i][0] * gradient + intercept];
results.push(coordinate);
}
var string = 'y = ' + Math.round(gradient*100) / 100 + 'x + ' + Math.round(intercept*100) / 100;
return {equation: [gradient, intercept], points: results, string: string};
},
exponential: function(data) {
var sum = [0, 0, 0, 0, 0, 0], n = 0, results = [];
for (len = data.length; n < len; n++) {
if (data[n][1] != null) {
sum[0] += data[n][0];
sum[1] += data[n][1];
sum[2] += data[n][0] * data[n][0] * data[n][1];
sum[3] += data[n][1] * Math.log(data[n][1]);
sum[4] += data[n][0] * data[n][1] * Math.log(data[n][1]);
sum[5] += data[n][0] * data[n][1];
}
}
var denominator = (sum[1] * sum[2] - sum[5] * sum[5]);
var A = Math.pow(Math.E, (sum[2] * sum[3] - sum[5] * sum[4]) / denominator);
var B = (sum[1] * sum[4] - sum[5] * sum[3]) / denominator;
for (var i = 0, len = data.length; i < len; i++) {
var coordinate = [data[i][0], A * Math.pow(Math.E, B * data[i][0])];
results.push(coordinate);
}
var string = 'y = ' + Math.round(A*100) / 100 + 'e^(' + Math.round(B*100) / 100 + 'x)';
return {equation: [A, B], points: results, string: string};
},
logarithmic: function(data) {
var sum = [0, 0, 0, 0], n = 0, results = [];
for (len = data.length; n < len; n++) {
if (data[n][1] != null) {
sum[0] += Math.log(data[n][0]);
sum[1] += data[n][1] * Math.log(data[n][0]);
sum[2] += data[n][1];
sum[3] += Math.pow(Math.log(data[n][0]), 2);
}
}
var B = (n * sum[1] - sum[2] * sum[0]) / (n * sum[3] - sum[0] * sum[0]);
var A = (sum[2] - B * sum[0]) / n;
for (var i = 0, len = data.length; i < len; i++) {
var coordinate = [data[i][0], A + B * Math.log(data[i][0])];
results.push(coordinate);
}
var string = 'y = ' + Math.round(A*100) / 100 + ' + ' + Math.round(B*100) / 100 + ' ln(x)';
return {equation: [A, B], points: results, string: string};
},
power: function(data) {
var sum = [0, 0, 0, 0], n = 0, results = [];
for (len = data.length; n < len; n++) {
if (data[n][1] != null) {
sum[0] += Math.log(data[n][0]);
sum[1] += Math.log(data[n][1]) * Math.log(data[n][0]);
sum[2] += Math.log(data[n][1]);
sum[3] += Math.pow(Math.log(data[n][0]), 2);
}
}
var B = (n * sum[1] - sum[2] * sum[0]) / (n * sum[3] - sum[0] * sum[0]);
var A = Math.pow(Math.E, (sum[2] - B * sum[0]) / n);
for (var i = 0, len = data.length; i < len; i++) {
var coordinate = [data[i][0], A * Math.pow(data[i][0] , B)];
results.push(coordinate);
}
var string = 'y = ' + Math.round(A*100) / 100 + 'x^' + Math.round(B*100) / 100;
return {equation: [A, B], points: results, string: string};
},
polynomial: function(data, order) {
if(typeof order == 'undefined'){
order = 2;
}
var lhs = [], rhs = [], results = [], a = 0, b = 0, i = 0, k = order + 1;
for (; i < k; i++) {
for (var l = 0, len = data.length; l < len; l++) {
if (data[l][1] != null) {
a += Math.pow(data[l][0], i) * data[l][1];
}
}
lhs.push(a), a = 0;
var c = [];
for (var j = 0; j < k; j++) {
for (var l = 0, len = data.length; l < len; l++) {
if (data[l][1] != null) {
b += Math.pow(data[l][0], i + j);
}
}
c.push(b), b = 0;
}
rhs.push(c);
}
rhs.push(lhs);
var equation = gaussianElimination(rhs, k);
for (var i = 0, len = data.length; i < len; i++) {
var answer = 0;
for (var w = 0; w < equation.length; w++) {
answer += equation[w] * Math.pow(data[i][0], w);
}
results.push([data[i][0], answer]);
}
var string = 'y = ';
for(var i = equation.length-1; i >= 0; i--){
if(i > 1) string += Math.round(equation[i] * Math.pow(10, i)) / Math.pow(10, i) + 'x^' + i + ' + ';
else if (i == 1) string += Math.round(equation[i]*100) / 100 + 'x' + ' + ';
else string += Math.round(equation[i]*100) / 100;
}
return {equation: equation, points: results, string: string};
},
lastvalue: function(data) {
var results = [];
var lastvalue = null;
for (var i = 0; i < data.length; i++) {
if (data[i][1]) {
lastvalue = data[i][1];
results.push([data[i][0], data[i][1]]);
}
else {
results.push([data[i][0], lastvalue]);
}
}
return {equation: [lastvalue], points: results, string: "" + lastvalue};
}
};
var regression = (function(method, data, order) {
if (typeof method == 'string') {
return methods[method](data, order);
}
});
if (typeof exports !== 'undefined') {
module.exports = regression;
} else {
window.regression = regression;
}
}());