| 1 | /** |
| 2 | * @license |
| 3 | * Copyright 2013 David Eberlein (david.eberlein@ch.sauter-bc.com) |
| 4 | * MIT-licensed (http://opensource.org/licenses/MIT) |
| 5 | */ |
| 6 | |
| 7 | /** |
| 8 | * @fileoverview DataHandler implementation for the combination |
| 9 | * of error bars and fractions options. |
| 10 | * @author David Eberlein (david.eberlein@ch.sauter-bc.com) |
| 11 | */ |
| 12 | |
| 13 | (function() { |
| 14 | |
| 15 | /*global Dygraph:false */ |
| 16 | "use strict"; |
| 17 | |
| 18 | Dygraph.DataHandlers.FractionsBarsHandler = Dygraph.DataHandler(); |
| 19 | var FractionsBarsHandler = Dygraph.DataHandlers.FractionsBarsHandler; |
| 20 | FractionsBarsHandler.prototype = new Dygraph.DataHandlers.BarsHandler(); |
| 21 | |
| 22 | // errorBars |
| 23 | FractionsBarsHandler.prototype.extractSeries = function(rawData, i, options) { |
| 24 | // TODO(danvk): pre-allocate series here. |
| 25 | var series = []; |
| 26 | var x, y, point, num, den, value, stddev, variance; |
| 27 | var mult = 100.0; |
| 28 | var sigma = options.get("sigma"); |
| 29 | var logScale = options.get('logscale'); |
| 30 | for ( var j = 0; j < rawData.length; j++) { |
| 31 | x = rawData[j][0]; |
| 32 | point = rawData[j][i]; |
| 33 | if (logScale && point !== null) { |
| 34 | // On the log scale, points less than zero do not exist. |
| 35 | // This will create a gap in the chart. |
| 36 | if (point[0] <= 0 || point[1] <= 0) { |
| 37 | point = null; |
| 38 | } |
| 39 | } |
| 40 | // Extract to the unified data format. |
| 41 | if (point !== null) { |
| 42 | num = point[0]; |
| 43 | den = point[1]; |
| 44 | if (num !== null && !isNaN(num)) { |
| 45 | value = den ? num / den : 0.0; |
| 46 | stddev = den ? sigma * Math.sqrt(value * (1 - value) / den) : 1.0; |
| 47 | variance = mult * stddev; |
| 48 | y = mult * value; |
| 49 | // preserve original values in extras for further filtering |
| 50 | series.push([ x, y, [ y - variance, y + variance, num, den ] ]); |
| 51 | } else { |
| 52 | series.push([ x, num, [ num, num, num, den ] ]); |
| 53 | } |
| 54 | } else { |
| 55 | series.push([ x, null, [ null, null, null, null ] ]); |
| 56 | } |
| 57 | } |
| 58 | return series; |
| 59 | }; |
| 60 | |
| 61 | FractionsBarsHandler.prototype.rollingAverage = function(originalData, rollPeriod, |
| 62 | options) { |
| 63 | rollPeriod = Math.min(rollPeriod, originalData.length); |
| 64 | var rollingData = []; |
| 65 | var sigma = options.get("sigma"); |
| 66 | var wilsonInterval = options.get("wilsonInterval"); |
| 67 | |
| 68 | var low, high, i, stddev; |
| 69 | var num = 0; |
| 70 | var den = 0; // numerator/denominator |
| 71 | var mult = 100.0; |
| 72 | for (i = 0; i < originalData.length; i++) { |
| 73 | num += originalData[i][2][2]; |
| 74 | den += originalData[i][2][3]; |
| 75 | if (i - rollPeriod >= 0) { |
| 76 | num -= originalData[i - rollPeriod][2][2]; |
| 77 | den -= originalData[i - rollPeriod][2][3]; |
| 78 | } |
| 79 | |
| 80 | var date = originalData[i][0]; |
| 81 | var value = den ? num / den : 0.0; |
| 82 | if (wilsonInterval) { |
| 83 | // For more details on this confidence interval, see: |
| 84 | // http://en.wikipedia.org/wiki/Binomial_confidence_interval |
| 85 | if (den) { |
| 86 | var p = value < 0 ? 0 : value, n = den; |
| 87 | var pm = sigma * Math.sqrt(p * (1 - p) / n + sigma * sigma / (4 * n * n)); |
| 88 | var denom = 1 + sigma * sigma / den; |
| 89 | low = (p + sigma * sigma / (2 * den) - pm) / denom; |
| 90 | high = (p + sigma * sigma / (2 * den) + pm) / denom; |
| 91 | rollingData[i] = [ date, p * mult, |
| 92 | [ low * mult, high * mult ] ]; |
| 93 | } else { |
| 94 | rollingData[i] = [ date, 0, [ 0, 0 ] ]; |
| 95 | } |
| 96 | } else { |
| 97 | stddev = den ? sigma * Math.sqrt(value * (1 - value) / den) : 1.0; |
| 98 | rollingData[i] = [ date, mult * value, |
| 99 | [ mult * (value - stddev), mult * (value + stddev) ] ]; |
| 100 | } |
| 101 | } |
| 102 | |
| 103 | return rollingData; |
| 104 | }; |
| 105 | |
| 106 | })(); |