datahandler/bars-error.js

   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 error bars option.
   9  * @author David Eberlein (david.eberlein@ch.sauter-bc.com)
  10  */
  11
  12 (function() {
  13
  14 /*global Dygraph:false */
  15 "use strict";
  16
  17 Dygraph.DataHandlers.ErrorBarsHandler = Dygraph.DataHandler();
  18 var ErrorBarsHandler = Dygraph.DataHandlers.ErrorBarsHandler;
  19 ErrorBarsHandler.prototype = new Dygraph.DataHandlers.BarsHandler();
  20
  21 // errorBars
  22 ErrorBarsHandler.prototype.extractSeries = function(rawData, i, options) {
  23   // TODO(danvk): pre-allocate series here.
  24   var series = [];
  25   var x, y, variance, point;
  26   var sigma = options.get("sigma");
  27   var logScale = options.get('logscale');
  28   for ( var j = 0; j < rawData.length; j++) {
  29     x = rawData[j][0];
  30     point = rawData[j][i];
  31     if (logScale && point !== null) {
  32       // On the log scale, points less than zero do not exist.
  33       // This will create a gap in the chart.
  34       if (point[0] <= 0 || point[0] - sigma * point[1] <= 0) {
  35         point = null;
  36       }
  37     }
  38     // Extract to the unified data format.
  39     if (point !== null) {
  40       y = point[0];
  41       if (y !== null && !isNaN(y)) {
  42         variance = sigma * point[1];
  43         // preserve original error value in extras for further
  44         // filtering
  45         series.push([ x, y, [ y - variance, y + variance, point[1] ] ]);
  46       } else {
  47         series.push([ x, y, [ y, y, y ] ]);
  48       }
  49     } else {
  50       series.push([ x, null, [ null, null, null ] ]);
  51     }
  52   }
  53   return series;
  54 };
  55
  56 ErrorBarsHandler.prototype.rollingAverage = function(originalData, rollPeriod,
  57     options) {
  58   rollPeriod = Math.min(rollPeriod, originalData.length);
  59   var rollingData = [];
  60   var sigma = options.get("sigma");
  61
  62   var i, j, y, v, sum, num_ok, stddev, variance, value;
  63
  64   // Calculate the rolling average for the first rollPeriod - 1 points
  65   // where there is not enough data to roll over the full number of points
  66   for (i = 0; i < originalData.length; i++) {
  67     sum = 0;
  68     variance = 0;
  69     num_ok = 0;
  70     for (j = Math.max(0, i - rollPeriod + 1); j < i + 1; j++) {
  71       y = originalData[j][1];
  72       if (y === null || isNaN(y))
  73         continue;
  74       num_ok++;
  75       sum += y;
  76       variance += Math.pow(originalData[j][2][2], 2);
  77     }
  78     if (num_ok) {
  79       stddev = Math.sqrt(variance) / num_ok;
  80       value = sum / num_ok;
  81       rollingData[i] = [ originalData[i][0], value,
  82           [value - sigma * stddev, value + sigma * stddev] ];
  83     } else {
  84       // This explicitly preserves NaNs to aid with "independent
  85       // series".
  86       // See testRollingAveragePreservesNaNs.
  87       v = (rollPeriod == 1) ? originalData[i][1] : null;
  88       rollingData[i] = [ originalData[i][0], v, [ v, v ] ];
  89     }
  90   }
  91
  92   return rollingData;
  93 };
  94
  95 })();