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