X-Git-Url: https://adrianiainlam.tk/git/?a=blobdiff_plain;f=datahandler%2Fbars-error.js;fp=datahandler%2Fbars-error.js;h=0000000000000000000000000000000000000000;hb=3123ca57f71d145bb5bcc4a2f754d3dff3225346;hp=71dbe34ce01b8ccec83f04bd91ede6f9571ddcf9;hpb=26ee953643ccd2d32e38e6b60b20e6a01c1dc9ba;p=dygraphs.git

diff --git a/datahandler/bars-error.js b/datahandler/bars-error.js
deleted file mode 100644
index 71dbe34..0000000
--- a/datahandler/bars-error.js
+++ /dev/null
@@ -1,102 +0,0 @@
-/**
- * @license
- * Copyright 2013 David Eberlein (david.eberlein@ch.sauter-bc.com)
- * MIT-licensed (http://opensource.org/licenses/MIT)
- */
-
-/**
- * @fileoverview DataHandler implementation for the error bars option.
- * @author David Eberlein (david.eberlein@ch.sauter-bc.com)
- */
-
-(function() {
-
-/*global Dygraph:false */
-"use strict";
-
-/**
- * @constructor
- * @extends Dygraph.DataHandlers.BarsHandler
- */
-Dygraph.DataHandlers.ErrorBarsHandler = function() {
-};
-
-var ErrorBarsHandler = Dygraph.DataHandlers.ErrorBarsHandler;
-ErrorBarsHandler.prototype = new Dygraph.DataHandlers.BarsHandler();
-
-/** @inheritDoc */
-ErrorBarsHandler.prototype.extractSeries = function(rawData, i, options) {
-  // TODO(danvk): pre-allocate series here.
-  var series = [];
-  var x, y, variance, point;
-  var sigma = options.get("sigma");
-  var logScale = options.get('logscale');
-  for ( var j = 0; j < rawData.length; j++) {
-    x = rawData[j][0];
-    point = rawData[j][i];
-    if (logScale && point !== null) {
-      // On the log scale, points less than zero do not exist.
-      // This will create a gap in the chart.
-      if (point[0] <= 0 || point[0] - sigma * point[1] <= 0) {
-        point = null;
-      }
-    }
-    // Extract to the unified data format.
-    if (point !== null) {
-      y = point[0];
-      if (y !== null && !isNaN(y)) {
-        variance = sigma * point[1];
-        // preserve original error value in extras for further
-        // filtering
-        series.push([ x, y, [ y - variance, y + variance, point[1] ] ]);
-      } else {
-        series.push([ x, y, [ y, y, y ] ]);
-      }
-    } else {
-      series.push([ x, null, [ null, null, null ] ]);
-    }
-  }
-  return series;
-};
-
-/** @inheritDoc */
-ErrorBarsHandler.prototype.rollingAverage =
-    function(originalData, rollPeriod, options) {
-  rollPeriod = Math.min(rollPeriod, originalData.length);
-  var rollingData = [];
-  var sigma = options.get("sigma");
-
-  var i, j, y, v, sum, num_ok, stddev, variance, value;
-
-  // Calculate the rolling average for the first rollPeriod - 1 points
-  // where there is not enough data to roll over the full number of points
-  for (i = 0; i < originalData.length; i++) {
-    sum = 0;
-    variance = 0;
-    num_ok = 0;
-    for (j = Math.max(0, i - rollPeriod + 1); j < i + 1; j++) {
-      y = originalData[j][1];
-      if (y === null || isNaN(y))
-        continue;
-      num_ok++;
-      sum += y;
-      variance += Math.pow(originalData[j][2][2], 2);
-    }
-    if (num_ok) {
-      stddev = Math.sqrt(variance) / num_ok;
-      value = sum / num_ok;
-      rollingData[i] = [ originalData[i][0], value,
-          [value - sigma * stddev, value + sigma * stddev] ];
-    } else {
-      // This explicitly preserves NaNs to aid with "independent
-      // series".
-      // See testRollingAveragePreservesNaNs.
-      v = (rollPeriod == 1) ? originalData[i][1] : null;
-      rollingData[i] = [ originalData[i][0], v, [ v, v ] ];
-    }
-  }
-
-  return rollingData;
-};
-
-})();