*/
(function() {
- /*global Dygraph:false */
- "use strict";
- var FractionsBarsHandler = Dygraph.DataHandler();
- FractionsBarsHandler.prototype = Dygraph.DataHandlers.createHandler("bars");
- Dygraph.DataHandlers.registerHandler("bars-fractions", FractionsBarsHandler);
- // errorBars
- FractionsBarsHandler.prototype.extractSeries = function(rawData, i, options) {
- // TODO(danvk): pre-allocate series here.
- var series = [];
- var x, y, point, num, den, value, stddev, variance;
- var mult = 100.0;
- 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[1] <= 0) {
- point = null;
- }
+/*global Dygraph:false */
+"use strict";
+
+/**
+ * @constructor
+ * @extends Dygraph.DataHandlers.BarsHandler
+ */
+Dygraph.DataHandlers.FractionsBarsHandler = function() {
+};
+
+var FractionsBarsHandler = Dygraph.DataHandlers.FractionsBarsHandler;
+FractionsBarsHandler.prototype = new Dygraph.DataHandlers.BarsHandler();
+
+/** @inheritDoc */
+FractionsBarsHandler.prototype.extractSeries = function(rawData, i, options) {
+ // TODO(danvk): pre-allocate series here.
+ var series = [];
+ var x, y, point, num, den, value, stddev, variance;
+ var mult = 100.0;
+ 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[1] <= 0) {
+ point = null;
}
- // Extract to the unified data format.
- if (point !== null) {
- num = point[0];
- den = point[1];
- if (num !== null && !isNaN(num)) {
- value = den ? num / den : 0.0;
- stddev = den ? sigma * Math.sqrt(value * (1 - value) / den) : 1.0;
- variance = mult * stddev;
- y = mult * value;
- // preserve original values in extras for further filtering
- series.push([ x, y, [ y - variance, y + variance, num, den ] ]);
- } else {
- series.push([ x, num, [ num, num, num, den ] ]);
- }
+ }
+ // Extract to the unified data format.
+ if (point !== null) {
+ num = point[0];
+ den = point[1];
+ if (num !== null && !isNaN(num)) {
+ value = den ? num / den : 0.0;
+ stddev = den ? sigma * Math.sqrt(value * (1 - value) / den) : 1.0;
+ variance = mult * stddev;
+ y = mult * value;
+ // preserve original values in extras for further filtering
+ series.push([ x, y, [ y - variance, y + variance, num, den ] ]);
} else {
- series.push([ x, null, [ null, null, null, null ] ]);
+ series.push([ x, num, [ num, num, num, den ] ]);
}
+ } else {
+ series.push([ x, null, [ null, null, null, null ] ]);
}
- return series;
- };
+ }
+ return series;
+};
- FractionsBarsHandler.prototype.rollingAverage = function(originalData, rollPeriod,
- options) {
- rollPeriod = Math.min(rollPeriod, originalData.length);
- var rollingData = [];
- var sigma = options.get("sigma");
- var wilsonInterval = options.get("wilsonInterval");
+/** @inheritDoc */
+FractionsBarsHandler.prototype.rollingAverage =
+ function(originalData, rollPeriod, options) {
+ rollPeriod = Math.min(rollPeriod, originalData.length);
+ var rollingData = [];
+ var sigma = options.get("sigma");
+ var wilsonInterval = options.get("wilsonInterval");
- var low, high, i, stddev;
- var num = 0;
- var den = 0; // numerator/denominator
- var mult = 100.0;
- for (i = 0; i < originalData.length; i++) {
- num += originalData[i][2][2];
- den += originalData[i][2][3];
- if (i - rollPeriod >= 0) {
- num -= originalData[i - rollPeriod][2][2];
- den -= originalData[i - rollPeriod][2][3];
- }
+ var low, high, i, stddev;
+ var num = 0;
+ var den = 0; // numerator/denominator
+ var mult = 100.0;
+ for (i = 0; i < originalData.length; i++) {
+ num += originalData[i][2][2];
+ den += originalData[i][2][3];
+ if (i - rollPeriod >= 0) {
+ num -= originalData[i - rollPeriod][2][2];
+ den -= originalData[i - rollPeriod][2][3];
+ }
- var date = originalData[i][0];
- var value = den ? num / den : 0.0;
- if (wilsonInterval) {
- // For more details on this confidence interval, see:
- // http://en.wikipedia.org/wiki/Binomial_confidence_interval
- if (den) {
- var p = value < 0 ? 0 : value, n = den;
- var pm = sigma * Math.sqrt(p * (1 - p) / n + sigma * sigma / (4 * n * n));
- var denom = 1 + sigma * sigma / den;
- low = (p + sigma * sigma / (2 * den) - pm) / denom;
- high = (p + sigma * sigma / (2 * den) + pm) / denom;
- rollingData[i] = [ date, p * mult,
- [ low * mult, high * mult ] ];
- } else {
- rollingData[i] = [ date, 0, [ 0, 0 ] ];
- }
+ var date = originalData[i][0];
+ var value = den ? num / den : 0.0;
+ if (wilsonInterval) {
+ // For more details on this confidence interval, see:
+ // http://en.wikipedia.org/wiki/Binomial_confidence_interval
+ if (den) {
+ var p = value < 0 ? 0 : value, n = den;
+ var pm = sigma * Math.sqrt(p * (1 - p) / n + sigma * sigma / (4 * n * n));
+ var denom = 1 + sigma * sigma / den;
+ low = (p + sigma * sigma / (2 * den) - pm) / denom;
+ high = (p + sigma * sigma / (2 * den) + pm) / denom;
+ rollingData[i] = [ date, p * mult,
+ [ low * mult, high * mult ] ];
} else {
- stddev = den ? sigma * Math.sqrt(value * (1 - value) / den) : 1.0;
- rollingData[i] = [ date, mult * value,
- [ mult * (value - stddev), mult * (value + stddev) ] ];
+ rollingData[i] = [ date, 0, [ 0, 0 ] ];
}
+ } else {
+ stddev = den ? sigma * Math.sqrt(value * (1 - value) / den) : 1.0;
+ rollingData[i] = [ date, mult * value,
+ [ mult * (value - stddev), mult * (value + stddev) ] ];
}
+ }
+
+ return rollingData;
+};
- return rollingData;
- };
})();
projects / dygraphs.git / blobdiff