*/
(function() {
- /*global Dygraph:false */
- "use strict";
- var CustomBarsHandler = Dygraph.DataHandler();
- CustomBarsHandler.prototype = Dygraph.DataHandlers.createHandler("bars");
- Dygraph.DataHandlers.registerHandler("bars-custom", CustomBarsHandler);
- // customBars
- CustomBarsHandler.prototype.extractSeries = function(rawData, i, options) {
- // TODO(danvk): pre-allocate series here.
- var series = [];
- var x, y, point;
- 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[2] <= 0) {
- point = null;
- }
+/*global Dygraph:false */
+"use strict";
+
+Dygraph.DataHandlers.CustomBarsHandler = Dygraph.DataHandler();
+var CustomBarsHandler = Dygraph.DataHandlers.CustomBarsHandler;
+CustomBarsHandler.prototype = new Dygraph.DataHandlers.BarsHandler();
+
+// customBars
+CustomBarsHandler.prototype.extractSeries = function(rawData, i, options) {
+ // TODO(danvk): pre-allocate series here.
+ var series = [];
+ var x, y, point;
+ 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[2] <= 0) {
+ point = null;
}
- // Extract to the unified data format.
- if (point !== null) {
- y = point[1];
- if (y !== null && !isNaN(y)) {
- series.push([ x, y, [ point[0], point[2] ] ]);
- } else {
- series.push([ x, y, [ y, y ] ]);
- }
+ }
+ // Extract to the unified data format.
+ if (point !== null) {
+ y = point[1];
+ if (y !== null && !isNaN(y)) {
+ series.push([ x, y, [ point[0], point[2] ] ]);
} else {
- series.push([ x, null, [ null, null ] ]);
+ series.push([ x, y, [ y, y ] ]);
}
+ } else {
+ series.push([ x, null, [ null, null ] ]);
}
- return series;
- };
+ }
+ return series;
+};
- CustomBarsHandler.prototype.rollingAverage = function(originalData, rollPeriod,
- options) {
- rollPeriod = Math.min(rollPeriod, originalData.length);
- var rollingData = [];
- var y, low, high, mid,count, i, extremes;
+CustomBarsHandler.prototype.rollingAverage = function(originalData, rollPeriod,
+ options) {
+ rollPeriod = Math.min(rollPeriod, originalData.length);
+ var rollingData = [];
+ var y, low, high, mid,count, i, extremes;
- low = 0;
- mid = 0;
- high = 0;
- count = 0;
- for (i = 0; i < originalData.length; i++) {
- y = originalData[i][1];
- extremes = originalData[i][2];
- rollingData[i] = originalData[i];
+ low = 0;
+ mid = 0;
+ high = 0;
+ count = 0;
+ for (i = 0; i < originalData.length; i++) {
+ y = originalData[i][1];
+ extremes = originalData[i][2];
+ rollingData[i] = originalData[i];
- if (y !== null && !isNaN(y)) {
- low += extremes[0];
- mid += y;
- high += extremes[1];
- count += 1;
- }
- if (i - rollPeriod >= 0) {
- var prev = originalData[i - rollPeriod];
- if (prev[1] !== null && !isNaN(prev[1])) {
- low -= prev[2][0];
- mid -= prev[1];
- high -= prev[2][1];
- count -= 1;
- }
- }
- if (count) {
- rollingData[i] = [
- originalData[i][0],
- 1.0 * mid / count,
- [ 1.0 * low / count,
- 1.0 * high / count ] ];
- } else {
- rollingData[i] = [ originalData[i][0], null, [ null, null ] ];
+ if (y !== null && !isNaN(y)) {
+ low += extremes[0];
+ mid += y;
+ high += extremes[1];
+ count += 1;
+ }
+ if (i - rollPeriod >= 0) {
+ var prev = originalData[i - rollPeriod];
+ if (prev[1] !== null && !isNaN(prev[1])) {
+ low -= prev[2][0];
+ mid -= prev[1];
+ high -= prev[2][1];
+ count -= 1;
}
}
+ if (count) {
+ rollingData[i] = [
+ originalData[i][0],
+ 1.0 * mid / count,
+ [ 1.0 * low / count,
+ 1.0 * high / count ] ];
+ } else {
+ rollingData[i] = [ originalData[i][0], null, [ null, null ] ];
+ }
+ }
+
+ return rollingData;
+};
- return rollingData;
- };
})();
*/
(function() {
- /*global Dygraph:false */
- "use strict";
- var ErrorBarsHandler = Dygraph.DataHandler();
- ErrorBarsHandler.prototype = Dygraph.DataHandlers.createHandler("bars");
- Dygraph.DataHandlers.registerHandler("bars-error", ErrorBarsHandler);
- // errorBars
- 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;
- }
+/*global Dygraph:false */
+"use strict";
+
+Dygraph.DataHandlers.ErrorBarsHandler = Dygraph.DataHandler();
+var ErrorBarsHandler = Dygraph.DataHandlers.ErrorBarsHandler;
+ErrorBarsHandler.prototype = new Dygraph.DataHandlers.BarsHandler();
+
+// errorBars
+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 ] ]);
- }
+ }
+ // 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, null, [ null, null, null ] ]);
+ series.push([ x, y, [ y, y, y ] ]);
}
+ } else {
+ series.push([ x, null, [ null, null, null ] ]);
}
- return series;
- };
+ }
+ return series;
+};
- ErrorBarsHandler.prototype.rollingAverage = function(originalData, rollPeriod,
- options) {
- rollPeriod = Math.min(rollPeriod, originalData.length);
- var rollingData = [];
- var sigma = options.get("sigma");
+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;
+ 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 ] ];
- }
+ // 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;
+};
- return rollingData;
- };
})();
*/
(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";
+
+Dygraph.DataHandlers.FractionsBarsHandler = Dygraph.DataHandler();
+var FractionsBarsHandler = Dygraph.DataHandlers.FractionsBarsHandler;
+FractionsBarsHandler.prototype = new Dygraph.DataHandlers.BarsHandler();
+
+// 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;
}
- // 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");
+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;
- };
})();
*/
(function() {
- /*global Dygraph:false */
- /*global DygraphLayout:false */
- "use strict";
-
- var BarsHandler = Dygraph.DataHandler();
- Dygraph.DataHandlers.registerHandler("bars", BarsHandler);
- // errorBars
- BarsHandler.prototype.extractSeries = function(rawData, i, options) {
- // Not implemented here must be extended
- };
-
- BarsHandler.prototype.rollingAverage = function(originalData, rollPeriod,
- options) {
- // Not implemented here, must be extended.
- };
-
- BarsHandler.prototype.onPointsCreated_ = function(series, points) {
- for (var i = 0; i < series.length; ++i) {
- var item = series[i];
- var point = points[i];
- point.y_top = NaN;
- point.y_bottom = NaN;
- point.yval_minus = DygraphLayout.parseFloat_(item[2][0]);
- point.yval_plus = DygraphLayout.parseFloat_(item[2][1]);
- }
- };
-
- BarsHandler.prototype.getExtremeYValues = function(series, dateWindow, options) {
- var minY = null, maxY = null, y;
-
- var firstIdx = 0;
- var lastIdx = series.length - 1;
-
- for ( var j = firstIdx; j <= lastIdx; j++) {
- y = series[j][1];
- if (y === null || isNaN(y)) continue;
-
- var low = series[j][2][0];
- var high = series[j][2][1];
-
- if (low > y) low = y; // this can happen with custom bars,
- if (high < y) high = y; // e.g. in tests/custom-bars.html
-
- if (maxY === null || high > maxY) maxY = high;
- if (minY === null || low < minY) minY = low;
- }
-
- return [ minY, maxY ];
- };
-
- BarsHandler.prototype.onLineEvaluated = function(points, axis, logscale) {
- var point;
- for (var j = 0; j < points.length; j++) {
- // Copy over the error terms
- point = points[j];
- point.y_top = DygraphLayout._calcYNormal(axis, point.yval_minus, logscale);
- point.y_bottom = DygraphLayout._calcYNormal(axis, point.yval_plus, logscale);
- }
- };
+
+/*global Dygraph:false */
+/*global DygraphLayout:false */
+"use strict";
+
+Dygraph.DataHandlers.BarsHandler = Dygraph.DataHandler();
+var BarsHandler = Dygraph.DataHandlers.BarsHandler;
+
+// errorBars
+BarsHandler.prototype.extractSeries = function(rawData, i, options) {
+ // Not implemented here must be extended
+};
+
+BarsHandler.prototype.rollingAverage =
+ function(originalData, rollPeriod, options) {
+ // Not implemented here, must be extended.
+};
+
+BarsHandler.prototype.onPointsCreated_ = function(series, points) {
+ for (var i = 0; i < series.length; ++i) {
+ var item = series[i];
+ var point = points[i];
+ point.y_top = NaN;
+ point.y_bottom = NaN;
+ point.yval_minus = DygraphLayout.parseFloat_(item[2][0]);
+ point.yval_plus = DygraphLayout.parseFloat_(item[2][1]);
+ }
+};
+
+BarsHandler.prototype.getExtremeYValues = function(series, dateWindow, options) {
+ var minY = null, maxY = null, y;
+
+ var firstIdx = 0;
+ var lastIdx = series.length - 1;
+
+ for ( var j = firstIdx; j <= lastIdx; j++) {
+ y = series[j][1];
+ if (y === null || isNaN(y)) continue;
+
+ var low = series[j][2][0];
+ var high = series[j][2][1];
+
+ if (low > y) low = y; // this can happen with custom bars,
+ if (high < y) high = y; // e.g. in tests/custom-bars.html
+
+ if (maxY === null || high > maxY) maxY = high;
+ if (minY === null || low < minY) minY = low;
+ }
+
+ return [ minY, maxY ];
+};
+
+BarsHandler.prototype.onLineEvaluated = function(points, axis, logscale) {
+ var point;
+ for (var j = 0; j < points.length; j++) {
+ // Copy over the error terms
+ point = points[j];
+ point.y_top = DygraphLayout._calcYNormal(axis, point.yval_minus, logscale);
+ point.y_bottom = DygraphLayout._calcYNormal(axis, point.yval_plus, logscale);
+ }
+};
+
})();
* errorBar / customBar: [x, yVal, [yTopVariance, yBottomVariance] ]
*
*/
-/*jshint globalstrict: true */
/*global Dygraph:false */
/*global DygraphLayout:false */
+
+(function() {
+
"use strict";
/**
* A collection of functions to create and retrieve data handlers.
+ * @type {Object.<!Dygraph.DataHandler>}
*/
Dygraph.DataHandlers = {};
/**
- * All registered data handlers are stored here.
- *
- * @private
- */
-Dygraph.DataHandlers.handlers_ = {};
-
-/**
- * @param name {!string} The name the data handler should be registered to.
- * Registers a data handler by the given name and makes it publicly
- * accessible.
- * @param handler {!Dygraph.DataHandler} DataHandler implementation which must be an
- * instance of Dygraph.DataHandler.
- * @public
- */
-Dygraph.DataHandlers.registerHandler = function(name, handler) {
- if (!handler instanceof Dygraph.DataHandler) {
- throw ("the handler must be a prototype of Dygraph.DataHandler");
- }
- Dygraph.DataHandlers.handlers_[name] = handler;
-};
-
-/**
- * Returns the data handler registered to the given name.
- * Note this is the data handler constructor method.
- *
- * @param name {!string} The name, the handler was registered to.
- * @returns {Dygraph.DataHandler} The data handler constructor.
- * @public
- */
-Dygraph.DataHandlers.getHandler = function(name) {
- return Dygraph.DataHandlers.handlers_[name];
-};
-
-/**
- * Returns the cunstructed data handler registered to the given name.
- *
- * @param name {!string} The name, the handler was registered to.
- * @returns {Dygraph.DataHandler} A constructed instance of the data handler.
- * @public
- */
-Dygraph.DataHandlers.createHandler = function(name) {
- return new Dygraph.DataHandlers.handlers_[name]();
-};
-
-/**
*
* The data handler is responsible for all data specific operations. All of the
* series data it receives and returns is always in the unified data format.
* Initially the unified data is created by the extractSeries method
- *
- * @class
*/
Dygraph.DataHandler = function () {
/**
return handler;
};
+
+})();
*/
(function() {
- /*global Dygraph:false */
- "use strict";
- var DefaultFractionHandler = Dygraph.DataHandler();
- DefaultFractionHandler.prototype = Dygraph.DataHandlers.createHandler("default");
- Dygraph.DataHandlers.registerHandler("default-fractions", DefaultFractionHandler);
+/*global Dygraph:false */
+"use strict";
- DefaultFractionHandler.prototype.extractSeries = function(rawData, i, options) {
- // TODO(danvk): pre-allocate series here.
- var series = [];
- var x, y, point, num, den, value;
- var mult = 100.0;
- 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;
- }
+Dygraph.DataHandlers.DefaultFractionHandler = Dygraph.DataHandler();
+var DefaultFractionHandler = Dygraph.DataHandlers.DefaultFractionHandler;
+DefaultFractionHandler.prototype = new Dygraph.DataHandlers.DefaultHandler();
+
+DefaultFractionHandler.prototype.extractSeries = function(rawData, i, options) {
+ // TODO(danvk): pre-allocate series here.
+ var series = [];
+ var x, y, point, num, den, value;
+ var mult = 100.0;
+ 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;
- y = mult * value;
- // preserve original values in extras for further filtering
- series.push([ x, y, [ num, den ] ]);
- } else {
- series.push([ x, 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;
+ y = mult * value;
+ // preserve original values in extras for further filtering
+ series.push([ x, y, [ num, den ] ]);
} else {
- series.push([ x, null, [ null, null ] ]);
+ series.push([ x, num, [ num, den ] ]);
}
+ } else {
+ series.push([ x, null, [ null, null ] ]);
}
- return series;
- };
-
- DefaultFractionHandler.prototype.rollingAverage = function(originalData, rollPeriod,
- options) {
- rollPeriod = Math.min(rollPeriod, originalData.length);
- var rollingData = [];
+ }
+ return series;
+};
- var i;
- var num = 0;
- var den = 0; // numerator/denominator
- var mult = 100.0;
- for (i = 0; i < originalData.length; i++) {
- num += originalData[i][2][0];
- den += originalData[i][2][1];
- if (i - rollPeriod >= 0) {
- num -= originalData[i - rollPeriod][2][0];
- den -= originalData[i - rollPeriod][2][1];
- }
+DefaultFractionHandler.prototype.rollingAverage = function(originalData, rollPeriod,
+ options) {
+ rollPeriod = Math.min(rollPeriod, originalData.length);
+ var rollingData = [];
- var date = originalData[i][0];
- var value = den ? num / den : 0.0;
- rollingData[i] = [ date, mult * value ];
+ var i;
+ var num = 0;
+ var den = 0; // numerator/denominator
+ var mult = 100.0;
+ for (i = 0; i < originalData.length; i++) {
+ num += originalData[i][2][0];
+ den += originalData[i][2][1];
+ if (i - rollPeriod >= 0) {
+ num -= originalData[i - rollPeriod][2][0];
+ den -= originalData[i - rollPeriod][2][1];
}
- return rollingData;
- };
+ var date = originalData[i][0];
+ var value = den ? num / den : 0.0;
+ rollingData[i] = [ date, mult * value ];
+ }
+
+ return rollingData;
+};
+
})();
*/
(function() {
- /*global Dygraph:false */
- "use strict";
- var DefaultHandler = Dygraph.DataHandler();
- Dygraph.DataHandlers.registerHandler("default", DefaultHandler);
+/*global Dygraph:false */
+"use strict";
- DefaultHandler.prototype.extractSeries = function(rawData, i, options) {
- // TODO(danvk): pre-allocate series here.
- var series = [];
- var logScale = options.get('logscale');
- for ( var j = 0; j < rawData.length; j++) {
- var x = rawData[j][0];
- var point = rawData[j][i];
- if (logScale) {
- // On the log scale, points less than zero do not exist.
- // This will create a gap in the chart.
- if (point <= 0) {
- point = null;
- }
+Dygraph.DataHandlers.DefaultHandler = Dygraph.DataHandler();
+var DefaultHandler = Dygraph.DataHandlers.DefaultHandler;
+
+DefaultHandler.prototype.extractSeries = function(rawData, i, options) {
+ // TODO(danvk): pre-allocate series here.
+ var series = [];
+ var logScale = options.get('logscale');
+ for ( var j = 0; j < rawData.length; j++) {
+ var x = rawData[j][0];
+ var point = rawData[j][i];
+ if (logScale) {
+ // On the log scale, points less than zero do not exist.
+ // This will create a gap in the chart.
+ if (point <= 0) {
+ point = null;
}
- series.push([ x, point ]);
}
- return series;
- };
+ series.push([ x, point ]);
+ }
+ return series;
+};
- DefaultHandler.prototype.rollingAverage = function(originalData, rollPeriod,
- options) {
- rollPeriod = Math.min(rollPeriod, originalData.length);
- var rollingData = [];
+DefaultHandler.prototype.rollingAverage = function(originalData, rollPeriod,
+ options) {
+ rollPeriod = Math.min(rollPeriod, originalData.length);
+ var rollingData = [];
- var i, j, y, sum, num_ok;
- // Calculate the rolling average for the first rollPeriod - 1 points
- // where
- // there is not enough data to roll over the full number of points
- if (rollPeriod == 1) {
- return originalData;
+ var i, j, y, sum, num_ok;
+ // Calculate the rolling average for the first rollPeriod - 1 points
+ // where
+ // there is not enough data to roll over the full number of points
+ if (rollPeriod == 1) {
+ return originalData;
+ }
+ for (i = 0; i < originalData.length; i++) {
+ sum = 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 += originalData[j][1];
}
- for (i = 0; i < originalData.length; i++) {
- sum = 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 += originalData[j][1];
- }
- if (num_ok) {
- rollingData[i] = [ originalData[i][0], sum / num_ok ];
- } else {
- rollingData[i] = [ originalData[i][0], null ];
- }
+ if (num_ok) {
+ rollingData[i] = [ originalData[i][0], sum / num_ok ];
+ } else {
+ rollingData[i] = [ originalData[i][0], null ];
}
+ }
- return rollingData;
- };
+ return rollingData;
+};
- DefaultHandler.prototype.getExtremeYValues = function(series, dateWindow,
- options) {
- var minY = null, maxY = null, y;
- var firstIdx = 0, lastIdx = series.length - 1;
+DefaultHandler.prototype.getExtremeYValues = function(series, dateWindow,
+ options) {
+ var minY = null, maxY = null, y;
+ var firstIdx = 0, lastIdx = series.length - 1;
- for ( var j = firstIdx; j <= lastIdx; j++) {
- y = series[j][1];
- if (y === null || isNaN(y))
- continue;
- if (maxY === null || y > maxY) {
- maxY = y;
- }
- if (minY === null || y < minY) {
- minY = y;
- }
+ for ( var j = firstIdx; j <= lastIdx; j++) {
+ y = series[j][1];
+ if (y === null || isNaN(y))
+ continue;
+ if (maxY === null || y > maxY) {
+ maxY = y;
}
- return [ minY, maxY ];
- };
+ if (minY === null || y < minY) {
+ minY = y;
+ }
+ }
+ return [ minY, maxY ];
+};
+
})();
"default": "[]",
"labels": ["Configuration"],
"type": "Array<plugin>",
- "description": "Defines per-graph plug-ins. Useful for per-graph customization"
+ "description": "Defines per-graph plugins. Useful for per-graph customization"
+ },
+ "dataHandler": {
+ "default": "(depends on data)",
+ "labels": ["Data"],
+ "type": "Dygraph.DataHandler",
+ "description": "Custom DataHandler. This is an advanced customization. See http://bit.ly/151E7Aq."
}
}
; // </JSON>
};
/**
+ * Returns the correct handler class for the currently set options.
* @private
- * Returns the correct handler ID for the currently set options.
- * The actual handler may then be retrieved using the
- * Dygraph.DataHandlers.getHandler() method.
- */
-Dygraph.prototype.getHandlerId_ = function() {
- var handlerId;
- if (this.attr_("dataHandlerId")) {
- handlerId = this.attr_("dataHandlerId");
- } else if (this.fractions_){
- if (this.attr_("errorBars")) {
- handlerId = "bars-fractions";
+ */
+Dygraph.prototype.getHandlerClass_ = function() {
+ var handlerClass;
+ if (this.attr_('dataHandler')) {
+ handlerClass = this.attr_('dataHandler');
+ } else if (this.fractions_) {
+ if (this.attr_('errorBars')) {
+ handlerClass = Dygraph.DataHandlers.FractionsBarsHandler;
} else {
- handlerId = "default-fractions";
+ handlerClass = Dygraph.DataHandlers.DefaultFractionHandler;
}
- } else if (this.attr_("customBars")) {
- handlerId = "bars-custom";
- } else if (this.attr_("errorBars")) {
- handlerId = "bars-error";
+ } else if (this.attr_('customBars')) {
+ handlerClass = Dygraph.DataHandlers.CustomBarsHandler;
+ } else if (this.attr_('errorBars')) {
+ handlerClass = Dygraph.DataHandlers.ErrorBarsHandler;
} else {
- handlerId = "default";
+ handlerClass = Dygraph.DataHandlers.DefaultHandler;
}
- return handlerId;
+ return handlerClass;
};
/**
var start = new Date();
// Create the correct dataHandler
- this.dataHandler_ = new (Dygraph.DataHandlers.getHandler(this.getHandlerId_()))();
+ this.dataHandler_ = new (this.getHandlerClass_())();
this.layout_.computePlotArea();
projects / dygraphs.git / commitdiff