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Performs a Holt-Winters forecast using the series as input data and plots the positive or negative deviation of the series data from the forecast. Performs a Holt-Winters forecast using the series as input data and plots the area between the upper and lower bands of the predicted forecast deviations.

Performs a Holt-Winters forecast using the series as input data and plots upper and lower bands with the predicted forecast deviations. Performs a Holt-Winters forecast using the series as input data. Data from bootstrapInterval one week by default previous to the series is used to bootstrap the initial forecast. Identity function: Returns datapoints where the value equals the timestamp of the datapoint. Useful when you have another series where the value is a timestamp, and you want to compare it to the time of the datapoint, to render an age.

This will show the sum over time, sort of like a continuous addition function. Useful for finding totals or trends in metrics that are collected per minute. This would start at zero on the left side of the graph, adding the sales each minute, and show the evolution of sales per day during the last 10 days.

Takes a metric or wildcard seriesList and counts up the number of non-null values. This is useful for understanding the number of metrics that have data at a given point in time i.

Returns a seriesList where 1 is specified for non-null values, and 0 is specified for null values. Appends a value to the metric name in the legend. Currently one or several of: last , avg , total , min , max. The last argument can be si default or binary , in that case values will be formatted in the corresponding system.

X parameter. Useful for highlighting a single metric out of many, or having multiple line widths in one graph. Takes one metric or a wildcard seriesList, followed by a quoted string with the time to start the line and another quoted string with the time to end the line.

The start and end times are inclusive default range is from to until. Datapoints in the range is used to regression. Takes one metric or a wildcard seriesList, a base, and draws the y-axis in logarithmic format.

If base is omitted, the function defaults to base Out of all metrics passed, draws only the N metrics with the lowest aggregated value over the time period specified.

Out of all metrics passed, draws only the bottom N metrics with the lowest average value for the time period specified. This is an alias for lowest with aggregation average. Out of all metrics passed, draws only the N metrics with the lowest value at the end of the time period specified. This is an alias for lowest with aggregation current. Takes a seriesList and maps it to a list of seriesList. Each seriesList has the given mapNodes in common.

This function is not very useful alone. It should be used with reduceSeries. For each datapoint from each metric passed in, pick the maximum value and graph it. This is an alias for aggregate with aggregation max. Takes one metric or a wildcard seriesList followed by a constant n. Draws only the metrics with a maximum value above n. Draws only the metrics with a maximum value below n. For each datapoint from each metric passed in, pick the minimum value and graph it.

This is an alias for aggregate with aggregation min. Draws only the metrics with a minimum value above n. Draws only the metrics with a minimum value below or equal to n. Draws the N most deviant metrics. To find the deviants, the standard deviation sigma of each series is taken and ranked.

The top N standard deviations are returned. Graphs the moving average of a metric or metrics over a fixed number of past points, or a time interval.

Graphs the average of the preceeding datapoints for each point on the graph. Graphs the moving maximum of a metric or metrics over a fixed number of past points, or a time interval. Graphs the maximum of the preceeding datapoints for each point on the graph. Graphs the moving median of a metric or metrics over a fixed number of past points, or a time interval. Graphs the median of the preceeding datapoints for each point on the graph.

Graphs the moving minimum of a metric or metrics over a fixed number of past points, or a time interval. Graphs the minimum of the preceeding datapoints for each point on the graph. Graphs the moving sum of a metric or metrics over a fixed number of past points, or a time interval.

Graphs the sum of the preceeding datapoints for each point on the graph. Graphs a moving window function of a metric or metrics over a fixed number of past points, or a time interval. Graphs the output of the function for the preceeding datapoints for each point on the graph. Setting it to 0 the default means that only a single value in a given interval needs to be non-null, setting it to 1 means that all values in the interval must be non-null.

A setting of 0. Takes two or more series and multiplies their points. A constant may not be used. To multiply by a constant, use the scale function. This is an alias for aggregate with aggregation multiply. An example above would be the same as running multiplySeries for each member of the list:. This is an alias for aggregateSeriesLists with aggregation multiply. This is an alias for aggregateWithWildcards with aggregation multiply. Same as the derivative function above, but ignores datapoints that trend down.

Useful for counters that increase for a long time, then wrap or reset. By default, a null value is returned in place of negative datapoints. When maxValue is supplied, the missing value is computed as if the counter had wrapped at maxValue. When minValue is supplied, the missing value is computed as if the counter had wrapped to minValue. Offsets a metric or wildcard seriesList by subtracting the minimum value in the series from each datapoint.

An example use case is for comparing different round trip time results. When measuring RTT like pinging a server , different devices may come back with consistently different results due to network latency which will be different depending on how many network hops between the probe and the device.

To compare different devices in the same graph, the network latency to each has to be factored out of the results. This is a shortcut that takes the fastest response lowest number in the series and sets that to zero and then offsets all of the other datapoints in that series by that amount.

This makes the assumption that the lowest response is the fastest the device can respond, of course the more datapoints that are in the series the more accurate this assumption is.

NonNegativeDerivative adjusted for the series time interval This is useful for taking a running total metric and showing how many requests per second were handled. The optional minValue and maxValue parameters have the same meaning as in nonNegativeDerivative. Unless interpolate is set to True, percentile values are actual values contained in one of the supplied series. Takes one metric or a wildcard seriesList followed by a constant, and raises the datapoint by the power of the constant provided at each point.

Returns a random walk starting at 0. This is great for testing when there is no real data in whisper. This is an alias for aggregate with aggregation rangeOf. Reduction is performed by matching the reduceNode in each series against the list of reduceMatchers. Then each series is passed to the reduceFunction as arguments in the order given by reduceMatchers. The reduceFunction should yield a single series. Removes data above the nth percentile from the series or list of series provided.

Values above this percentile are assigned a value of None. Removes data above the given threshold from the series or list of series provided. Values above this threshold are assigned a value of None. Removes data below the nth percentile from the series or list of series provided. Values below this percentile are assigned a value of None. Removes data below the given threshold from the series or list of series provided. Values below this threshold are assigned a value of None. Out of all metrics passed, draws only the metrics with not empty data.

Setting it to 0 the default means that only a single value in the series needs to be non-null for it to be considered non-empty, setting it to 1 means that all values in the series must be non-null. Takes one metric or a wildcard seriesList optionally followed by a precision, and rounds each datapoint to the specified precision.

Takes one metric or a wildcard seriesList followed by a constant, and multiplies the datapoint by the constant provided at each point. Useful in conjunction with derivative or integral function if you want to normalize its result to a known resolution for arbitrary retentions.

Returns a seriesList of all series that have tag1 set to value1, AND do not have tag2 set to value2. See querying tagged series for more detail. When a series needs to be consolidated, this sets the fraction of values in an interval that must not be null for the consolidation to be considered valid. If there are not enough values then None will be returned for that interval. A default for the entire render request can also be set using the xFilesFactor query parameter.

Just returns the sine of the current time. The optional amplitude parameter changes the amplitude of the wave. The alignToFrom boolean parameter has been replaced by alignTo and no longer has any effect. Alignment can be to years, months, weeks, days, hours, and minutes. Takes one metric or a wildcard seriesList followed by an aggregation function and an optional reverse parameter. Sorts the list of metrics in descending order by the maximum value across the time period specified.

Sorts the list of metrics by the lowest value across the time period specified, including only series that have a maximum value greater than 0. Sorts the list of metrics by the metric name using either alphabetical order or natural sorting. Natural sorting allows names containing numbers to be sorted more naturally, e. Sorts the list of metrics in descending order by the sum of values across the time period specified.

Takes one metric or a wildcard seriesList and change them so they are stacked. This is a way of stacking just a couple of metrics without having to use the stacked area mode that stacks everything. By means of this a mixed stacked and non stacked graph can be made. It can also take an optional argument with a name of the stack, in case there is more than one, e. Draws the standard deviation of all metrics passed at each time. This is an alias for aggregate with aggregation stddev.

Draw the Standard Deviation of all metrics passed for the past N datapoints. If the ratio of null points in the window is greater than windowTolerance, skip the calculation. The default for windowTolerance is 0. Note that if this is set to 0.

Takes one metric or a wildcard seriesList followed by 1 or 2 integers. Assume that the metric name is a list or array, with each element separated by dots. Prints n - length elements of the array if only one integer n is passed or n - m elements of the array if two integers n and m are passed.

The list starts with element 0 and ends with element length - 1. This will add metrics together and return the sum at each datapoint. See integral for a sum over time. This would show the sum of all requests handled per minute provided requestsHandled are collected once a minute.

If metrics with different retention rates are combined, the coarsest metric is graphed, and the sum of the other metrics is averaged for the metrics with finer retention rates. This is an alias for aggregate with aggregation sum. An example above would be the same as running sumSeries for each member of the list:. This is an alias for aggregateSeriesLists with aggregation sum. This is an alias for aggregateWithWildcards with aggregation sum. By default, the contents of each interval bucket are summed together.

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