SignalFlow Functions and Methods Index
This is an alphabetical list of SignalFlow functions and methods
Functions
SignalFlow functions perform operations on an input stream or expression and return an input stream or value.
The primary difference between functions and SignalFlow methods is syntax. Functions take input arguments and return values, while methods implicitly act on the input stream object that they’re called on.
Function example


Alphabetical list of functions
Function 
Returns 
Absolute value of the input 

Ceiling of the input 

Stream of constantvalue timeseries 

Counts the number of metric timeseries that are reporting data 

Stream from live metrics data 

SignalFx detector 

SignalFx filter 

Floor of the input 

Stream that interprets a metric query coming from graphite 

Convenience wrapper that provides the 

Log _{10} of the input 

Log_{e} of the input 

Maximum of each metric in the input 

Mean (average) of each metric in the input 

Median value of each metric in the input 

Minimum value of each stream in the input arguments 

Interprets a stream as a metric query containing slashseparated dimensions 

Subsetting timeseries filter 

nth percentile of each metric in the input 

nth power of each metric in the input 

Square root of each metric in the input 

Merged time series from the union of all the input timeseries 

Returns a 
Methods
Methods use an objectoriented "dot" syntax. To call a method someMethod
on an input stream object someStream
, you
use the syntax:
value = someStream.someMethod()
For example, this SignalFlow program publishes an output stream containing the ceiling of cpu.utilization
:


Alphabetical list of methods
Method 
Returns 
Only pass through input data that’s above a specified value, or force data above that value to a specified value 

Calculate and return the absolute value of each metric in the stream object on which it’s called 

Only pass through input data that’s below a specified value, or force data below that value to a specified value 

Only pass through input data that’s between two specified values, or replace data that’s not between two specified values with the value it’s closest to. 

Get the bottom values in the stream 

Get the ceil values for each metric in the stream object on which it’s called 

The stream method for counting events in the stream 

Counts the number of inputs that have data 

Calculates the difference between the current value and the previous value for each time interval in the input resolution of the stream object on which it’s called 

Duplicates or renames metadata in the input stream on which it’s called 

Applies double exponential smoothing to the input stream during a specified time window or based on smoothing parameters 

Only pass through input data that’s equal to a specified value, or replace data that’s not equal to a value with a specified value 

Calculates the exponentiallyweighted moving average of the stream during a specified time duration or based on a smoothing parameter 

Fills in missing values for timeseries in a stream 

Calculates the floor of the MTS in the stream object on which it’s called 

Multiplies the values of each input timeseries in the stream object by the computation resolution in seconds. The stream object is the one on which the method is called. 

Calculates the Kwiatkowski–Phillips–Schmidt–Shin statistic on the specified time window of the stream object on which it’s called. 

Calculates the common logarithm (log_{10}) of the metric timeseries in the input stream on which it’s called 

Calculates the natural logarithm (log_{e}) of the metric timeseries in the input stream on which it’s called 

Applies a 

Finds the maximum value of the metric timeseries in the stream object on which it’s called 

Calculates the mean plus n standard deviations of metric timeseries in the input stream on which it’s called 

Calculates the mean of metric timeseries in the input stream on which it’s called 

Calculates the median of metric timeseries in the input stream on which it’s called 

Finds the minimum value of the metric timeseries in the input stream on which it’s called 

Only pass through data in the data stream if it isn’t between two specified values. The data stream is the object on which this method is called. 

Only pass through data in the data stream if it isn’t equal to a specified value, or replace data that’s equal to a specified value with another value. The data stream is the object on which this method is called. 

Calculates the nth percentile of metric timeseries in the input stream on which it’s called 

Raise the value of a metric timeseries in the input stream to an exponent, or raise a base to an exponent in a metric timeseries in the input stream 

For the input stream object on which it’s called, promotes one or more custom properties to dimensions 

Stream method for publishing the output of a detect stream. The optional 

Publishes the input stream on which it’s called to make it visible outside of a computation. 

Get random values from the input stream by count or percentage 

For the input stream on which it’s called, calculates the difference between the current and previous value of the metric for each time interval, then divides the result by the length in seconds of the time interval. 

Calculates the sample standard deviation of metrics in the input stream on which it’s called 

Calculates the sample variance of metrics in the input stream on which it’s called 

For the input stream on which it’s called, scale metrics by a multiplier value 

Counts the number of metrics in the input stream on which it’s called. 

Calculates the square root of metrics in the input stream on which it’s called 

Calculates the standard deviation of metrics in the input stream on which it’s called 

Calculates the sum of each metric timeseries in the input stream on which it’s called 

Timeshifts each datapoint in the input stream on which it’s called, offsetting them by a specified time period. 

Returns one or more of the largest metrics in the input stream on which it’s called 

Calculates the variance of metrics in the input stream on which it’s called 
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