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rolling-min

Input Stack:
w: Window
expr: TimeSeriesExpr
 ⇨ Output Stack:
TimeSeriesExpr
 

Find the minimum value within a rolling window of datapoints. This operation is useful for tracking low-water marks, establishing lower bounds for noisy data, and creating envelope functions that follow the lowest points in fluctuating signals.

Parameters

  • expr: The time series expression to find rolling minimum for
  • w: Window size, either a number of datapoints including the current value, such as 5, or a duration, such as 5m. See Window Size

Window Size

The window can be specified as a number of datapoints or as an amount of time. A number of datapoints, 5, will consider the last 5 values, including the current value. The amount of time covered then changes with the step size, for example when zooming out to a time frame that causes consolidation. A duration, 5m, will consider the values for the last 5 minutes independent of the step size. The duration is rounded down to the nearest step boundary, so a 5m window with a 2m step will use a 4m window with two datapoints. If the step size is larger than the window, then the window will be a single datapoint and the input is passed through unchanged. The window must be positive.

Behavior

  • Minimum selection: Returns the lowest value in the current window
  • Missing data: NaN values are ignored in the calculation
  • All NaN window: If all values in window are NaN, emits NaN

Alerting Example

Using rolling min to establish recent low baseline:

name,sps,:eq,:sum,
:dup,
5,:rolling-min

This creates both the current value and its recent minimum for comparison.

Data Processing Example

Input 3,:rolling-min
0 0
1 0
-1 -1
NaN -1
0 -1
1 0
1 0
1 1
1 1
0 0

Examples

5-point rolling minimum:

BeforeAfter
name,sps,:eq,
:sum

name,sps,:eq,
:sum,
5,:rolling-min

Since: 1.6