Aggregating Data with Sliding Windows in Seeq

[Lindsey.Wilcox]

There are many cases where a moving average needs to be monitored. To create any statistic that is associated with a sliding time frame, first use the periods() function in Formula to create the periodic capsules. A few examples are listed below.

Intent	Seeq Formula
30 day average every 1 day	periods(30d,1d)
24 hour average every 1 hour	periods(1d,1h)
30 minute average every 5 minutes	periods(30min,5min)

Once the periodic condition is created, use Signal from Condition to calculate a moving average, max, min, or other statistic.

The sliding capsules will appear overlapped in the capsules lane. Refer to the capsules pane to verify the capsules meet your expectation of start time and duration, then apply the desired "moving" aggregation (average, standard deviation, etc.) to any signal with the Signal from Condition tool. Below shows a moving 30 minute average sampled every 5 minutes on the Example Temperature data.

[Lindsey.Wilcox]

In Seeq Version R21.0.42, a .movingAverageFilter() operator was introduced in Formula.  This operator smooths a signal by averaging values with their neighboring values.  Its important to note that this operator is intended to smooth a signal.  The aggregate operator should be used for computing averages on a periodic basis, such as hourly or daily moving averages.

The following example uses the .movingAverageFilter() operator to resample the Temperature signal to 5 minutes and use a window size of 30 min.