ETAS MDA V8.6 User Manual page 75

ETAS
result = Accumulate_Rolling_<reduction function>
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(input, range)
Arguments:
T result: the reduction function applied to the given range
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T input: the signal to be reduced
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double range: a sequence of ranges
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Note: T can be any type supported by the given reduction function.
Accumulate_Rolling(input, windowStart)
The Accumulate_Rolling behavior applies the reduction function to a moving
window. The windowStart signal specifies a window (see "Ranges" on the pre-
vious page). For each range, the samples in that range from the input signal
are reduced according to the reduction function and produce an output
sample which has the same timestamp as the end of the range.
Examples:
Rolling average over the last 2 seconds:
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Accumulate_Rolling_Average(input, Master()-2)
Rolling average over the last 10 samples:
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Accumulate_Rolling_Average(input, State_Delay(Master
(), 0, 10))
Notes:
The memory usage of accumulate rolling behavior grows with the num-
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ber of samples in the window. It is possible to use windowStart = 0, how-
ever each new sample will increase the memory. Depending on the
input signal, this may lead to using significant amounts of memory.
For correct functionality, the start times of the ranges must be mono-
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tonously increasing.
Window_Signal
Calculates a window with a given "size".
Syntax:
Window_Signal_<reduction function>(input, limit)
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Arguments:
double result: ranges of input that have the given size of limit
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T input: the input signal that is reduced to determine the size of a win-
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dow
T limit: desired "size" of the calculated ranges
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Note: T can be any type supported by the given reduction function.
MDA V8.6 – User Guide
4 Calculated Signals
75