ETAS MDA V8.5 - Reduction Functions

ETAS 4 Calculated Signals
The Accumulate_Samples function calculates the reduction over the last count
samples before and including the current sample. At the beginning when there
are less than count samples, all available samples are reduced.
Note: Accumulate_RollingSample<R>(input, count) = Accu-
mulate_Rolling<R>(input, State_Delay(Master(), -Infin-
ity, count))
4.4.3.3 Reduction Functions
A reduction function is a function that takes a sequence of values and calculates
a single result value, the reduction.
reduction = Reduce(value[1], …, value[n])
In the border case n=0 the reduction function is applied to an empty sequence of
values:
neutral = Reduce()
This defines a "neutral" element of the reduction.
A reduction function can be defined by repeatedly combining two values with a
combine function. For example if we use the addition as the combine function
we get the sum of the input values:
tmp[0] = 0
tmp[i] = tmp[i-1] + value[i]
reduction = tmp[n]
A reduction function can also be defined based on existing reduction functions.
Minimum
The Minimum reduction function returns the minimum of all input values:
combine(a, b) = min(a, b)
The Minimum is available for all numeric data types.
Maximum
The Maximum reduction function returns the maximum of all input values:
combine(a, b) = max(a, b)
The Maximum is available for all numeric data types.
Count
The reduction function returns the number of samples:
Count(values[1], …, values[n]) = n
Add
The Add reduction function returns the sum of all input values:
combine(a, b) = a + b
MDA V8.5 - User Guide 72