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Will average event data either over an infinite time ("infinite" checked in configuration) or a settable finite number of events (generated internally using the SumN pattern). For the finite case be careful not to set N too large as it can consume a lot of memory. The PickN produces an array of numbers/1D-arrays/2D-arrays which are, respectively, 1D/2D/3D arrays (with "time" being the added dimension). AMI allows you to average over any of those axes, but users will typically want to average over axis=0 ("time"), unless you want to see an average projection (axis=1 or 2) vs. time.
This pattern is similar to an MPI "reduce" operation.
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Used to generate 1D and 2D summed histograms from per-event x (1D) or x/y (2D) coordinates. This is an infinite sum, i.e. there is currently no support for a time window). Internally it uses the Accumulator pattern (see below). See the numpy.histogram documentation for a description of the "density" parameter. This pattern is similar to an MPI "reduce" operation.
MeanVsScan, MeanWaveformVsScan
Compute Useful for either step-scans or fly-scans. Compute the mean of a value or waveform as a function of step number (for an LCLS step-scana step-scan) or the fly-scanned value (for a fly-scan). Internally uses the ReduceByKey pattern below.
SumN
Sum N events with a pattern very similar to the PickN pattern. See the PickN section below for some integer-arithmetic related subtleties. This pattern is similar to an MPI "reduce" operation.
Global Operations Typically Used Internally By AMI
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