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SumEventsByLogValue v1¶

Summary ¶

Produces a single spectrum workspace containing the total summed events in the workspace as a function of a specified log.

Properties ¶

Name	Direction	Type	Default	Description
InputWorkspace	Input	EventWorkspace	Mandatory	The input EventWorkspace. Must contain ‘raw’ (unweighted) events
MonitorWorkspace	Input	EventWorkspace		A workspace containing the monitor counts relating to the input workspace
OutputWorkspace	Output	Workspace	Mandatory	The name of the workspace to be created as the output of the algorithm. The output workspace will be a [[TableWorkspace]] in the case that a log holding integer values is given, and a single-spectrum [[Workspace2D]] otherwise.
LogName	Input	string	Mandatory	The name of the number series log against which the data should be summed
OutputBinning	Input	dbl list		Binning parameters for the output workspace (see [[Rebin]] for syntax) (Optional for logs holding integer values, mandatory otherwise)

Description ¶

This algorithm counts up the events in a workspace against the values of a log within the workspace. It will most commonly be used as a sub-algorithm of the StepScan algorithm.

The algorithm has two modes:

This option can be used for integer-typed logs and will produce a table with a row for each integer value between the minimum and maximum contained in the log, and a further column containing the total events for which the log had each value. Further columns will be added for:

Monitors, if any - this requires an event workspace with the same name as the input workspace plus a ‘_monitors’ suffix (this is what LoadEventNexus v1 will give).
The total time duration, in seconds, during which the log had each value.
The integrated proton charge during the period(s) for which the log had each value.
The time-weighted average value of any other number-series logs which had more than a single value during the run.

Warning: This mode is intended for logs with a small range (e.g. scan index, period number, status). Be aware that if it is used for a log with a large range, it will create a table row for every integer value between the minimum and maximum log value. This might take a long time!

Single-spectrum option ¶

This option can be used for integer or floating point type logs and requires that the OutputBinning property is specified. It will produce a single spectrum workspace where the X values are derived from the OutputBinning property and the Y values are the total counts in each bin of the log value.

Usage ¶

Example - Single-Spectrum Mode

# a sample workspace with a sample instrument
ws = CreateSampleWorkspace("Event",BankPixelWidth=1)

AddTimeSeriesLog(ws, Name="Log2FilterBy", Time="2010-01-01T00:00:00", Value=1)
AddTimeSeriesLog(ws, Name="Log2FilterBy", Time="2010-01-01T00:10:00", Value=2)
AddTimeSeriesLog(ws, Name="Log2FilterBy", Time="2010-01-01T00:20:00", Value=3)
AddTimeSeriesLog(ws, Name="Log2FilterBy", Time="2010-01-01T00:30:00", Value=1)
AddTimeSeriesLog(ws, Name="Log2FilterBy", Time="2010-01-01T00:40:00", Value=2)
AddTimeSeriesLog(ws, Name="Log2FilterBy", Time="2010-01-01T00:50:00", Value=3)

#split the events by the log value
wsOut = SumEventsByLogValue(ws,LogName="Log2FilterBy",OutputBinning=[1,1,4])

#all of the events should be included
integral = Integration(wsOut)
print("Events were split into %i sections based on the log 'Log2FilterBy'." % wsOut.blocksize())
for i in range(0,wsOut.blocksize()):
  print(" section %i: %.2f" % (i+1,wsOut.readY(0)[i]))
print("Totalling %.0f events, matching the %i events in the input workspace" % (integral.readY(0)[0],ws.getNumberEvents()))

Output:

Events were split into 3 sections based on the log 'Log2FilterBy'.
 section 1: 6...
 section 2: 6...
 section 3: 6...
Totalling 1900 events, matching the 1900 events in the input workspace

Categories: AlgorithmIndex | Events