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OSIRISDiffractionReduction v1

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Summary

This Python algorithm performs the operations necessary for the reduction of diffraction data from the Osiris instrument at ISIS into dSpacing, by correcting for the monitor and linking the various d-ranges together.

See Also

ISISIndirectDiffractionReduction

Properties

Name	Direction	Type	Default	Description
Sample	Input	str list		The list of run numbers that are part of the sample run. There should be five of these in most cases. Enter them as comma separated values.
Vanadium	Input	str list		The list of run numbers that are part of the sample run. There should be five of these in most cases. Enter them as comma separated values.
Container	Input	str list		The list of run numbers that are part of the sample run. There should be five of these in most cases. Enter them as comma separated values.
ContainerScaleFactor	Input	number	1	Factor by which to scale the container
CalFile	Input	string	Mandatory	Filename of the .cal file to use in the [[AlignDetectors]] and [[DiffractionFocussing]] child algorithms.
SpectraMin	Input	long	3	Minimum Spectrum to Load from (Must be more than 3)
SpectraMax	Input	long	962	Maximum Spectrum to Load from file (Must be less than 962)
OutputWorkspace	Output	MatrixWorkspace	Mandatory	Name to give the output workspace. If no name is provided, one will be generated based on the run numbers.
LoadLogFiles	Input	boolean	True	Load log files when loading runs

Description

Performs a diffraction reduction for OSIRIS using normalisation to a set of vanadium sample runs.

The dRanges are numbered as per the OSIRIS manual. Otherwise the dRange is determined based on the table provided in the manual.

Workflow

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Usage

Example - Running OSIRISDiffractionReduction.

import os

def createDummyOSIRISWorkspace(name, func, xmin, xmax, bin_width):
  """Creates a workspace that looks something like an OSIRIS diffraction run"""
  #create workspace according to function
  ws = CreateSampleWorkspace("Histogram", Function="User Defined", UserDefinedFunction=func, XMin=xmin, XMax=xmax, Random=True, BinWidth=bin_width, NumBanks=11, OutputWorkspace=name)
  ws = CropWorkspace(ws, StartWorkspaceIndex=0, EndWorkspaceIndex=1009, OutputWorkspace=name)
  AddSampleLog(ws, 'gd_prtn_chrg', '30.01270866394043',  'Number')

  #load instrument parameters
  LoadInstrument(ws, RewriteSpectraMap=True, InstrumentName='OSIRIS')
  param_file = config['instrumentDefinition.directory'] + 'OSIRIS_diffraction_diffspec_Parameters.xml'
  LoadParameterFile(ws, Filename=param_file)
  return ws

#create two dummy workspaces with one peak
function = "name=Lorentzian, Amplitude=350000,PeakCentre=40000, FWHM=80"
ws1 = createDummyOSIRISWorkspace('ws1', function, 1.17e+04, 5.17e+04, 4.7)
ws2 = createDummyOSIRISWorkspace('ws2', function, 29400, 69400, 16.1)

#create two vanadium runs
function = "name=FlatBackground, A0=10"
van1 = createDummyOSIRISWorkspace('van1', function, 1.17e+04, 5.17e+04, 4.7)
van2 = createDummyOSIRISWorkspace('van2', function, 29400, 69400, 16.1)

samples = [ws1.name(),  ws2.name() ]
vanadium = [van1.name(), van2.name()]

#OSIRISDiffractionReduction currently only support loading from file.
for ws in (samples + vanadium):
  path = os.path.join(os.path.expanduser("~"), ws + ".nxs")
  SaveNexus(ws, path)

#run OSIRISDiffractionReduction
samples = [os.path.join(os.path.expanduser("~"), sample + ".nxs") for sample in samples]
vanadium = [os.path.join(os.path.expanduser("~"), van  + ".nxs") for van in vanadium]
ws = OSIRISDiffractionReduction(Sample=','.join(samples), Vanadium=','.join(vanadium), CalFile="osiris_041_RES10.cal")

print("Number of Spectra: {}, Number of bins: {}".format(ws.getNumberHistograms(), ws.blocksize()))

Output:

Number of Spectra: 1, Number of bins: 7581

Categories: AlgorithmIndex | Diffraction\Reduction

Source

Python: OSIRISDiffractionReduction.py