ConvertCWSDExpToMomentum v1

../_images/ConvertCWSDExpToMomentum-v1_dlg.png

ConvertCWSDExpToMomentum dialog.

Summary

Load and convert a set of files in an HB3A experiment.

Properties

Name Direction Type Default Description
InputWorkspace Input TableWorkspace Mandatory Name of table workspace for data file names in the experiment.
InstrumentFilename Input string   Allowed extensions: [‘.xml’]
DetectorSampleDistanceShift Input number 0 Amount of shift in sample-detector distance from 0.3750 meter.
DetectorCenterXShift Input number 0 Amount of shift of detector center in X-direction from (115, 128).
DetectorCenterYShift Input number 0 Amount of shift of detector center in Y-direction from (115, 128).
UserDefinedWavelength Input number Optional User defined wave length if it is specified.
CreateVirtualInstrument Input boolean False Flag to create virtual instrument.
DetectorTableWorkspace Input TableWorkspace   Name of table workspace containing all the detectors.
OutputWorkspace Output MDEventWorkspace Mandatory Name of MDEventWorkspace containing all experimental data.
SourcePosition Input dbl list   A vector of 3 doubles for position of source.
SamplePosition Input dbl list   A vector of 3 doubles for position of sample.
PixelDimension Input dbl list   A vector of 8 doubles to determine a cubic pixel’s size.
IsBaseName Input boolean True It is specified as true if the data file names listed in InputWorkspace are base name without directory.
BackgroundWorkspace Input MatrixWorkspace   Name of optional background workspace.
Directory Input string   Directory where data files are if InputWorkspace gives data file name as the base file name as indicated by ‘IsBaseName’.

Description

This algorithms is to convert an experiment done on reactor-based four-circle instrument (such as HFIR HB3A) to a MDEventWorkspace with each MDEvent in momentum space.

In this algorithm’s name, ConvertCWSDToMomentum, CW stands for constant wave (reactor-source instrument); SD stands for single crystal diffraction.

This algorithm takes ??? as inputs.

Furthermore, the unit of the output matrix workspace can be converted to momentum transfer (Q).

Outline of algorithm

  1. Create output workspace
  • Build a virtual instrument, requiring
    • position of source
    • position of sample
    • detector ID, position, detector size of pixels
  1. Read in data via table workspace
  • From each row, (1) file name and (2) starting detector ID are read in.
  • Detector position in (virtual) instrument of MDEventWorkspace is compared with the position in MatrixWorkspace
  • Momentum is calculated by goniometry values

Input Workspaces

Two TableWorkspaces, which contain experiment information, are required.

InputWorkspace is a TableWorkspace containing the data files names to be loaded for the experiment. It is required to have 4 columns. They are Scan, Pt, Filename and StartDetID respectively.

A typical HB3A experiment consists of multiple scans, each of which contains multiple measurement point (i.e., Pt). FileName is the XML data file for 2D detector information for a specific Scan/Pt pair. StartDetID is the starting detector ID of a specific Scan/Pt mapped to the virtual instrument.

DetectorTableWorkspace is a TableWorkspace that list the parameters of all detector pixels belonged to the virtual instrument. The parameters include detector ID in virtual instrument, detector’s position in cartesian coordinate, and detector’s original detector ID.

Outputs

The output is an MDEventWorkspace that stores the data of an HB3A experiment. Every non-zero count recorded by detector is converted to an MDEvent in the output workspace.

MDEvent

Each MDEvent in output MDEventWorkspace contain * Kx * Ky * Kz * Signal * Error * Detector ID * Run Number

Combine Experiment Into One MDEventWorkspace

One typical HB3A (reactor-based four-circle diffractometer) experiment consists of a set of scans, each of which contains multiple experiment point (labeled as Pt. in SPICE).

Each experiment point is independent to the others. They can have various detector positions, goniometer setup and even sample environment setup.

In order to integrate them into an organized data structure, i.e., MDEventWorkspace, a virtual instrument is built in the algorithm.

Virtual instrument

A virtual instrument is built in the algorithm. In this virtual instrument, the number of detectors and their position are determined by the number of individual detector’s positions in the experiment.

MDEventWorkspace

There is only one virtual instrument and N ExperimentInfo. N is the total number of experiment points in the experiment.

Inconsistency between using virtual instrument and copying instrument

It is found that the results, i.e., the peak’s position in sample-momentum space, by FindPeaksMD, are different betweent the MDEventWorkspaces output by this algorithm with copying instrument or creating virtual instrument.

It is caused by the difference of the instruments in the MDEventWorkspace. The native HB3A’s detector is of type RectangularDetector, while the virtual instrument’s detector is just of class ComAssembly.

FindPeaksMD calculates the centre of the mass for peak centre, and then locates the nearest pixel of the peak center and re-define the position of the pixel as peak center.

For virtual instrument, CompAssembly::testIntersectionWithChildren() is used to find the pixel’s position; while for rectangular detector, RectangularDetector::testIntersectionWithChildren() is used. Due to the difference in algorithm, there is slightly difference between the position of the pixel found.

Use cases

It is found that creating an instrument with tens of thousands detectors is very time consuming in Mantid. It is caused by creating a map upon these detectors. With this generation of Mantid, there is no simple solution for it.

For HB3A, there are usually 2\theta scan, \omega scan and \phi. Only the 2\theta scan requires to create virtual instrument, while the MDEventWorkspace can be created by copying instrument instance from parent MatrixWorkspace for the other type of scans.

Therefore, it is suggested to do \omega and \phi scans for HB3A with 2D angular detector.

Usage

Example - convert an HB3A’s experiment to MDWorkspace in sample momentum workspae and creating virtual instrument

# Create input table workspaces for experiment information and virtual instrument parameters
CollectHB3AExperimentInfo(ExperimentNumber='355', ScanList='11', PtLists='-1,11',
    DataDirectory='',
    GenerateVirtualInstrument = True,
    OutputWorkspace='ExpInfoTable', DetectorTableWorkspace='VirtualInstrumentTable')

# Convert to MDWorkspace
ConvertCWSDExpToMomentum(InputWorkspace='ExpInfoTable', DetectorTableWorkspace='VirtualInstrumentTable',
    CreateVirtualInstrument = True,
    OutputWorkspace='QSampleMD', SourcePosition='0,0,2', SamplePosition='0,0,0', PixelDimension='1,2,2,3,3,4,3,3',
    Directory='')

# Find peak in the MDEventWorkspace
FindPeaksMD(InputWorkspace='QSampleMD', DensityThresholdFactor=0.10000000000000001,
    OutputWorkspace='PeakTable')

# Examine
mdws = mtd['QSampleMD']
print('Output MDEventWorkspace has {} events.'.format(mdws.getNEvents()))
peakws = mtd['PeakTable']
print('There are {} peaks found in output MDWorkspace'.format(peakws.getNumberPeaks()))
peak = peakws.getPeak(0)
qsample = peak.getQSampleFrame()
print('In Q-sample frame, center of peak 0 is at ({:.5f}, {:.5f}, {:.5f}) at detector with ID {}'.
    format(qsample.X(), qsample.Y(), qsample.Z(), peak.getDetectorID()))

Output:

Output MDEventWorkspace has 397 events.
There are 1 peaks found in output MDWorkspace
In Q-sample frame, center of peak 0 is at (-6.93624, -0.08360, 8.16733) at detector with ID 35723

Example - convert an HB3A experiment to MDEventWorkspace by copying instrument.:

# Create input table workspaces for experiment information and virtual instrument parameters
CollectHB3AExperimentInfo(ExperimentNumber='355', ScanList='11', PtLists='-1,11',
    DataDirectory='',
    GenerateVirtualInstrument=False,
    OutputWorkspace='ExpInfoTable', DetectorTableWorkspace='VirtualInstrumentTable')

# Convert to MDWorkspace
ConvertCWSDExpToMomentum(InputWorkspace='ExpInfoTable',
    CreateVirtualInstrument = False,
    OutputWorkspace='QSampleMD', Directory='')

# Find peak in the MDEventWorkspace
FindPeaksMD(InputWorkspace='QSampleMD', DensityThresholdFactor=0.10000000000000001,
    OutputWorkspace='PeakTable')

# Examine
mdws = mtd['QSampleMD']
print('Output MDEventWorkspace has {} events.'.format(mdws.getNEvents()))
peakws = mtd['PeakTable']
print('There are {} peaks found in output MDWorkspace'.format(peakws.getNumberPeaks()))
peak = peakws.getPeak(0)
qsample = peak.getQSampleFrame()
print('In Q-sample frame, center of peak 0 is at ({:.5f}, {:.5f}, {:.5f}) at detector with ID {}'.
    format(qsample.X(), qsample.Y(), qsample.Z(), peak.getDetectorID()))

Output:

Output MDEventWorkspace has 397 events.
There are 1 peaks found in output MDWorkspace
In Q-sample frame, center of peak 0 is at (-3.58246, -4.40802, -3.06320) at detector with ID 32881

Categories: AlgorithmIndex | Diffraction\ConstantWavelength | DataHandling\Text

Source

C++ source: ConvertCWSDExpToMomentum.cpp (last modified: 2019-07-17)

C++ header: ConvertCWSDExpToMomentum.h (last modified: 2018-10-05)