3.5

MaskDetectors v1

../_images/MaskDetectors-v1_dlg.png

MaskDetectors dialog.

Summary

An algorithm to mask a detector, or set of detectors, as not to be used. The workspace spectra associated with those detectors are zeroed.

Properties

Name Direction Type Default Description
Workspace InOut Workspace Mandatory The name of the input and output workspace on which to perform the algorithm.
SpectraList Input int list   An ArrayProperty containing a list of spectra to mask
DetectorList Input int list   An ArrayProperty containing a list of detector ID’s to mask
WorkspaceIndexList Input unsigned int list   An ArrayProperty containing the workspace indices to mask
MaskedWorkspace Input MatrixWorkspace   If given but not as a SpecialWorkspace2D, the masking from this workspace will be copied. If given as a SpecialWorkspace2D, the masking is read from its Y values.
StartWorkspaceIndex Input number 0 The index of the first workspace index of input MaskedWorkspace to be included in the calculation. Default is 0.
EndWorkspaceIndex Input number Optional The index number of the last workspace index of input MaskedWorkspace to be included in the calculation. Default is the last histogram.

Description

This algorithm will flag the detectors listed as masked(IDetector::isMasked() method) and will zero the data in the spectra for MatrixWorkspaces related to those detectors. For PeaksWorkspaces, only the detectors listed are masked and the mask must be specified by a DetectorList or MaskedWorkspace.

All but the first property are optional and at least one of them must be set. If several are set, the first will be used.

The set of detectors to be masked can be given as a list of either spectrum numbers, detector IDs or workspace indices. The list should be set against the appropriate property.

Mask Detectors According To Instrument

If the input MaskedWorkspace is not a SpecialWorkspace2D object, this algorithm will check every detectors in input MaskedWorkspace’s Instrument. If the detector is masked, then the corresponding detector will be masked in Workspace.

Mask Detectors According to Masking Workspace

If the input MaskedWorkspace is a MaskWorkspace object, i.e., masking workspace, then the algorithm will mask Workspace’s detector according to the histogram data of the SpecialWorkspace2D object.

Definition of Mask

  • If a pixel is masked, it means that the data from this pixel won’t be used. In the masking workspace (i.e., SpecialWorkspace2D), the corresponding value is 1.
  • If a pixel is NOT masked, it means that the data from this pixel will be used. In the masking workspace (i.e., SpecialWorkspace2D), the corresponding value is 0.

About Input Parameters

MaskDetectors v1 supports various format of input to mask detectors, including

  • Workspace indices
  • Spectra
  • Detectors
  • MaskWorkspace
  • General MatrixWorkspace other than MaskWorkspace (In this case, the mask will be extracted from this workspace)

Rules

Here are the rules for input information for masking

  1. At least one of the inputs must be specified.
  2. Workspace indices and Spectra cannot be given at the same time.
  3. MaskWorkspace and general MatrixWorkspace cannot be given at the same time.
  4. When a general MatrixWorkspace is specified, then all detectors in a spectrum are treated as masked if the effective detector of that spectrum is masked.
  5. The masks specified from
    1. workspace indices/spectra
    2. detectors
    3. MaskWorkspace /general MatrixWorkspace will be combined by the plus operation.

Operations Involved in Masking

There are 2 operations to mask a detector and thus spectrum related

  1. Set the detector in workspace’s instrument’s parameter map to masked.
  2. Clear the data associated with the spectrum with detectors that are masked.

Implementation

In the plan, the workflow to mask detectors should be

  1. Convert input detectors, workspace indices or spectra, and general MatrixWorkspace to a MaskWorkspace.
  2. Mask detectors according to MaskWorkspace.
  3. Clear data on all spectra, which have at least one detector that is masked.

Concern

  • Speed!

Usage

Example 1: specifying spectrum numbers

import numpy as np

# Create a workspace containing some data.
ws = CreateSampleWorkspace()
# Mask two detectors by specifying numbers 1 and 3
MaskDetectors(ws,SpectraList=[1,3])

# Check that spectra with spectrum numbers 1 and 3 are masked

# Get the 1st spectrum in the workspace
spec = ws.getSpectrum(0)
detid = spec.getDetectorIDs()[0]
print 'Spectrum number is',spec.getSpectrumNo()
print 'Detector of this spectrum is masked:',ws.getInstrument().getDetector(detid).isMasked()
y = ws.readY(0)
print 'All counts in the spectrum are 0:   ',np.all( y == 0.0 )

# Get the 2nd spectrum in the workspace
spec = ws.getSpectrum(1)
detid = spec.getDetectorIDs()[0]
print 'Spectrum number is',spec.getSpectrumNo()
print 'Detector of this spectrum is masked:',ws.getInstrument().getDetector(detid).isMasked()
y = ws.readY(1)
print 'All counts in the spectrum are 0:   ',np.all( y == 0.0 )

# Get the 3rd spectrum in the workspace
spec = ws.getSpectrum(2)
detid = spec.getDetectorIDs()[0]
print 'Spectrum number is',spec.getSpectrumNo()
print 'Detector of this spectrum is masked:',ws.getInstrument().getDetector(detid).isMasked()
y = ws.readY(2)
print 'All counts in the spectrum are 0:   ',np.all( y == 0.0 )

# Get the 4th spectrum in the workspace
spec = ws.getSpectrum(3)
detid = spec.getDetectorIDs()[0]
print 'Spectrum number is',spec.getSpectrumNo()
print 'Detector of this spectrum is masked:',ws.getInstrument().getDetector(detid).isMasked()
y = ws.readY(3)
print 'All counts in the spectrum are 0:   ',np.all( y == 0.0 )

Output

Spectrum number is 1
Detector of this spectrum is masked: True
All counts in the spectrum are 0:    True
Spectrum number is 2
Detector of this spectrum is masked: False
All counts in the spectrum are 0:    False
Spectrum number is 3
Detector of this spectrum is masked: True
All counts in the spectrum are 0:    True
Spectrum number is 4
Detector of this spectrum is masked: False
All counts in the spectrum are 0:    False

Example 2: specifying detector IDs

# Create a workspace containing some data.
ws = CreateSampleWorkspace()
# Mask two detectors by specifying detector IDs 101 and 103
MaskDetectors(ws,DetectorList=[101,103])

# Check that spectra with spectrum numbers 1 and 3 are masked

# Check the 1st detector
det = ws.getInstrument().getDetector(101)
print 'Detector ',det.getID(),' is masked:',det.isMasked()

# Check the 2nd detector
det = ws.getInstrument().getDetector(103)
print 'Detector ',det.getID(),' is masked:',det.isMasked()

# Check some other detectors
det = ws.getInstrument().getDetector(100)
print 'Detector ',det.getID(),' is masked:',det.isMasked()
det = ws.getInstrument().getDetector(102)
print 'Detector ',det.getID(),' is masked:',det.isMasked()
det = ws.getInstrument().getDetector(105)
print 'Detector ',det.getID(),' is masked:',det.isMasked()

Output

Detector  101  is masked: True
Detector  103  is masked: True
Detector  100  is masked: False
Detector  102  is masked: False
Detector  105  is masked: False

Example 3: specifying workspace indices

# Create a workspace containing some data.
ws = CreateSampleWorkspace()
# Mask two detectors by specifying workspace indices 0 and 2
MaskDetectors(ws,WorkspaceIndexList=[0,2])

# Check that spectra with workspace indices 0 and 2 are masked

# Check the 1st spectrum
workspaceIndex = 0
det = ws.getDetector( workspaceIndex )
print 'Detector in spectrum with workspace index ',workspaceIndex,' is masked:',det.isMasked()

# Check the 2nd spectrum
workspaceIndex = 2
det = ws.getDetector( workspaceIndex )
print 'Detector in spectrum with workspace index ',workspaceIndex,' is masked:',det.isMasked()

# Check some other spectra
workspaceIndex = 1
det = ws.getDetector( workspaceIndex )
print 'Detector in spectrum with workspace index ',workspaceIndex,' is masked:',det.isMasked()
workspaceIndex = 3
det = ws.getDetector( workspaceIndex )
print 'Detector in spectrum with workspace index ',workspaceIndex,' is masked:',det.isMasked()
workspaceIndex = 4
det = ws.getDetector( workspaceIndex )
print 'Detector in spectrum with workspace index ',workspaceIndex,' is masked:',det.isMasked()

Output

Detector in spectrum with workspace index  0  is masked: True
Detector in spectrum with workspace index  2  is masked: True
Detector in spectrum with workspace index  1  is masked: False
Detector in spectrum with workspace index  3  is masked: False
Detector in spectrum with workspace index  4  is masked: False

Example 4: specifying a masking workspace

# Create a masking workspace

# Create a intermediate workspace to help create the masking workspace
tmp = CreateSampleWorkspace()
# Mask two detectors
MaskDetectors(tmp,WorkspaceIndexList=[1,3])
# Extract created mask into specialised masking workspace
masking_ws,dummy = ExtractMask( tmp )

print 'A masking workspace has',masking_ws.blocksize(),'spectrum'
print 'Unmasked spectrum, value=',masking_ws.readY(0)[0]
print 'Masked spectrum,   value=',masking_ws.readY(1)[0]
print 'Unmasked spectrum, value=',masking_ws.readY(2)[0]
print 'Masked spectrum,   value=',masking_ws.readY(3)[0]
print 'Unmasked spectrum, value=',masking_ws.readY(4)[0]
print

# Create a data workspace
ws = CreateSampleWorkspace()
# Mask it using the mask in masking_ws
MaskDetectors(ws, MaskedWorkspace=masking_ws)

# Check masking of first 5 detectors
det = ws.getDetector(0)
print 'Detector',det.getID(),'is masked:',det.isMasked()
det = ws.getDetector(1)
print 'Detector',det.getID(),'is masked:',det.isMasked()
det = ws.getDetector(2)
print 'Detector',det.getID(),'is masked:',det.isMasked()
det = ws.getDetector(3)
print 'Detector',det.getID(),'is masked:',det.isMasked()
det = ws.getDetector(4)
print 'Detector',det.getID(),'is masked:',det.isMasked()

Output

A masking workspace has 1 spectrum
Unmasked spectrum, value= 0.0
Masked spectrum,   value= 1.0
Unmasked spectrum, value= 0.0
Masked spectrum,   value= 1.0
Unmasked spectrum, value= 0.0

Detector 100 is masked: False
Detector 101 is masked: True
Detector 102 is masked: False
Detector 103 is masked: True
Detector 104 is masked: False

Categories: Algorithms | Transforms | Masking

Source

C++ source: MaskDetectors.cpp

C++ header: MaskDetectors.h