SANSILLAutoProcess v1

../_images/SANSILLAutoProcess-v1_dlg.png

SANSILLAutoProcess dialog.

Summary

Performs complete SANS data reduction at the ILL.

Properties

Name Direction Type Default Description
OutputWorkspace Output WorkspaceGroup Mandatory The output workspace group containing reduced data.
SampleRuns Input list of str lists   Sample run(s). Allowed values: [‘nxs’]
AbsorberRuns Input list of str lists   Absorber (Cd/B4C) run(s). Allowed values: [‘nxs’]
BeamRuns Input list of str lists   Empty beam run(s). Allowed values: [‘nxs’]
FluxRuns Input list of str lists   Empty beam run(s) for flux calculation only; if left blank flux will be calculated from BeamRuns. Allowed values: [‘nxs’]
ContainerRuns Input list of str lists   Empty container run(s). Allowed values: [‘nxs’]
SampleTransmissionRuns Input list of str lists   Sample transmission run(s). Allowed values: [‘nxs’]
ContainerTransmissionRuns Input list of str lists   Container transmission run(s). Allowed values: [‘nxs’]
TransmissionBeamRuns Input list of str lists   Empty beam run(s) for transmission. Allowed values: [‘nxs’]
TransmissionAbsorberRuns Input list of str lists   Absorber (Cd/B4C) run(s) for transmission. Allowed values: [‘nxs’]
ThetaDependent Input boolean True Whether or not to use 2theta dependent transmission correction
SensitivityMaps Input string   File(s) or workspaces containing the maps of relative detector efficiencies.
DefaultMaskFile Input string   File or workspace containing the default mask (typically the detector edges and dead pixels/tubes) to be applied to all the detector configurations.
MaskFiles Input string   File(s) or workspaces containing the detector mask (typically beam stop).
ReferenceFiles Input string   File(s) or workspaces containing the corrected water data (in 2D) for absolute normalisation.
SensitivityOutputWorkspace Output MatrixWorkspace   The output sensitivity map workspace.
NormaliseBy Input string Timer Choose the normalisation type. Allowed values: [‘None’, ‘Timer’, ‘Monitor’]
SampleThickness Input number 0.1 Sample thickness [cm]
BeamRadius Input number 0.05 Beam radius [m]; used for beam center finding, transmission and flux calculations.
WaterCrossSection Input number 1 Provide water cross-section; used only if the absolute scale is done by dividing to water.
MaxQxy Input dbl list -1 Maximum of absolute Qx and Qy.
DeltaQ Input dbl list -1 The dimension of a Qx-Qy cell.
OutputPanels Input boolean False Whether or not process the individual detector panels.
OutputType Input string I(Q) Choose the output type. Allowed values: [‘I(Q)’, ‘I(Qx,Qy)’, ‘I(Phi,Q)’]
CalculateResolution Input string None Choose to calculate the Q resolution. Allowed values: [‘MildnerCarpenter’, ‘None’]
DefaultQBinning Input string PixelSizeBased Choose how to calculate the default Q binning. Allowed values: [‘PixelSizeBased’, ‘ResolutionBased’]
BinningFactor Input number 1 Specify a multiplicative factor for default Q binning (pixel or resolution based).
OutputBinning Input dbl list   The manual Q binning of the output
NPixelDivision Input number 1 Number of subpixels to split the pixel (NxN)
NumberOfWedges Input number 0 Number of wedges to integrate separately.
WedgeAngle Input number 30 Wedge opening angle [degrees].
WedgeOffset Input number 0 Wedge offset angle from x+ axis.
AsymmetricWedges Input boolean False Whether to have asymmetric wedges.
IQxQyLogBinning Input boolean False I(Qx, Qy) log binning when binning is not specified.
ClearCorrected2DWorkspace Input boolean True Whether to clear the fully corrected 2D workspace.

Description

This algorithms performs complete treatment of SANS data recorded with the ILL instruments D11, D22 and D33. This high level algorithm steers the reduction and performs the full set of corrections for a given sample run; measured with one or more detector distances.

The sample measurement will be corrected for all the effects and converted to Q-space, producing by default the azimuthal average curve I(Q). One can use water reference measurement in order to derive the relative inter-pixel sensitivity map of the detector or the reduced water data for absolute normalisation of the subsequent samples. The regular output will contain fully corrected water run, and there will be an additional output containing the sensitivity map itself. The sensitivity map, as well as reduced water can be saved out to a file and used for sample reductions.

Caching with ADS

This algorithm does not clean-up the intermediate workspaces after execution. This is done intentionally for performance reasons. For example, once the transmission of a sample is calculated, it will be reused for further iterations of processing of the same sample at different detector distances. As other example, once the container is processed at a certain distance, it will be reused for all the subsequent samples measured at the same distance, if the container run is the same. The same caching is done for absorber, empty beam, container, sensitivity and mask workspaces. The caching relies on Analysis Data Service (ADS) through naming convention by appending the relevant process name to the run number. When multiple runs are summed, the run number of the first run is attributed to the summed workspace name.

Note

To run these usage examples please first download the usage data, and add these to your path. In Mantid this is done using Manage User Directories.

Example - full treatment of 3 samples at 3 different distances in D11

beams = '2866,2867+2868,2878'
containers = '2888+2971,2884+2960,2880+2949'
container_tr = '2870+2954'
beam_tr = '2867+2868'
samples = ['2889,2885,2881',
           '2887,2883,2879',
           '3187,3177,3167']
sample_tr = ['2871', '2869', '3172']
thick = [0.1, 0.2, 0.2]

# reduce samples
for i in range(len(samples)):
    SANSILLAutoProcess(
        SampleRuns=samples[i],
        BeamRuns=beams,
        ContainerRuns=containers,
        MaskFiles='mask1.nxs,mask2.nxs,mask3.nxs',
        SensitivityMaps='sens-lamp.nxs',
        SampleTransmissionRuns=sample_tr[i],
        ContainerTransmissionRuns=container_tr,
        TransmissionBeamRuns=beam_tr,
        SampleThickness=thick[i],
        OutputWorkspace='iq_s' + str(i + 1)
    )

print('Distance 1 Q-range:{0:4f}-{1:4f} AA'.format(mtd['iq_s1_1'].readX(0)[0], mtd['iq_s1_1'].readX(0)[-1]))
print('Distance 2 Q-range:{0:4f}-{1:4f} AA'.format(mtd['iq_s1_2'].readX(0)[0], mtd['iq_s1_2'].readX(0)[-1]))
print('Distance 3 Q-range:{0:4f}-{1:4f} AA'.format(mtd['iq_s1_3'].readX(0)[0], mtd['iq_s1_3'].readX(0)[-1]))

Output:

Distance 1 Q-range:0.001440-0.020011 AA
Distance 2 Q-range:0.007263-0.091701 AA
Distance 3 Q-range:0.033776-0.342831 AA

Example 2 - full treatment of 5 samples in D33

from mantid.simpleapi import *
import matplotlib.pyplot as plt

config.setFacility('ILL')
config['default.instrument'] = 'D33'
config.appendDataSearchSubDir('ILL/D33/')

absorber = '002227'

tr_beam = '002192'

can_tr = '002193'

empty_beam = '002219'

can = '002228'

mask = 'D33Mask2.nxs'

sample_names = ['H2O', 'D2O', 'AgBE', 'F127_D2O', 'F127_D2O_Anethol']
sample_legends = ['H$_2$O', 'D$_2$O', 'AgBE', 'F127 D$_2$O', 'F127 D$_2$O Anethol']

samples = ['002229', '001462', '001461', '001463', '001464']

transmissions = ['002194', '002195', '', '002196', '002197']

# Autoprocess every sample
for i in range(len(samples)):
    SANSILLAutoProcess(
        SampleRuns=samples[i],
        SampleTransmissionRuns=transmissions[i],
        MaskFiles=mask,
        AbsorberRuns=absorber,
        BeamRuns=empty_beam,
        ContainerRuns=can,
        ContainerTransmissionRuns=can_tr,
        TransmissionBeamRuns=tr_beam,
        CalculateResolution='None',
        OutputWorkspace=sample_names[i]
    )

fig, ax = plt.subplots(subplot_kw={'projection':'mantid'})

plt.yscale('log')
plt.xscale('log')

# Plot the result of every autoprocess
for wName in sample_names:
    ax.errorbar(mtd[wName][0])

plt.legend(sample_legends)
ax.set_ylabel('d$\sigma$/d$\Omega$ ($cm^{-1}$)')

#fig.show()

(Source code, png, hires.png, pdf)

../_images/SANSILLAutoProcess-v1-1.png

Categories: AlgorithmIndex | ILL\SANS | ILL\Auto

Source

Python: SANSILLAutoProcess.py (last modified: 2020-09-10)