4.0

EstimateDivergence v1

../_images/EstimateDivergence-v1_dlg.png

EstimateDivergence dialog.

Summary

Estimate the divergence of each detector pixel

Properties

Name Direction Type Default Description
InputWorkspace Input MatrixWorkspace Mandatory Workspace to have divergence calculated from
alpha Input number 0 Vertical divergence parameter
beta0 Input number 0 Horizontal divergence parameter
beta1 Input number 0 Other horizontal divergence parameter
OutputWorkspace Output MatrixWorkspace Mandatory Workspace containing the divergence of each detector/spectrum

Description

This algorithm estimates the divergence of a diffraction instrument using equation 6.9 of Windsor

\Delta\theta_{div} = \frac{1}{2} \sqrt{\Delta(2\theta)^2 + \alpha_0 + \frac{4\left(\beta_0^2 + \beta_1^2\right)}{\sin^2(2\theta)}}

Where \Delta\theta_{div} is the divergence, \Delta(2\theta) is the angular uncertainty due to the detector size, \alpha_0 is the uncertainty in the incident collimation in the scattering plane, and the \beta terms are the angular uncertainties out of the scattering plane for the incident and scattered beam.

The results of this calculation can be supplied as an optional workspace to EstimateResolutionDiffraction.

Usage

Example - EstimateDivergence

LoadEmptyInstrument(Filename='POWGEN_Definition_2017-05-01.xml', OutputWorkspace='PG3')
ws = EstimateDivergence(InputWorkspace='PG3')

# Print the result
print("The output workspace has {} spectra".format(ws.getNumberHistograms()))

Output:

The output workspace has 43121 spectra

References

  1. Windsor, C. G. Pulsed Neutron Scattering. London: Taylor & Francis, 1981. Print. ISBN-10: 0470271310, ISBN-13: 978-0470271315

See also

Algorithm EstimateResolutionDiffraction v1

Categories: Algorithm Index | Diffraction\Utility

Source

C++ source: EstimateDivergence.cpp (last modified: 2018-10-05)

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