Q1DWeighted v1¶

Q1DWeighted dialog.

Table of Contents

Summary
- See Also
Properties
Description
Usage
I/O
Additional options
Source

Summary ¶

Performs azimuthal averaging on a 2D SANS data to produce I(Q).

Properties ¶

Name	Direction	Type	Default	Description
InputWorkspace	Input	MatrixWorkspace	Mandatory	Input workspace containing the SANS 2D data
OutputWorkspace	Output	MatrixWorkspace	Mandatory	Workspace that will contain the I(Q) data
OutputBinning	Input	dbl list	Mandatory	The new bin boundaries in the form: <math>x_1,Delta x_1,x_2,Delta x_2,dots,x_n</math>
NPixelDivision	Input	number	1	Number of sub-pixels used for each detector pixel in each direction.The total number of sub-pixels will be NPixelDivision*NPixelDivision.
NumberOfWedges	Input	number	2	Number of wedges to calculate.
WedgeAngle	Input	number	30	Opening angle of the wedge, in degrees.
WedgeOffset	Input	number	0	Wedge offset relative to the horizontal axis, in degrees.
WedgeWorkspace	Output	WorkspaceGroup		Name for the WorkspaceGroup containing the wedge I(q) distributions.
PixelSizeX	Input	number	5.15	Pixel size in the X direction (mm).
PixelSizeY	Input	number	5.15	Pixel size in the Y direction (mm).
ErrorWeighting	Input	boolean	False	Choose whether each pixel contribution will be weighted by 1/error^2.
AsymmetricWedges	Input	boolean	False	Choose to produce the results for asymmetric wedges.
AccountForGravity	Input	boolean	False	Take the nominal gravity drop into account.

Performs azimuthal averaging for a 2D SANS data set by going through each wavelength bin of each detector pixel, determining its Q-value, and adding its amplitude $I$ to the appropriate Q bin. The algorithm works both for monochromatic and TOF SANS data.

Note that the algorithm performs averaging in 2 steps. First, for each wavelength slice of the input it performs azimuthal averaging in radial rings. This results in a stack of I(Q)s, one for each input wavelength. As a second step, all the I(Q)s corresponding to different wavelengths are averaged again. Note that for the TOF data, this is mathematically not equivalent to performing averaging with one step; that is averaging everything into a single I(Q) histogram. The latter is done in Q1D algorithm. See the Rebin documentation for details about choosing the OutputBinning parameter.

Usage ¶

This algorithm is used as a part of the SANSReduction and SANSILLIntegration. However, it can also be used directly, provided that the input data is already corrected for all the effects.

I/O ¶

The input to this algorithm must be a histogram with common wavelength bins for each pixel. The output will be a distribution though.

Additional options ¶

NPixelDivision ¶

For greater precision, each detector pixel can be sub-divided in sub-pixels by setting the NPixelDivision parameters. This will split each pixel to a grid of NPixelDivision * NPixelDivision pixels. PixelSizeX and PixelSizeY inputs will be used only if pixels are to be split.

ErrorWeighting ¶

Each pixel has a weight of 1 by default, but the weight of each pixel can be set to $1/\sigma^2 I$ by setting the ErrorWeighting parameter to True. This will effectively transmute the average to a weighted average, where the weight is inversely proportional to the absolute statistical uncertainty on the intensity. This option will potentially produce very different results, so care must be taken when analysing the data with this option. In the reduction workflows this option is deprecated.

Q1DWeighted v1¶

Summary ¶

See Also ¶

Properties ¶

Description ¶

Usage ¶

I/O ¶

Additional options ¶

NPixelDivision ¶

ErrorWeighting ¶

Wedges ¶

Symmetric ¶

Asymmetric ¶

Masked Bins ¶

AccountForGravity ¶

Source ¶