Table of Contents
Fourier transform from S(Q) to G(r), which is paired distribution function (PDF). G(r) will be stored in another named workspace.
Name | Direction | Type | Default | Description |
---|---|---|---|---|
InputWorkspace | Input | MatrixWorkspace | Mandatory | S(Q), S(Q)-1, or Q[S(Q)-1] |
OutputWorkspace | Output | MatrixWorkspace | Mandatory | Result paired-distribution function |
InputSofQType | Input | string | S(Q) | To identify whether input function. Allowed values: [‘S(Q)’, ‘S(Q)-1’, ‘Q[S(Q)-1]’] |
Qmin | Input | number | Optional | Minimum Q in S(Q) to calculate in Fourier transform (optional). |
Qmax | Input | number | Optional | Maximum Q in S(Q) to calculate in Fourier transform. (optional) |
Filter | Input | boolean | False | Set to apply Lorch function filter to the input |
PDFType | Input | string | G(r) | Type of output PDF including G(r). Allowed values: [‘G(r)’, ‘g(r)’, ‘RDF(r)’] |
DeltaR | Input | number | Optional | Step size of r of G(r) to calculate. Default = ![]() |
Rmax | Input | number | 20 | Maximum r for G(r) to calculate. |
rho0 | Input | number | Optional | Average number density used for g(r) and RDF(r) conversions (optional) |
The algorithm transforms a single spectrum workspace containing
spectral density ,
, or
(as a function of MomentumTransfer or dSpacing units) to a PDF
(pair distribution function) as described below.
The input Workspace spectrum should be in the Q-space (MomentumTransfer) units . (d-spacing is not supported any more. Contact development team to fix that and enable dSpacing again)
Example - PDF transformation examples:
# Simulates Load of a workspace with all necessary parameters
import numpy as np;
xx = np.array(range(0,100))*0.1
yy = np.exp(-(2.0 * xx)**2)
ws = CreateWorkspace(DataX=xx, DataY=yy, UnitX='MomentumTransfer')
Rt = PDFFourierTransform(ws, InputSofQType='S(Q)', PDFType='g(r)')
# Look at sample results:
print('part of S(Q) and its correlation function')
for i in range(10):
print('! {0:4.2f} ! {1:5f} ! {2:f} ! {3:5f} !'.format(xx[i], yy[i], Rt.readX(0)[i], Rt.readY(0)[i]))
Output:
part of S(Q) and its correlation function
! 0.00 ! 1.000000 ! 0.317333 ! -3.977330 !
! 0.10 ! 0.960789 ! 0.634665 ! 2.247452 !
! 0.20 ! 0.852144 ! 0.951998 ! 0.449677 !
! 0.30 ! 0.697676 ! 1.269330 ! 1.313403 !
! 0.40 ! 0.527292 ! 1.586663 ! 0.803594 !
! 0.50 ! 0.367879 ! 1.903996 ! 1.140167 !
! 0.60 ! 0.236928 ! 2.221328 ! 0.900836 !
! 0.70 ! 0.140858 ! 2.538661 ! 1.079278 !
! 0.80 ! 0.077305 ! 2.855993 ! 0.940616 !
! 0.90 ! 0.039164 ! 3.173326 ! 1.050882 !
Categories: Algorithm Index | Diffraction\Utility
C++ source: PDFFourierTransform.cpp (last modified: 2019-01-07)
C++ header: PDFFourierTransform.h (last modified: 2018-10-05)