-
Notifications
You must be signed in to change notification settings - Fork 2
Description
Executive summary
Provide choice of other output functions from PDF data reduction
Context and background knowledge
It is quite common to plot different quantities at the end of PDF data reduction.
- Pair correlation function
$G(r) = \frac{2}{\pi}\int_0^{Q_{\rm max}} Q ; [S(Q)-1] ; \sin(Qr) ; {\rm d}Q$ - Pair distribution function
$g(r) = 1+ \frac{G(r)}{4\pi \rho r },$ where$\rho$ is the atomic density - Radial distribution function
${\rm RDF}(r) = 4\pi \rho r^2 g(r),$ where$\rho$ is the atomic density - Linearised radial distribution function
$T(r) = {\rm RDF}(r)/r$ - Running coordination number $ \int_0^r {\rm RDF}(r') ; {\rm d}r'$
The first one is already implemented in essdiffraction: ess.powder.transform.compute_pdf_from_structure_factor
The follow-up work is to add this final step to the PDF data reduction workflow in essdiffraction (not done yet)
Inputs
Input: S(Q)
Methodology
See above for the expressions of the formula to implement
Outputs
Output: different 2-column files where the first one is r and the other is one of the following quantities: G(r), g(r), T(r), RDF(r) or the running coordination number.
Which interfaces are required?
Python module / function
Test cases
See attached zipped folder (jupyter notebook and test input and output datafiles
PDF_Scipp_requirement_files_for_tests.zip
Existing implementations
No response
Comments
No response