Software

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A common question for new GISAXS users is: "What software can I use to analyze my data?" Unfortunately, there is no single package that will allow you to perform any possible analysis. This is in part due to the diversity of possible kinds of data analysis one might want to do on GISAXS or GIWAXS images. The following lists a variety of packages that are available.

Data Viewing, Reduction, and Simple Analysis

These packages provide ways to view data, and perform simple operations (linecuts, etc.).

Geared towards 2D data

Geared towards 1D data

Data Modeling and Fitting

These packages can predict scattering curves for various possible nano- or molecular- structures. Some of the packages allow fitting of experimental data.

SAXS

BioSAXS

GISAXS

Reflectivity

Crystallography

Computing Materials Properties

General

  • SciStreams: Simple workflow/pipeline software (building on Dask and Streams), intended for asynchronous and distributed computations at a beamline.
  • ParaView: Generalized GUI for visualizing scientific data, such as 3D images (uses Python and QT).
  • Mantid: Framework for computing and visualizing materials science data.
    • Official site.
    • Citation: O. Arnold, et al., Mantid—Data analysis and visualization package for neutron scattering and μSR experiments, Nuclear Instruments and Methods in Physics Research Section A, Volume 764, 11 November 2014, Pages 156-166. doi: 10.1016/j.nima.2014.07.029
  • DAWN (Data Analysis WorkbeNch): An application (based on Eclipse) for general scientific data analysis. It is mainly developed by the Diamond Light Source and is well-optimized for analysis of x-ray data, including SAXS-specific features.

Custom

It is of course possible to code your own software for modeling or fitting scattering data. This is not as difficult as it may at first seem. The fundamental scattering equations are well-known (c.f. scattering, Fourier transform, Form Factor, Structure Factor, Lattice Factor), and can be brute-force solved numerical. Or, they can be solved (or simplified) analytically for a particular case. Many modern programming languages provide libraries for numerical integration, fitting, minimizing multi-dimensional parameter spaces, etc. (e.g. Python is particularly clean and powerful).

See Also