
The pygid package converts raw detector images into cylindrical, Cartesian, polar, and pseudo-polar coordinate representations and stores the results in the NXsas file format. It supports both grazing-incidence (GID) and transmission geometries and provides tools for radial and azimuthal profiling. The provided Jupyter Notebook demonstrates the pygid workflow using three different datasets. The first example presents a GID pattern of a diindenoperylene (DIP) thin film acquired at the ESRF ID10 beamline equipped with a EIGER2 X CdTe 4M detector. The second dataset contains a typical GIWAXS pattern of a methylammonium lead iodide (MAPbI₃) perovskite thin film measured at the PETRA III P08 beamline using a PerkinElmer flat-panel detector. Finally, the third example shows GID data of PbTe nanoplatelet clusters obtained with an in-house X-ray scattering setup (Xeuss 2.0, Xenocs) operating at an X-ray energy of 8 keV and equipped with a Pilatus 300k detector. The raw images were converted to cylindrical and polar coordinates and saved as PNG images and HDF5 files containing experimental parameters and sample metadata, following the FAIR data principles. A detailed description of the package functionality and code is available in the GitHub repository: https://github.com/mlgid-project/pygid.
grazing-incidence wide-angle X-ray scattering GIWAXS, data analysis, grazing-incidence X-ray diffraction GIXD, data reduction, Python package
grazing-incidence wide-angle X-ray scattering GIWAXS, data analysis, grazing-incidence X-ray diffraction GIXD, data reduction, Python package
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