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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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pygid: Fast Preprocessing of Grazing Incidence Diffraction Data (GID). Usage examples.

Authors: Abukaev, Ainur; Völter, Constantin; Romodin, Mikhail; Schwartzkopff, Sebastian; Bertram, Florian; Konovalov, Oleg; Hinderhofer, Alexander; +2 Authors

pygid: Fast Preprocessing of Grazing Incidence Diffraction Data (GID). Usage examples.

Abstract

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.

Keywords

grazing-incidence wide-angle X-ray scattering GIWAXS, data analysis, grazing-incidence X-ray diffraction GIXD, data reduction, Python package

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average