Speaker
Description
Synchrotron X-ray diffraction (XRD) experiments are a versatile tool in understanding material properties and processes in a wide range of applications. However, advanced synchrotron diffraction data analysis has traditionally required strong physics expertise, limiting broader adoption of diffraction methods. In addition, faster experiments and the increasing use of in situ environments require rapid data processing and feedback during beamtime to enable efficient experimental decision making.
To address these challenges, we present pydidas [1], an open source Python based diffraction data analysis suite developed at Helmholtz Zentrum Hereon. pydidas is designed to improve the data processing for existing users and broaden the potential user base for our XRD experiments by delivering a user-friendly and fast processing tool. It is designed to inherently use community-standard data formats like NeXus and make use of parallelization.
pydidas aims to integrate all essential steps of XRD data processing—including data browsing and visualization, experiment calibration, workflow setup, processing, and result visualization—into a single software environment with an intuitive graphical user interface.
To accommodate diverse analysis requirements, pydidas uses a modular, plugin based workflow architecture. Core processing functionality includes commonly required steps such as azimuthal integration (using pyFAI), corrections, and fitting. In addition, custom plugins can be easily integrated to support specialized or experiment specific workflows beyond the provided generic functionality. pydidas is actively developed and used in routine beamline operation, with ongoing extensions driven by user feedback and emerging analysis needs.
[1] http://pydidas.hereon.de
