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Goal

To develop a Python-based data corrections library for X-ray and neutron data that will improve on Reductus, adcorr and DAWN’s approaches by adding:

• Modular architecture with separation for universal, technique-specific, and instrument-specific components.
• Functionality for handling units, resolution, and propagating (optionally multiple) uncertainties.
• Support for diverse scientific techniques, ensuring broad applicability across X-ray and neutron datasets.

In this package, we hopefully can maintain simplicity and clarity without much impact on performance.

Key Focus Areas

The library aims to be highly modular and as correct and fast as feasible. The library should be constructed in a pragmatic manner, i.e. using well-maintained existing packages where possible.

TOF Neutrons are, at least for now, not the focus of this package. Due to significant differences in data handling and processing needs, monochromatic and TOF datasets should be handled separately, reducing complexity and minimizing scope bloat.

example correction graph with divergent and convergent nodes:

more details on corrections:

This paper describes the full correction sequence that's worked well for many samples. Many of the corrections themselves are described in this paper.