An open-source software ecosystem for the interactive exploration of ultrafast electron scattering data

Area of Science:

• Materials Science
• Physical Chemistry
• Computational Science

Background:

• Ultrafast electron scattering (UES) experiments generate large, complex datasets.
• Efficient processing and analysis tools are crucial for extracting meaningful scientific insights from UES data.
• Existing software may lack the specialized functionalities or user-friendliness required for modern UES research.

Purpose of the Study:

• To present a comprehensive software ecosystem for processing and analyzing ultrafast electron scattering (UES) data.
• To provide researchers with free and open-source tools for efficient data handling and interactive exploration.
• To enhance the accessibility and reproducibility of UES data analysis.

Main Methods:

• Development of three integrated Python packages: 'iris' (GUI for interactive exploration), 'npstreams' (high-throughput data reduction), and 'scikit-ued' (specialized analysis routines).
• Implementation of parallel processing for efficient data reduction.
• Inclusion of specialized algorithms for image registration, simulation, and crystal structure manipulation.

Main Results:

• A robust software ecosystem enabling interactive exploration and analysis of UES data.
• Demonstration of high-throughput parallel data reduction capabilities.
• Provision of well-documented, tested, and permissively licensed software packages.

Conclusions:

• The developed Python packages offer a powerful, user-friendly solution for UES data analysis.
• This software ecosystem lowers the barrier to entry for UES data processing and interpretation.
• The open-source nature promotes collaboration and further development in the field of ultrafast electron scattering.