
Contributed to the google-deepmind/torax repository by expanding post-processing capabilities for plasma physics simulations, focusing on the addition of global plasma parameter calculations and time-series visualizations. Leveraged Python and scientific computing techniques to enhance data analysis workflows, introducing new metrics such as q95 and te/ti volume-averages with improved plotting configurations for clearer insights. Updated test data and configurations to maintain compatibility with evolving outputs, ensuring continuous integration reliability. Emphasized configuration management and data visualization, refining plot readability through font and legend adjustments. This work strengthened observability of simulation metrics and maintained robust testing standards within the project’s development cycle.
December 2024: Delivered notable post-processing and data-validation improvements for the torax project, strengthening observability of global plasma metrics and CI reliability. This period focused on expanding post-processing capabilities, updating test data to reflect new outputs, and polishing visualizations for clearer insights.
December 2024: Delivered notable post-processing and data-validation improvements for the torax project, strengthening observability of global plasma metrics and CI reliability. This period focused on expanding post-processing capabilities, updating test data to reflect new outputs, and polishing visualizations for clearer insights.

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