xpsi-group/xpsi
Dec 2024 – Mar 2026
3 Months active
Languages Used
C++PythonRSTYAMLNonereStructuredTextrst
Technical Skills
Data VisualizationHDF5MatplotlibNumPyPlotting Library DevelopmentPython
Sebastien Guillot
PROFILE
Sebastien Guillot
Sebastien Guillot developed and maintained core features for the xpsi-group/xpsi repository, focusing on data visualization, environment management, and scientific computing. He built an advanced plotting library using Python, NumPy, and Matplotlib, centralizing 1D/2D pulse profile and instrument response visualization with standardized aesthetics. Sebastien improved reproducibility by standardizing environment configurations and updating dependencies, enhancing CI reliability and onboarding. He also addressed data fidelity by refining background plot accuracy and fixing initialization bugs in signal processing. His work included modernizing Jupyter Notebooks for modeling workflows and updating documentation, demonstrating depth in technical writing, numerical analysis, and collaborative repository hygiene practices.
Overall Statistics
Feature vs Bugs
83%Features
Repository Contributions
14Total
Bugs
1
Commits
14
Features
5
Lines of code
36,493
Activity Months3
Your Network
14 peopleShared Repositories
14
Work History
March 2026
12 Commits • 3 Features
Mar 1, 2026March 2026 (2026-03) monthly summary for xpsi-group/xpsi: Delivered targeted feature work and critical bug fixes with a focus on data fidelity, reliability, and developer experience. Key outcomes include improved background plot accuracy via integration-based processing, robust initialization of interstellar extinction parameters, notebook modernization for modeling/instrument synergy and synthetic data, and comprehensive documentation/repo hygiene updates to streamline onboarding and maintenance. These deliverables enhance data reliability, visualization clarity, and collaboration efficiency, enabling faster insight and deployment pipelines.
12 Commits • 3 Features
Mar 1, 2026March 2026 (2026-03) monthly summary for xpsi-group/xpsi: Delivered targeted feature work and critical bug fixes with a focus on data fidelity, reliability, and developer experience. Key outcomes include improved background plot accuracy via integration-based processing, robust initialization of interstellar extinction parameters, notebook modernization for modeling/instrument synergy and synthetic data, and comprehensive documentation/repo hygiene updates to streamline onboarding and maintenance. These deliverables enhance data reliability, visualization clarity, and collaboration efficiency, enabling faster insight and deployment pipelines.
March 2026
May 2025
1 Commits • 1 Features
May 1, 2025May 2025: Delivered environment standardization and dependency updates for the xpsi project to improve reproducibility, CI reliability, and onboarding. Focused on aligning environment naming, updating dependencies, and documenting changes to ensure consistent deployment and development experiences across the repository. No major bug fixes this month; the emphasis was on technical debt reduction and stabilizing the build/test pipeline.
May 2025
1 Commits • 1 Features
May 1, 2025May 2025: Delivered environment standardization and dependency updates for the xpsi project to improve reproducibility, CI reliability, and onboarding. Focused on aligning environment naming, updating dependencies, and documenting changes to ensure consistent deployment and development experiences across the repository. No major bug fixes this month; the emphasis was on technical debt reduction and stabilizing the build/test pipeline.
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for xpsi-group/xpsi: Delivered the Advanced plotting library for xpsi data visualization, centralizing 1D/2D pulse profiles, instrument responses, effective areas, and meshes, with standardized aesthetics and plotting APIs across the package.
1 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for xpsi-group/xpsi: Delivered the Advanced plotting library for xpsi data visualization, centralizing 1D/2D pulse profiles, instrument responses, effective areas, and meshes, with standardized aesthetics and plotting APIs across the package.
December 2024
Activity
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Quality Metrics
Correctness97.2%
Maintainability95.8%
Architecture95.8%
Performance94.2%
AI Usage24.2%
Skills & Technologies
Programming Languages
C++NonePythonRSTYAMLreStructuredTextrst
Technical Skills
Data VisualizationDocumentationEnvironment ManagementHDF5Jupyter NotebookJupyter NotebooksMatplotlibNumPyPlotting Library DevelopmentPythonPython programmingSciPydata analysisdata visualizationdocumentation
Repositories Contributed To
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