cta-observatory/cta-lstchain
Nov 2024 – Nov 2024
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
AstrophysicsAstropyData AnalysisData VisualizationGammapyPython
morcuended
PROFILE
Morcuended
Developed and delivered an updated Post-DL3 analysis notebook for the cta-observatory/cta-lstchain repository, ensuring compatibility with Gammapy 1.2 for spectral and light-curve analysis workflows. The work focused on refining data loading, analysis steps, and visualization to leverage new features in Gammapy, improving both usability and reproducibility for scientific users. Utilizing Python and Jupyter Notebook, the update integrated Astropy and scientific computing techniques to align the analysis process with the latest DL3 standards. This contribution enhanced the repository’s analytical capabilities, providing a more robust and maintainable example for astrophysics data analysis and visualization within the CTA community.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
587
Activity Months1
Your Network
49 peopleShared Repositories
12
Maria LainezMember
Arnau Aguasca-CabotMember
Mathieu de BonyMember
Daniel MorcuendeMember
Guillaume GrolleronMember
Maximilian LinhoffMember
moralejoMember
Paula KorneckiMember
rcervinoucmMember
Work History
November 2024
1 Commits • 1 Features
Nov 1, 2024November 2024: Delivered a Gammapy 1.2–compatible Post-DL3 analysis notebook for the cta-observatory/cta-lstchain repository, focusing on spectral and light-curve analysis. The update refines data loading, analysis steps, and plotting to utilize the latest Gammapy features, enhancing usability, reproducibility, and alignment with the DL3 workflow.
1 Commits • 1 Features
Nov 1, 2024November 2024: Delivered a Gammapy 1.2–compatible Post-DL3 analysis notebook for the cta-observatory/cta-lstchain repository, focusing on spectral and light-curve analysis. The update refines data loading, analysis steps, and plotting to utilize the latest Gammapy features, enhancing usability, reproducibility, and alignment with the DL3 workflow.
November 2024
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
AstrophysicsAstropyData AnalysisData VisualizationGammapyPythonScientific Computing
Repositories Contributed To
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