Keck-DataReductionPipelines/KPF-Pipeline
Apr 2025 – Apr 2025
1 Month active
Languages Used
Python
Technical Skills
Backend DevelopmentCommand Line InterfaceData AnalysisData ValidationData VisualizationFile Processing
Dhriti Vasu
PROFILE
Dhriti Vasu
During April 2025, Dida Vasu enhanced the Keck-DataReductionPipelines/KPF-Pipeline by developing per-fiber radial velocity time-series visualizations with wavelength metadata, enabling granular diagnostics across multiple chips. Dida refactored parameter access in plotting routines for greater robustness and improved the accuracy of time-series filtering by fixing object-like query formatting for SQL LIKE clauses. Additionally, Dida introduced an automated WLS file date consistency checker that processes files or directories, updates headers, and triggers downstream automation on mismatches. These contributions, implemented in Python and leveraging skills in data analysis, scripting, and file processing, improved both the reliability and interpretability of pipeline outputs.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
4Total
Bugs
1
Commits
4
Features
2
Lines of code
331
Activity Months1
Your Network
15 people
Work History
April 2025
4 Commits • 2 Features
Apr 1, 2025April 2025 — Keck-DataReductionPipelines/KPF-Pipeline (performance-review ready) 1) Key features delivered - AnalyzeTimeSeries: Added plot_rv_per_fiber_wavelength to visualize RV time-series per fiber (SCI1/SCI2/SCI3) across green/red chips with wavelength information. Refactored panel dictionary parameter access to .get() and improved object-like handling and plotting label robustness. Commits: 916d92687ea392eae867a87a4e8230cccd3c3d0e; 7d9eaf6130cc36056d7e16f46ffbd3e7e996bf66 - WLS file date consistency checker: check_wls_files_match.py introduced to verify date consistency between WLSFILE headers; supports processing files or directories, adds WLSMATCH header, and can trigger kpf_slowtouch.sh on mismatches. Commit: ec43fb01571d5614f48054388ae5792351337893 2) Major bugs fixed - AnalyzeTimeSeries: Fixed object_like query formatting to ensure proper quoting and escaping for LIKE clause filtering, improving accuracy of time-series filtering. Commit: 6a3f9c2477c42f73bb52fd6c7151cfe9667a1289 3) Overall impact and accomplishments - Improved reliability and interpretability of RV analyses through per-fiber visualizations and consistent metadata checks, enabling faster troubleshooting and higher confidence in results across SCI1/SCI2/SCI3 and green/red chips. - Automated data quality gate for WLS files, reducing manual inspection and enabling smoother downstream processing with automated mismatch handling. 4) Technologies/skills demonstrated - Python-based data analysis tooling, plotting, and data-quality automation. - Refactoring for robust configuration access (.get()), enhanced object-like handling, and plotting labels. - File/directory processing, header-level consistency checks, and automation hooks (kpf_slowtouch.sh). Top 3-5 achievements (business value oriented): - Delivered per-fiber RV visualization across chips enabling granular time-series diagnostics (commit 916d9268..., 7d9eaf61...). - Strengthened data filtering accuracy with object_like query formatting fix (commit 6a3f9c24...). - Introduced automated WLS date consistency checks with mismatch-triggered automation (commit ec43fb01...).
4 Commits • 2 Features
Apr 1, 2025April 2025 — Keck-DataReductionPipelines/KPF-Pipeline (performance-review ready) 1) Key features delivered - AnalyzeTimeSeries: Added plot_rv_per_fiber_wavelength to visualize RV time-series per fiber (SCI1/SCI2/SCI3) across green/red chips with wavelength information. Refactored panel dictionary parameter access to .get() and improved object-like handling and plotting label robustness. Commits: 916d92687ea392eae867a87a4e8230cccd3c3d0e; 7d9eaf6130cc36056d7e16f46ffbd3e7e996bf66 - WLS file date consistency checker: check_wls_files_match.py introduced to verify date consistency between WLSFILE headers; supports processing files or directories, adds WLSMATCH header, and can trigger kpf_slowtouch.sh on mismatches. Commit: ec43fb01571d5614f48054388ae5792351337893 2) Major bugs fixed - AnalyzeTimeSeries: Fixed object_like query formatting to ensure proper quoting and escaping for LIKE clause filtering, improving accuracy of time-series filtering. Commit: 6a3f9c2477c42f73bb52fd6c7151cfe9667a1289 3) Overall impact and accomplishments - Improved reliability and interpretability of RV analyses through per-fiber visualizations and consistent metadata checks, enabling faster troubleshooting and higher confidence in results across SCI1/SCI2/SCI3 and green/red chips. - Automated data quality gate for WLS files, reducing manual inspection and enabling smoother downstream processing with automated mismatch handling. 4) Technologies/skills demonstrated - Python-based data analysis tooling, plotting, and data-quality automation. - Refactoring for robust configuration access (.get()), enhanced object-like handling, and plotting labels. - File/directory processing, header-level consistency checks, and automation hooks (kpf_slowtouch.sh). Top 3-5 achievements (business value oriented): - Delivered per-fiber RV visualization across chips enabling granular time-series diagnostics (commit 916d9268..., 7d9eaf61...). - Strengthened data filtering accuracy with object_like query formatting fix (commit 6a3f9c24...). - Introduced automated WLS date consistency checks with mismatch-triggered automation (commit ec43fb01...).
April 2025
Activity
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Quality Metrics
Correctness82.6%
Maintainability85.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Backend DevelopmentCommand Line InterfaceData AnalysisData ValidationData VisualizationFile ProcessingPlottingPythonPython ScriptingScriptingTime Series Analysis
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