pypeit/PypeIt
Oct 2024 – Jan 2026
16 Months active
Languages Used
PythonrstpythonbashRSTYAMLreStructuredText
Technical Skills
Astrophysics SoftwareData AnalysisData VisualizationDocumentationImage ProcessingScientific Computing
Debora Pelliccia
PROFILE
Debora Pelliccia
Over 16 months, Dan Pelliccia engineered robust enhancements to the pypeit/PypeIt repository, focusing on astronomical data reduction and calibration workflows. He delivered features such as flexible tilt tracing, improved flux calibration, and robust extraction logic, addressing challenges in spectroscopic data quality and pipeline reliability. Leveraging Python, YAML, and reStructuredText, Dan refactored core modules for maintainability, introduced new parameters for user control, and automated CI workflows to ensure test coverage. His work included detailed documentation, targeted bug fixes, and code cleanup, resulting in a more scalable, reproducible, and user-friendly pipeline that supports advanced scientific computing and data analysis.
Overall Statistics
Feature vs Bugs
75%Features
Repository Contributions
147Total
Bugs
15
Commits
147
Features
46
Lines of code
3,135,031
Activity Months16
Your Network
22 peopleSame Organization
@ucolick.org3
Shared Repositories
19
Brad HoldenMember
Brad HoldenMember
Brad HoldenMember
Brad HoldenMember
Frederick DaviesMember
Dusty ReichweinMember
Eric JeschkeMember
feigeMember
Frank VerdiMember
Work History
January 2026
8 Commits • 4 Features
Jan 1, 2026Monthly summary for 2026-01 focusing on delivering tangible business value and technical achievements in pypeit/PypeIt. Highlights include feature delivery for tilt tracing, calibration/config improvements for MMT Binospec, slitmask data handling refinements, and codebase cleanup to reduce maintenance burden. These efforts improved data reduction accuracy, reliability, and maintainability, enabling faster science results and easier onboarding.
8 Commits • 4 Features
Jan 1, 2026Monthly summary for 2026-01 focusing on delivering tangible business value and technical achievements in pypeit/PypeIt. Highlights include feature delivery for tilt tracing, calibration/config improvements for MMT Binospec, slitmask data handling refinements, and codebase cleanup to reduce maintenance burden. These efforts improved data reduction accuracy, reliability, and maintainability, enabling faster science results and easier onboarding.
January 2026
December 2025
20 Commits • 4 Features
Dec 1, 2025December 2025 (pypeit/PypeIt) delivered substantial improvements to maintainability, stability, and functionality. The team focused on documentation and code quality, a Slitshift Propagation Redesign to boost accuracy and performance, and targeted fixes around mask design, IFU workflows, and core stability. These changes reduce onboarding time, improve data processing reliability, and set a solid foundation for upcoming feature work.
December 2025
20 Commits • 4 Features
Dec 1, 2025December 2025 (pypeit/PypeIt) delivered substantial improvements to maintainability, stability, and functionality. The team focused on documentation and code quality, a Slitshift Propagation Redesign to boost accuracy and performance, and targeted fixes around mask design, IFU workflows, and core stability. These changes reduce onboarding time, improve data processing reliability, and set a solid foundation for upcoming feature work.
November 2025
13 Commits • 2 Features
Nov 1, 2025In November 2025, PypeIt delivered significant enhancements to 2D slit spectra processing and GMOS spectroscopy robustness, with an emphasis on practical data reduction improvements and documentation to support reproducible workflows. The month focused on end-to-end rectification tooling for 2D slit spectra (including ALLSLITS file creation, rotation control, headers, and interpolation updates) and strengthened the GMOS module with mask design handling and binning parameter validation. Substantial bug fixes and comprehensive documentation updates further improved pipeline reliability and user onboarding, laying a foundation for higher-quality spectral analyses.
13 Commits • 2 Features
Nov 1, 2025In November 2025, PypeIt delivered significant enhancements to 2D slit spectra processing and GMOS spectroscopy robustness, with an emphasis on practical data reduction improvements and documentation to support reproducible workflows. The month focused on end-to-end rectification tooling for 2D slit spectra (including ALLSLITS file creation, rotation control, headers, and interpolation updates) and strengthened the GMOS module with mask design handling and binning parameter validation. Substantial bug fixes and comprehensive documentation updates further improved pipeline reliability and user onboarding, laying a foundation for higher-quality spectral analyses.
November 2025
October 2025
8 Commits • 2 Features
Oct 1, 2025October 2025 monthly summary for pypeit/PypeIt: Focus on robustness and reliability of spectroscopy data processing, documentation improvements, and test reliability. Delivered improvements across edge handling and 2D coadds, multi-slit traces, and input handling; enhanced user guides for FOCAS; and strengthened test suite for SensFunc instantiation. This work improves data quality, pipeline stability, and onboarding for users.
October 2025
8 Commits • 2 Features
Oct 1, 2025October 2025 monthly summary for pypeit/PypeIt: Focus on robustness and reliability of spectroscopy data processing, documentation improvements, and test reliability. Delivered improvements across edge handling and 2D coadds, multi-slit traces, and input handling; enhanced user guides for FOCAS; and strengthened test suite for SensFunc instantiation. This work improves data quality, pipeline stability, and onboarding for users.
September 2025
10 Commits • 5 Features
Sep 1, 2025September 2025 monthly summary for pypeit/PypeIt focused on delivering robust calibration, scalable extraction across detectors, and automation to improve reliability and velocity. Key engineering efforts included enhancements to the sensitivity function pipeline (support for multiple standard-star files, robustness when data overlap is absent, and improved wavelength handling across ranges) with accompanying 1D spectrum documentation and release notes. A new mosaic spectra splitting feature enables extraction across detectors with varying quantum efficiencies, improving cross-detector consistency for both science targets and standard stars. CI workflow automation was added to run cron and push-based tests, increasing test coverage and release confidence. Calibration data for Gemini GMOS were updated (gain and readout noise) to boost data accuracy. Finally, a cleanup—removing the unused SensFileArchive—reduces dead code and maintenance burden. Overall, these changes elevate data quality, reproducibility, and development efficiency, translating to better science outcomes and faster delivery of reliable calibrations and features.
10 Commits • 5 Features
Sep 1, 2025September 2025 monthly summary for pypeit/PypeIt focused on delivering robust calibration, scalable extraction across detectors, and automation to improve reliability and velocity. Key engineering efforts included enhancements to the sensitivity function pipeline (support for multiple standard-star files, robustness when data overlap is absent, and improved wavelength handling across ranges) with accompanying 1D spectrum documentation and release notes. A new mosaic spectra splitting feature enables extraction across detectors with varying quantum efficiencies, improving cross-detector consistency for both science targets and standard stars. CI workflow automation was added to run cron and push-based tests, increasing test coverage and release confidence. Calibration data for Gemini GMOS were updated (gain and readout noise) to boost data accuracy. Finally, a cleanup—removing the unused SensFileArchive—reduces dead code and maintenance burden. Overall, these changes elevate data quality, reproducibility, and development efficiency, translating to better science outcomes and faster delivery of reliable calibrations and features.
September 2025
August 2025
17 Commits • 8 Features
Aug 1, 2025August 2025 (2025-08) — Delivered substantial feature work, robust metadata improvements, and targeted fixes in pypeit/PypeIt that improve data provenance, pipeline reliability, and user-facing usability. Key outcomes include Gemini GMOS R150 template support with dithering metadata, a refactor of the boxcar radius naming (BOX_R_PIX and BOX_R_ASEC) to improve clarity and downstream code consistency, explicit GNIRS/Gemini platescale units and camera_pos metadata with improved unit handling, a new min_frac_use parameter for datacube extraction with accompanying documentation, and enhanced reference object handling with unique identifiers for coadds (SPAT_PIXPOS_ID and ECH_FRACPOS_ID) and updated coadd workflows. Additional improvements cover extraction class attribute consistency, telluric model fitting validation, and install script path robustness, alongside a bug fix in wvutils cross-correlation return order. These changes collectively enhance data products, reproducibility, and developer workflows, with documentation updates ensuring clear guidance for users and contributors.
August 2025
17 Commits • 8 Features
Aug 1, 2025August 2025 (2025-08) — Delivered substantial feature work, robust metadata improvements, and targeted fixes in pypeit/PypeIt that improve data provenance, pipeline reliability, and user-facing usability. Key outcomes include Gemini GMOS R150 template support with dithering metadata, a refactor of the boxcar radius naming (BOX_R_PIX and BOX_R_ASEC) to improve clarity and downstream code consistency, explicit GNIRS/Gemini platescale units and camera_pos metadata with improved unit handling, a new min_frac_use parameter for datacube extraction with accompanying documentation, and enhanced reference object handling with unique identifiers for coadds (SPAT_PIXPOS_ID and ECH_FRACPOS_ID) and updated coadd workflows. Additional improvements cover extraction class attribute consistency, telluric model fitting validation, and install script path robustness, alongside a bug fix in wvutils cross-correlation return order. These changes collectively enhance data products, reproducibility, and developer workflows, with documentation updates ensuring clear guidance for users and contributors.
July 2025
11 Commits • 4 Features
Jul 1, 2025July 2025 monthly performance for pypeit/PypeIt focused on delivering user-facing features, improving data extraction reliability, and hardening the codebase across multiple spectrograph workflows. Key enhancements emphasize business value: more control for optimal extraction, consistent unit usage, and robust object identification, alongside targeted bug fixes to stabilize production pipelines and testing coverage. Documentation and test alignment were improved to support maintainability and faster onboarding across the team.
11 Commits • 4 Features
Jul 1, 2025July 2025 monthly performance for pypeit/PypeIt focused on delivering user-facing features, improving data extraction reliability, and hardening the codebase across multiple spectrograph workflows. Key enhancements emphasize business value: more control for optimal extraction, consistent unit usage, and robust object identification, alongside targeted bug fixes to stabilize production pipelines and testing coverage. Documentation and test alignment were improved to support maintainability and faster onboarding across the team.
July 2025
June 2025
11 Commits • 3 Features
Jun 1, 2025June 2025 monthly summary for pypeit/PypeIt: Key pipeline enhancements delivered to improve flux calibration accuracy, telluric handling, and standard-star processing, with a strong emphasis on robustness and maintainability. The work focused on calibrations, trimming, and user feedback to enhance scientific throughput and reliability in production analyses.
June 2025
11 Commits • 3 Features
Jun 1, 2025June 2025 monthly summary for pypeit/PypeIt: Key pipeline enhancements delivered to improve flux calibration accuracy, telluric handling, and standard-star processing, with a strong emphasis on robustness and maintainability. The work focused on calibrations, trimming, and user feedback to enhance scientific throughput and reliability in production analyses.
May 2025
3 Commits • 1 Features
May 1, 2025Month: 2025-05. This period focused on enhancing data quality and robustness in the PypeIt pipeline, delivering improvements in extraction accuracy and spectrum processing, with a strengthened validation suite to support reliable future development. Key features delivered: - Enhanced masking for optimal extraction to improve accuracy and robustness, ensuring the masked sub-array weighted by the optimal profile sums to >0.9 (commit 02de6ca5280f5b82c42edf3998429e94482a75ce). Major bugs fixed: - Robust spectrum loading: pass only valid (unmasked) data points to monotonic wavelength enforcement, preventing errors with masked data (commits 7bc0034c2985a4559270e8a1684d48bdd52ad149; 0b7d2a65c66d8860d05123a48c7fe4e1d4e2f0ec). - Test stability: fixes for vet tests and PypeIt Unit Tests to stabilize the validation suite (associated commits). Overall impact and accomplishments: - Higher-quality spectral extractions and more robust spectrum analysis, reducing pipeline failures and increasing trust in automated workflows. - Improved maintainability and traceability through explicit commit-based changes enabling easier future audits and onboarding of new contributors. Technologies/skills demonstrated: - Python-based masking and spectrum processing algorithms, data validation, unit testing, and robust debugging. Demonstrated strong focus on maintainability, performance, and traceability through commit history.
3 Commits • 1 Features
May 1, 2025Month: 2025-05. This period focused on enhancing data quality and robustness in the PypeIt pipeline, delivering improvements in extraction accuracy and spectrum processing, with a strengthened validation suite to support reliable future development. Key features delivered: - Enhanced masking for optimal extraction to improve accuracy and robustness, ensuring the masked sub-array weighted by the optimal profile sums to >0.9 (commit 02de6ca5280f5b82c42edf3998429e94482a75ce). Major bugs fixed: - Robust spectrum loading: pass only valid (unmasked) data points to monotonic wavelength enforcement, preventing errors with masked data (commits 7bc0034c2985a4559270e8a1684d48bdd52ad149; 0b7d2a65c66d8860d05123a48c7fe4e1d4e2f0ec). - Test stability: fixes for vet tests and PypeIt Unit Tests to stabilize the validation suite (associated commits). Overall impact and accomplishments: - Higher-quality spectral extractions and more robust spectrum analysis, reducing pipeline failures and increasing trust in automated workflows. - Improved maintainability and traceability through explicit commit-based changes enabling easier future audits and onboarding of new contributors. Technologies/skills demonstrated: - Python-based masking and spectrum processing algorithms, data validation, unit testing, and robust debugging. Demonstrated strong focus on maintainability, performance, and traceability through commit history.
May 2025
April 2025
2 Commits • 2 Features
Apr 1, 2025This month delivered two focused enhancements for pypeit/PypeIt, with an emphasis on documentation clarity and robustness of frame management in the HIRES/Keck workflow. 1) Documentation improvements: clarified jdaviz usage in Jupyter notebooks and refined HIRES data reduction performance estimates, accompanied by minor code tweaks to improve clarity and accuracy (commit 1d751ae1b1e43cac5d0036a69b3a68271f84f13e). 2) KECKHIRESSpectrograph frame management: improved frame identification and frame selection logic, including a RA/Dec-based check for standard files and an adjusted metadata tolerance (commit f42144ae21e7fc251cce59d567372609d0071910).
April 2025
2 Commits • 2 Features
Apr 1, 2025This month delivered two focused enhancements for pypeit/PypeIt, with an emphasis on documentation clarity and robustness of frame management in the HIRES/Keck workflow. 1) Documentation improvements: clarified jdaviz usage in Jupyter notebooks and refined HIRES data reduction performance estimates, accompanied by minor code tweaks to improve clarity and accuracy (commit 1d751ae1b1e43cac5d0036a69b3a68271f84f13e). 2) KECKHIRESSpectrograph frame management: improved frame identification and frame selection logic, including a RA/Dec-based check for standard files and an adjusted metadata tolerance (commit f42144ae21e7fc251cce59d567372609d0071910).
March 2025
5 Commits • 2 Features
Mar 1, 2025Monthly summary for 2025-03: Focused on delivering targeted UX and reliability improvements in pypeit/PypeIt, emphasizing onboarding, documentation quality, and calibration data processing accuracy. The month achieved clearer user guidance, more robust pipelines, and faster reproducibility of results across common HIRES workflows.
5 Commits • 2 Features
Mar 1, 2025Monthly summary for 2025-03: Focused on delivering targeted UX and reliability improvements in pypeit/PypeIt, emphasizing onboarding, documentation quality, and calibration data processing accuracy. The month achieved clearer user guidance, more robust pipelines, and faster reproducibility of results across common HIRES workflows.
March 2025
February 2025
8 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for the pypeit/PypeIt development effort. Focused on enhancing data quality, calibration reliability, and documentation. Delivered features to mask off-detector regions, refined telluric corrections in flux calibration, and fixed a QA plot inconsistency observed in fluxed standard stars. These changes improve spectroscopic data quality, QA reliability, and cross-instrument calibration workflows, delivering tangible business value through more robust pipelines and clearer release notes.
February 2025
8 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for the pypeit/PypeIt development effort. Focused on enhancing data quality, calibration reliability, and documentation. Delivered features to mask off-detector regions, refined telluric corrections in flux calibration, and fixed a QA plot inconsistency observed in fluxed standard stars. These changes improve spectroscopic data quality, QA reliability, and cross-instrument calibration workflows, delivering tangible business value through more robust pipelines and clearer release notes.
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for pypeit/PypeIt: Delivered a Flux Calibration Refactor with Blaze-Corrected Zeropoint to improve flux calibration accuracy and future maintainability. The changes introduce a blaze correction in zeropoint evaluation, modify how flux calibration coefficients are applied in SpecObjs, and imply changes in the storage/access pattern for sensitivity functions. This work lays groundwork for more robust, instrument-agnostic flux calibration across observations.
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for pypeit/PypeIt: Delivered a Flux Calibration Refactor with Blaze-Corrected Zeropoint to improve flux calibration accuracy and future maintainability. The changes introduce a blaze correction in zeropoint evaluation, modify how flux calibration coefficients are applied in SpecObjs, and imply changes in the storage/access pattern for sensitivity functions. This work lays groundwork for more robust, instrument-agnostic flux calibration across observations.
January 2025
December 2024
8 Commits • 2 Features
Dec 1, 2024December 2024 monthly summary for pypeit/PypeIt focused on strengthening spectral calibration reliability, diagnostics, and maintainability. Delivered targeted features and bug fixes that improve calibration fidelity and pipeline robustness, with clear traceability to commits. The work enhances scientific value by reducing miscalibration risk and enabling faster debugging in production workflows.
December 2024
8 Commits • 2 Features
Dec 1, 2024December 2024 monthly summary for pypeit/PypeIt focused on strengthening spectral calibration reliability, diagnostics, and maintainability. Delivered targeted features and bug fixes that improve calibration fidelity and pipeline robustness, with clear traceability to commits. The work enhances scientific value by reducing miscalibration risk and enabling faster debugging in production workflows.
November 2024
19 Commits • 2 Features
Nov 1, 2024November 2024: Delivered robust enhancements to spatial flexure QA, improved flat-field extraction robustness with API updates, and enhanced wave tilts QC, resulting in more reliable instrument calibrations and faster data processing. Key outcomes include saved QA plots with enhanced visualization controls, resilient handling of missing flats via prioritized pixelflat_raw/illumflat_raw and FlatImages API support, and stricter QC checks on tilt calibrations. Documentation updates accompany all changes, improving maintainability and onboarding. These efforts reduce manual QA time, prevent pipeline interruptions, and strengthen data quality across the PypeIt workflow. Technologies/skills demonstrated include Python data processing, cross-correlation optimization, image processing, API integration, and comprehensive release/documentation practices.
19 Commits • 2 Features
Nov 1, 2024November 2024: Delivered robust enhancements to spatial flexure QA, improved flat-field extraction robustness with API updates, and enhanced wave tilts QC, resulting in more reliable instrument calibrations and faster data processing. Key outcomes include saved QA plots with enhanced visualization controls, resilient handling of missing flats via prioritized pixelflat_raw/illumflat_raw and FlatImages API support, and stricter QC checks on tilt calibrations. Documentation updates accompany all changes, improving maintainability and onboarding. These efforts reduce manual QA time, prevent pipeline interruptions, and strengthen data quality across the PypeIt workflow. Technologies/skills demonstrated include Python data processing, cross-correlation optimization, image processing, API integration, and comprehensive release/documentation practices.
November 2024
October 2024
3 Commits • 2 Features
Oct 1, 2024Month: 2024-10 — Concise monthly summary for pypeit/PypeIt highlighting key features delivered, major bug fixes, and overall impact for performance reviews. Emphasis on business value, technical achievements, and skills demonstrated.
October 2024
3 Commits • 2 Features
Oct 1, 2024Month: 2024-10 — Concise monthly summary for pypeit/PypeIt highlighting key features delivered, major bug fixes, and overall impact for performance reviews. Emphasis on business value, technical achievements, and skills demonstrated.
Activity
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Quality Metrics
Correctness86.6%
Maintainability86.8%
Architecture83.0%
Performance78.6%
AI Usage21.6%
Skills & Technologies
Programming Languages
PythonRSTYAMLbashpythonreStructuredTextrst
Technical Skills
API documentationAstronomical Data AnalysisAstronomy SoftwareAstronomy Software DevelopmentAstronomy software developmentAstrophysicsAstrophysics SoftwareAstropyAstropy library usageAttribute RenamingBackend DevelopmentBug FixBug FixingCI/CDCode Cleanup
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