NNPDF/nnpdf
Jun 2025 – Jul 2026
10 Months active
Languages Used
PythonYAMLreStructuredText
Technical Skills
Python programmingdata processingscientific computingyaml parsingYAMLdata analysis
vschutze-alt
PROFILE
Vschutze-alt
Over ten months, contributed to the NNPDF/nnpdf repository by building and refining data pipelines, metadata frameworks, and documentation for high-energy physics datasets. Developed Python and YAML-driven workflows for data ingestion, uncertainty handling, and configuration management, enabling reproducible analyses of ATLAS photon and W boson measurements. Enhanced data integrity through systematic metadata cleanup, robust statistical modeling, and standardized naming conventions. Improved documentation quality using Sphinx and reStructuredText, resolving navigation and build issues to support onboarding and downstream analytics. The work emphasized maintainability, clarity, and alignment with evolving theoretical frameworks, resulting in more reliable data processing and streamlined scientific reporting.
Overall Statistics
Feature vs Bugs
64%Features
Repository Contributions
83Total
Bugs
10
Commits
83
Features
18
Lines of code
206,715
Activity Months10
Your Network
25 peopleShared Repositories
25
Andrew PietraszkiewiczMember
achiefaMember
Giovanni De CrescenzoMember
Eva GroenendijkMember
Ella ColeMember
Eva Doortje Zee GroenendijkMember
Eva Doortje Zee GroenendijkMember
Eva Doortje Zee GroenendijkMember
Eleanor ColeMember
Work History
July 2026
14 Commits • 2 Features
Jul 1, 2026During July 2026, the NNPDF/nnpdf work focused on strengthening dataset documentation and data configuration integrity. Delivered comprehensive Data Documentation Improvements with a new Dataset Tutorial, standardized naming conventions, and cross-reference cleanup to enhance navigability and consistency. Also completed a Data Configuration Cleanup removing deprecated or unused systematic uncertainties to reduce misconfigurations and improve data processing reliability. These efforts, combined with careful documentation reviews, improve onboarding for new users and stabilize downstream analytics.
14 Commits • 2 Features
Jul 1, 2026During July 2026, the NNPDF/nnpdf work focused on strengthening dataset documentation and data configuration integrity. Delivered comprehensive Data Documentation Improvements with a new Dataset Tutorial, standardized naming conventions, and cross-reference cleanup to enhance navigability and consistency. Also completed a Data Configuration Cleanup removing deprecated or unused systematic uncertainties to reduce misconfigurations and improve data processing reliability. These efforts, combined with careful documentation reviews, improve onboarding for new users and stabilize downstream analytics.
July 2026
April 2026
29 Commits
Apr 1, 2026NNPDF/nnpdf — April 2026 (2026-04) monthly report focused on documentation quality, link integrity, and build reliability. Key features delivered: - Documentation link and label integrity improvements across docs to prevent inexistent/duplicate labels and broken references (commits: 5c537b5a1782994d2329cd1cdc023e8422f1578f, 4c716112b8f85a9f7bb8e6867de3b0892f02d613, dee45c6fb7bc2640aacec155a4de43d242ea403f, 55a7f292288c13f104905eb8d6b41eeccd372371, 7a2d3c6f43652049d12bcfd50d3d426e54d4cb14, 8667c47f23ef8d8b75d57be48f0b340f9606d68f) - External URL link bug fixed for a non-existent site; external link resolution corrected (commit: 961bb616ec93e3dc3b403781e527382beaede6e0) - Documentation build and docstring formatting bugs resolved; formatting, indentation, and typo fixes for Sphinx generation (commits: 4c52750ef16176e577c07953d15452831f67bf1d, bb4335e3b393fe3dcc712711956d327e88f41d23, db6d51bafeeec71189e7d100b444428abf1e6737, 658008a9fbd250d51074a43275929db5cb53a5fb, a399654712890d26793a2ed5bed40a0042622050, 906898225a4bc7ed187b946bbd862760722804b6, 590138aaa69df6c50fa8b678d5ec55432cac8992, a4ab1e5bd8a05f43f66545cc579c3026270f0757) - TOC/Target name resolution improvements; removal of invalid links and handling of unknown/duplicate target names to ensure clean navigation (commits: 0f89811f9c871c8ad0a3f39683770f14eba811ab, d9d57be4c781a0cc9c83e3f0c7f0bf859edb6a75, 48caa1d1bd600a94353706b9d15fe5cb01a01212, e2dc11b3418fc6007f8f16c941d5ecbe5e2cfd71, c447da2792674a031ea241d9c92fc8f045c8a0c0, a46e64c2e9af492702fc6dc53951864fe1dfe453) - Indentation, punctuation, and typography fixes for improved readability and consistency across docs (commits: ad8c17803cc8c750ef7108a2784f0a9d42596ee5, 8720bbf08152b45ff0503277e40a9fa1ff4f7b66, a4063522a3b8419ee6e6513f78ae11b32f20c481, f99768b651e07c111b0102b353a80df43180a434, f91d8625832ac27758269db4c6a23225de499571) - Missing/broken labels fixes; addressed missing or broken labels across the batch (commit: 78c0e611856cf6cd8feaf851c867af1782e81c96) - Remove unsupported option; aligned configuration with currently supported features (commit: fb9e31285c427bebef7db960566ee44f4679f312) - Math not compiling properly; fixes for math-related compilation issues to ensure correct building (commit: 7f587d2162081975fdb66e3d3ae07f0d67910bdc) Major bugs fixed: - Resolved inexistent or duplicate labels and broken references in docs; corrected broken references and ensured label presence. - Fixed incorrect external URLs and improved external link resolution. - Corrected docstring formatting, indentation and typos to ensure Sphinx docs compile cleanly. - Cleaned up toctree handling and target name resolution to remove links to non-existent websites and unknown/duplicate target names. - Fixed missing/broken labels and removed unsupported options to stabilize configuration and builds. - Addressed math-related compilation issues to ensure successful builds. Overall impact and accomplishments: - Significantly improved documentation reliability and navigation, reducing user confusion and support overhead. - Enhanced release readiness by guaranteeing that docs build cleanly and links stay up to date for end users. - Streamlined contributor experience with clearer docs structure and fewer navigation errors. Technologies/skills demonstrated: - Sphinx, reStructuredText, and docstring formatting for reliable doc builds - TOC/toctree handling and navigation integrity in large docs suites - Python-based docs tooling, build pipelines, and commit hygiene - Git-based collaboration and targeted bug-fix workflows
April 2026
29 Commits
Apr 1, 2026NNPDF/nnpdf — April 2026 (2026-04) monthly report focused on documentation quality, link integrity, and build reliability. Key features delivered: - Documentation link and label integrity improvements across docs to prevent inexistent/duplicate labels and broken references (commits: 5c537b5a1782994d2329cd1cdc023e8422f1578f, 4c716112b8f85a9f7bb8e6867de3b0892f02d613, dee45c6fb7bc2640aacec155a4de43d242ea403f, 55a7f292288c13f104905eb8d6b41eeccd372371, 7a2d3c6f43652049d12bcfd50d3d426e54d4cb14, 8667c47f23ef8d8b75d57be48f0b340f9606d68f) - External URL link bug fixed for a non-existent site; external link resolution corrected (commit: 961bb616ec93e3dc3b403781e527382beaede6e0) - Documentation build and docstring formatting bugs resolved; formatting, indentation, and typo fixes for Sphinx generation (commits: 4c52750ef16176e577c07953d15452831f67bf1d, bb4335e3b393fe3dcc712711956d327e88f41d23, db6d51bafeeec71189e7d100b444428abf1e6737, 658008a9fbd250d51074a43275929db5cb53a5fb, a399654712890d26793a2ed5bed40a0042622050, 906898225a4bc7ed187b946bbd862760722804b6, 590138aaa69df6c50fa8b678d5ec55432cac8992, a4ab1e5bd8a05f43f66545cc579c3026270f0757) - TOC/Target name resolution improvements; removal of invalid links and handling of unknown/duplicate target names to ensure clean navigation (commits: 0f89811f9c871c8ad0a3f39683770f14eba811ab, d9d57be4c781a0cc9c83e3f0c7f0bf859edb6a75, 48caa1d1bd600a94353706b9d15fe5cb01a01212, e2dc11b3418fc6007f8f16c941d5ecbe5e2cfd71, c447da2792674a031ea241d9c92fc8f045c8a0c0, a46e64c2e9af492702fc6dc53951864fe1dfe453) - Indentation, punctuation, and typography fixes for improved readability and consistency across docs (commits: ad8c17803cc8c750ef7108a2784f0a9d42596ee5, 8720bbf08152b45ff0503277e40a9fa1ff4f7b66, a4063522a3b8419ee6e6513f78ae11b32f20c481, f99768b651e07c111b0102b353a80df43180a434, f91d8625832ac27758269db4c6a23225de499571) - Missing/broken labels fixes; addressed missing or broken labels across the batch (commit: 78c0e611856cf6cd8feaf851c867af1782e81c96) - Remove unsupported option; aligned configuration with currently supported features (commit: fb9e31285c427bebef7db960566ee44f4679f312) - Math not compiling properly; fixes for math-related compilation issues to ensure correct building (commit: 7f587d2162081975fdb66e3d3ae07f0d67910bdc) Major bugs fixed: - Resolved inexistent or duplicate labels and broken references in docs; corrected broken references and ensured label presence. - Fixed incorrect external URLs and improved external link resolution. - Corrected docstring formatting, indentation and typos to ensure Sphinx docs compile cleanly. - Cleaned up toctree handling and target name resolution to remove links to non-existent websites and unknown/duplicate target names. - Fixed missing/broken labels and removed unsupported options to stabilize configuration and builds. - Addressed math-related compilation issues to ensure successful builds. Overall impact and accomplishments: - Significantly improved documentation reliability and navigation, reducing user confusion and support overhead. - Enhanced release readiness by guaranteeing that docs build cleanly and links stay up to date for end users. - Streamlined contributor experience with clearer docs structure and fewer navigation errors. Technologies/skills demonstrated: - Sphinx, reStructuredText, and docstring formatting for reliable doc builds - TOC/toctree handling and navigation integrity in large docs suites - Python-based docs tooling, build pipelines, and commit hygiene - Git-based collaboration and targeted bug-fix workflows
March 2026
18 Commits • 8 Features
Mar 1, 2026March 2026: Delivered metadata-driven improvements and a data-structure refinement for NNPDF/nnpdf that enhance plot clarity, reporting consistency, and maintainability. Key outcomes include y-axis label rendering improvements, LaTeX-friendly eta label formatting, and enhanced observable and unit descriptions in metadata.yaml; standardized dataset labels and fb^-1 unit formatting with naming consistency (139FB); polishing typos and obsolete metadata files; and a simplification of the kinematic data model by removing the sqrts key. Business value includes clearer, publication-ready plots, more reproducible analyses, reduced maintenance burden, and improved alignment with data standards. Technologies demonstrated include YAML metadata management, LaTeX formatting, unit handling, and targeted code refactors in filter.py.
18 Commits • 8 Features
Mar 1, 2026March 2026: Delivered metadata-driven improvements and a data-structure refinement for NNPDF/nnpdf that enhance plot clarity, reporting consistency, and maintainability. Key outcomes include y-axis label rendering improvements, LaTeX-friendly eta label formatting, and enhanced observable and unit descriptions in metadata.yaml; standardized dataset labels and fb^-1 unit formatting with naming consistency (139FB); polishing typos and obsolete metadata files; and a simplification of the kinematic data model by removing the sqrts key. Business value includes clearer, publication-ready plots, more reproducible analyses, reduced maintenance burden, and improved alignment with data standards. Technologies demonstrated include YAML metadata management, LaTeX formatting, unit handling, and targeted code refactors in filter.py.
March 2026
February 2026
3 Commits • 2 Features
Feb 1, 2026February 2026 performance summary for NNPDF/nnpdf focusing on uncertainty handling and data display improvements for ATLAS_WPWM_8TEV, alongside luminosity uncertainty integration in filtering. Emphasis on delivering precise uncertainty treatment, improved data output quality, and configuration-driven controls to support downstream physics analyses.
February 2026
3 Commits • 2 Features
Feb 1, 2026February 2026 performance summary for NNPDF/nnpdf focusing on uncertainty handling and data display improvements for ATLAS_WPWM_8TEV, alongside luminosity uncertainty integration in filtering. Emphasis on delivering precise uncertainty treatment, improved data output quality, and configuration-driven controls to support downstream physics analyses.
December 2025
4 Commits • 1 Features
Dec 1, 2025Month: 2025-12 — Delivered a data processing and uncertainty-management package for ATLAS W boson analysis (8 TeV) within NNPDF/nnpdf. The work centers on a HEP data filtering pipeline with enhanced uncertainty handling, plus updates to YAML-based uncertainty classifications. Deliverables include metadata and raw data generation for cross-section and charge asymmetry measurements, with more robust statistical and systematic uncertainty calculations and clearer uncertainty definitions. The effort enhances analysis reliability, reproducibility, and scalability for future 8 TeV ATLAS studies.
4 Commits • 1 Features
Dec 1, 2025Month: 2025-12 — Delivered a data processing and uncertainty-management package for ATLAS W boson analysis (8 TeV) within NNPDF/nnpdf. The work centers on a HEP data filtering pipeline with enhanced uncertainty handling, plus updates to YAML-based uncertainty classifications. Deliverables include metadata and raw data generation for cross-section and charge asymmetry measurements, with more robust statistical and systematic uncertainty calculations and clearer uncertainty definitions. The effort enhances analysis reliability, reproducibility, and scalability for future 8 TeV ATLAS studies.
December 2025
November 2025
3 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for NNPDF/nnpdf: Focused improvements to metadata and theory-card inputs to enhance data quality, reproducibility, and downstream reliability.
November 2025
3 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for NNPDF/nnpdf: Focused improvements to metadata and theory-card inputs to enhance data quality, reproducibility, and downstream reliability.
October 2025
2 Commits • 1 Features
Oct 1, 2025Month: 2025-10. This month focused on updating the NNPDF/nnpdf dataset configuration to align with the latest release/version and theoretical framework. Delivered YAML configuration updates to reflect NNPDF version changes and the shift from NNLO to NLO QCD QED, including the introduction of QED in the NNPDF4.1 NNLO dataset. These changes were implemented via two commits updating theory_cards YAML files. No major bugs were fixed in this period; the primary value was improving configuration correctness, reproducibility, and alignment with the latest theory and data standards, enabling accurate downstream analyses and smoother migrations to NNPDF4.1 with QED support. Tech highlights include YAML configuration management, version-controlled edits, and careful documentation of theoretical changes in dataset cards. This work enhances dataset reliability for analysts and supports ongoing research in QCD, QED, and their interplay.
2 Commits • 1 Features
Oct 1, 2025Month: 2025-10. This month focused on updating the NNPDF/nnpdf dataset configuration to align with the latest release/version and theoretical framework. Delivered YAML configuration updates to reflect NNPDF version changes and the shift from NNLO to NLO QCD QED, including the introduction of QED in the NNPDF4.1 NNLO dataset. These changes were implemented via two commits updating theory_cards YAML files. No major bugs were fixed in this period; the primary value was improving configuration correctness, reproducibility, and alignment with the latest theory and data standards, enabling accurate downstream analyses and smoother migrations to NNPDF4.1 with QED support. Tech highlights include YAML configuration management, version-controlled edits, and careful documentation of theoretical changes in dataset cards. This work enhances dataset reliability for analysts and supports ongoing research in QCD, QED, and their interplay.
October 2025
August 2025
6 Commits • 1 Features
Aug 1, 2025Month 2025-08 — NNPDF/nnpdf: Delivered key data infrastructure and metadata improvements enabling more accurate photon-production analyses and safer metadata handling. Highlights include new raw data tables and uncertainty classifications for photon production variants (R=0.2 and R=0.4) and targeted Metadata.yaml cleanup with explicit units initialization to prevent undefined values. These changes improve data fidelity, reproducibility, and configuration robustness, reinforcing downstream analytics and model integration.
August 2025
6 Commits • 1 Features
Aug 1, 2025Month 2025-08 — NNPDF/nnpdf: Delivered key data infrastructure and metadata improvements enabling more accurate photon-production analyses and safer metadata handling. Highlights include new raw data tables and uncertainty classifications for photon production variants (R=0.2 and R=0.4) and targeted Metadata.yaml cleanup with explicit units initialization to prevent undefined values. These changes improve data fidelity, reproducibility, and configuration robustness, reinforcing downstream analytics and model integration.
July 2025
2 Commits • 1 Features
Jul 1, 2025July 2025: Focused on advancing YAML-based data extraction and formatting for ATLAS photon production (13 TeV) within NNPDF/nnpdf, enabling cross-section, kinematic data, and uncertainties to be parsed from YAML and prepared for downstream analytics. This work enhances reproducibility and speeds up data readiness for HEP analyses.
2 Commits • 1 Features
Jul 1, 2025July 2025: Focused on advancing YAML-based data extraction and formatting for ATLAS photon production (13 TeV) within NNPDF/nnpdf, enabling cross-section, kinematic data, and uncertainties to be parsed from YAML and prepared for downstream analytics. This work enhances reproducibility and speeds up data readiness for HEP analyses.
July 2025
June 2025
2 Commits • 1 Features
Jun 1, 2025June 2025 performance summary for NNPDF/nnpdf: Delivered a Photon Production Data Dataset (ATLAS & 13 TeV) with parsing, aggregation logic, and metadata/configuration support. This work establishes a solid data foundation for photon production analyses and accelerates downstream reporting and model validation. No major bugs reported; stability maintained while laying groundwork for future enhancements.
June 2025
2 Commits • 1 Features
Jun 1, 2025June 2025 performance summary for NNPDF/nnpdf: Delivered a Photon Production Data Dataset (ATLAS & 13 TeV) with parsing, aggregation logic, and metadata/configuration support. This work establishes a solid data foundation for photon production analyses and accelerates downstream reporting and model validation. No major bugs reported; stability maintained while laying groundwork for future enhancements.
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Quality Metrics
Correctness98.4%
Maintainability96.6%
Architecture94.6%
Performance95.2%
AI Usage28.0%
Skills & Technologies
Programming Languages
PythonYAMLreStructuredText
Technical Skills
CI/CDCode refactoringData CleaningData ConfigurationData EngineeringDocumentationGitHub ActionsPhysics Data AnalysisPythonPython programmingPython scriptingSphinxYAMLYAML configurationconfiguration management
Repositories Contributed To
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