NNPDF/nnpdf
Feb 2025 – Jul 2025
3 Months active
Languages Used
YAMLPythonpythonyaml
Technical Skills
Configuration ManagementData ManagementCode RefactoringPythonData AnalysisScientific Computing
jacoterh
PROFILE
Jacoterh
J.J. ter Hoeve contributed to the NNPDF/nnpdf repository by standardizing metadata naming, refactoring the fitting pipeline, and correcting data normalization for 2D distributions. He improved metadata governance by aligning YAML key conventions, which enhanced data consistency and simplified downstream referencing. In Python, he streamlined the fitting pipeline by removing unused arguments and calculations, reducing API complexity and improving maintainability. He also addressed a normalization bug by adjusting central values and errors in filter.py and ensuring unit consistency in metadata. His work demonstrated depth in configuration management, data analysis, and scientific computing, resulting in more reliable and reproducible data workflows.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
3Total
Bugs
1
Commits
3
Features
2
Lines of code
3,700
Activity Months3
Your Network
36 people
Work History
July 2025
1 Commits
Jul 1, 2025Month: 2025-07 — Focused on correcting normalization for 2D distributions and ensuring y_t units in metadata are consistent. Implemented a fix to normalize central values and errors by the bin width in filter.py and corrected the units of the y_t variable in metadata.yaml. Change recorded in commit 0c57a1854fad5a4ffe2993b690a8843da2e58697 with message 'fixing normalisation 2D dist'. This enhances data integrity, reliability of downstream analyses (e.g., PDF evaluations), and reproducibility across runs.
1 Commits
Jul 1, 2025Month: 2025-07 — Focused on correcting normalization for 2D distributions and ensuring y_t units in metadata are consistent. Implemented a fix to normalize central values and errors by the bin width in filter.py and corrected the units of the y_t variable in metadata.yaml. Change recorded in commit 0c57a1854fad5a4ffe2993b690a8843da2e58697 with message 'fixing normalisation 2D dist'. This enhances data integrity, reliability of downstream analyses (e.g., PDF evaluations), and reproducibility across runs.
July 2025
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for NNPDF/nnpdf: Delivered a targeted code cleanup affecting the fitting pipeline by removing the unused diagonal_frac argument from fitting_data_dict and dropping the unused invcovmat calculation. This reduces API surface, eliminates unnecessary computation, and improves maintainability, enabling safer future refactors and faster onboarding for new contributors. No major bugs were fixed this month; the focus was on quality improvements that reduce risk and simplify future enhancements. Technologies demonstrated include Python refactoring, API hygiene, and performance-conscious optimization.
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for NNPDF/nnpdf: Delivered a targeted code cleanup affecting the fitting pipeline by removing the unused diagonal_frac argument from fitting_data_dict and dropping the unused invcovmat calculation. This reduces API surface, eliminates unnecessary computation, and improves maintainability, enabling safer future refactors and faster onboarding for new contributors. No major bugs were fixed this month; the focus was on quality improvements that reduce risk and simplify future enhancements. Technologies demonstrated include Python refactoring, API hygiene, and performance-conscious optimization.
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for NNPDF/nnpdf: Focused on metadata governance and small, high-value refactors to improve data quality and downstream reliability for ATLAS_PH_8TEV data. The month centered on standardizing metadata naming to prevent drift and to simplify cross-dataset referencing.
1 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for NNPDF/nnpdf: Focused on metadata governance and small, high-value refactors to improve data quality and downstream reliability for ATLAS_PH_8TEV data. The month centered on standardizing metadata naming to prevent drift and to simplify cross-dataset referencing.
February 2025
Activity
Loading activity data...
Quality Metrics
Correctness86.6%
Maintainability86.6%
Architecture86.6%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonYAMLpythonyaml
Technical Skills
Code RefactoringConfiguration ManagementData AnalysisData ManagementPythonScientific ComputingYAML
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline