flipoyo/MOLONARI1D
Oct 2024 – Nov 2024
2 Months active
Languages Used
CSVJSONJupyter NotebookPythonSQL
Technical Skills
CSV ManipulationCSV ParsingData AnalysisData CleaningData EngineeringData Preprocessing
alexandrenoel20
PROFILE
Alexandrenoel20
Developed an end-to-end permeability data analysis and time-series analytics pipeline for the flipoyo/MOLONARI1D repository, focusing on robust CSV data ingestion, MCMC-based parameter estimation, and reproducible Jupyter Notebook workflows. Leveraged Python, Pandas, and NumPy to implement data loading, date normalization, and advanced plotting, while introducing Pearson coefficient analytics for both simulated and real-world datasets. Enhanced project maintainability through comprehensive code refactoring, file reorganization, and targeted bug fixes. Expanded core data structures to support richer per-point metrics and dynamic visualizations, reducing processing errors and technical debt. Documented workflows and automated tests ensured reliable, repeatable analysis for material property validation.
Overall Statistics
Feature vs Bugs
81%Features
Repository Contributions
48Total
Bugs
3
Commits
48
Features
13
Lines of code
127,289
Activity Months2
Your Network
65 peopleSame Organization
@etu.minesparis.psl.eu20
Adam HaïkMember
Antoine de La RoncièreMember
ArmanDLFMember
Aurélie ReynaudMember
barnabetherondMember
Bastien AvrillonMember
Clément GoujonMember
Colin DrouineauMember
Elyes BeloucifMember
Shared Repositories
45
Adam HaïkMember
Antoine de La RoncièreMember
ArmanDLFMember
Aurélie ReynaudMember
barnabetherondMember
Barnabé ThérondMember
Bastien AvrillonMember
Ombline BrunetMember
Clément GoujonMember
Work History
November 2024
30 Commits • 10 Features
Nov 1, 2024November 2024 performance summary for flipoyo/MOLONARI1D: Delivered a structural overhaul and robust time-series analytics pipeline, enabling reliable data processing, richer per-point metrics, and actionable visualizations. Key outcomes include project-wide file cleanup and reorganization, notebook initialization with automated data integration and dynamic titles, expanded time-series core object (dt, per-day metrics, and real-data support), Pearson coefficient analytics and plotting, refactored riverbed temperature plotting, addition of temperature and pressure/temperature datasets, along with targeted bug fixes and comprehensive documentation updates. These changes reduce data processing errors, accelerate insight generation, and improve maintainability for the team.
30 Commits • 10 Features
Nov 1, 2024November 2024 performance summary for flipoyo/MOLONARI1D: Delivered a structural overhaul and robust time-series analytics pipeline, enabling reliable data processing, richer per-point metrics, and actionable visualizations. Key outcomes include project-wide file cleanup and reorganization, notebook initialization with automated data integration and dynamic titles, expanded time-series core object (dt, per-day metrics, and real-data support), Pearson coefficient analytics and plotting, refactored riverbed temperature plotting, addition of temperature and pressure/temperature datasets, along with targeted bug fixes and comprehensive documentation updates. These changes reduce data processing errors, accelerate insight generation, and improve maintainability for the team.
November 2024
October 2024
18 Commits • 3 Features
Oct 1, 2024October 2024 performance summary for flipoyo/MOLONARI1D: Implemented an end-to-end permeability data analysis pipeline with MCMC-based estimation of permeability (k) from CSV data, including data loading, date normalization, and plotting. Added Pearson coefficient analyses for daily measurements and simulation data, with tests and a real-world data notebook to validate correlations. Built data ingestion utilities (data reader, convertDates) to support robust MCMC workflows and resolved access to k values within parameter objects for data_traite. Cleaned up legacy work by deprecating the Temp_ampl_ratio_diffusive_case notebook, resetting execution state, and removing outdated artifacts to reduce technical debt. Overall, these efforts increased data fidelity, reproducibility, and insight velocity for model validation and material property estimation.
October 2024
18 Commits • 3 Features
Oct 1, 2024October 2024 performance summary for flipoyo/MOLONARI1D: Implemented an end-to-end permeability data analysis pipeline with MCMC-based estimation of permeability (k) from CSV data, including data loading, date normalization, and plotting. Added Pearson coefficient analyses for daily measurements and simulation data, with tests and a real-world data notebook to validate correlations. Built data ingestion utilities (data reader, convertDates) to support robust MCMC workflows and resolved access to k values within parameter objects for data_traite. Cleaned up legacy work by deprecating the Temp_ampl_ratio_diffusive_case notebook, resetting execution state, and removing outdated artifacts to reduce technical debt. Overall, these efforts increased data fidelity, reproducibility, and insight velocity for model validation and material property estimation.
Activity
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Quality Metrics
Correctness83.0%
Maintainability86.8%
Architecture78.8%
Performance72.8%
AI Usage20.8%
Skills & Technologies
Programming Languages
CSVJSONJupyter NotebookPythonSQL
Technical Skills
Bug FixingCSV ManipulationCSV ParsingClass DesignCode DocumentationCode RefactoringData AnalysisData CleaningData EngineeringData ManagementData PreprocessingData ProcessingData ReadingData VisualizationData Wrangling
Repositories Contributed To
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