EPICS-HDR/New-Code-Layout
Nov 2024 – May 2025
6 Months active
Languages Used
CSSGitHTMLMarkdownPythonSQL
Technical Skills
CSSCode OrganizationFront End DevelopmentFrontend DevelopmentHTMLVersion Control
Klahre, Glenn Alastair
PROFILE
Klahre, Glenn Alastair
Graham Klahre developed and maintained the EPICS-HDR/New-Code-Layout repository over six months, delivering a robust time-series forecasting system with end-to-end automation. He architected scalable frontend scaffolding and improved user experience using HTML and CSS, while also reorganizing project assets for maintainability. On the backend, Graham implemented ARIMA, TBATS, and RNN-based forecasting pipelines in Python, enhancing data preprocessing, model persistence, and evaluation workflows. He introduced detailed documentation to streamline onboarding and deployment, and refactored model training for reliability and observability. His work demonstrated depth in data science, machine learning, and system design, resulting in maintainable, production-ready forecasting infrastructure.
Overall Statistics
Feature vs Bugs
90%Features
Repository Contributions
17Total
Bugs
1
Commits
17
Features
9
Lines of code
3,474
Activity Months6
Your Network
102 people
Work History
May 2025
1 Commits • 1 Features
May 1, 2025Month: 2025-05 — EPICS-HDR/New-Code-Layout: Focused on delivering a robust Model Training Pipeline upgrade. Major feature delivered: refactored data handling and model training in models.py, added robust data filling, daily data support and sample frequency parameters for ARIMA and TBATS, improved RNN input shape calculation, and enhanced error handling with detailed timing metrics for model creation and updates. No critical bugs were reported this month. Impact includes more reliable forecasting pipelines, faster iterations with daily data, and improved observability. Technologies demonstrated include Python refactors, data engineering for ML pipelines, ARIMA/TBATS support, and improved exception handling and metrics capture.
1 Commits • 1 Features
May 1, 2025Month: 2025-05 — EPICS-HDR/New-Code-Layout: Focused on delivering a robust Model Training Pipeline upgrade. Major feature delivered: refactored data handling and model training in models.py, added robust data filling, daily data support and sample frequency parameters for ARIMA and TBATS, improved RNN input shape calculation, and enhanced error handling with detailed timing metrics for model creation and updates. No critical bugs were reported this month. Impact includes more reliable forecasting pipelines, faster iterations with daily data, and improved observability. Technologies demonstrated include Python refactors, data engineering for ML pipelines, ARIMA/TBATS support, and improved exception handling and metrics capture.
May 2025
April 2025
6 Commits • 2 Features
Apr 1, 2025April 2025: Focused on delivering major feature work in EPICS-HDR/New-Code-Layout. End-to-End Time Series Forecasting System Overhaul (RNN/MAE) with SKTime and Keras introduced enhanced data preparation and training pipelines for more robust forecasts. Implemented Model Persistence and Reuse for TBATS/ARIMA using pickle, with memory limits and refactored training/loading logic to reuse existing models for efficiency. No major bugs fixed this month; efforts centered on capability expansion and reliability. Notable commits include 523587d95fe033be8ae2566efe88fcaf98448a31, 85eb7f47cba92a9042ccd271972afb26a51e4020, 44f0e78ef9626310074280a6ce6edf2d1666ccf6, b59f6b3e0d91bea006a8bcaab0b6641b66dea2d4, ee343e5be7f150334284bba78baacabd4a0739c8, and b61c9be5bc207290b4532b42efe2039891d68cdc.
April 2025
6 Commits • 2 Features
Apr 1, 2025April 2025: Focused on delivering major feature work in EPICS-HDR/New-Code-Layout. End-to-End Time Series Forecasting System Overhaul (RNN/MAE) with SKTime and Keras introduced enhanced data preparation and training pipelines for more robust forecasts. Implemented Model Persistence and Reuse for TBATS/ARIMA using pickle, with memory limits and refactored training/loading logic to reuse existing models for efficiency. No major bugs fixed this month; efforts centered on capability expansion and reliability. Notable commits include 523587d95fe033be8ae2566efe88fcaf98448a31, 85eb7f47cba92a9042ccd271972afb26a51e4020, 44f0e78ef9626310074280a6ce6edf2d1666ccf6, b59f6b3e0d91bea006a8bcaab0b6641b66dea2d4, ee343e5be7f150334284bba78baacabd4a0739c8, and b61c9be5bc207290b4532b42efe2039891d68cdc.
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 focused on delivering robust Time-Series Forecasting capabilities and strengthening the forecasting API within EPICS-HDR/New-Code-Layout. The work emphasizes business value through improved forecast accuracy, end-to-end automation, and reusable components for downstream analytics.
1 Commits • 1 Features
Mar 1, 2025March 2025 focused on delivering robust Time-Series Forecasting capabilities and strengthening the forecasting API within EPICS-HDR/New-Code-Layout. The work emphasizes business value through improved forecast accuracy, end-to-end automation, and reusable components for downstream analytics.
March 2025
February 2025
2 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for EPICS-HDR/New-Code-Layout. Focused on delivering end-to-end time-series data modeling and preprocessing enhancements to boost forecasting readiness and business value. Implemented data retrieval, gap filling, and train/test splitting; added ARIMA and TBATS modeling capabilities; improved datetime handling to manage time gaps and 24:00 formats; extended tbats_model to accept a list of values and added plotting of model outputs. Result: more reliable, forecast-ready data pipelines, enabling faster iteration and clearer visualization for decision-making.
February 2025
2 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for EPICS-HDR/New-Code-Layout. Focused on delivering end-to-end time-series data modeling and preprocessing enhancements to boost forecasting readiness and business value. Implemented data retrieval, gap filling, and train/test splitting; added ARIMA and TBATS modeling capabilities; improved datetime handling to manage time gaps and 24:00 formats; extended tbats_model to accept a list of values and added plotting of model outputs. Result: more reliable, forecast-ready data pipelines, enabling faster iteration and clearer visualization for decision-making.
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 highlights for EPICS-HDR/New-Code-Layout focused on delivering onboarding and deployment clarity through documentation improvements. Delivered HDR Server Documentation: Setup and Run Guide (README) that details environment setup, package installation, server start, browser access, and guidance for subsequent runs. No major bugs were fixed this month; primary effort was in documenting the correct workflow to enable repeatable deployments and faster onboarding. The change is captured in the commit "add README" (ab75b5731db184470cfc6fb71c15c86d8563d1f1).
1 Commits • 1 Features
Jan 1, 2025January 2025 highlights for EPICS-HDR/New-Code-Layout focused on delivering onboarding and deployment clarity through documentation improvements. Delivered HDR Server Documentation: Setup and Run Guide (README) that details environment setup, package installation, server start, browser access, and guidance for subsequent runs. No major bugs were fixed this month; primary effort was in documenting the correct workflow to enable repeatable deployments and faster onboarding. The change is captured in the commit "add README" (ab75b5731db184470cfc6fb71c15c86d8563d1f1).
January 2025
November 2024
6 Commits • 3 Features
Nov 1, 2024Monthly summary for 2024-11: Delivered foundational frontend scaffolding and UI enhancements, reorganized the project for long-term maintainability, and improved repository hygiene. The work focused on establishing a scalable frontend foundation, refining user experience, and reducing maintenance risk, aligning with the New-Code-Layout initiative. Key outcomes include: - Locofy-based frontend scaffolding and a landing page with navigation and core sections, enabling rapid UI iteration and a clear entry point for users. - Homepage UX improvements with responsive refinements and a dedicated services dropdown to clarify offerings and improve navigation paths. - Project structure cleanup and asset organization to centralize static assets and consolidate HTML templates, reducing maintenance overhead and merge conflicts. - Maintenance hygiene: updated gitignore to prevent environment/config leakage and removed extraneous CSS comment characters to ensure cleaner commits. Overall impact: - Establishes a scalable frontend foundation, accelerates future feature delivery, and reduces onboarding time for new contributors. - Improves user experience and consistency across the landing page and homepage, driving better engagement. - Improves code cleanliness and repo hygiene, lowering risk of accidental commits and configuration drift. Technologies and skills demonstrated: - Frontend scaffolding and UI work with Locofy, CSS refinements, responsive design, and HTML template consolidation. - Asset management and project structure organization for maintainability. - Version control hygiene and repo management (gitignore, commit hygiene).
November 2024
6 Commits • 3 Features
Nov 1, 2024Monthly summary for 2024-11: Delivered foundational frontend scaffolding and UI enhancements, reorganized the project for long-term maintainability, and improved repository hygiene. The work focused on establishing a scalable frontend foundation, refining user experience, and reducing maintenance risk, aligning with the New-Code-Layout initiative. Key outcomes include: - Locofy-based frontend scaffolding and a landing page with navigation and core sections, enabling rapid UI iteration and a clear entry point for users. - Homepage UX improvements with responsive refinements and a dedicated services dropdown to clarify offerings and improve navigation paths. - Project structure cleanup and asset organization to centralize static assets and consolidate HTML templates, reducing maintenance overhead and merge conflicts. - Maintenance hygiene: updated gitignore to prevent environment/config leakage and removed extraneous CSS comment characters to ensure cleaner commits. Overall impact: - Establishes a scalable frontend foundation, accelerates future feature delivery, and reduces onboarding time for new contributors. - Improves user experience and consistency across the landing page and homepage, driving better engagement. - Improves code cleanliness and repo hygiene, lowering risk of accidental commits and configuration drift. Technologies and skills demonstrated: - Frontend scaffolding and UI work with Locofy, CSS refinements, responsive design, and HTML template consolidation. - Asset management and project structure organization for maintainability. - Version control hygiene and repo management (gitignore, commit hygiene).
Activity
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Quality Metrics
Correctness83.6%
Maintainability82.4%
Architecture81.2%
Performance70.6%
AI Usage23.6%
Skills & Technologies
Programming Languages
CSSGitHTMLMarkdownPythonSQL
Technical Skills
ARIMABackend DevelopmentCSSCode OrganizationData InterpolationData ModelingData PersistenceData PreprocessingData ScienceDeep LearningDocumentationForecastingFront End DevelopmentFrontend DevelopmentHTML
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