MetOffice/CSET
Nov 2024 – Mar 2025
5 Months active
Languages Used
PythonrstJavaScript
Technical Skills
Data VisualizationDocumentationMatplotlibPlotting LibrariesIris Cube LibraryPython
Sylviabohnenstengel
PROFILE
Sylviabohnenstengel
Sylvia Bohnenstengel developed and enhanced data visualization and plotting capabilities for the MetOffice/CSET repository, focusing on meteorological data workflows. She implemented robust support for multi-dataset plotting using Python and the Iris Cube library, enabling analysts to visualize and compare related datasets efficiently. Her work included extending plotting functions to handle CubeLists, standardizing colorbars for cross-model comparisons, and improving website navigation with deterministic plot ordering and category-based filtering. By refactoring code for maintainability and introducing unit conversion and metadata-driven labeling, Sylvia improved both the reliability and usability of the plotting suite, supporting faster, more consistent scientific analysis and decision-making.
Overall Statistics
Feature vs Bugs
85%Features
Repository Contributions
39Total
Bugs
2
Commits
39
Features
11
Lines of code
1,107
Activity Months5
Your Network
56 people
Work History
March 2025
15 Commits • 2 Features
Mar 1, 20252025-03 monthly summary for MetOffice/CSET focused on delivering a more usable plotting UI, deterministic plot ordering, and enhanced precipitation visualization. The work improves business value by delivering accessible navigation, reliable plot indexing, and richer data representation across precipitation plots. Emphasis on end-user experience, maintainable plotting pipelines, and future extensibility through code refactoring.
15 Commits • 2 Features
Mar 1, 20252025-03 monthly summary for MetOffice/CSET focused on delivering a more usable plotting UI, deterministic plot ordering, and enhanced precipitation visualization. The work improves business value by delivering accessible navigation, reliable plot indexing, and richer data representation across precipitation plots. Emphasis on end-user experience, maintainable plotting pipelines, and future extensibility through code refactoring.
March 2025
February 2025
8 Commits • 3 Features
Feb 1, 2025February 2025 monthly summary for MetOffice/CSET focusing on reliability, multi-cube visualization, and improved website plotting navigation. Deliverables centralized plotting robustness with stable visuals, expanded support for CubeLists in histograms, and case_date-aware indexing to improve discoverability of plots on the website. Minor maintenance fixes addressed path/index correctness to ensure consistent behavior across the plotting suite and website. Key outcomes: - Implemented plotting robustness and visualization enhancements (robust first-cube access, disabled x-axis auto-scaling for consistent visuals, code quality cleanup, and pressure-level dependent colorbars). - Extended histogram plotting to support CubeLists, enabling multi-cube visualization with proper range calculations and metadata-based labeling. - Enhanced website plotting index and navigation by introducing case_date as a subcategory, updating index generation, and refining the sidebar for category/case_date filtering. - Minor maintenance and quality improvements (ruff formatting, path fixes) to bolster stability and consistency across the plotting and website tooling.
February 2025
8 Commits • 3 Features
Feb 1, 2025February 2025 monthly summary for MetOffice/CSET focusing on reliability, multi-cube visualization, and improved website plotting navigation. Deliverables centralized plotting robustness with stable visuals, expanded support for CubeLists in histograms, and case_date-aware indexing to improve discoverability of plots on the website. Minor maintenance fixes addressed path/index correctness to ensure consistent behavior across the plotting suite and website. Key outcomes: - Implemented plotting robustness and visualization enhancements (robust first-cube access, disabled x-axis auto-scaling for consistent visuals, code quality cleanup, and pressure-level dependent colorbars). - Extended histogram plotting to support CubeLists, enabling multi-cube visualization with proper range calculations and metadata-based labeling. - Enhanced website plotting index and navigation by introducing case_date as a subcategory, updating index generation, and refining the sidebar for category/case_date filtering. - Minor maintenance and quality improvements (ruff formatting, path fixes) to bolster stability and consistency across the plotting and website tooling.
January 2025
11 Commits • 3 Features
Jan 1, 2025January 2025 (Month: 2025-01) – MetOffice/CSET visualization enhancements and reliability improvements. Key features delivered: - Line plotting and CubeList support enhancements: extended line plotting to render multiple cubes on a single line, fixed axis association during line series plotting, refactored to use CubeList naming and removed intermediate storage, and extended vertical plotting to handle CubeLists. - Scatter plotting with CubeList support: robust handling of CubeList inputs, ensured cube_x and cube_y are iterable, and extracted units from the first CubeList element for accurate labeling. - Unified colorbars for cross-model visualization: standardized colorbars for relative humidity and cloud base altitude across UM and LFRic to improve comparability. Major bugs fixed: - Axis handling in line plotting (big fix in the plot command) to correctly associate axes for multi-cube line series. - Ensured cube_x and cube_y are iterable by wrapping single cubes into CubeLists when needed. - Correctly retrieving units when inputs are CubeLists (cube[0].units). - Documentation: fixed typo 'CUbeList' to 'CubeList' in scatter_plot docstring. Overall impact and accomplishments: - Improved reliability and interpretability of meteorological visualizations across models, enabling faster cross-model comparisons and decision-making. - Enhanced maintainability through CubeList-based data structures and consistent naming, reducing future regression risk. - Demonstrated end-to-end capability: from data structures (Cube/CubeList) to user-facing plots with accurate labeling and units. Technologies/skills demonstrated: - Python, Cube/CubeList data models, unit handling, robust input validation, and cross-model visualization standardization.
11 Commits • 3 Features
Jan 1, 2025January 2025 (Month: 2025-01) – MetOffice/CSET visualization enhancements and reliability improvements. Key features delivered: - Line plotting and CubeList support enhancements: extended line plotting to render multiple cubes on a single line, fixed axis association during line series plotting, refactored to use CubeList naming and removed intermediate storage, and extended vertical plotting to handle CubeLists. - Scatter plotting with CubeList support: robust handling of CubeList inputs, ensured cube_x and cube_y are iterable, and extracted units from the first CubeList element for accurate labeling. - Unified colorbars for cross-model visualization: standardized colorbars for relative humidity and cloud base altitude across UM and LFRic to improve comparability. Major bugs fixed: - Axis handling in line plotting (big fix in the plot command) to correctly associate axes for multi-cube line series. - Ensured cube_x and cube_y are iterable by wrapping single cubes into CubeLists when needed. - Correctly retrieving units when inputs are CubeLists (cube[0].units). - Documentation: fixed typo 'CUbeList' to 'CubeList' in scatter_plot docstring. Overall impact and accomplishments: - Improved reliability and interpretability of meteorological visualizations across models, enabling faster cross-model comparisons and decision-making. - Enhanced maintainability through CubeList-based data structures and consistent naming, reducing future regression risk. - Demonstrated end-to-end capability: from data structures (Cube/CubeList) to user-facing plots with accurate labeling and units. Technologies/skills demonstrated: - Python, Cube/CubeList data models, unit handling, robust input validation, and cross-model visualization standardization.
January 2025
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024 — Key accomplishments and impact for MetOffice/CSET. Feature delivered: multi-dataset line plotting in plot_line_series by supporting iris.cube.CubeList input. The plotting logic now iterates through each cube in the CubeList and returns the plotted cube(s), enabling a single plot of multiple related datasets. Code change committed: eeeed2e8c5023b661fbd7c1018cc79a8918a712d with message 'include cubeList in line plotting operator.' Major bugs fixed: none reported this month; minor robustness improvements were made to the plotting pipeline to better handle CubeList inputs. Business value: faster, more informative visual analysis; supports consistent visualization for related datasets and reduces manual plotting steps for analysts. Technologies/skills demonstrated: Python, iris library usage, data visualization, version control (Git) and codebase integration in MetOffice/CSET.
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024 — Key accomplishments and impact for MetOffice/CSET. Feature delivered: multi-dataset line plotting in plot_line_series by supporting iris.cube.CubeList input. The plotting logic now iterates through each cube in the CubeList and returns the plotted cube(s), enabling a single plot of multiple related datasets. Code change committed: eeeed2e8c5023b661fbd7c1018cc79a8918a712d with message 'include cubeList in line plotting operator.' Major bugs fixed: none reported this month; minor robustness improvements were made to the plotting pipeline to better handle CubeList inputs. Business value: faster, more informative visual analysis; supports consistent visualization for related datasets and reduces manual plotting steps for analysts. Technologies/skills demonstrated: Python, iris library usage, data visualization, version control (Git) and codebase integration in MetOffice/CSET.
November 2024
4 Commits • 2 Features
Nov 1, 2024November 2024 monthly summary for MetOffice/CSET. Focused on two key feature improvements: updating welcome content to clearly communicate capabilities and aligning with RAL model development, and enhancing plotting for readability and consistency. Deliverables improve user onboarding, interpretation of results, and plot usability across datasets.
4 Commits • 2 Features
Nov 1, 2024November 2024 monthly summary for MetOffice/CSET. Focused on two key feature improvements: updating welcome content to clearly communicate capabilities and aligning with RAL model development, and enhancing plotting for readability and consistency. Deliverables improve user onboarding, interpretation of results, and plot usability across datasets.
November 2024
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Quality Metrics
Correctness85.4%
Maintainability86.6%
Architecture80.8%
Performance73.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
JavaScriptPythonrst
Technical Skills
Atmospheric ModelingBack-end DevelopmentBackend DevelopmentBug FixingCode FormattingCode OrganizationCode RefactoringData AnalysisData HandlingData ProcessingData StructuringData VisualizationDocumentationFile HandlingFront End Development
Repositories Contributed To
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