aolabNeuro/analyze
Dec 2024 – Feb 2026
11 Months active
Languages Used
JSONPythonRSTYAMLpythonyamlSQLJupyter Notebook
Technical Skills
API DesignBehavioral AnalysisCode RefactoringData AnalysisData VisualizationData Wrangling
Katherine
PROFILE
Katherine
Katherine Perks developed and maintained the aolabNeuro/analyze repository, delivering a suite of features for behavioral data analysis and experimental data processing. She engineered robust trial segmentation, trajectory analysis, and coordinate transformation workflows, addressing challenges such as variable sample rates, baseline rotation, and edge-case event handling. Using Python, Pandas, and NumPy, Katherine refactored core data pipelines to improve reliability, added comprehensive test coverage, and enhanced documentation with runnable examples. Her work included targeted bug fixes, data integrity safeguards, and modular code organization, resulting in a maintainable analytics platform that supports reproducible research and scalable behavioral experiment analysis across diverse datasets.
Overall Statistics
Feature vs Bugs
81%Features
Repository Contributions
52Total
Bugs
4
Commits
52
Features
17
Lines of code
4,672
Activity Months11
Your Network
125 peopleSame Organization
@uw.edu116
Work History
February 2026
5 Commits • 2 Features
Feb 1, 2026February 2026: Focused on stabilizing the BMI3D tracking data pipeline in aolabNeuro/analyze and improving maintainability through documentation enhancements. Delivered robustness improvements to BMI3D data handling, including extracting common logic into a helper, adding safeguards and warnings for legacy entries, and reprocessing test data to reflect the changes. Also clarified the tabulated kinematic data samplerate behavior to support fixed or per-segment samplerates. These changes improve data integrity, reduce edge-case failures, and shorten onboarding for new contributors.
5 Commits • 2 Features
Feb 1, 2026February 2026: Focused on stabilizing the BMI3D tracking data pipeline in aolabNeuro/analyze and improving maintainability through documentation enhancements. Delivered robustness improvements to BMI3D data handling, including extracting common logic into a helper, adding safeguards and warnings for legacy entries, and reprocessing test data to reflect the changes. Also clarified the tabulated kinematic data samplerate behavior to support fixed or per-segment samplerates. These changes improve data integrity, reduce edge-case failures, and shorten onboarding for new contributors.
February 2026
January 2026
11 Commits • 4 Features
Jan 1, 20262026-01 Monthly Summary for aolabNeuro/analyze focusing on delivering high-value features, fixing critical data processing bugs, and strengthening test/data validation. Emphasis on business value: improved data fidelity, reliability of analysis, and maintainability to support per-subject variability and scalable testing.
January 2026
11 Commits • 4 Features
Jan 1, 20262026-01 Monthly Summary for aolabNeuro/analyze focusing on delivering high-value features, fixing critical data processing bugs, and strengthening test/data validation. Emphasis on business value: improved data fidelity, reliability of analysis, and maintainability to support per-subject variability and scalable testing.
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025: Delivered BMI3D Data Preparation Enhancements in the aolabNeuro/analyze repository, focusing on refining task handling and data transformations to improve accuracy in user input processing. No major bugs fixed this month. Impact: enhanced BMI3D input processing pipelines, leading to more reliable downstream analytics and model development. Technologies demonstrated: Python-based data processing, data transformation pipelines, and strong commit hygiene for maintainability and traceability.
1 Commits • 1 Features
Dec 1, 2025December 2025: Delivered BMI3D Data Preparation Enhancements in the aolabNeuro/analyze repository, focusing on refining task handling and data transformations to improve accuracy in user input processing. No major bugs fixed this month. Impact: enhanced BMI3D input processing pipelines, leading to more reliable downstream analytics and model development. Technologies demonstrated: Python-based data processing, data transformation pipelines, and strong commit hygiene for maintainability and traceability.
December 2025
October 2025
1 Commits
Oct 1, 2025Month: 2025-10 — Focused on hardening data quality in the aolabNeuro/analyze pipeline by ensuring boolean integrity for reward and penalty columns after data concatenation. This change prevents type drift when empty DataFrames are involved, safeguarding downstream analytics and model inputs. Implemented explicit casting to boolean in the data preparation step, linked to a concrete fix and commit for traceability.
October 2025
1 Commits
Oct 1, 2025Month: 2025-10 — Focused on hardening data quality in the aolabNeuro/analyze pipeline by ensuring boolean integrity for reward and penalty columns after data concatenation. This change prevents type drift when empty DataFrames are involved, safeguarding downstream analytics and model inputs. Implemented explicit casting to boolean in the data preparation step, linked to a concrete fix and commit for traceability.
September 2025
1 Commits • 1 Features
Sep 1, 20252025-09 monthly summary for aolabNeuro/analyze: Delivered targeted documentation enhancement to improve usability of tabulate_behavior_data_center_out, enabling faster adoption and fewer support queries. The change adds a concrete docstring example with a Python code block and an image reference, improving clarity and usability for developers and external users. The work is tracked in a single commit in the repository with clear traceability.
1 Commits • 1 Features
Sep 1, 20252025-09 monthly summary for aolabNeuro/analyze: Delivered targeted documentation enhancement to improve usability of tabulate_behavior_data_center_out, enabling faster adoption and fewer support queries. The change adds a concrete docstring example with a Python code block and an image reference, improving clarity and usability for developers and external users. The work is tracked in a single commit in the repository with clear traceability.
September 2025
June 2025
2 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary focusing on key accomplishments for aolabNeuro/analyze. Delivered a high-impact feature to enhance coordinate transformation accuracy by introducing baseline rotation handling and by refactoring rotation data imports to ensure correct rotation matrix usage. The work improves experimental data processing by accounting for initial orientation, enabling more reliable downstream analytics and reproducibility.
June 2025
2 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary focusing on key accomplishments for aolabNeuro/analyze. Delivered a high-impact feature to enhance coordinate transformation accuracy by introducing baseline rotation handling and by refactoring rotation data imports to ensure correct rotation matrix usage. The work improves experimental data processing by accounting for initial orientation, enabling more reliable downstream analytics and reproducibility.
May 2025
1 Commits • 1 Features
May 1, 2025May 2025 summary for aolabNeuro/analyze: groundwork laid for Baseline Rotation Metadata Support; no new features delivered this month and no bugs fixed. Key outcomes include documentation of planned integration in the codebase, enabling clear scoping for the upcoming work and reducing ambiguity in the data-path changes.
1 Commits • 1 Features
May 1, 2025May 2025 summary for aolabNeuro/analyze: groundwork laid for Baseline Rotation Metadata Support; no new features delivered this month and no bugs fixed. Key outcomes include documentation of planned integration in the codebase, enabling clear scoping for the upcoming work and reducing ambiguity in the data-path changes.
May 2025
April 2025
4 Commits • 2 Features
Apr 1, 2025April 2025 performance summary for aolabNeuro/analyze: Delivered focused enhancements to the tabulation module to support newer experiment formats and richer behavior data tracking. Implemented event_idx across tracking task and behavior data corners tabulations, updated unit tests, and expanded documentation with runnable examples. These changes improve data integrity, enable richer analytics pipelines, and enhance maintainability through better docs and test coverage.
April 2025
4 Commits • 2 Features
Apr 1, 2025April 2025 performance summary for aolabNeuro/analyze: Delivered focused enhancements to the tabulation module to support newer experiment formats and richer behavior data tracking. Implemented event_idx across tracking task and behavior data corners tabulations, updated unit tests, and expanded documentation with runnable examples. These changes improve data integrity, enable richer analytics pipelines, and enhance maintainability through better docs and test coverage.
February 2025
4 Commits • 1 Features
Feb 1, 2025February 2025: delivered major enhancements to Behavioral Data Tracking and trajectory segmentation in aolabNeuro/analyze, improving data quality and analytics capabilities across multiple task versions. Refactored segmentation logic to exclude ramp periods, expanded test coverage for ramp-phase events, and added new output columns for timing of key events, enabling more robust downstream analysis and reporting.
4 Commits • 1 Features
Feb 1, 2025February 2025: delivered major enhancements to Behavioral Data Tracking and trajectory segmentation in aolabNeuro/analyze, improving data quality and analytics capabilities across multiple task versions. Refactored segmentation logic to exclude ramp periods, expanded test coverage for ramp-phase events, and added new output columns for timing of key events, enabling more robust downstream analysis and reporting.
February 2025
January 2025
13 Commits • 2 Features
Jan 1, 2025January 2025 performance summary: Delivered two major features in aolabNeuro/analyze with accompanying test coverage and documentation updates. Implemented robust trial segmentation with repeating start events and extended the segmentation APIs to support optional repeating_start_events, backed by tests to validate behavior. Introduced comprehensive corner target support, including new task codes, a tabulation wrapper, handling variable target sequences, pause and ramp-up/down cursor events, and extensive documentation and tests. These changes improve data reliability, enable more nuanced analyses of behavioral experiments, and reduce risk of regressions through automated tests and clear docs.
January 2025
13 Commits • 2 Features
Jan 1, 2025January 2025 performance summary: Delivered two major features in aolabNeuro/analyze with accompanying test coverage and documentation updates. Implemented robust trial segmentation with repeating start events and extended the segmentation APIs to support optional repeating_start_events, backed by tests to validate behavior. Introduced comprehensive corner target support, including new task codes, a tabulation wrapper, handling variable target sequences, pause and ramp-up/down cursor events, and extensive documentation and tests. These changes improve data reliability, enable more nuanced analyses of behavioral experiments, and reduce risk of regressions through automated tests and clear docs.
December 2024
9 Commits • 2 Features
Dec 1, 2024Month: 2024-12 — Performance review-ready monthly summary for aolabNeuro/analyze. Focused on business value, reliability, and developer experience, with targeted feature delivery, critical bug fixes, and clear demonstrations of technical proficiency. Key outcomes include packaging and dependency stability, robustness of analytics utilities, corrected data tabulation for trials, and improved documentation and examples to accelerate adoption and reproducibility.
9 Commits • 2 Features
Dec 1, 2024Month: 2024-12 — Performance review-ready monthly summary for aolabNeuro/analyze. Focused on business value, reliability, and developer experience, with targeted feature delivery, critical bug fixes, and clear demonstrations of technical proficiency. Key outcomes include packaging and dependency stability, robustness of analytics utilities, corrected data tabulation for trials, and improved documentation and examples to accelerate adoption and reproducibility.
December 2024
Activity
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Quality Metrics
Correctness91.4%
Maintainability90.0%
Architecture88.4%
Performance87.2%
AI Usage20.4%
Skills & Technologies
Programming Languages
HDF5JSONJupyter NotebookPythonRSTSQLYAMLpythonyaml
Technical Skills
API DesignAlgorithm DevelopmentBehavioral AnalysisBehavioral Data ProcessingCode DocumentationCode OrganizationCode RefactoringCoordinate TransformationsData AnalysisData ManipulationData ProcessingData VisualizationData WranglingDependency ManagementDocumentation
Repositories Contributed To
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