neuroinformatics-unit/movement
Feb 2026 – Feb 2026
1 Month active
Languages Used
MarkdownPython
Technical Skills
PythonPython programmingdata analysisdata verificationdocumentationunit testing
Eduardo Augusto Almeida lira
PROFILE
Eduardo Augusto Almeida Lira
Developed two core features for the neuroinformatics-unit/movement repository, focusing on data verification and pose-based analytics. Built the poses_to_bboxes function in Python to compute 2D bounding boxes from pose keypoints, incorporating centroid and shape calculations, padding, and robust handling of NaN values, all supported by comprehensive unit tests. Enhanced contributor onboarding by updating documentation, relocating dataset verification examples, and streamlining the workflow with automated pre-commit CI checks. Leveraged Python, xarray, and Markdown to improve data integrity and reduce friction for new contributors, while refactoring test suites and code paths to ensure reliability and maintainability in downstream data analysis tasks.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
405
Activity Months1
Your Network
20 peopleWork History
February 2026
2 Commits • 2 Features
Feb 1, 2026February 2026 monthly summary: Delivered two high-impact features in neuroinformatics-unit/movement that enhance data verification and pose-based analytics, improved contributor docs and onboarding, and strengthened test coverage. These changes improve data integrity, reduce contributor friction, and provide robust primitives for downstream analysis such as 2D bounding boxes from pose keypoints. Tech stack and practices demonstrated include Python, testing, code organization, and documentation updates, with strong emphasis on automated quality checks via pre-commit CI.
2 Commits • 2 Features
Feb 1, 2026February 2026 monthly summary: Delivered two high-impact features in neuroinformatics-unit/movement that enhance data verification and pose-based analytics, improved contributor docs and onboarding, and strengthened test coverage. These changes improve data integrity, reduce contributor friction, and provide robust primitives for downstream analysis such as 2D bounding boxes from pose keypoints. Tech stack and practices demonstrated include Python, testing, code organization, and documentation updates, with strong emphasis on automated quality checks via pre-commit CI.
February 2026
Activity
Loading activity data...
Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture90.0%
Performance80.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
MarkdownPython
Technical Skills
PythonPython programmingdata analysisdata verificationdocumentationunit testingxarray
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline