arayabrain/barebone-studio
Mar 2025 – Mar 2025
1 Month active
Languages Used
MarkdownPythonTypeScriptYAML
Technical Skills
API IntegrationAlgorithm DevelopmentAlgorithm ImplementationBackend DevelopmentConfiguration ManagementData Processing
ykyamane
PROFILE
Ykyamane
Developed a new ROI processing pathway for the arayabrain/barebone-studio repository, focusing on the vacant_roi feature to support future manual ROI editing and robust data workflows. Designed and implemented the core algorithm in Python, integrating utility modules and YAML-based configuration management to ensure modularity and maintainability. Refactored zero-ROI handling to address edge cases and enhance data integrity, while deprecating direct timeseries_dff storage to decouple data layers and enable future extensibility. Prepared the visualization module for manual ROI editing and provided comprehensive documentation. The work emphasized backend development, algorithm implementation, and configuration-driven design, laying a foundation for stable ROI visualization features.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
1
Lines of code
340
Activity Months1
Your Network
8 peopleShared Repositories
8
tiendayMember
emuemuJPMember
MilesMember
Sang Le vinhMember
Yutaka TsuchiyamaMember
tsuchiyama-arayaMember
tuannaMember
Yutaka TsuchiyamaMember
Work History
March 2025
3 Commits • 1 Features
Mar 1, 2025March 2025 performance summary for arayabrain/barebone-studio. Delivered the vacant_roi ROI processing pathway and prepared visualization workflows for manual ROI editing. Implemented algorithm, added wrapper and utility layers and YAML config, documented changes, and refactored zero-ROI handling. Deprecated direct timeseries_dff storage within vacant_roi to improve data integrity and future-proof ROI workflows. These changes lay groundwork for stable ROI visualization, future manual editing features, and a more maintainable ROI data model.
3 Commits • 1 Features
Mar 1, 2025March 2025 performance summary for arayabrain/barebone-studio. Delivered the vacant_roi ROI processing pathway and prepared visualization workflows for manual ROI editing. Implemented algorithm, added wrapper and utility layers and YAML config, documented changes, and refactored zero-ROI handling. Deprecated direct timeseries_dff storage within vacant_roi to improve data integrity and future-proof ROI workflows. These changes lay groundwork for stable ROI visualization, future manual editing features, and a more maintainable ROI data model.
March 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance66.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPythonTypeScriptYAML
Technical Skills
API IntegrationAlgorithm DevelopmentAlgorithm ImplementationBackend DevelopmentConfiguration ManagementData ProcessingDocumentationRefactoring
Repositories Contributed To
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