Version 0.0.12

Major Features

Comprehensive Visualization System

• New visualization modules for neural data analysis:
  • neural.py: Spike rasters, population activity, connectivity matrices, firing rate maps
  • three_d.py: 3D visualizations for neural networks, brain surfaces, trajectories, electrode arrays
  • statistical.py: Statistical plotting tools (confusion matrices, ROC curves, correlation plots)
  • interactive.py: Interactive visualizations with Plotly support
  • colormaps.py: Neural-specific colormaps and publication-ready styling
• 15+ new tutorial notebooks covering all visualization techniques
• Brain-specific colormaps for membrane potential, spike activity, and connectivity

Enhanced Numerical Integration

• New ODE integrators:
  • Runge-Kutta methods: RK23, RK45, RKF45, DOP853, DOPRI5, SSPRK33
  • Specialized methods: Midpoint, Heun, RK4(3/8), Ralston RK2/RK3, Bogacki-Shampine
• New SDE integrators: Heun, Tamed Euler, Implicit Euler, SRK2, SRK3, SRK4
• IMEX integrators for stiff equations: Euler, ARS(2,2,2), CNAB
• DDE integrators for delay differential equations
• Comprehensive test coverage and accuracy verification

Advanced Spike Processing

• Spike encoders: Rate, Poisson, Population, Latency, and Temporal encoders
• Enhanced spike operations with bitwise functionality
• Spike metrics: Victor-Purpura distance, spike train synchrony, correlation indices
• Tutorial notebooks for spike encoding and analysis

New Optimization Framework

• NevergradOptimizer: Integration with Nevergrad optimization library
• ScipyOptimizer: Enhanced scipy optimization with flexible bounds support
• Refactored optimizer architecture for better extensibility
• Support for dict and sequence parameter bounds

Improvements

File Management

• Enhanced msgpack serialization with mismatch handling options
• Improved checkpoint loading with better error recovery
• Support for handling mismatched keys during state restoration

Metrics and Analysis

• LFP analysis functions: Power spectral density, coherence analysis, phase-amplitude coupling
• Functional connectivity: Dynamic connectivity computation
• Classification metrics: Binary, multiclass, focal loss, and smoothing techniques
• Regression losses: MSE, MAE, Huber, and quantile losses

Documentation

• Added comprehensive API documentation for all new modules
• Created tutorials for:
  • ODE/SDE integration methods
  • Classification and regression losses
  • Pairwise and embedding similarity
  • Spiking metrics and LFP analysis
  • Advanced neural visualization techniques
• Updated project description from "brain modeling" to "brain simulation"
• Changed references from BrainPy to BrainTools throughout

Code Quality

• Added extensive unit tests for all new modules
• Improved type hints and parameter documentation
• Better error handling and validation
• Consistent API design across modules

Breaking Changes

• Refactored optimizer module structure (moved from single optimizer.py to separate modules)
• Removed unused key parameter from spike encoder methods
• Updated some function signatures for clarity

Bug Fixes

• Fixed Softplus unit scaling issues
• Corrected paths in publish workflow
• Fixed formatting in ODE integrator documentation
• Resolved msgpack checkpoint handling errors

What's Changed

• ⬆️ Bump actions/download-artifact from 4 to 5 by @dependabot[bot] in #34
• ⬆️ Bump actions/setup-python from 5 to 6 by @dependabot[bot] in #35
• Add new metrics, integrators, encoders, and optimizers; update documentation by @chaoming0625 in #36
• Add comprehensive visualization modules and msgpack mismatch handling by @chaoming0625 in #37
• Add animation and dynamics tutorial by @chaoming0625 in #38

Full Changelog: v0.0.11...v0.0.12