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Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[Unreleased]

[0.9.0] - 2026-04-19

Added

  • RNG accessors: new public API for reproducible random draws
    • myogen.get_random_generator() — always returns the current global RNG (tracks the latest set_random_seed call)
    • myogen.get_random_seed() — returns the seed currently in effect
    • myogen.derive_subseed(*labels) — deterministic sub-seed helper for seeding non-NumPy generators (Cython spike generators, sklearn random_state, etc.) so they also track set_random_seed
  • Optional elephant extra: install via pip install myogen[elephant]. The extra bundles both elephant>=1.1.1 and viziphant>=0.4.0 (viziphant was moved out of core dependencies because its only transitive import chain in core came from elephant). Core install is now genuinely elephant-free — verified with importlib.util.find_spec('elephant') is None on a fresh uv sync. The five modules that import elephant (utils/helper.py, surface_emg.py, intramuscular_emg.py, force_model.py, force_model_vectorized.py) were already guarded with try/except ImportError and now emit an accurate install hint when the extra is missing. neo>=0.14.0 is now an explicit core dependency — it was previously only reached transitively through elephant/viziphant, so removing those would otherwise break import myogen
  • Test suite under tests/
    • test_determinism.py — 10 regressions covering seed propagation, sub-seed collision avoidance, and deprecation warnings for the legacy RNG names
    • test_firing_rate_statistics.py — 4 regressions covering FR_std and CV_ISI NaN edge cases
    • Added pytest>=8.0 to the dev dependency-group and a [tool.pytest.ini_options] section
  • Per-muscle ISI/CV figure: new plot_cv_vs_fr_per_muscle() in examples/02_finetune/05_plot_isi_cv_multi_muscle_comparison.py emits a 3-panel VL / VM / FDI breakdown alongside the existing pooled plot

Changed

  • RNG architecture (internal refactor): the six internal modules and eight example scripts that previously did from myogen import RANDOM_GENERATOR, SEED at module scope now call the accessor at each site, eliminating the stale-reference bug where set_random_seed didn't reach downstream modules or seed-derived generators
  • Per-cell seed derivation: the three sites in myogen/simulator/neuron/cells.py that built a per-cell seed as SEED + (class_id+1)*(global_id+1) — a formula that collided on swapped factors, e.g. (0, 5) and (1, 2) both resolved to +6 — now use derive_subseed(class_id, global_id) (collision-free with respect to label order, built on numpy.random.SeedSequence). The motor_unit_sim.py KMeans random_state uses the same helper. Consequence: for a given global seed, RNG output differs from earlier releases; byte-identical reproduction of pre-0.9.0 outputs is not possible without matching code
  • Example figures: bar graphs in 02_finetune/01_optimize_dd_for_target_firing_rate.py, 02_finetune/02_compute_force_from_optimized_dd.py and 03_papers/watanabe/01_compute_baseline_force.py replaced with dumbbell / violin + box + jittered-scatter plots that show the underlying distribution (all points when n<10, violin + box when n≥10)
  • NEURON version alignment: README.md, docs/source/README.md, docs/source/index.md, and setup.py Windows-install messaging now reference NEURON 8.2.7 (matching the Linux/macOS pip pin in pyproject.toml and the CI workflow) with the correct installer filename (py-39-310-311-312-313)
  • Docs build: pinned sphinx<9 in the docs dependency-group to work around a sphinx-hoverxref regression on Sphinx 9, and moved [tool.pytest.ini_options] in pyproject.toml so it no longer re-parents the docs dependency-group

Deprecated

  • myogen.RANDOM_GENERATOR and myogen.SEED module attributes. They remain accessible via a module-level __getattr__ that emits a DeprecationWarning and returns the current RNG / current seed. External code should migrate to get_random_generator() / get_random_seed(); module-level from myogen import RANDOM_GENERATOR captures a stale reference and does not reflect later set_random_seed calls

Fixed

  • FR_std = NaN with a single active unit: myogen/utils/helper.py::calculate_firing_rate_statistics now returns FR_std = 0.0 when fewer than two units pass the firing-rate filter, instead of propagating the np.std(..., ddof=1) NaN into downstream ensemble statistics
  • CV_ISI = NaN for n=1 ISI: same function's per-neuron branch now returns 0.0 when min_spikes_for_cv is set to 2 and a neuron has exactly two spikes
  • set_random_seed did not propagate: module-level from myogen import RANDOM_GENERATOR, SEED imports in the internal modules captured a stale reference at import time; reseeding the package rebinding did not affect them. The accessor refactor above is the fix
  • Typos / placeholder docstrings: extandable → extensible in README and docs; "as determined by no one" docstring comments in myogen/simulator/core/muscle/muscle.py replaced with concrete physiological rationale

[0.8.5] - 2026-01-15

Fixed

  • Beartype Type Validators: Fixed SURFACE_MUAP__Block and SURFACE_EMG__Block type validators to expect 2D signal shapes (samples, n_electrodes) instead of 3D, matching the actual output from create_grid_signal() which was refactored for NWB compatibility in v0.8.3
  • Firing Rate Calculation: Fixed inf Hz firing rates in example 02_simulate_spike_trains_current_injection.py by requiring at least 2 spikes to compute rate over spike range (single-spike neurons caused division by zero)

Changed

  • Build System: Pinned build dependencies in pyproject.toml to exact versions from uv.lock (numpy==1.26.4, scipy==1.16.3) to ensure reproducible wheel builds

[0.8.4] - 2026-01-06

Added

  • Verbose Parameter: Added verbose=True parameter throughout the codebase to control tqdm progress bars and informational print statements
    • ForceModel.generate_force(verbose=True) - controls progress bars during force generation
    • ForceModelVectorized.generate_force(verbose=True) - controls print statements
    • SurfaceEMG.simulate_muaps(verbose=True) and simulate_surface_emg(verbose=True) - controls progress bars
    • IntramuscularEMG.simulate_muaps(verbose=True) and simulate_intramuscular_emg(verbose=True) - controls progress bars and print statements
    • Muscle.generate_muscle_fiber_centers(verbose=True) and assign_mfs2mns(verbose=True) - controls progress bars and status messages
    • MotorUnitSim.calc_sfaps(verbose=True) - controls progress bar during SFAP calculation
    • SimulationRunner.run(verbose=True) - controls simulation progress bar and completion message
    • ContinuousSaver(verbose=True), load_and_combine_chunks(verbose=True), convert_chunks_to_neo(verbose=True) - controls all logging output
    • plot_innervation_areas_2d(verbose=True) - controls plotting progress bar
    • All parameters default to True (original behavior). Set verbose=False to silence output.

[0.8.3] - 2026-01-01

Added

  • NWB Export Support: New utilities for exporting simulation data to Neurodata Without Borders (NWB) format
    • Added myogen.utils.nwb module with export_to_nwb(), export_simulation_to_nwb(), and validate_nwb() functions
    • New optional dependency group [nwb] with pynwb>=2.8.0 and nwbinspector>=0.5.0
    • Example script 13_load_and_inspect_nwb_data.py demonstrating NWB export and loading
  • Grid Signal Utilities: New myogen.utils.neo module for grid-annotated signals
    • create_grid_signal(): Create NWB-compatible AnalogSignals with grid metadata in annotations
    • signal_to_grid(): Convert 2D signals back to 3D grid format for analysis

Changed

  • Grid Signal Storage: Electrode array signals now stored as 2D (time, n_electrodes) for NWB compatibility
    • Grid structure preserved in signal annotations (grid_shape, electrode_positions, ied)
    • Use signal_to_grid() to convert back to 3D (time, rows, cols) for analysis
  • Neo Signal Naming: Improved signal naming conventions for NWB compatibility
    • AnalogSignal names now follow NWB-compliant patterns

Fixed

  • Sphinx Gallery NEURON State: Added reset_neuron() function to reset NEURON state between examples
    • Fixes "works on second run" issue caused by HOC state persistence
  • Example Scripts: Updated examples to use new grid signal API
    • 05_simulate_surface_muaps.py: Use signal_to_grid() for 3D grid access
    • 06_simulate_surface_emg.py: Access grid dimensions from annotations
    • 12_extract_data_from_neo_blocks.py: Use signal_to_grid() for grid analysis

[0.8.2] - 2025-12-28

Added

  • Windows Prerequisites Documentation: Added Visual C++ Build Tools requirement to README
    • Users must install Visual C++ Build Tools
    • Required components: MSVC Build Tools for x64/x86 (Latest), MSVC v143 – VS 2022 C++ x64/x86 build tools, Windows 11 SDK (latest), C++ core desktop features

[0.8.1] - 2025-12-28

Changed

  • Dependencies: Removed unused dependencies
    • Removed pyqt6 (not used in codebase)
    • Moved scipy-stubs to dev dependencies only (was duplicated)

[0.8.0] - 2025-12-28

Added

  • Spinal Network Simulator: Enhanced connectivity and afferent population support
    • Improved interneuron and motor neuron connectivity patterns
    • Added Group II (GII) afferent pathway support
    • Enhanced afferent population configuration options
  • Strict Mode for NEURON: New error handling mode for mechanism loading
    • Added strict parameter to load_nmodl_files() function
    • Warnings by default, exceptions opt-in with strict=True
    • Clearer error messages when NEURON mechanisms fail to load
  • API Documentation: Added missing classes to API docs and module exports
    • HillModel - Hill-type muscle model
    • Network - Spinal network container
    • SimulationRunner - Simulation orchestration
    • JointDynamics - Joint dynamics model
    • SpindleModel - Muscle spindle proprioceptor
    • GolgiTendonOrganModel - Golgi tendon organ proprioceptor
    • ContinuousSaver and convert_chunks_to_neo utility functions

Changed

  • NEO Blocks Documentation: Consolidated 4 documentation files into single docs/neo_blocks.md
    • Reduced from ~47KB across multiple files to ~4.5KB single digestible document
    • Clearer structure with block types, access patterns, and troubleshooting
  • API Documentation Order: Reorganized simulator_api.rst to follow simulation workflow
    • RecruitmentThresholds → Populations → Network → SimulationRunner → Muscle → Proprioception → JointDynamics → Force → Electrodes → EMG
  • Watanabe Examples: Updated paper citations from 2013 to 2015 (J. Neurosci.)
    • Corrected DOI references across all example scripts
    • Simplified README to essential information only
  • README: Rewritten for beginners with uv as primary installation method

Fixed

  • Documentation Links: Fixed examples toctree paths (01_basic, 02_finetune)
  • Literature Reproductions Link: Added watanabe-reproduction ref label for cross-references

[0.7.0] - 2025-12-24

Added

  • Windows Registry Detection: Automatic detection of NEURON installations on any drive
    • Implements Windows Registry-based NEURON discovery for multi-drive support
    • Checks HKCU\SOFTWARE\NEURON_Simulator\nrn\Install_Dir and HKLM equivalents
    • Parses uninstall registry entries to locate NEURON installation path
    • Supports NEURON installations on D:, E:, or any drive (not just C:)
    • Registry detection takes priority over hardcoded paths for more reliable discovery

Changed

  • NEURON Detection Priority: Updated detection order for Windows installations
    1. Windows Registry (new - works for any drive)
    2. NEURONHOME environment variable
    3. Hardcoded C: drive paths (backwards compatibility)
    4. PATH search for mknrndll.bat
  • Applied registry detection to both build-time (setup.py) and runtime (nmodl.py) functions

[0.6.11] - 2025-12-16

Fixed

  • Windows Installation: Improved NEURON DLL loading during installation
    • Uses os.add_dll_directory() to properly add NEURON bin to DLL search path
    • Installation proceeds even if NEURON DLLs can't be loaded
    • CSV files and package data get installed successfully regardless
    • NEURON mechanisms can be compiled later after fixing NEURON setup
    • Better error messages showing NEURON paths for debugging

[0.6.10] - 2025-12-16

Fixed

  • Windows Installation: Added NEURON DLL detection in setup.py
    • Verifies NEURON can be imported before compilation
    • Provides clear PATH configuration instructions if DLLs not found
    • Resolves "DLL load failed while importing hoc" error
  • Package Data: Added CSV files to package distribution
    • Includes voronoi_pi1e5.csv and other data files
    • Added to both MANIFEST.in and pyproject.toml package-data

[0.6.9] - 2025-12-16

Fixed

  • CI Build: Fixed multi-line command execution in GitHub Actions
    • Changed CIBW_BEFORE_BUILD commands to single-line with && chaining
    • Resolves command concatenation error on macOS builds

Changed

  • CI Build: Temporarily disabled macOS wheel building
    • Focusing on Linux wheels to unblock PyPI publication
    • macOS users can install from source distribution

[0.6.8] - 2025-12-16

Fixed

  • Build System: Compile NEURON mechanisms before wheel build in CI
    • Added nrnivmodl compilation step in CIBW_BEFORE_BUILD
    • Mechanisms now properly included in wheels published to PyPI
    • Verified locally that wheels contain x86_64/libnrnmech.so

[0.6.7] - 2025-12-16

Fixed

  • CRITICAL: Compiled NEURON Mechanisms Missing from PyPI Wheels: Fixed CI workflow to preserve compiled mechanisms in published wheels
    • Replaced auditwheel repair with custom wheel renaming that preserves x86_64/ and arm64/ directories
    • Wheels now correctly tagged as manylinux_2_17_x86_64 while including all compiled NEURON mechanisms
    • Resolves "NEURON mechanisms not found" errors when installing from PyPI
    • Resolves "unsupported platform tag 'linux_x86_64'" upload error to PyPI
    • Users can now successfully pip install myogen or uv add MyoGen without compilation errors

[0.6.6] - 2025-12-16

Changed

  • Package Data Inclusion: Enhanced MANIFEST.in and pyproject.toml to include additional file types
    • Improved package data inclusion for better distribution completeness
    • Ensures all necessary files are included in source distributions and wheels

[0.6.5] - 2025-12-16

Fixed

  • NEURON Mechanisms Not Loading: Critical fix for "argument not a density mechanism name" error
    • Added automatic loading of NMODL mechanisms on MyoGen import
    • Added architecture-specific directories (x86_64, aarch64, arm64) to package-data
    • Mechanisms now load automatically from installed wheels
    • Resolves ValueError: argument not a density mechanism name for napp, kdrRL, etc.

[0.6.4] - 2025-12-16

Fixed

  • Missing Config Files: Added YAML configuration files to package distribution
    • Fixed FileNotFoundError: Configuration file not found: alpha_mn_default.yaml
    • Added **/*.yaml to tool.setuptools.package-data in pyproject.toml
    • Config files now properly included in wheels and source distributions

[0.6.2] - 2025-12-16

Changed

  • Package Description: Updated pyproject.toml description to match README overview
    • Now matches the language used in README for consistency
    • Emphasizes: modular framework, physiologically grounded, motor-unit activity, muscle force, surface EMG
  • README Installation Section: Improved layout for better user experience
    • Quick install commands (uv add MyoGen / pip install MyoGen) now at top
    • Windows NEURON warning prominently displayed before install commands
    • Detailed system requirements and prerequisites moved below quick start
    • Better visual organization with horizontal rules

[0.6.1] - 2025-12-16

Fixed

  • README Display on PyPI: Fixed logo not showing on PyPI package page
  • Version Badge: Updated from 0.5.0 to 0.6.1

[0.6.0] - 2025-12-16

Added

  • Package Metadata: Complete PyPI metadata following Python packaging best practices
    • Added authors and maintainers information
    • Added license field (AGPL-3.0-or-later)
    • Added comprehensive classifiers for PyPI categorization
    • Added project URLs (homepage, documentation, repository, issues, changelog)
    • Added keywords for better package discoverability
  • Automatic Build System: Comprehensive automatic NMODL compilation during package build
    • New setup.py with custom BuildWithNMODL class that compiles NMODL files during wheel building
    • Automatic Cython extension compilation integrated into build process
    • Platform-specific NMODL compilation for Linux (nrnivmodl) and Windows (mknrndll.bat)
    • No more manual uv run poe setup_myogen required for end users installing via pip
  • CI/CD Workflow: GitHub Actions workflow for automated wheel building and publishing
    • Uses cibuildwheel for PyPI-compatible manylinux wheels (Linux) and universal wheels (macOS)
    • Automatic wheel building for Linux (x86_64) and macOS ARM (arm64) with pre-compiled NMODL mechanisms
    • Updated to use macos-latest (ARM) runner (macos-13 deprecated)
    • Wheels built on manylinux2014 with proper manylinux_2_17_x86_64 platform tags
    • MPI libraries marked as external dependencies (users install system MPI separately)
    • Multi-platform testing of built wheels before publishing
    • OIDC-based PyPI publishing (no API tokens needed)
    • Automated MPI/OpenMPI installation in CI for both Linux and macOS
    • Source distribution (sdist) building alongside wheels
    • Auto-trigger PyPI publishing on GitHub releases and version tags
    • Automatic upload of wheels and sdist to GitHub release assets
  • Windows Installation Support: Clear error handling for Windows users
    • Installation fails with helpful error message if NEURON not pre-installed on Windows
    • Directs users to download NEURON installer from official source
    • Automatic build from source when NEURON is available

Changed

  • Platform Dependencies: Updated NEURON dependency to be platform-specific
    • neuron==8.2.7 now only installed automatically on Linux and macOS
    • Windows users must manually install NEURON before pip installing MyoGen
    • Combined dependency declaration for both Linux and macOS using sys_platform conditions
  • Elephant Dependency: Added elephant from PyPI as required dependency
    • Elephant 1.1.1 included for spike train conversion and statistics
    • Provides BinnedSpikeTrain conversion and isi for EMG/force simulations
    • Graceful error handling if elephant import fails (development safety)
  • NumPy Version: Pinned to numpy <2.0 for elephant compatibility
    • Elephant 1.1.1 requires numpy <2.0
    • Ensures stable, tested dependency versions
  • Sphinx Workflow: Kept setup_myogen call in documentation build workflow
    • Required for editable installs used in CI/CD environments
    • Ensures NMODL mechanisms are compiled for documentation examples
  • Wheel Distribution: Changed wheel building strategy
    • Pre-built wheels only for Linux and macOS (platforms with pip-installable NEURON)
    • Windows users install from source distribution with automatic build
    • Improved test isolation by removing source checkout from wheel testing job

Fixed

  • CI Testing: Fixed wheel testing to use installed packages instead of source
    • Removed source checkout from test_wheels job to prevent import conflicts
    • Tests now properly validate compiled Cython extensions in wheels
    • Ensures wheels contain all necessary compiled components

Removed

  • Windows Wheels: No longer building Windows wheels in CI
    • Windows users install from source distribution instead
    • Simplifies build process and avoids NEURON installation complications on Windows

[0.5.0] - 2025-12-15

Changed

  • Version bump to 0.5.0
  • Updated documentation links to latest version
  • Updated Python version badge to indicate support for Python 3.12
  • Improved basically everything

[0.4.0] - 2025-08-10

Added

  • Type System Enhancement: New RECRUITMENT_THRESHOLDS__ARRAY custom type alias for 1D recruitment threshold arrays with runtime validation via Beartype
  • Development Guidelines: Comprehensive CLAUDE.md with development protocols:
    • Git workflow with logical commit chunking and co-authorship requirements
    • Example development guidelines with professional plotting styles and Sphinx Gallery format
    • API testing requirements and font warning suppression protocols
    • CHANGELOG.md update requirements for all changes
  • Naming Standards: Enhanced CLAUDE.md with comprehensive naming conventions:
    • Prohibition of unclear abbreviations (e.g., mf, cv)
    • Mandatory unit suffixes for all physical quantities
    • Consistent spatial coordinate notation (positions__mm, centers__mm)
    • Velocity notation standards (conduction_velocities__mm_per_s)
  • Class Documentation: Added comprehensive Attributes sections to class docstrings documenting all computed properties
  • EMG API Consistency: Updated SurfaceEMG and IntramuscularEMG classes with proper MyoGen framework patterns:
    • Immutable public argument pattern: constructor arguments accessible but never modified
    • Private result storage: simulation results stored in _private attributes
    • Property-based access: computed results accessed via validated @property methods
    • Comprehensive error handling: informative errors with guidance for beginners
    • Enhanced method docstrings: document where results are stored after execution
  • Electrode Array Framework: Standardized SurfaceElectrodeArray and IntramuscularElectrodeArray classes:
    • Applied immutable public arguments pattern with private copies for internal use
    • Added comprehensive property-based access to computed attributes (pos_z, pos_theta, electrode_positions)
    • Enhanced error handling with informative messages and guidance for beginners
    • Added detailed Attributes sections to class docstrings documenting all computed properties
  • Force Model Integration: Enhanced ForceModel class with improved parameter naming and type validation:
    • Applied @beartowertype decorator for runtime parameter validation
    • Standardized parameter names with clear unit suffixes (contraction_time_range__unitless)
    • Updated property names for consistency (peak_twitch_forces__unitless, contraction_times__samples)
  • Current Generation API: Standardized current generation functions with consistent parameter naming:
    • Updated sawtooth_current: widths → widths__ratio, timestep_ms → timestep__ms
    • Updated step_current: timestep_ms → timestep__ms
    • Updated trapezoid_current: timestep_ms → timestep__ms
  • Import Organization: Restructured import statements across all modules for better dependency management and consistency

Changed

  • API Breaking Changes: Enhanced generate_mu_recruitment_thresholds function with improved type safety:
    • Added @beartowertype decorator for runtime parameter validation
    • Updated parameter names with scientific unit suffixes:
      • recruitment_range → recruitment_range__ratio (dimensionless ratio)
      • konstantin__max_threshold → konstantin__max_threshold__ratio (dimensionless ratio)
      • deluca__slope__per_hundred_units → deluca__slope (dimensionless shape parameter)
    • Return type now uses RECRUITMENT_THRESHOLDS__ARRAY custom type
    • Enhanced docstring with explicit dimensionality information and corrected examples
  • Muscle Class API Breaking Changes: Standardized attribute naming with clear unit suffixes and descriptive names:
    • mf_centers → muscle_fiber_centers__mm (muscle fiber center positions in mm)
    • mf_diameters → muscle_fiber_diameters__mm (muscle fiber diameters in mm)
    • mf_cv → muscle_fiber_conduction_velocities__mm_per_s (conduction velocities in mm/s)
    • muscle_border → muscle_border__mm (muscle boundary points in mm)
    • innervation_center_positions → innervation_center_positions__mm (motor unit centers in mm)
    • Applied class-level @beartowertype decorator for automatic method type validation
    • Enhanced class docstring with comprehensive Attributes section documenting all computed properties
    • Updated plotting utilities and EMG simulation modules to use new attribute names
  • Example Updates: Updated all examples to use new API parameter names and consistent patterns:
    • Updated 00_simulate_recruitment_thresholds.py with new parameter names
    • Updated 02_simulate_muscle.py with reduced fiber density for faster demonstration
    • Updated 03_simulate_surface_muaps.py to remove deprecated MUs_to_simulate parameter
    • Updated 04_simulate_surface_emg.py with corrected file path references
    • Updated 05_simulate_currents.py with standardized current generation parameter names
    • Updated 06_simulate_force.py with new force model parameter names and property access
    • Updated 08_simulate_intramuscular_emg.py with new recruitment threshold parameter names
  • Repository Cleanup: Enhanced .gitignore to exclude generated files and development artifacts:
    • Added .idea/ (IDE configuration files)
    • Added docs/source/auto_examples/, docs/source/generated/, docs/source/sg_execution_times.rst (Sphinx generated files)
    • Added examples/results/, results/ (temporary simulation outputs)
    • Added test_*.png, *.code-workspace (development artifacts)

Fixed

  • Parameter Naming: Removed misleading __per_hundred_units suffix from deluca__slope parameter that incorrectly suggested it had units
  • Scientific Accuracy: Corrected deluca__slope description as dimensionless curvature control parameter rather than rate parameter

Removed

  • Deprecated Plotting Module: Removed myogen/utils/plotting/plotting.py module with generic plotting functions
    • Functionality has been moved to specialized plotting modules (currents.py, force.py, muscle.py, etc.)
    • This provides better organization and clearer separation of concerns

[0.3.0] - 2025-08-08

Added

  • Intramuscular EMG Framework: Enhanced intramuscular EMG simulation capabilities with improved framework
  • Optional CUDA/CuPy support for accelerated computations in intramuscular EMG
  • New type definitions for EMG simulation components:
    • CORTICAL_INPUT__MATRIX type for cortical input data
    • INTRAMUSCULAR_MUAP_SHAPE__TENSOR for intramuscular electrode arrays

Changed

  • Major Refactor: Improved intramuscular EMG simulation framework with better type annotations and imports
  • Enhanced IntramuscularEMG class with better parameter handling
  • Optimized bioelectric field calculations for needle electrodes
  • Updated surface EMG components for consistency with intramuscular framework
  • Enhanced muscle model integration with electrode positioning
  • Improved motor unit simulation with better parameter handling
  • Enhanced recruitment thresholds plotting utilities
  • Updated project dependencies and compatibility with latest package versions
  • Enhanced Sphinx documentation configuration with better type aliases and extensions
  • Renamed MUAP_SHAPE__TENSOR to SURFACE_MUAP_SHAPE__TENSOR for better clarity

Fixed

  • Ensured Mermaid diagrams have consistent white background in documentation
  • Improved readability and visual consistency in documentation
  • Enhanced development experience with updated VSCode settings

[0.2.0] - 2025-07-26

Added

  • Cortical Input Module: Comprehensive cortical input generation functionality with multiple waveform types:
    • create_sinusoidal_cortical_input() - Sinusoidal cortical inputs with configurable amplitude, frequency, offset, and phase
    • create_sawtooth_cortical_input() - Sawtooth waveform inputs with adjustable width and phase
    • create_step_cortical_input() - Step function inputs with configurable duration and height
    • create_ramp_cortical_input() - Linear ramp inputs between start and end firing rates
    • create_trapezoid_cortical_input() - Trapezoidal inputs with configurable rise, plateau, and fall times
  • New example script 07_simulate_cortical_input.py demonstrating cortical input simulation
  • Enhanced spike train plotting functionality with improved visualization tools

Changed

  • API Simplification: Removed explicit load_nmodl_files() calls from example scripts for cleaner user experience
  • Improved code readability and organization in spike train classes
  • Enhanced error handling and callback mechanisms in spike train simulation

Fixed

  • Fixed callback errors in spike train simulation for improved stability
  • Improved code structure and readability across multiple modules

[0.1.1] - 2025-07-26

Added

  • Surface electrode array classes (SurfaceElectrodeArray) for EMG simulation
  • Numba dependency for performance optimization

Changed

  • Refactored surface EMG simulation for improved performance and API consistency
  • Updated current creation functions for better usability
  • MUAPs will be min-max scaled when generating surface EMG signals to avoid numerical instability
  • Generated EMG signals will be sampled to the sampling rate of the MUAPs to avoid numerical instability
  • Enhanced Muscle model documentation and updated parameters for improved accuracy
  • Improved simulation scripts readability and updated muscle parameters
  • Updated numpy version requirement to >=1.26 for better compatibility
  • Updated time axis calculation for surface EMG plotting
  • Adapted saved surface EMG data format to work with new API

Fixed

  • Improved handling of NaN values in MUAP scaling
  • Updated tensor dimensions in type annotations for better type safety
  • Commented out IntramuscularEMG and IntramuscularElectrodeArray imports to resolve import issues

Removed

  • Unnecessary files cleaned up from repository

[0.1.0] - 2025-07-19

Added

  • Initial release of MyoGen EMG simulation toolkit
  • Surface EMG simulation capabilities
  • Motor neuron pool modeling
  • Muscle fiber simulation
  • Force generation modeling
  • Comprehensive plotting utilities
  • Documentation with Sphinx
  • Example gallery with multiple simulation scenarios
  • Support for Python >=3.12

Features

  • Surface EMG Simulation: Complete framework for simulating surface electromyography signals
  • Motor Unit Modeling: Physiological motor neuron pool simulation with recruitment thresholds
  • Muscle Mechanics: Detailed muscle fiber and force generation modeling
  • Signal Processing: Tools for EMG signal analysis and visualization
  • Extensible Architecture: Modular design for easy extension and customization

Documentation

  • Comprehensive API documentation
  • Tutorial examples covering key use cases
  • Gallery of simulation examples with visualizations
  • Getting started guide and installation instructions

Types of Changes

  • Added for new features
  • Changed for changes in existing functionality
  • Deprecated for soon-to-be removed features
  • Removed for now removed features
  • Fixed for any bug fixes
  • Security for vulnerability fixes