API Reference¶

This section provides complete API documentation for all CoMPASS-Labyrinth modules, automatically generated from docstrings in the source code.

Overview¶

The CoMPASS-Labyrinth API is organized into several main modules:

Core Module¶

Core utilities for project initialization, data loading, and figure management.

Core Utilities - Project initialization, data loading, configuration

Behavior Module¶

Tools for behavioral data preprocessing and analysis.

Preprocessing - Data preprocessing utilities
Pose Estimation - DeepLabCut utilities
Performance Metrics - Task performance analysis
Success Metrics - Success rate computation
Trajectory Analysis - Movement trajectory analysis
Simulated Agents - Agent-based modeling

CoMPASS Module¶

Implementation of the two-level hierarchical probabilistic framework.

Level 1: Motor State Inference¶

Data Preparation - Prepare data for Level 1 modeling
HMM Models - Hidden Markov Model classes and fitting
Visualization - Level 1 visualization utilities

Level 2: Cognitive State Inference¶

Data Streams - Feature computation for Level 2
Models - BGMM and GMM-HMM implementations
Plotting - Level 2 visualization functions
Utilities - Helper functions for Level 2

Post-hoc Analysis Module¶

Tools for analyzing model outputs.

Spatial Analysis - Spatial distribution analysis
Temporal Analysis - Temporal dynamics analysis
Bout Analysis - Bout-wise analysis
Grid Heatmaps - Grid-based visualization

Quick Import Reference¶

# Core functions
from compass_labyrinth import init_project, load_project

# Behavior analysis
from compass_labyrinth.behavior.preprocessing import preprocessing_utils
from compass_labyrinth.behavior.behavior_metrics.task_performance_analysis import (
    performance_metrics,
    success_metrics,
    trajectory_analysis
)

# CoMPASS Level 1
from compass_labyrinth.compass.level_1 import prep_data, momentu, visualization

# CoMPASS Level 2
from compass_labyrinth.compass.level_2 import datastreams, model, plots, utils

# Post-hoc analysis
from compass_labyrinth.post_hoc_analysis.level_1 import (
    spatial_analysis,
    temporal_analysis,
    bout_analysis,
    grid_heatmap
)

Documentation Conventions¶

Parameters Function parameters with type hints and descriptions
Returns: Return values with type information
Examples: Usage examples where available
Source: Link to view source code on GitHub

All documentation is auto-generated from numpy-style docstrings in the source code.