User Guide

This guide provides detailed explanations of neurospatial's features and workflows.

Contents

• Environments: Creating and working with Environment objects
• Layout Engines: Understanding different discretization strategies
• Regions: Defining and managing regions of interest
• Video Annotation: Define environments from video frames interactively
• Composite Environments: Merging multiple environments
• Alignment & Transforms: Transforming spatial representations
• Spatial Analysis: Trajectory analysis, movement patterns, and field operations
• Performance & Caching: Memory management, optimization, and benchmarks
• Complete Workflows: End-to-end analysis examples

Who This Guide Is For

This guide is for users who:

• Have completed the Quickstart
• Want to understand specific features in depth
• Need to solve complex spatial analysis problems
• Want to customize neurospatial for their use case

Prerequisites

• Completed Getting Started section
• Familiarity with NumPy arrays and basic Python
• Understanding of spatial coordinates

Navigation

Each page covers a specific feature area with:

• Conceptual explanations
• Code examples
• Common patterns and best practices
• Troubleshooting tips

Quick Links

Common Tasks:

• Creating different environment types
• Choosing the right layout engine
• Defining regions
• Annotating video frames
• Computing occupancy and firing rates
• Analyzing movement patterns
• Computing distance fields
• Combining multiple environments
• Aligning spatial maps
• Optimizing performance and managing memory

See Also

• API Reference: Detailed API documentation
• Examples: Real-world use cases
• Getting Started: Beginner tutorials