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API Reference

Complete API documentation for neurospatial, automatically generated from source code docstrings.

Core Modules

neurospatial.environment

The main Environment class and related functionality (modular package).

Key Classes:

  • Environment: Main class for discretized spatial environments

Modules:

  • environment.core: Core dataclass with state and properties
  • environment.factories: Factory classmethods for creating environments
  • environment.queries: Spatial query methods
  • environment.trajectory: Trajectory analysis methods
  • environment.fields: Spatial field operations
  • environment.metrics: Environment metrics and properties

neurospatial.composite

Merge multiple environments into composite structures.

Key Classes:

  • CompositeEnvironment: Combine multiple environments with automatic bridge inference

neurospatial.regions

Define and manage named regions of interest (ROIs).

Key Classes:

  • Region: Immutable point or polygon region
  • Regions: Container for managing multiple regions

neurospatial.layout

Layout engines for discretizing continuous space.

Key Modules:

  • layout.base: LayoutEngine protocol definition
  • layout.engines.*: Concrete layout implementations
  • layout.factories: Factory functions for creating layouts

neurospatial.alignment

Transform and align spatial representations.

Key Functions:

  • map_probabilities(): Align probability distributions between environments
  • get_2d_rotation_matrix(): Create 2D rotation matrices

neurospatial.transforms

2D affine transformations.

Key Classes:

  • Affine2D: Composable 2D affine transformations

neurospatial.simulation v0.2.0+

Generate synthetic spatial data, neural activity, and spike trains for testing and validation.

Key Modules:

  • simulation.trajectory: Trajectory generation (OU process, structured laps)
  • simulation.models: Neural models (place cells, boundary cells, grid cells)
  • simulation.spikes: Spike generation (Poisson process, refractory periods)
  • simulation.session: High-level session simulation API
  • simulation.validation: Automated validation against ground truth
  • simulation.examples: Pre-configured example sessions

Key Classes:

  • PlaceCellModel: Gaussian place field model with ground truth
  • BoundaryCellModel: Distance-tuned boundary/border cell model
  • GridCellModel: Hexagonal grid cell model (2D only)
  • SimulationSession: Complete simulation session dataclass

Key Functions:

  • simulate_trajectory_ou(): Ornstein-Uhlenbeck process for realistic exploration
  • simulate_trajectory_sinusoidal(): Sinusoidal movement for 1D tracks
  • simulate_trajectory_laps(): Structured lap-based trajectories
  • generate_poisson_spikes(): Generate spikes from firing rates
  • generate_population_spikes(): Generate spikes for neuron populations
  • simulate_session(): One-call workflow for complete sessions
  • validate_simulation(): Compare detected fields to ground truth
  • open_field_session(), linear_track_session(), etc.: Pre-configured examples

See Also:

Layout Engines

Detailed documentation for each layout engine:

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Docstring Format

All docstrings follow NumPy docstring conventions for consistency with the scientific Python ecosystem.