larvaworld.lib.sim.agent_simulations

Functions

sim_models(→ list)	Simulate multiple agent models with specified configurations.
sim_model(→ Any)	Simulate single agent model with specified configuration.

Module Contents

larvaworld.lib.sim.agent_simulations.sim_models(modelIDs: list[str], colors: list[str] | None = None, groupIDs: list[str] | None = None, lgs: list[larvaworld.lib.reg.LarvaGroup | None] | None = None, data_dir: str | None = None, **kwargs: Any) → list

Simulate multiple agent models with specified configurations.

Runs simulations for multiple model configurations in parallel, returning datasets for each simulation run.

Args:

modelIDs: List of model configuration IDs to simulate. colors: Optional list of colors for visualization. groupIDs: Optional list of group IDs for batch processing. lgs: Optional list of LarvaGroup instances or None. data_dir: Optional directory for saving results. **kwargs: Additional simulation parameters.

Returns:

List of LarvaDataset instances, one for each simulation.

Example:

>>> datasets = sim_models(['explorer', 'forager'], N=100)

larvaworld.lib.sim.agent_simulations.sim_model(mID: str, Nids: int = 1, refID: str | None = None, refDataset: Any | None = None, imitation: bool = False, tor_durs: list[int] = [], dsp_starts: list[int] = [0], dsp_stops: list[int] = [40], enrichment: bool = True, parameter_dict: dict[str, Any] = {}, lg: larvaworld.lib.reg.LarvaGroup | None = None, env_params: dict[str, Any] = {}, dir: str | None = None, duration: float = 3, dt: float = 1 / 16, color: str = 'blue', dataset_id: str | None = None, **kwargs: Any) → Any

Simulate single agent model with specified configuration.

Runs a single simulation with the specified model configuration and returns the resulting dataset.

Args:

mID: Model configuration ID to simulate. Nids: Number of agents. lg: Optional LarvaGroup instance for simulation. enrichment: Whether to enrich dataset with analysis. **kwargs: Simulation parameters and configuration.

Returns:

LarvaDataset containing simulation results.

Example:

>>> dataset = sim_model(mID='explorer', duration=100.0)