egttools.numerical.structure.factories.AbstractSpatialGame¶
- class AbstractSpatialGame(self: egttools.numerical.numerical_.games.AbstractSpatialGame)¶
Bases:
pybind11_object
Abstract base class for spatially structured games.
This interface supports general spatial interaction models, where the fitness of a strategy is computed based on a local context (e.g., neighborhood composition).
This is typically used in network-based or spatial grid environments.
Note
This interface is still under active development and may change in future versions.
Methods
Calculates the fitness of a strategy in a local interaction context.
Returns the number of strategies in the spatial game.
Identifier for the type of spatial game.
- __init__(self: egttools.numerical.numerical_.games.AbstractSpatialGame) None ¶
Abstract base class for spatially structured games.
This interface supports general spatial interaction models, where the fitness of a strategy is computed based on a local context (e.g., neighborhood composition).
This is typically used in network-based or spatial grid environments.
Note
This interface is still under active development and may change in future versions.
- __new__(**kwargs)¶
- __str__(self: egttools.numerical.numerical_.games.AbstractSpatialGame) str ¶
String representation of the spatial game.
- calculate_fitness(self: egttools.numerical.numerical_.games.AbstractSpatialGame, strategy_index: int, state: numpy.ndarray[numpy.uint64[m, 1]]) float ¶
Calculates the fitness of a strategy in a local interaction context.
- Parameters:
strategy_index (int) – The strategy of the focal player.
state (numpy.ndarray[int]) – Vector representing the local configuration (e.g., neighbor counts).
- Returns:
The computed fitness of the strategy in the given local state.
- Return type:
- nb_strategies(self: egttools.numerical.numerical_.games.AbstractSpatialGame) int ¶
Returns the number of strategies in the spatial game.
- type(self: egttools.numerical.numerical_.games.AbstractSpatialGame) str ¶
Identifier for the type of spatial game.
- __annotations__ = {}¶