egttools.plotting.simplified.MatrixNPlayerGameHolder

class MatrixNPlayerGameHolder(self: egttools.numerical.numerical_.games.MatrixNPlayerGameHolder, nb_strategies: SupportsInt | SupportsIndex, group_size: SupportsInt | SupportsIndex, payoff_matrix: Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]', 'flags.c_contiguous'])

Bases: AbstractGame

Matrix-based N-player game holder.

Parameters:

  • nb_strategies (int) – Number of strategies in the game.

  • group_size (int) – Size of the interacting group.

  • payoff_matrix (numpy.ndarray) – Matrix encoding payoffs for all strategy-group pairs.

Methods

calculate_fitness

Computes the fitness of a strategy based on the current population state.

calculate_payoffs

Returns the internal matrix of precomputed payoffs.

group_size

nb_group_configurations

nb_strategies

payoff

Returns the payoff for a strategy given a specific group configuration.

payoffs

Returns the full payoff matrix.

play

Simulates the game based on a predefined payoff matrix.

save_payoffs

Saves the payoff matrix to a text file.

type

update_payoff_matrix

Replaces the stored payoff matrix with a new one.
__init__(self: egttools.numerical.numerical_.games.MatrixNPlayerGameHolder, nb_strategies: SupportsInt | SupportsIndex, group_size: SupportsInt | SupportsIndex, payoff_matrix: Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]', 'flags.c_contiguous']) → None

Matrix-based N-player game holder.

Parameters:

  • nb_strategies (int) – Number of strategies in the game.

  • group_size (int) – Size of the interacting group.

  • payoff_matrix (numpy.ndarray) – Matrix encoding payoffs for all strategy-group pairs.

__new__(**kwargs)
__str__(self: egttools.numerical.numerical_.games.MatrixNPlayerGameHolder) → str
calculate_fitness(self: egttools.numerical.numerical_.games.MatrixNPlayerGameHolder, player_strategy: SupportsInt | SupportsIndex, pop_size: SupportsInt | SupportsIndex, population_state: Annotated[numpy.typing.NDArray[numpy.uint64], '[m, 1]']) → float

Computes the fitness of a strategy based on the current population state.

Parameters:

  • player_strategy (int) – Index of the strategy used by the focal player.

  • pop_size (int) – Population size.

  • population_state (numpy.ndarray) – Vector of strategy counts in the population.

Returns:

Fitness of the focal strategy.

Return type:

float

calculate_payoffs(self: egttools.numerical.numerical_.games.MatrixNPlayerGameHolder) → Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]']

Returns the internal matrix of precomputed payoffs.

Return type:

numpy.ndarray

group_size(self: egttools.numerical.numerical_.games.MatrixNPlayerGameHolder) → int
nb_group_configurations(self: egttools.numerical.numerical_.games.MatrixNPlayerGameHolder) → int
nb_strategies(self: egttools.numerical.numerical_.games.MatrixNPlayerGameHolder) → int
payoff(self: egttools.numerical.numerical_.games.MatrixNPlayerGameHolder, strategy: SupportsInt | SupportsIndex, strategy_pair: collections.abc.Sequence[SupportsInt | SupportsIndex]) → float

Returns the payoff for a strategy given a specific group configuration.

payoffs(self: egttools.numerical.numerical_.games.MatrixNPlayerGameHolder) → Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]']

Returns the full payoff matrix.

play(self: egttools.numerical.numerical_.games.MatrixNPlayerGameHolder, arg0: collections.abc.Sequence[SupportsInt | SupportsIndex], arg1: collections.abc.Sequence[SupportsFloat | SupportsIndex]) → None

Simulates the game based on a predefined payoff matrix.

Parameters:

  • group_composition (numpy.ndarray) – Number of players using each strategy in the group.

  • game_payoffs (numpy.ndarray) – Output vector for storing player payoffs.

save_payoffs(self: egttools.numerical.numerical_.games.MatrixNPlayerGameHolder, arg0: str) → None

Saves the payoff matrix to a text file.

type(self: egttools.numerical.numerical_.games.MatrixNPlayerGameHolder) → str
update_payoff_matrix(self: egttools.numerical.numerical_.games.MatrixNPlayerGameHolder, payoff_matrix: Annotated[numpy.typing.ArrayLike, numpy.float64, '[m, n]']) → None

Replaces the stored payoff matrix with a new one.

__annotations__ = {}