egttools.numerical.numerical_.GeneralPopulationEvolver¶

class GeneralPopulationEvolver¶

Bases: pybind11_object

Evolves a general population structure.

This class simulates evolutionary dynamics based on a user-defined structure (e.g., spatial, group, or network-based interaction).

Parameters:: structure (egttools.numerical.structure.AbstractStructure) – The structure that defines how individuals interact and update their strategies.

Example

>>> from egttools.numerical.structure import SomeConcreteStructure
>>> struct = SomeConcreteStructure(...)
>>> evolver = GeneralPopulationEvolver(struct)

Methods

`evolve`	Evolves the population and returns the final state.
`run`	Simulates the population and returns the final state after discarding transitory steps.
`structure`	Returns the structure used by the evolver.

__init__()¶

Evolves a general population structure.

This class simulates evolutionary dynamics based on a user-defined structure (e.g., spatial, group, or network-based interaction).

Parameters:: structure (egttools.numerical.structure.AbstractStructure) – The structure that defines how individuals interact and update their strategies.

Example

>>> from egttools.numerical.structure import SomeConcreteStructure
>>> struct = SomeConcreteStructure(...)
>>> evolver = GeneralPopulationEvolver(struct)

__new__(**kwargs)¶

evolve()¶

Evolves the population and returns the final state.

Runs the simulation for a fixed number of generations and returns the final counts of each strategy in the population.

Parameters:: nb_generations (int) – Number of generations to simulate.
Returns:: Final counts of each strategy in the population.
Return type:: NDArray[np.int64]

Example

>>> final = evolver.evolve(1000)

run()¶

Simulates the population and returns the final state after discarding transitory steps.

This method evolves the population for nb_generations generations but returns the final state after discarding the first transitory generations.

Parameters:

nb_generations (int) – Total number of generations to simulate.
transitory (int) – Number of initial generations to discard (burn-in period).

Returns:

Final counts of each strategy after the transitory phase.

Return type:

NDArray[np.int64]

Example

>>> final = evolver.run(2000, 500)

structure()¶

Returns the structure used by the evolver.

Returns:: The structure defining interaction and update rules.
Return type:: egttools.numerical.structure.AbstractStructure

Example

>>> structure = evolver.structure()

__annotations__ = {}¶