User’s API

class MoranProcess.MoranProcess(size_list, label_list, BirthPayoffMatrix, DeathPayoffMatrix, TransitionMatrix=None)

General Moran Process with multiple types of individuals.

__init__(size_list, label_list, BirthPayoffMatrix, DeathPayoffMatrix, TransitionMatrix=None)

Class initializer.

Parameters:

• size_list (list of int) – cardinalities of subpopulations.

• label_list (list of str) – distinct labels of subpopulations.

• BirthPayoffMatrix (np.array) – payoff matrix for the birth process.

• DeathPayoffMatrix (np.array) – payoff matrix for the death process.

• TransitionMatrix (np.array, optional) – transition probabilities between types. Defaults to None.

population

entire population.

Type:

list of Individual

init_size_list

cardinalities of initial subpopulations.

Type:

list of int

curr_size_list

cardinalities of current subpopulations.

Type:

list of int

init_label_list

distinct labels of initial subpopulations.

Type:

list of str

BirthPayoffMatrix

payoff matrix for the birth process.

Type:

np.array

DeathPayoffMatrix

payoff matrix for the death process.

Type:

np.array

w

selection pressure weight for the fitness calculation.

Type:

float

AvgBirthPayoffDict

current average birth payoffs for distinct subpopulations.

Type:

dict of str-float

AvgDeathPayoffDict

current average death payoffs for distinct subpopulations.

Type:

dict of str-float

BirthFitnessDict

current birth fitnesses for distinct subpopulations.

Type:

dict of str-float

DeathFitnessDict

current death fitnesses for distinct subpopulations.

Type:

dict of str-float

Entropy

current entropy of the whole population.

Type:

float

TransitionMatrix

transition probabilities between types. Defaults to None.

Type:

np.array, optional

Raises:

• AssertionError – on invalid arguments.

• IncorrectValueError – on wrong values in the Transition Matrix.

property population

Python getter.

property init_size_list

Python getter.

property curr_size_list

Python getter.

property init_label_list

Python getter.

property BirthPayoffMatrix

Python getter.

property DeathPayoffMatrix

Python getter.

property w

Python getter.

property AvgBirthPayoffDict

Python getter.

property AvgDeathPayoffDict

Python getter.

property BirthFitnessDict

Python getter.

property DeathFitnessDict

Python getter.

property Entropy

Python getter.

property TransitionMatrix

Python getter.

simulate(generations)

Simulate population evolution.

Simulate population evolution: Birth-Death process with fitness-based selection of individuals.

Parameters:

generations (int) – number of time steps.

Returns:

table with simulation logs.

Return type:

pd.DataFrame

PlotSize(df, path)

Plot the sub-populations’ sizes after a simulation.

Parameters:

• df (pd.DataFrame) – table with simulation logs.

• path (str) – path for the plot.

PlotAvgBirthPayoff(df, path)

Plot the sub-populations’ AvgBirthPayoff after a simulation.

Parameters:

• df (pd.DataFrame) – table with simulation logs.

• path (str) – path for the plot.

PlotAvgDeathPayoff(df, path)

Plot the sub-populations’ AvgDeathPayoff after a simulation.

Parameters:

• df (pd.DataFrame) – table with simulation logs.

• path (str) – path for the plot.

PlotBirthFitness(df, path)

Plot the sub-populations’ BirthFitness after a simulation.

Parameters:

• df (pd.DataFrame) – table with simulation logs.

• path (str) – path for the plot.

PlotDeathFitness(df, path)

Plot the sub-populations’ DeathFitness after a simulation.

Parameters:

• df (pd.DataFrame) – table with simulation logs.

• path (str) – path for the plot.

PlotEntropy(df, path)

Plot the whole populations entropy after a simulation.

Parameters:

• df (pd.DataFrame) – table with simulation logs.

• path (str) – path for the plot.

class MoranProcess2D.MoranProcess2D(size_list, label_list, grid, BirthPayoffMatrix, DeathPayoffMatrix, TransitionMatrix=None)

2D Moran Process with multiple types of individuals.

__init__(size_list, label_list, grid, BirthPayoffMatrix, DeathPayoffMatrix, TransitionMatrix=None)

Class initializer.

Parameters:

• size_list (list of int) – cardinalities of subpopulations.

• label_list (list of str) – distinct labels of subpopulations.

• grid (np.array) – subpopulations’ position in 2D.

• BirthPayoffMatrix (np.array) – payoff matrix for the birth process.

• DeathPayoffMatrix (np.array) – payoff matrix for the death process.

• TransitionMatrix (np.array, optional) – transition probabilities between types. Defaults to None.

population

entire population.

Type:

list of Individual

init_size_list

cardinalities of initial subpopulations.

Type:

list of int

curr_size_list

cardinalities of current subpopulations.

Type:

list of int

init_label_list

distinct labels of initial subpopulations.

Type:

list of str

BirthPayoffMatrix

payoff matrix for the birth process.

Type:

np.array

DeathPayoffMatrix

payoff matrix for the death process.

Type:

np.array

w

selection pressure weight for the fitness calculation.

Type:

float

Entropy

current entropy of the whole population.

Type:

float

TransitionMatrix

transition probabilities between types. Defaults to None.

Type:

np.array, optional

init_grid

subpopulations’ initial position in 2D.

Type:

np.array

curr_grid

subpopulations’ initial position in 2D.

Type:

np.array

Raises:

• AssertionError – on invalid arguments.

• IncorrectValueError – on wrong values in the Transition Matrix.

property population

Python getter.

property init_size_list

Python getter.

property curr_size_list

Python getter.

property init_label_list

Python getter.

property init_grid

Python getter.

property curr_grid

Python getter.

property BirthPayoffMatrix

Python getter.

property DeathPayoffMatrix

Python getter.

property w

Python getter.

property Entropy

Python getter.

property TransitionMatrix

Python getter.

simulate(generations)

Simulate 2D population evolution.

Simulate 2D population evolution: Birth-Death process with fitness-based selection of individuals.

Parameters:

generations (int) – number of time steps.

Returns:

table with simulation logs.

Return type:

pd.DataFrame

PlotSize2D(df, path)

Plot the sub-populations’ sizes after a simulation.

Parameters:

• df (pd.DataFrame) – table with simulation logs.

• path (str) – path for the plot.

PlotEntropy2D(df, path)

Plot the whole populations entropy after a simulation.

Parameters:

• df (pd.DataFrame) – table with simulation logs.

• path (str) – path for the plot.

PlotPopulationSnapshot2D(path)

Plot a grid snapshot of the current state of the whole population.

Parameters:

path (str) – path for the plot.

class MoranProcess3D.MoranProcess3D(size_list, label_list, grid, BirthPayoffMatrix, DeathPayoffMatrix, TransitionMatrix=None)

3D Moran Process with multiple types of individuals.

__init__(size_list, label_list, grid, BirthPayoffMatrix, DeathPayoffMatrix, TransitionMatrix=None)

Class initializer.

Parameters:

• size_list (list of int) – cardinalities of subpopulations.

• label_list (list of str) – distinct labels of subpopulations.

• grid (np.array) – subpopulations’ position in 3D.

• BirthPayoffMatrix (np.array) – payoff matrix for the birth process.

• DeathPayoffMatrix (np.array) – payoff matrix for the death process.

• TransitionMatrix (np.array, optional) – transition probabilities between types. Defaults to None.

population

entire population.

Type:

list of Individual

init_size_list

cardinalities of initial subpopulations.

Type:

list of int

curr_size_list

cardinalities of current subpopulations.

Type:

list of int

init_label_list

distinct labels of initial subpopulations.

Type:

list of str

BirthPayoffMatrix

payoff matrix for the birth process.

Type:

np.array

DeathPayoffMatrix

payoff matrix for the death process.

Type:

np.array

w

selection pressure weight for the fitness calculation.

Type:

float

Entropy

current entropy of the whole population.

Type:

float

TransitionMatrix

transition probabilities between types. Defaults to None.

Type:

np.array, optional

init_grid

subpopulations’ initial position in 3D.

Type:

np.array

curr_grid

subpopulations’ initial position in 3D.

Type:

np.array

Raises:

• AssertionError – on invalid arguments.

• IncorrectValueError – on wrong values in the Transition Matrix.

property population

Python getter.

property init_size_list

Python getter.

property curr_size_list

Python getter.

property init_label_list

Python getter.

property init_grid

Python getter.

property curr_grid

Python getter.

property BirthPayoffMatrix

Python getter.

property DeathPayoffMatrix

Python getter.

property w

Python getter.

property Entropy

Python getter.

property TransitionMatrix

Python getter.

simulate(generations)

Simulate 3D population evolution.

Simulate 3D population evolution: Birth-Death process with fitness-based selection of individuals.

Parameters:

generations (int) – number of time steps.

Returns:

table with simulation logs.

Return type:

pd.DataFrame

PlotSize3D(df, path)

Plot the sub-populations’ sizes after a simulation.

Parameters:

• df (pd.DataFrame) – table with simulation logs.

• path (str) – path for the plot.

PlotEntropy3D(df, path)

Plot the whole populations entropy after a simulation.

Parameters:

• df (pd.DataFrame) – table with simulation logs.

• path (str) – path for the plot.