popdyn 0.6.0

Simulation of population dynamics

popdyn

Library for simulation of population dynamics.

Allows to simulate the interaction between specific groups in a population, calculating the amount of members for each group along the time. The transitions between groups are defined using probabilistic rules. The results can be obtained through one of the deterministic or indeterministic solvers.

Installing

pip3 install popdyn

Using the library

Let's dive in a simple example to see how it works.

First step is define the model, for this example the SIR model.

from popdyn import Model, Transition

# storage in a dict the ID and the initial population for each group
groups = {
    'S': 1000000,
    'I': 10000,
    'R': 5000
}

# intialize the model
sir = Model(list(groups.keys()))

# add transitions between groups
sir['S', 'I'] = Transition(0.0561215, 'S', 'I', N=True)
sir['I', 'R'] = Transition(0.0455331, 'I')

If we print the model, we can see the transitions for each group (N is the total population):

>>> print(sir)
S -> {'I': 0.0561215 * S * I / N^1}
I -> {'R': 0.0455331 * I}
R -> {}

Once ready the model, we can simulate the behavior of the groups in a period of time using one of the available solvers: Gillespie, TauLeaping or ODE.

results = sir.solve(t=100, initial_pop=list(groups.values()), solver='Gillespie')

Getting in results a dictionary with a key 'time' and a key for each group with the population at every time point.