ContactNetwork

class contagion.ContactNetwork(G: networkx.classes.graph.Graph, fraction_infected: float = 0, fraction_recovered: float = 0)

For creating contact networks fron NetworkX graphs.

Methods

generate_random_walk(walk_length)	Generates an unbiased random walk of a specified length along the nodes/edges of the contact network.
generate_random_walk_degree_sequence(walk_length)	Generates an unbiased random walk of a specified length along the nodes/edges of the contact network and returns the degree of each node encountered during the walk.
immunize_network(Im[, im_type, …])	Immunizes a network according to a provided Immunization array.
init_Su_In_Re()	Initializes susceptible, infected, and recovered arrays, ensuring there is no overlap/redundancy among them.
reset_Su_In_Re()	Resets susceptible, infected, and recovered arrays to their original initializations.

generate_random_walk(walk_length: int = 1)

Generates an unbiased random walk of a specified length along the nodes/edges of the contact network. Elements of the walk are node indices.

Parameters:

walk_length : int

number of nodes to include in the random walk

Returns:

walk : List

the node indices for the walk

generate_random_walk_degree_sequence(walk_length: int = 1)

Generates an unbiased random walk of a specified length along the nodes/edges of the contact network and returns the degree of each node encountered during the walk.

Parameters:

walk_length : int

number of nodes to include in the random walk

Returns:

degrees : List

the degree of each element of a random walk

immunize_network(Im, im_type='vaccinate', im_starts_after=0, efficacy=1.0, mo_thresh=1)

Immunizes a network according to a provided Immunization array. The immunization array may be generated independently, or using the methods in the Immunization class. Immunization is either “vaccinate” (implemented by placing individuals in the Recovered compartment) or “monitor” (which tracks specified nodes, stopping a contagion simulation when mo_thresh monitored nodes have been ever infected).

Parameters:

Im : numpy.ndarray

a (self.n, 1) array with 1 at indices to be immunized and 0 elsewhere

im_type : str

immunization type. Can be either “vaccinate” or “monitor”

im_starts_after : int

step index after which the immunization policy should be implemented

efficacy : float

efficacy of the immunization (as a float in [0, 1.]) only operates with im_type == “vacciante”.

mo_thresh : int

monitor threshold.

Returns:

None

Raises:

ValueError: when immunization array is the wrong dimensions

ValueError: when invalid immunization type is provided.

init_Su_In_Re()

Initializes susceptible, infected, and recovered arrays, ensuring there is no overlap/redundancy among them.

Returns:None

reset_Su_In_Re()

Resets susceptible, infected, and recovered arrays to their original initializations.

Parameters:None Returns:None