epiworldpy.ModelDiffNet

class epiworldpy.ModelDiffNet(self: epiworldpy._core.ModelDiffNet, name: str, prevalence: float, prob_adopt: float, normalize_exposure: bool, data: float, data_ncols: int, data_cols: std::vector<unsigned long, std::allocator<unsigned long> >, params: std::vector<double, std::allocator<double> >)

A network diffusion model.

Create a new DiffNet model.

__init__(self: epiworldpy._core.ModelDiffNet, name: str, prevalence: float, prob_adopt: float, normalize_exposure: bool, data: float, data_ncols: int, data_cols: std::vector<unsigned long, std::allocator<unsigned long> >, params: std::vector<double, std::allocator<double> >) → None

Create a new DiffNet model.

Methods

__init__(self, name, prevalence, prob_adopt, ...)	Create a new DiffNet model.
add_entity(self, arg0)
add_state(self, lab, fun)
add_tool(self, tool)	Adds a tool to modify the model.
add_virus(self, virus)	Adds a virus to the model
agents_from_edgelist(self, source, target, ...)	Populatates the model's agents from an edge list.
agents_smallworld(self, n, k, d, p)	Populate the model without an edgelist.
get_db(self)	Get the data from the model run, which may then be queried with associated methods.
get_entity(self, arg0, arg1)
get_name(self)	Get the name of the type of model.
get_states(self)
print(self[, summary])	Print a summary of the model run.
run(self, ndays[, seed])	Run the model according to the previously specific parameters.