Diffusion TrendΒΆ

The Diffusion Trend plot compares the trends of all the statuses allowed by the diffusive model tested.

Each trend line describes the variation of the number of nodes for a given status iteration after iteration.

Below is shown an example of Diffusion Trend description and visualization for the SIR model.

import networkx as nx
import ndlib.models.ModelConfig as mc
import ndlib.models.epidemics as ep
from ndlib.viz.mpl.DiffusionTrend import DiffusionTrend


# Network topology
g = nx.erdos_renyi_graph(1000, 0.1)

# Model selection
model = ep.SIRModel(g)

# Model Configuration
cfg = mc.Configuration()
cfg.add_model_parameter('beta', 0.001)
cfg.add_model_parameter('gamma', 0.01)
cfg.add_model_parameter("fraction_infected", 0.01)
model.set_initial_status(cfg)

# Simulation execution
iterations = model.iteration_bunch(200)
trends = model.build_trends(iterations)

# Visualization
viz = DiffusionTrend(model, trends)
viz.plot("diffusion.pdf")
SIR Diffusion Trend Example

SIR Diffusion Trend Example.