Network Graphs for Epidemiology

Geometric Graph

# Visualization
import networkx as nx
import matplotlib.pyplot as plt
import warnings
warnings.filterwarnings("ignore")
%matplotlib inline

# Network topology
g = nx.random_geometric_graph(1000, 0.1, seed=896803) # Random Clustered graph 1000 nodes - distance =0.05, no self loops

pos = nx.get_node_attributes(g, "pos")
plt.figure(figsize=(16, 16))
dmin = 1
ncenter = 0
for n in pos:
    x, y = pos[n]
    d = (x - 0.5) ** 2 + (y - 0.5) ** 2
    if d < dmin:
        ncenter = n
        dmin = d

# color by path length from node near center
p = dict(nx.single_source_shortest_path_length(g, ncenter))

plt.figure(figsize=(16, 16))
nx.draw_networkx_edges(g, pos, alpha=0.2, edge_color="black")
nx.draw_networkx_nodes(
    g,
    pos,
    nodelist=list(p.keys()),
    node_size=80,
    node_color=list(p.values()),
    cmap=plt.cm.Reds_r,
    alpha=0.8
)

plt.xlim(-0.05, 1.05)
plt.ylim(-0.05, 1.05)
plt.axis("off")
plt.show()