def test_determine_new_infections():
"""
Tests the update infection status method is correctly updating.
We set the resistance low for the first 10 nodes (including the first 5 which are initially infected)
We expect to see the first 10 to be infected, and no more.
"""
test_sim_2 = complex_epidemic_simulation(
G=G_test,
beta=0.008,
infection_period_parameters=1.5,
initial_infected=[0, 1, 2, 3, 4],
infection_period_distribution=fixed_length,
time_increment=0.1,
max_iterations=1000)
test_copy = test_sim_2
nodes = list(test_copy.G.nodes())
[
test_copy.epi_data[node].update({"Resistance": 0.039})
for node in nodes[0:10]
]
[
test_copy.epi_data[node].update({"Resistance": 100})
for node in nodes[10:200]
]
test_copy.iterate_epidemic()
lifetime_infections = [
node for node in test_copy.epi_data
if test_copy.epi_data[node]["Times Infected"] == 1
]
assert lifetime_infections == list(range(10))
def test_initialise_infection_list():
test_list = [1, 2, 3, 4, 5]
epidemic_simulation = complex_epidemic_simulation(
G=G_test,
beta=0.008,
infection_period_parameters=1.5,
initial_infected=test_list,
time_increment=0.1,
max_iterations=1000)
assert epidemic_simulation.infected_nodes == test_list
def test_node_list_complex():
"""For some graphs, i.e; a lattice where nodes are named using lists. We cannot refer to them numerically, so we have more advanced logic to handle this.
"""
G_test_lattice = nx.grid_2d_graph(1, 1)
my_epidemic = complex_epidemic_simulation(G_test_lattice,
beta=0.008,
infection_period_parameters=1.5,
initial_infected=1,
time_increment=0.1,
max_iterations=1000)
my_epidemic.iterate_epidemic()
assert my_epidemic.final_size == 1
def test_complex_node_list_iteration():
"""We check that the iteration can be successfully performed over a complex node list
"""
G_test_lattice = nx.grid_2d_graph(2, 2)
my_epidemic = complex_epidemic_simulation(G_test_lattice,
beta=100,
infection_period_parameters=1,
initial_infected=1,
time_increment=0.1,
max_iterations=1000)
my_epidemic.iterate_epidemic()
assert my_epidemic.final_size == 4
import networkx as nx
import numpy as np
import numpy.random as npr
from NetworkEpidemicSimulation.Simulation import complex_epidemic_simulation
G_test = nx.complete_graph(200)
def fixed_length(para, n):
return np.array([5] * n)
test_sim_2 = complex_epidemic_simulation(
G=G_test,
beta=0.008,
infection_period_parameters=1.5,
initial_infected=[0, 1, 2, 3, 4],
infection_period_distribution=fixed_length,
time_increment=0.1,
max_iterations=1000)
test_copy = test_sim_2
test_copy_2 = test_sim_2
def test_initialise_infection_list():
test_list = [1, 2, 3, 4, 5]
epidemic_simulation = complex_epidemic_simulation(
G=G_test,
beta=0.008,
infection_period_parameters=1.5,