def main():
from complex_systems.dygraph import DyGraph
from complex_systems.quasi_unit_disk_graph import gen_quasi_unit_disk_weight
from complex_systems.diffusion import Diffusion
import networkx as nx
import pylab as plt
# Variables
size_of_simulation_area = 1000.0
inner_radius = 10
outer_radius = 50
number_of_node = 100
simulation_length = 1000.0
sample_interval = 10.0
alpha = 0.8
# Generate a Graph with position
G = DyGraph(time_stop=simulation_length, time_step=sample_interval)
G.generate_mobility_levy_walk(
alpha=0.9,
beta=0.9,
size_max=size_of_simulation_area,
f_min=10,
f_max=1000,
s_min=5,
s_max=1000.0,
b_c=2,
radius=outer_radius,
nb_node=number_of_node,
)
G.generate_weights(inner_radius=inner_radius,
outer_radius=outer_radius, alpha=alpha)
slice_time_list = G.get_slice_time()
i = 1
for t in slice_time_list:
if t == 0.0:
[states, time_stamps, strategies, payoffs] = G.diffusion(t,
nb_steps=10, synergy=8.0,
cooperator_ratio=0.5)
else:
Gslice = G.get_graph(t)
pos = nx.get_node_attributes(Gslice, 'pos')
[states, time_stamps, strategies, payoffs] = G.diffusion(
t,
nb_steps=10,
synergy=8.0,
states=states,
time_stamps=time_stamps,
strategies=strategies,
payoffs=payoffs,
)
nbcoops = [strategy for strategy in strategies if strategy == 'C'].count()
Gslice = G.get_graph(t)
pos = nx.get_node_attributes(Gslice, 'pos')
nodelist_infected = [key for (key, val) in states.iteritems()
if val == 'I']
nodelist_not_infected = [key for (key, val) in
states.iteritems() if val == 'S']
plt.figure()
nx.draw_networkx(Gslice, nodelist=nodelist_infected, pos=pos, with_labels=False, node_size=20)
nx.draw_networkx(Gslice, nodelist=nodelist_not_infected, pos=pos, with_labels=False, node_size=20, node_color='g')
filename = 'diffusion_' + str("%04d" % i) + '.jpg'
plt.savefig(filename)
i += 1
time_stamps_list = [vals for (key, vals) in time_stamps.iteritems()]
plt.figure()
(n, bins, patches) = plt.hist(time_stamps_list, 50, normed=1,
histtype='bar', rwidth=0.8)
plt.show()
