def reset_simulation(self):
"""
Resets the simulation between each run
"""
self.graph = self.graph_og.copy()
self.vaccinated = set()
self.sim_info = defaultdict()
self.infected = set(
np.random.choice(list(self.graph.nodes),
size=int(self.prm['c'] * len(self.graph)),
replace=False).tolist())
# decrease network diffusion
if self.prm['diffusion'] == 'min' and self.prm['k'] > 0:
if get_attack_category(self.prm['method']) == 'node':
self.vaccinated = set(
run_attack_method(self.graph,
self.prm['method'],
self.prm['k'],
seed=self.prm['seed']))
self.infected = self.infected.difference(self.vaccinated)
elif get_attack_category(self.prm['method']) == 'edge':
edge_info = run_attack_method(self.graph,
self.prm['method'],
self.prm['k'],
seed=self.prm['seed'])
self.graph.remove_edges_from(edge_info)
else:
print(self.prm['method'], 'not available')
# increase network diffusion
elif self.prm['diffusion'] == 'max' and self.prm['k'] > 0:
if get_defense_category(self.prm['method']) == 'edge':
edge_info = run_defense_method(self.graph,
self.prm['method'],
self.prm['k'],
seed=self.prm['seed'])
self.graph.add_edges_from(edge_info['added'])
self.graph.remove_edges_from(edge_info['removed'])
else:
print(self.prm['method'], 'not available')
elif self.prm['diffusion'] is not None:
print(self.prm['diffusion'], "not available or k <= 0")
def reset_simulation(self):
"""
Resets the simulation between each run
"""
self.graph_ = self.graph.copy()
self.attacked = []
self.protected = []
self.connectivity = []
# attacked nodes or edges
if self.prm['attack'] is not None and self.prm['k_a'] > 0:
self.attacked = run_attack_method(self.graph_, self.prm['attack'], self.prm['k_a'], approx=self.prm['attack_approx'], seed=self.prm['seed'])
if get_attack_category(self.prm['attack']) == 'edge':
self.graph_.remove_nodes_from(self.attacked)
elif self.prm['attack'] is not None:
print(self.prm['attack'], "not available or k <= 0")
# defended nodes or edges
if self.prm['defense'] is not None and self.prm['steps'] > 0:
if get_defense_category(self.prm['defense']) == 'node':
self.protected = run_defense_method(self.graph_, self.prm['defense'], self.prm['steps'], seed=self.prm['seed'])
elif get_defense_category(self.prm['defense']) == 'edge':
self.protected = run_defense_method(self.graph_, self.prm['defense'], self.prm['steps'], seed=self.prm['seed'])
elif self.prm['defense'] is not None:
print(self.prm['defense'], "not available or k <= 0")
# remove attacked nodes after checking that they are not defended
if get_attack_category(self.prm['attack']) == 'node':
if get_defense_category(self.prm['defense']) == 'node':
diff = set(self.protected) - set(self.attacked)
self.graph_.remove_nodes_from(diff)
else:
self.graph_.remove_nodes_from(self.attacked)
def run_single_sim(self):
"""
Run the defense simulation
"""
for step in range(self.prm['steps']):
if step < len(self.protected) and len(self.protected) > 0 and get_defense_category(self.prm['defense']) == 'edge':
self.track_simulation(step)
u, v = self.protected['added'][step]
self.graph_.add_edge(u, v)
if 'removed' in self.protected[step]:
u, v = self.protected['removed'][step]
self.graph.remove_edge(u, v)
else:
self.track_simulation(step)
print("Ending defense simulation early, not an 'edge' defense or out of {}s".format(get_attack_category(self.prm['defense'])))
results = [v['measure'] if v['measure'] is not None else 0 for k, v in self.sim_info.items()]
return results
def reset_simulation(self):
"""
Resets the simulation between each run
"""
self.protected = set()
self.failed = set()
self.load = defaultdict()
self.sim_info = defaultdict()
self.capacity = self.capacity_og.copy()
for n in self.graph.nodes:
self.load[n] = self.capacity[n] * np.random.uniform(
0, self.prm['l']
) # self.capacity[n] * np.random.uniform(0, self.prm['l']) # self.capacity[n] *
self.capacity[n] = self.capacity[n] * (1.0 + self.prm['r'])
self.track_simulation(step=0)
# attacked nodes or edges
if self.prm['attack'] is not None and self.prm['k_a'] > 0:
self.failed = set(
run_attack_method(self.graph,
self.prm['attack'],
self.prm['k_a'],
approx=self.prm['attack_approx'],
seed=self.prm['seed']))
if get_attack_category(self.prm['attack']) == 'node':
for n in self.failed:
self.load[n] = 2 * self.load[
n] # increase load by 2x when attacked
elif get_attack_category(self.prm['attack']) == 'edge':
self.graph.remove_edges_from(self.failed)
# defended nodes or edges
if self.prm['defense'] is not None and self.prm['k_d'] > 0:
if get_defense_category(self.prm['defense']) == 'node':
self.protected = run_defense_method(self.graph,
self.prm['defense'],
self.prm['k_d'],
seed=self.prm['seed'])
for n in self.protected:
self.capacity[n] = 2 * self.capacity[
n] # double the capacity when defended
elif get_defense_category(self.prm['defense']) == 'edge':
edge_info = run_defense_method(self.graph,
self.prm['defense'],
self.prm['k_d'],
seed=self.prm['seed'])
self.graph.add_edges_from(edge_info['added'])
if 'removed' in edge_info:
self.graph.remove_edges_from(edge_info['removed'])
elif self.prm['defense'] is not None:
print(self.prm['defense'], "not available or k <= 0")
self.track_simulation(step=1)