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gen_simulation_tools.py
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gen_simulation_tools.py
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import random
import networkx as nx
def get_beta(node, G, infection_parameters):
age = G.nodes[node]["age"]
gender = G.nodes[node]["gender"]
eth = G.nodes[node]["ethnicity"]
if age >= 0 and age <= 14:
age_p = infection_parameters["child"]
elif age >= 15 and age <= 54:
age_p = infection_parameters["adult"]
elif age >= 55:
age_p = infection_parameters["senior"]
male_p = infection_parameters["male"]
female_p = infection_parameters["female"]
white_p = infection_parameters["white"]
sa_p = infection_parameters["asian"]
black_p = infection_parameters["black"]
mixed_p = infection_parameters["other"]
if eth == 0:
if gender == 0:
beta = age_p * male_p * sa_p
else:
beta = age_p * female_p * sa_p
elif eth == 1:
if gender == 0:
beta = age_p * male_p * black_p
else:
beta = age_p * female_p * black_p
elif eth == 2:
if gender == 0:
beta = age_p * male_p * white_p
else:
beta = age_p * female_p * white_p
elif eth == 3:
if gender == 0:
beta = age_p * male_p * mixed_p
else:
beta = age_p * female_p * mixed_p
return beta
def get_rec(node, G, recovery_parameters):
age = G.nodes[node]["age"]
gender = G.nodes[node]["gender"]
eth = G.nodes[node]["ethnicity"]
white_p = recovery_parameters["white"]
sa_p = recovery_parameters["asian"]
black_p = recovery_parameters["black"]
mixed_p = recovery_parameters["other"]
male_p = recovery_parameters["male"]
female_p = recovery_parameters["female"]
if age >= 0 and age <= 14:
age_p = recovery_parameters["child"]
elif age >= 15 and age <= 54:
age_p = recovery_parameters["adult"]
elif age >= 55:
age_p = recovery_parameters["senior"]
if eth == 0:
if gender == 0:
gamma = age_p * male_p * sa_p
else:
gamma = age_p * female_p * sa_p
elif eth == 1:
if gender == 0:
gamma = age_p * male_p * black_p
else:
gamma = age_p * female_p * black_p
elif eth == 2:
if gender == 0:
gamma = age_p * male_p * white_p
else:
gamma = age_p * female_p * white_p
elif eth == 3:
if gender == 0:
gamma = age_p * male_p * mixed_p
else:
gamma = age_p * female_p * mixed_p
return gamma
def seed_graph(G, seeds):
nodes = G.number_of_nodes()
seeds_int = int((nodes * seeds) / 100)
rand_nodes = random.sample(range(nodes), seeds_int)
for n in range(0, nodes):
if n in rand_nodes:
G.nodes[n]["status"] = "I"
else:
G.nodes[n]["status"] = "S"
def infect(a_nodes, G, infection_parameters):
for n in a_nodes:
neighbors = list(G.neighbors(n))
for neighbor in neighbors:
if G.nodes[n]["status"] == "S":
con = G.nodes[neighbor]["age"]
if random.uniform(0, 1) < get_beta(n, G, infection_parameters):
G.nodes[n]["status"] = "I"
def recover_sir(a_nodes, G, recovery_parameters):
for n in a_nodes:
if G.nodes[n]["status"] == "I":
if random.uniform(0, 1) < get_rec(n, G, recovery_parameters):
G.nodes[n]["status"] = "R"
def recover_sis(a_nodes, G, recovery_parameters):
for n in a_nodes:
if G.nodes[n]["status"] == "I":
if random.uniform(0, 1) < get_rec(n, G, recovery_parameters):
G.nodes[n]["status"] = "S"
def init_si_counts():
counts_list = [
"inf_total",
"sus_total",
"white_sus",
"white_inf",
"black_sus",
"black_inf",
"asian_sus",
"asian_inf",
"other_sus",
"other_inf",
"male_inf",
"male_sus",
"female_inf",
"female_sus",
"child_inf",
"child_sus",
"adult_inf",
"adult_sus",
"senior_inf",
"senior_sus",
]
count_dicts = {k: [] for k in counts_list}
return count_dicts
def init_sir_counts():
counts_list = [
"inf_total",
"sus_total",
"rec_total",
"white_sus",
"white_rec",
"white_inf",
"black_sus",
"black_rec",
"black_inf",
"asian_sus",
"asian_rec",
"asian_inf",
"other_sus",
"other_rec",
"other_inf",
"male_inf",
"male_rec",
"male_sus",
"female_inf",
"female_rec",
"female_sus",
"child_inf",
"child_rec",
"child_sus",
"adult_inf",
"adult_rec",
"adult_sus",
"senior_inf",
"senior_rec",
"senior_sus",
]
count_dicts = {k: [] for k in counts_list}
return count_dicts
def update_sir_counts(count_dicts, data):
count_dicts["sus_total"].append(data["total_sus"])
count_dicts["inf_total"].append(data["total_inf"])
count_dicts["rec_total"].append(data["total_rec"])
count_dicts["white_sus"].append(data["white_sus"])
count_dicts["white_inf"].append(data["white_inf"])
count_dicts["white_rec"].append(data["white_rec"])
count_dicts["black_sus"].append(data["black_sus"])
count_dicts["black_inf"].append(data["black_inf"])
count_dicts["black_rec"].append(data["black_rec"])
count_dicts["asian_sus"].append(data["asian_sus"])
count_dicts["asian_inf"].append(data["asian_inf"])
count_dicts["asian_rec"].append(data["asian_rec"])
count_dicts["other_sus"].append(data["other_sus"])
count_dicts["other_inf"].append(data["other_inf"])
count_dicts["other_rec"].append(data["other_rec"])
count_dicts["male_sus"].append(data["male_sus"])
count_dicts["male_inf"].append(data["male_inf"])
count_dicts["male_rec"].append(data["male_rec"])
count_dicts["female_sus"].append(data["female_sus"])
count_dicts["female_inf"].append(data["female_inf"])
count_dicts["female_rec"].append(data["female_rec"])
count_dicts["child_sus"].append(data["child_sus"])
count_dicts["child_inf"].append(data["child_inf"])
count_dicts["child_rec"].append(data["child_rec"])
count_dicts["adult_sus"].append(data["adult_sus"])
count_dicts["adult_inf"].append(data["adult_inf"])
count_dicts["adult_rec"].append(data["adult_rec"])
count_dicts["senior_sus"].append(data["senior_sus"])
count_dicts["senior_inf"].append(data["senior_inf"])
count_dicts["senior_rec"].append(data["senior_rec"])
return count_dicts
def update_si_counts(count_dicts, data):
count_dicts["sus_total"].append(data["total_sus"])
count_dicts["inf_total"].append(data["total_inf"])
count_dicts["white_sus"].append(data["white_sus"])
count_dicts["white_inf"].append(data["white_inf"])
count_dicts["black_sus"].append(data["black_sus"])
count_dicts["black_inf"].append(data["black_inf"])
count_dicts["asian_sus"].append(data["asian_sus"])
count_dicts["asian_inf"].append(data["asian_inf"])
count_dicts["other_sus"].append(data["other_sus"])
count_dicts["other_inf"].append(data["other_inf"])
count_dicts["male_sus"].append(data["male_sus"])
count_dicts["male_inf"].append(data["male_inf"])
count_dicts["female_sus"].append(data["female_sus"])
count_dicts["female_inf"].append(data["female_inf"])
count_dicts["child_sus"].append(data["child_sus"])
count_dicts["child_inf"].append(data["child_inf"])
count_dicts["adult_sus"].append(data["adult_sus"])
count_dicts["adult_inf"].append(data["adult_inf"])
count_dicts["senior_sus"].append(data["senior_sus"])
count_dicts["senior_inf"].append(data["senior_inf"])
return count_dicts