def size_series():
SERIES = [5000, 10000, 50 * 1000, 100 * 1000]
M = 10
tau = 0.5
gamma = 1.0
NUM_INIT = 10
NUM_ITER = 25
db = MongoClient('localhost', 27017)[qm.DB4]
for serie in SERIES:
N = serie
rho = float(NUM_INIT / N)
NAME = 'size_series_' + str(serie)
graph_id = qm.insert_ba_graph(db, N, M)
epi_id = qm.insert_epidemic_params(db, tau, gamma, rho, name=NAME)
prop_list = []
for i in range(RESOLUTION):
prop_list.append(i / RESOLUTION)
qm.populate_quarantine_by_prop(db,
graph_id,
epi_id,
prop_list,
NUM_ITER,
name=NAME,
save_full_data=False,
prefix=str(serie))
def cluster_series():
SERIES = [0.05, 0.1, 0.15, 0.2, 0.25]
N = 10 * 1000
M = 10
tau = 0.5
gamma = 1.0
NUM_INIT = 10
NUM_ITER = 25
db = MongoClient('localhost', 27017)[qm.DB4]
rho = float(NUM_INIT / N)
for serie in SERIES:
NAME = 'cluster_series_' + str(serie)
p = make_plc_cluster(N, M, serie)
graph_id = qm.insert_plc_graph(db, N, M, p)
epi_id = qm.insert_epidemic_params(db, tau, gamma, rho, name=NAME)
prop_list = []
for i in range(RESOLUTION):
prop_list.append(i / RESOLUTION)
qm.populate_quarantine_by_prop(db,
graph_id,
epi_id,
prop_list,
NUM_ITER,
name=NAME,
save_full_data=False,
prefix=str(serie))
def main(args):
name = args.name
# Parse graph params
graph_type = args.graph_type
N = int(float(args.N))
graph_params = args.graph_params
# Parse infection params
tau = float(args.tau)
gamma = float(args.gamma)
rho = float(args.init_infected / N)
# Parse run params
num_iter = args.num_iter
# Run thing we want to run (and print as we go along!)
db = MongoClient('localhost', 27017)[qm.DB2]
if graph_type == 'ba':
m = int(graph_params[0])
graph_id = qm.insert_ba_graph(db, N, m, name=name)
elif graph_type == 'plc':
m = int(graph_params[0])
p = float(graph_params[1])
graph_id = qm.insert_plc_graph(db, N, m, p, name=name)
elif graph_type == 'rw':
qe = float(graph_params[0])
qv = float(graph_params[1])
graph_id = qm.insert_rw_graph(db, N, qe, qv, name=name)
elif graph_type == 'nn':
u = float(graph_params[0])
k = int(graph_params[1])
graph_id = qm.insert_nn_graph(db, N, u, k, name=name)
elif graph_type == 'ws':
k = int(graph_params[0])
p = float(graph_params[1])
graph_id = qm.insert_ws_graph(db, N, k, p, name=name)
else:
raise NotImplementedError("Only BA/PLC graphs supported")
epi_id = qm.insert_epidemic_params(db, tau, gamma, rho, name=name)
prop_range = [_ / RESOLUTION for _ in range(0, RESOLUTION)]
qm.populate_quarantine_by_prop(db,
graph_id,
epi_id,
prop_range,
num_iter,
name=name,
save_full_data=False)
def main(args):
name = args.name
# Parse graph params
graph_type = args.graph_type
graph_params = args.graph_params
if len(graph_params) == 1:
graph_params = graph_params[0]
#Parse infection params
tau = float(args.tau)
gamma = float(args.gamma)
# Parse run params
num_iter = args.num_iter
# Run thing we want to run (and print as we go along!)
db = MongoClient('localhost', 27017)[qm.DB2]
if graph_type == 'gemsec_fb':
graph = gg.load_gemsec_fb(graph_params)
elif graph_type == 'gemsec_deezer':
graph = gg.load_gemsec_deezer(graph_params)
elif graph_type == 'arxiv':
graph = gg.load_arxiv_collab(graph_params)
elif graph_type == 'hiv':
graph = gg.load_hiv(int(graph_params))
return graph
elif graph_type == 'hs':
minutes = float(graph_params[0])
scale = int(graph_params[1])
graph = gg.load_highschool(minutes, scale=scale)
return graph
else:
raise NotImplementedError("Nope")
rho = float(args.init_infected / len(graph))
epi_id = qm.insert_epidemic_params(db, tau, gamma, rho, name=name)
prop_range = [_ / RESOLUTION for _ in range(0, RESOLUTION)]
qm.populate_quarantine_by_prop(db,
None,
epi_id,
prop_range,
num_iter,
name=name,
save_full_data=False,
graph=graph)
def prod(iter_list):
count = 1
for el in iter_list:
count *= len(el)
return count
if __name__ == '__main__':
client = pymongo.MongoClient('localhost', 27017)
N = 10 ** 4
ms = [3, 5]
p = 0.4
tau = 0.1
r0s = [0.1, 0.2, 0.5, 1.0, 2.0, 5.0, 10.0]
rho = 25 / N
qprop = [[x / 20, y / 20] for x in range(16) for y in range(16)]
num_runs = 5
total_count = prod([ms, r0s, qprop])
count = 0
for m in ms:
graph_id = qm.insert_plc_graph(client, N, m, p)
for r0 in r0s:
epidemic_id = qm.insert_epidemic_params(client, tau, tau / r0, rho)
for qlist in qprop:
count += 1
print("%s/ %s" % (count, total_count))
qm.populate_plc_qtines(client, graph_id, epidemic_id, num_runs,
qlist)
main()