def simulate(config_file, scenarios, nsim, jobs, interactive, write_csv,
write_parquet, index):
config.set_file(config_file)
spatial_config = config["spatial_setup"]
spatial_base_path = pathlib.Path(spatial_config["base_path"].get())
if not scenarios:
scenarios = config["interventions"]["scenarios"].as_str_seq()
print(f"Scenarios to be run: {', '.join(scenarios)}")
if not nsim:
nsim = config["nsimulations"].as_number()
spatial_setup = setup.SpatialSetup(
setup_name=spatial_config["setup_name"].get(),
geodata_file=spatial_base_path / spatial_config["geodata"].get(),
mobility_file=spatial_base_path / spatial_config["mobility"].get(),
popnodes_key=spatial_config["popnodes"].get(),
nodenames_key=spatial_config["nodenames"].get())
start = time.monotonic()
for scenario in scenarios:
s = setup.Setup(
setup_name=config["name"].get() + "_" + str(scenario),
spatial_setup=spatial_setup,
nsim=nsim,
npi_scenario=scenario,
npi_config=config["interventions"]["settings"][scenario],
seeding_config=config["seeding"],
ti=config["start_date"].as_date(),
tf=config["end_date"].as_date(),
interactive=interactive,
write_csv=write_csv,
write_parquet=write_parquet,
dt=config["dt"].as_number(),
first_sim_index=index)
try:
s.load_filter(config["dynfilter_path"].get())
print(' We are using a filter')
except:
print('No filter used')
print(f"""
>> Scenario: {scenario}
>> Starting {s.nsim} model runs beginning from {s.first_sim_index} on {jobs} processes
>> Setup *** {s.setup_name} *** from {s.ti} to {s.tf}
>> writing to folder : {s.datadir}{s.setup_name}
""")
seir.run_parallel(s, n_jobs=jobs)
print(f">> All runs completed in {time.monotonic() - start:.1f} seconds")
def test_constant_population():
config.set_file(f"{DATA_DIR}/config.yml")
ss = setup.SpatialSetup(setup_name="test_seir",
geodata_file=f"{DATA_DIR}/geodata.csv",
mobility_file=f"{DATA_DIR}/mobility.txt",
popnodes_key="population",
nodenames_key="geoid")
s = setup.Setup(setup_name="test_seir",
spatial_setup=ss,
nsim=1,
npi_scenario="None",
npi_config=config["interventions"]["settings"]["None"],
ti=config["start_date"].as_date(),
tf=config["end_date"].as_date(),
interactive=True,
write_csv=False,
dt=0.25)
seeding = np.zeros((len(s.t_inter), s.nnodes))
mobility_geoid_indices = s.mobility.indices
mobility_data_indices = s.mobility.indptr
mobility_data = s.mobility.data
npi = NPI.NPIBase.execute(npi_config=s.npi_config,
global_config=config,
geoids=s.spatset.nodenames)
parameters = setup.parameters_quick_draw(config["seir"]["parameters"],
len(s.t_inter), s.nnodes)
parameters = setup.parameters_reduce(parameters, npi, s.dt)
states = seir.steps_SEIR_nb(*parameters, seeding, s.dt, s.t_inter,
s.nnodes, s.popnodes, mobility_geoid_indices,
mobility_data_indices, mobility_data,
s.dynfilter)
completepop = s.popnodes.sum()
origpop = s.popnodes
for it in range(len(s.t_inter)):
totalpop = 0
for i in range(s.nnodes):
totalpop += states[:5, i, it].sum()
#Sum of S, E, I#, R for the geoid that is 'i'
assert (origpop[i] == states[:5, i, it].sum())
assert (completepop == totalpop)
def test_check_values():
config.set_file(f"{DATA_DIR}/config.yml")
ss = setup.SpatialSetup(setup_name="test_values",
geodata_file=f"{DATA_DIR}/geodata.csv",
mobility_file=f"{DATA_DIR}/mobility.txt",
popnodes_key="population",
nodenames_key="geoid")
s = setup.Setup(setup_name="test_values",
spatial_setup=ss,
nsim=1,
npi_scenario="None",
npi_config=config["interventions"]["settings"]["None"],
ti=config["start_date"].as_date(),
tf=config["end_date"].as_date(),
interactive=True,
write_csv=False,
dt=0.25)
with warnings.catch_warnings(record=True) as w:
seeding = np.zeros((len(s.t_inter), s.nnodes))
if np.all(seeding == 0):
warnings.warn("provided seeding has only value 0", UserWarning)
seeding[0,0] = 1
if np.all(seeding == 0):
warnings.warn("provided seeding has only value 0", UserWarning)
if(np.all(s.mobility.data < 1)):
warnings.warn("highest mobility value is less than 1", UserWarning)
s.mobility.data[0] = 0.8
s.mobility.data[1] = 0.5
if(np.all(s.mobility.data < 1)):
warnings.warn("highest mobility value is less than 1", UserWarning)
assert(len(w) == 2)
assert(issubclass(w[0].category, UserWarning))
assert(issubclass(w[1].category, UserWarning))
assert("seeding" in str(w[0].message))
assert("mobility" in str(w[1].message))
def test_steps_SEIR_no_spread():
config.set_file(f"{DATA_DIR}/config.yml")
ss = setup.SpatialSetup(setup_name="test_seir",
geodata_file=f"{DATA_DIR}/geodata.csv",
mobility_file=f"{DATA_DIR}/mobility.txt",
popnodes_key="population",
nodenames_key="geoid")
s = setup.Setup(setup_name="test_seir",
spatial_setup=ss,
nsim=1,
npi_scenario="None",
npi_config=config["interventions"]["settings"]["None"],
ti=config["start_date"].as_date(),
tf=config["end_date"].as_date(),
interactive=True,
write_csv=False,
dt=0.25)
seeding = np.zeros((len(s.t_inter), s.nnodes))
seeding[:, 0] = 100
mobility_geoid_indices = s.mobility.indices
mobility_data_indices = s.mobility.indptr
mobility_data = s.mobility.data * 0
npi = NPI.NPIBase.execute(npi_config=s.npi_config,
global_config=config,
geoids=s.spatset.nodenames)
parameters = setup.parameters_quick_draw(config["seir"]["parameters"],
len(s.t_inter), s.nnodes)
parameters = setup.parameters_reduce(parameters, npi, s.dt)
for i in range(100):
states = seir.steps_SEIR_nb(*parameters, seeding, s.dt, s.t_inter,
s.nnodes, s.popnodes,
mobility_geoid_indices,
mobility_data_indices, mobility_data,
s.dynfilter)
assert states[seir.cumI][1].max() == 0
def test_Setup_set_filter():
ss = setup.SpatialSetup(setup_name=TEST_SETUP_NAME,
geodata_file=f"{DATA_DIR}/geodata.csv",
mobility_file=f"{DATA_DIR}/mobility.txt",
popnodes_key="population",
nodenames_key="geoid")
s = setup.Setup(setup_name="test_set_filter_name",
spatial_setup=ss,
nsim=1,
npi_scenario="test_set_filter_scenario",
npi_config=confuse.Configuration("test"),
ti=datetime.date(2020, 1, 31),
tf=datetime.date(2020, 12, 31),
interactive=True,
write_csv=False,
dt=0.25)
# filter has bad dimensions
with pytest.raises(ValueError):
s.set_filter(np.zeros((1, 1)))