def test_school_location(est_data, num_regression, dataframe_regression):
from activitysim.estimation.larch import component_model, update_size_spec
m, data = component_model("school_location", return_data=True)
m.load_data()
loglike_prior = m.loglike()
r = m.maximize_loglike(method="BHHH")
num_regression.check(
{
"loglike_prior": loglike_prior,
"loglike_converge": r.loglike
},
basename="test_school_location_loglike",
)
_regression_check(dataframe_regression, m.pf)
size_spec = update_size_spec(
m,
data,
result_dir=None,
output_file=None,
)
dataframe_regression.check(
size_spec,
basename="test_school_location_size_spec",
default_tolerance=dict(atol=1e-6, rtol=1e-2),
)
def test_location_model(est_data, num_regression, dataframe_regression, name,
method):
from activitysim.estimation.larch import component_model, update_size_spec
m, data = component_model(name, return_data=True)
m.load_data()
loglike_prior = m.loglike()
r = m.maximize_loglike(method=method)
num_regression.check(
{
"loglike_prior": loglike_prior,
"loglike_converge": r.loglike
},
basename=f"test_loc_{name}_loglike",
)
_regression_check(dataframe_regression, m.pf)
size_spec = update_size_spec(
m,
data,
result_dir=None,
output_file=None,
)
dataframe_regression.check(
size_spec,
basename=f"test_loc_{name}_size_spec",
default_tolerance=dict(atol=1e-6, rtol=1e-2)
# set a little loose, as there is sometimes a little variance in these
# results when switching backend implementations.
)
def test_workplace_location(est_data, num_regression, dataframe_regression):
from activitysim.estimation.larch import component_model, update_size_spec
m, data = component_model("workplace_location", return_data=True)
m.load_data()
loglike_prior = m.loglike()
r = m.maximize_loglike(method="SLSQP")
num_regression.check(
{
"loglike_prior": loglike_prior,
"loglike_converge": r.loglike
},
basename="test_workplace_location_loglike",
)
_regression_check(dataframe_regression, m.pf)
size_spec = update_size_spec(
m,
data,
result_dir=None,
output_file=None,
)
dataframe_regression.check(
size_spec,
basename="test_workplace_location_size_spec",
)
def test_stop_freq_model(est_data, num_regression, dataframe_regression):
from activitysim.estimation.larch import component_model
name = "stop_frequency"
m, data = component_model(name, return_data=True)
m.load_data()
loglike_prior = m.loglike()
r = m.maximize_loglike()
num_regression.check(
{"loglike_prior": loglike_prior, "loglike_converge": r.loglike},
basename=f"test_{name}_loglike",
)
_regression_check(dataframe_regression, m.pf)
def test_scheduling_model(est_data, num_regression, dataframe_regression, name, method):
from activitysim.estimation.larch import component_model, update_size_spec
m, data = component_model(name, return_data=True)
m.load_data()
m.doctor(repair_ch_av='-')
loglike_prior = m.loglike()
r = m.maximize_loglike(method=method)
num_regression.check(
{"loglike_prior": loglike_prior, "loglike_converge": r.loglike},
basename=f"test_{name}_loglike",
)
_regression_check(dataframe_regression, m.pf)
def test_simple_simulate(est_data, num_regression, dataframe_regression, name, method):
from activitysim.estimation.larch import component_model
m = component_model(name)
m.load_data()
m.doctor(repair_ch_av='-')
loglike_prior = m.loglike()
r = m.maximize_loglike(method=method, options={"maxiter": 1000})
num_regression.check(
{"loglike_prior": loglike_prior, "loglike_converge": r.loglike},
basename=f"test_simple_simulate_{name}_{method}_loglike",
default_tolerance=dict(atol=1e-6, rtol=1e-3),
)
_regression_check(dataframe_regression, m.pf)
def test_nonmand_and_joint_tour_dest_choice(est_data, num_regression, dataframe_regression):
from activitysim.estimation.larch import component_model
modelname = ("non_mandatory_tour_destination", "joint_tour_destination")
m, d = component_model(modelname, return_data=True)
m.load_data()
m.doctor(repair_ch_av="-")
loglike_prior = m.loglike()
r = m.maximize_loglike(method="SLSQP", options={"maxiter": 1000})
num_regression.check(
{"loglike_prior": loglike_prior, "loglike_converge": r.loglike},
basename="test_nonmand_and_joint_tour_dest_choice_loglike",
)
_regression_check(dataframe_regression, m.pf)
