def test_direct():
from dolo import yaml_import
from dolo.algos.dtcscc.perturbations import approximate_controls
from dolo.algos.dtcscc.time_iteration import time_iteration_direct, time_iteration
model = yaml_import("examples/models/rbc_full.yaml")
# Check without complementarity conditions
dr = time_iteration_direct(model, with_complementarities=False)
ddr = time_iteration(model, with_complementarities=False)
x0 = dr(dr.grid)
x1 = ddr(dr.grid)
print(abs(x1 - x0).max() < 1e-5)
# Check with complementarity conditions
dr = time_iteration_direct(model, with_complementarities=True)
ddr = time_iteration(model, with_complementarities=True)
x0 = dr(dr.grid)
x1 = ddr(dr.grid)
print(abs(x1 - x0).max() < 1e-5)
def test_direct():
from dolo import yaml_import
from dolo.algos.dtcscc.perturbations import approximate_controls
from dolo.algos.dtcscc.time_iteration import time_iteration_direct, time_iteration
model = yaml_import("examples/models/compat/rbc_full.yaml")
# Check without complementarity conditions
dr = time_iteration_direct(model, with_complementarities=False)
ddr = time_iteration(model, with_complementarities=False)
x0 = dr(dr.grid)
x1 = ddr(dr.grid)
print(abs(x1 - x0).max()<1e-5)
# Check with complementarity conditions
dr = time_iteration_direct(model, with_complementarities=True)
ddr = time_iteration(model, with_complementarities=True)
x0 = dr(dr.grid)
x1 = ddr(dr.grid)
print(abs(x1 - x0).max()<1e-5)
def test_omega_errors():
from dolo import yaml_import
from dolo.algos.dtcscc.time_iteration import time_iteration as time_iteration
model = yaml_import('examples/models/rbc.yaml')
from dolo.algos.dtcscc.perturbations import approximate_controls
dr = approximate_controls(model)
dr_global = time_iteration(model,
smolyak_order=3,
verbose=False,
pert_order=1)
sigma = model.covariances
model.sigma = sigma
s_0 = dr.S_bar
from dolo.algos.dtcscc.accuracy import omega
res_1 = omega(model, dr, orders=[10, 10], time_discount=0.96)
res_2 = omega(model, dr_global)
print(res_1)
print(res_2)
def test_denhaan_errors():
from dolo import yaml_import
from dolo.algos.dtcscc.time_iteration import time_iteration as time_iteration
model = yaml_import('examples/models/rbc.yaml')
from dolo.algos.dtcscc.perturbations import approximate_controls
dr = approximate_controls(model)
dr_global = time_iteration(model, verbose=False)
s0 = model.calibration['states']
sigma = model.get_distribution().sigma
from dolo.algos.dtcscc.accuracy import denhaanerrors
denerr_1 = denhaanerrors(model, dr)
denerr_2 = denhaanerrors(model, dr_global)
print(denerr_1)
print(denerr_2)
print(denerr_2['max_errors'][0])
assert( max(denerr_2['max_errors']) < 10-7) # errors with solyak colocations at order 4 are very small
def test_denhaan_errors():
from dolo import yaml_import
from dolo.algos.dtcscc.time_iteration import time_iteration as time_iteration
model = yaml_import('examples/models/rbc.yaml')
from dolo.algos.dtcscc.perturbations import approximate_controls
dr = approximate_controls(model)
dr_global = time_iteration(model, verbose=False)
s0 = model.calibration['states']
sigma = model.get_distribution().sigma
from dolo.algos.dtcscc.accuracy import denhaanerrors
denerr_1 = denhaanerrors(model, dr)
denerr_2 = denhaanerrors(model, dr_global)
print(denerr_1)
print(denerr_2)
print(denerr_2['max_errors'][0])
assert (max(denerr_2['max_errors']) < 10 - 7
) # errors with solyak colocations at order 4 are very small
def test_omega_errors():
from dolo import yaml_import
from dolo.algos.dtcscc.time_iteration import time_iteration as time_iteration
model = yaml_import('examples/models/rbc.yaml')
from dolo.algos.dtcscc.perturbations import approximate_controls
dr = approximate_controls(model)
dr_global = time_iteration(model, smolyak_order=3, verbose=False, pert_order=1)
sigma = model.covariances
model.sigma = sigma
s_0 = dr.S_bar
from dolo.algos.dtcscc.accuracy import omega
res_1 = omega( model, dr, orders=[10,10], time_discount=0.96)
res_2 = omega( model, dr_global)
print(res_1)
print(res_2)
def time_iteration(model, *args, **kwargs):
if model.model_type == 'dtcscc':
from dolo.algos.dtcscc.time_iteration import time_iteration
elif model.model_type == 'dtmscc':
from dolo.algos.dtmscc.time_iteration import time_iteration
else:
raise Exception("Model type {} not supported.".format(model.model_type))
return time_iteration(model, *args, **kwargs)
def time_iteration(model, *args, **kwargs):
if model.model_type == 'dtcscc':
from dolo.algos.dtcscc.time_iteration import time_iteration
elif model.model_type == 'dtmscc':
from dolo.algos.dtmscc.time_iteration import time_iteration
else:
raise Exception("Model type {} not supported.".format(
model.model_type))
return time_iteration(model, *args, **kwargs)
def test_direct():
from dolo import yaml_import
from dolo.algos.dtcscc.perturbations import approximate_controls
from dolo.algos.dtcscc.time_iteration import time_iteration_direct, time_iteration
model = yaml_import("examples/models/rbc_full.yaml")
dr = time_iteration_direct(model)
ddr = time_iteration(model)
x0 = dr(dr.grid)
x1 = ddr(dr.grid)
print(abs(x1 - x0).max()<1e-5)
def test_direct():
from dolo import yaml_import
from dolo.algos.dtcscc.perturbations import approximate_controls
from dolo.algos.dtcscc.time_iteration import time_iteration_direct, time_iteration
model = yaml_import("examples/models/rbc_full.yaml")
dr = time_iteration_direct(model)
ddr = time_iteration(model)
x0 = dr(dr.grid)
x1 = ddr(dr.grid)
print(abs(x1 - x0).max() < 1e-5)
def test_parameterized_expectations():
from dolo import yaml_import
from dolo.algos.dtcscc.parameterized_expectations import parameterized_expectations
from dolo.algos.dtcscc.time_iteration import time_iteration
model = yaml_import("examples/models/compat/rbc_full.yaml")
dr_ti = time_iteration(model)
dr_pea = parameterized_expectations(model, direct=False)
x_ti = dr_ti(dr_ti.grid)
x_pea = dr_pea(dr_ti.grid)
print(abs(x_ti - x_pea).max() < 1e-5)
def test_parameterized_expectations():
from dolo import yaml_import
from dolo.algos.dtcscc.parameterized_expectations import parameterized_expectations
from dolo.algos.dtcscc.time_iteration import time_iteration
model = yaml_import("examples/models/compat/rbc_full.yaml")
dr_ti = time_iteration(model)
dr_pea = parameterized_expectations(model, direct=False)
x_ti = dr_ti(dr_ti.grid)
x_pea = dr_pea(dr_ti.grid)
print(abs(x_ti - x_pea).max() < 1e-5)
def test_big_system():
from dolo import yaml_import
from dolo.algos.dtcscc.nonlinearsystem import nonlinear_system
from dolo.algos.dtcscc.time_iteration import time_iteration
model = yaml_import("examples/models/rbc.yaml")
dr = time_iteration(model, grid={"type": "smolyak", "mu": 3}, verbose=True)
sol = nonlinear_system(model, grid={"type": "smolyak", "mu": 3})
diff = (sol.__values__) - dr.__values__
assert abs(diff).max() < 1e-6
sol_high_precision = nonlinear_system(model, grid={"type": "smolyak", "mu": 5}, initial_dr=sol)
assert sol_high_precision.grid.shape == (145, 2)
def test_big_system():
from dolo import yaml_import
from dolo.algos.dtcscc.nonlinearsystem import nonlinear_system
from dolo.algos.dtcscc.time_iteration import time_iteration
model = yaml_import('examples/models/compat/rbc.yaml')
dr = time_iteration(model, grid={'type': 'smolyak', 'mu': 3}, verbose=True)
sol = nonlinear_system(model, grid={'type': 'smolyak', 'mu': 3})
diff = (sol.__values__) - dr.__values__
assert(abs(diff).max() < 1e-6)
sol_high_precision = nonlinear_system(model, grid={'type': 'smolyak', 'mu': 5}, initial_dr=sol)
assert(sol_high_precision.grid.shape == (145, 2))
def test_big_system():
from dolo import yaml_import
from dolo.algos.dtcscc.nonlinearsystem import nonlinear_system
from dolo.algos.dtcscc.time_iteration import time_iteration
model = yaml_import('examples/models/compat/rbc.yaml')
dr = time_iteration(model, grid={'type': 'smolyak', 'mu': 3}, verbose=True)
sol = nonlinear_system(model, grid={'type': 'smolyak', 'mu': 3})
diff = (sol.__values__) - dr.__values__
assert (abs(diff).max() < 1e-6)
sol_high_precision = nonlinear_system(model,
grid={
'type': 'smolyak',
'mu': 5
},
initial_dr=sol)
assert (sol_high_precision.grid.shape == (145, 2))
def test_omega_errors():
from dolo import yaml_import
from dolo.algos.dtcscc.time_iteration import time_iteration as time_iteration
model = yaml_import('examples/models/compat/rbc.yaml')
from dolo.algos.dtcscc.perturbations import approximate_controls
dr = approximate_controls(model)
dr_global = time_iteration(model, verbose=False, pert_order=1)
sigma = model.get_distribution().sigma
s_0 = dr.S_bar
from dolo.algos.dtcscc.accuracy import omega
res_1 = omega(model, dr, grid=dict(orders=[10, 10]), time_discount=0.96)
res_2 = omega(model, dr_global)
print(res_1)
print(res_2)
def test_omega_errors():
from dolo import yaml_import
from dolo.algos.dtcscc.time_iteration import time_iteration as time_iteration
model = yaml_import('examples/models/compat/rbc.yaml')
from dolo.algos.dtcscc.perturbations import approximate_controls
dr = approximate_controls(model)
dr_global = time_iteration(model, verbose=False, pert_order=1)
sigma = model.get_distribution().sigma
s_0 = dr.S_bar
from dolo.algos.dtcscc.accuracy import omega
res_1 = omega(model, dr, grid=dict(orders=[10, 10]), time_discount=0.96)
res_2 = omega(model, dr_global)
print(res_1)
print(res_2)
def global_solve(*args, **kwargs):
return time_iteration(*args, **kwargs)