def test_second_order_accuracy(self):
# This solves the optimal growth example at second order
# and computes the second order correction to the steady-state
# We test that both the statefree method and the perturbation to states
# yield the same result.
from dolo.algos.perturbations import yaml_import
model = yaml_import('examples/models/compat/rbc.yaml', compiler=None)
from trash.dolo.numeric.perturbations import solve_decision_rule
from trash.dolo.numeric.perturbations_to_states import approximate_controls
coeffs = approximate_controls(model,order=2, return_dr=False)
state_perturb = coeffs[0]
dr = solve_decision_rule(model)
statefree_perturb = dr['ys'] + dr['g_ss']/2.0
ctls = model.symbols_s['controls']
ctls_ind = [model.variables.index(v) for v in ctls]
# the two methods should yield exactly the same result
from numpy.testing import assert_almost_equal
A = statefree_perturb[ctls_ind]
B = state_perturb
assert_almost_equal(A, B) # we compare the risk-adjusted constants
def test_perturbation_3(self):
from dolo import yaml_import
from dolo.algos.perturbations import approximate_controls
model = yaml_import('examples/models/compat/rbc.yaml')
dr = approximate_controls(model,order=3)
def test_perturbation_1_old(self):
from dolo import yaml_import
model = yaml_import('examples/models/rbc.yaml')
from dolo.algos.perturbations import approximate_controls
dr = approximate_controls(model, order=1)
def test_perturbation_1_old(self):
from dolo import yaml_import
model = yaml_import('examples/models/rbc.yaml')
from dolo.algos.perturbations import approximate_controls
dr = approximate_controls(model,order=1)
