def get_domain(self):
calibration = self.get_calibration()
states = self.symbols['states']
sdomain = self.data.get("domain", {})
for k in sdomain.keys():
if k not in states:
sdomain.pop(k)
# backward compatibility
if len(sdomain) == 0 and len(states) > 0:
try:
import warnings
min = get_address(self.data,
["options:grid:a", "options:grid:min"])
max = get_address(self.data,
["options:grid:b", "options:grid:max"])
for i, s in enumerate(states):
sdomain[s] = [min[i], max[i]]
# shall we raise a warning for deprecated syntax ?
except Exception as e:
print(e)
pass
if len(sdomain) < len(states):
missing = [s for s in states if s not in sdomain]
raise Exception("Missing domain for states: {}.".format(
str.join(', ', missing)))
from dolo.compiler.objects import CartesianDomain
from dolo.compiler.language import eval_data
sdomain = eval_data(sdomain, calibration)
domain = CartesianDomain(**sdomain)
domain.states = states
return domain
### from dolo.numeric.distribution import UNormal exogenous = UNormal(σ=0.001) # ### # ### Discretized grid for endogenous states # ### # from dolo.numeric.grids import UniformCartesianGrid # grid = UniformCartesianGrid(min=[-0.01, 5], max=[0.01, 15], n=[20, 20]) ### ### Domain for endogenous states domain = CartesianDomain(z=[-0.01, 0.01], k=[5, 15]) ### ### Solve model ### # now we should be able to solve the model using # any of the availables methods model = PureModel(symbols, calibration, functions, domain, exogenous) from dolo.algos.time_iteration import time_iteration from dolo.algos.perturbation import perturb from dolo.algos.simulations import simulate from dolo.algos.improved_time_iteration import improved_time_iteration