def reorder_preamble(pr):
import sympy
from dolang.triangular_solver import solve_triangular_system
unknowns = [*pr.keys()]
incidence = [[str(e) for e in sympy.sympify((exp)).atoms()]
for exp in pr.values()]
sol = solve_triangular_system(dict(zip(unknowns, incidence)))
return dict([(k, pr[k]) for k in sol.keys()])
def calibration_to_vector(symbols, calibration_dict):
from dolang.triangular_solver import solve_triangular_system
from numpy import nan
sol = solve_triangular_system(calibration_dict)
calibration = dict()
for group in symbols:
# t = numpy.array([sol.get(s, nan) for s in symbols[group]], dtype=float)
t = numpy.array([sol.get(s, nan) for s in symbols[group]], dtype=float)
calibration[group] = t
return calibration
def get_calibration(self):
from dolang.symbolic import remove_timing
import copy
calibration = dict()
for k, v in self.data.get("calibration", {}).items():
if v.tag == "tag:yaml.org,2002:str":
expr = parse_string(v)
expr = remove_timing(expr)
expr = str_expression(expr)
else:
expr = float(v.value)
kk = remove_timing(parse_string(k))
kk = str_expression(kk)
calibration[kk] = expr
from dolang.triangular_solver import solve_triangular_system
return solve_triangular_system(calibration)
# with timeit("Conversion mod -> json"):
# from dolo.compiler.import_dynare import import_dynare
# model = import_dynare("/home/pablo/Downloads/EA_QUEST3.mod", output_type='json')
# txt = json.dumps(model)
# model['calibration']
# with open("EA_QUEST3.json",'w') as f:
# json.dump(model,f)
with timeit('Load json'):
with open("EA_QUEST3.json") as f:
model = json.load(f)
model['symbols'].keys()
with timeit("Solve triangular system"):
calibration = model['calibration']
sol = solve_triangular_system(calibration)
with timeit("Parse equations"):
equations = model['equations']
compat = lambda s: s.replace("^", "**").replace('==', '=').replace(
'=', '==')
equations = [compat(eq) for eq in equations]
equations = ['{} - ({})'.format(*str.split(eq, '==')) for eq in equations]
equations = [parse_string(e) for e in equations]
with timeit("stringify equations"):
all_variables = [(v, 1) for v in model['symbols']['variables']] + \
[(v, 0) for v in model['symbols']['variables']] + \
# = e"ndogenous variables",
n="0.33",
z="zbar",
rk="1/β-1+δ",
w="(1-α)*exp(z)*(k/n)**(α)",
k="n/(rk/α)**(1/(1-α))",
y="exp(z)*k**α*n**(1-α)",
i="δ*k",
c="y - i",
V="log(c)/(1-β)",
u="c**(1-σ)/(1-σ) - χ*n**(1+η)/(1+η)",
m="β/c**σ*(1-δ+rk)")
from dolang.triangular_solver import solve_triangular_system
calibration_dict = solve_triangular_system(calibration_strings)
calibration_vector = calibration_to_vector(symbols, calibration_dict)
calibration = CalibrationDict(symbols, calibration_vector)
calibration
###
### Define functions
###
# the basic formulation of the functions (aka kernel)
# take and return "tuples" of floats because tuples are supposed
# to be easy to be optimzed away by the compiler
# after the definition of the function, there is some boilerplate
# to translate these functions into broadcastable ones, with
def get_calibration(self):
# if self.__calibration__ is None:
from dolang.symbolic import remove_timing
import copy
symbols = self.symbols
calibration = dict()
for k, v in self.data.get("calibration", {}).items():
if v.tag == "tag:yaml.org,2002:str":
expr = parse_string(v)
expr = remove_timing(expr)
expr = str_expression(expr)
else:
expr = float(v.value)
kk = remove_timing(parse_string(k))
kk = str_expression(kk)
calibration[kk] = expr
definitions = self.definitions
initial_values = {
"exogenous": 0,
"expectations": 0,
"values": 0,
"controls": float("nan"),
"states": float("nan"),
}
# variables defined by a model equation default to using these definitions
initialized_from_model = {
"values": "value",
"expectations": "expectation",
"direct_responses": "direct_response",
}
for k, v in definitions.items():
kk = remove_timing(k)
if kk not in calibration:
if isinstance(v, str):
vv = remove_timing(v)
else:
vv = v
calibration[kk] = vv
for symbol_group in symbols:
if symbol_group not in initialized_from_model.keys():
if symbol_group in initial_values:
default = initial_values[symbol_group]
else:
default = float("nan")
for s in symbols[symbol_group]:
if s not in calibration:
calibration[s] = default
from dolang.triangular_solver import solve_triangular_system
return solve_triangular_system(calibration)
# model = import_dynare("/home/pablo/Downloads/EA_QUEST3.mod", output_type='json')
# txt = json.dumps(model)
# model['calibration']
# with open("EA_QUEST3.json",'w') as f:
# json.dump(model,f)
with timeit('Load json'):
with open("EA_QUEST3.json") as f:
model = json.load(f)
model['symbols'].keys()
with timeit("Solve triangular system"):
calibration = model['calibration']
sol = solve_triangular_system(calibration)
with timeit("Parse equations"):
equations = model['equations']
compat = lambda s: s.replace("^", "**").replace('==','=').replace('=','==')
equations = [compat(eq) for eq in equations]
equations = ['{} - ({})'.format(*str.split(eq,'==')) for eq in equations]
equations = [parse_string(e) for e in equations]
with timeit("stringify equations"):
all_variables = [(v, 1) for v in model['symbols']['variables']] + \