def test_mulstd_read_failure():
onet = Var([50, 60], [2000, 2010])
with pytest.raises(ValueError):
onet.get_mulstd("else")
# Here the key is good, but there is nothing there.
assert isnan(onet.get_mulstd('dage'))
def var_from_mean(self):
"""Given a prior grid, create a Var from the mean of the value priors.
Returns:
Var: A new Var object with the same ages and times and value
equal to the mean.
"""
var = Var(self.ages, self.times)
for age, time in self.age_time():
var[age, time] = self.value[age, time].mean
return var
def _ensure_weights(self):
"""If weights weren't made, then make them constant. Must be done after
there is data in the Model."""
# Find an age and time already in the model because adding an
# age and time outside the model can change the integration ranges.
arbitrary_grid = next(iter(self.rate.values()))
one_age_time = (arbitrary_grid.ages[0:1], arbitrary_grid.times[0:1])
for kind in (weight.name for weight in WeightEnum):
if kind not in self.weights:
self.weights[kind] = Var(*one_age_time)
self.weights[kind].grid.loc[:, "mean"] = 1.0
def get_weights(self):
"""
Gets the weights to be written for the model.
"""
weights = self.weights.copy()
arbitrary_grid = next(iter(self.rate.values()))
one_age_time = (arbitrary_grid.ages[0:1], arbitrary_grid.times[0:1])
for kind in (weight.name for weight in WeightEnum):
if kind not in self.weights:
weights[kind] = Var(*one_age_time)
weights[kind].grid.loc[:, "mean"] = 1.0
return weights
def test_const_square(a, t, v):
two = Var([0, 1], [5, 10])
two[:, :] = 36.9
assert isclose(two(a, t), v)
def test_works_as_a_function():
const = Var([0], [0])
const[0, 0] = 21.2
assert const(0, 0) == 21.2
assert const(365, -29) == 21.2
def test_mulstd_failure(name, value):
onet = Var([50, 60], [2000, 2010])
with pytest.raises(ValueError):
onet.set_mulstd(name, value)