def init_same_param_shapes(cls):
M = 10
D = 8
prior = TPrior(D // 2, mu_scale=1.0, scale_scale=5.0)
priors = [prior] * M
simulators = [
MultivariateTSimulator(df) for df in np.arange(1, 101, M)
]
generative_model = MetaGenerativeModel(model_prior, priors, simulators)
return generative_model
def init_different_param_shapes(cls):
priors = [
ex.priors.model1_params_prior, ex.priors.model2_params_prior,
ex.priors.model3_params_prior
]
simulators = [
ex.simulators.forward_model1, ex.simulators.forward_model2,
ex.simulators.forward_model3
]
generative_model = MetaGenerativeModel(model_prior, priors, simulators)
return generative_model
def test_meta_generative_model_different_param_shapes(self):
priors = [
ex.priors.model1_params_prior, ex.priors.model2_params_prior,
ex.priors.model3_params_prior
]
simulators = [
ex.simulators.forward_model1, ex.simulators.forward_model2,
ex.simulators.forward_model3
]
generative_model = MetaGenerativeModel(model_prior, priors, simulators)
_model_indices, _params, _sim_data = generative_model(n_sim=16,
n_obs=150)
def test_same_data_transform(self):
def data_transform(x):
noise = 0.001 * np.random.random(x.shape)
return x + noise
M = 10
D = 8
prior = TPrior(D // 2, mu_scale=1.0, scale_scale=5.0)
priors = [prior] * M
simulators = [
MultivariateTSimulator(df) for df in np.arange(1, 101, M)
]
_generative_model = MetaGenerativeModel(model_prior=model_prior,
priors=priors,
simulators=simulators,
data_transforms=data_transform)
def test_same_param_transform(self):
def param_transform(x):
return np.exp(x)
M = 10
D = 8
prior = TPrior(D // 2, mu_scale=1.0, scale_scale=5.0)
priors = [prior] * M
simulators = [
MultivariateTSimulator(df) for df in np.arange(1, 101, M)
]
_generative_model = MetaGenerativeModel(
model_prior=model_prior,
priors=priors,
simulators=simulators,
param_transforms=param_transform)
def test_same_param_and_data_transform(self):
def data_transform(x):
noise = 0.001 * np.random.random(x.shape)
return x + noise
def param_transform(x):
return np.exp(x)
M = 10
D = 8
prior = ex.priors.TPrior(D // 2, mu_scale=1.0, scale_scale=5.0)
priors = [prior] * M
simulators = [
ex.simulators.MultivariateT(df) for df in np.arange(1, 101, M)
]
_generative_model = MetaGenerativeModel(
model_prior=ex.priors.model_prior,
priors=priors,
simulators=simulators,
param_transforms=param_transform,
data_transforms=data_transform)
def test_individual_param_and_data_transform(self):
param_transforms = [
lambda x: np.exp(x), None, lambda x: np.round(x, 3)
]
data_transforms = [
lambda x: x + np.random.random(x.shape), lambda x: np.exp(x), None
]
M = 3
D = 4
prior = TPrior(D // 2, mu_scale=1.0, scale_scale=5.0)
priors = [prior] * M
simulators = [
MultivariateTSimulator(df)
for df in np.round(np.linspace(1, 101, M))
]
_generative_model = MetaGenerativeModel(
model_prior=model_prior,
priors=priors,
simulators=simulators,
param_transforms=param_transforms,
data_transforms=data_transforms)