def test_linear_variable_get_vec(spline_variable):
uprior = UniformPrior(lb=0.0, ub=1.0, size=spline_variable.size)
gprior = GaussianPrior(mean=0.0, sd=1.0, size=spline_variable.size)
spline_variable.add_priors([uprior, gprior])
uvec = spline_variable.get_uvec()
gvec = spline_variable.get_gvec()
assert uvec.shape == (2, spline_variable.size)
assert gvec.shape == (2, spline_variable.size)
def result_to_priors(self,
result: Dict[str, np.ndarray],
min_var: float = 0.1) -> Dict[str, Prior]:
mean = result["coefs"]
sd = np.sqrt(np.maximum(min_var, np.diag(result["vcov"])))
slices = sizes_to_sclices([var.size for var in self.variables])
return {
var_name: GaussianPrior(mean=mean[slices[i]], sd=sd[slices[i]])
for i, var_name in enumerate(self.var_names)
}
def gprior():
return GaussianPrior(mean=0.0, sd=1.0)