def __init__(self, X, Y, kern, name="PseudoGPR"):
super(PseudGPR, self).__init__(name=name)
# GPy.Parameterized.__init__(self, name=name)
self.X = GPy.Param("input", X)
self.link_parameter(self.X)
self.Y = GPy.Param("target", Y)
self.link_parameter(self.Y)
self.kern = kern
self.link_parameter(self.kern)
self.likelihood = GPy.likelihoods.Gaussian()
self.link_parameter(self.likelihood)
def create_models(self, X, Y):
for i in range(self.control_dim):
kernel = GPy.kern.RBF(input_dim=self.state_dim, ARD=1)
model = PseudGPR(X, Y[:, i:i + 1], kernel)
# model = GPy.models.GPRegression(X, Y[:, i:i+1], kernel)
# model.likelihood = GPy.likelihoods.Gaussian()
# model.X = GPy.Param(X)
# model.Y = GPy.Param(Y)
# model._add_parameter_name()
self.models.append(model)
display(model)
self.models = GPy.Param("Models", self.models)
