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)