diff --git a/GPy/core/model.py b/GPy/core/model.py index 4b569f98..09e815ca 100644 --- a/GPy/core/model.py +++ b/GPy/core/model.py @@ -29,7 +29,7 @@ class Model(Parameterized): def log_likelihood(self): raise NotImplementedError, "this needs to be implemented to use the model class" def _log_likelihood_gradients(self): - return self.gradient + return self.gradient.copy() def optimize_restarts(self, num_restarts=10, robust=False, verbose=True, parallel=False, num_processes=None, **kwargs): """ @@ -207,7 +207,7 @@ class Model(Parameterized): raise self._fail_count += 1 obj_f = np.inf - obj_grads = np.clip(self._transform_gradients(self.objective_function_gradients()), -1e100, 1e100) + obj_grads = np.clip(self._transform_gradients(self.objective_function_gradients()), -1e10, 1e10) return obj_f, obj_grads def optimize(self, optimizer=None, start=None, **kwargs): diff --git a/GPy/core/parameterization/param.py b/GPy/core/parameterization/param.py index 78bc4fa2..4b480c55 100644 --- a/GPy/core/parameterization/param.py +++ b/GPy/core/parameterization/param.py @@ -273,11 +273,11 @@ class Param(Parameterizable, ObsAr): header = header_format.format(x=self.hierarchy_name(), c=__constraints_name__, i=__index_name__, t=__tie_name__, p=__priors_name__) # nice header for printing if not ties: ties = itertools.cycle(['']) return "\n".join([""""""] + ['
| {i} | {x} | {c} | {p} | {t} |