From 485665241fd3a8051b44e66a8cb3a32de0eecaa8 Mon Sep 17 00:00:00 2001 From: Ricardo Date: Thu, 2 May 2013 15:53:38 +0100 Subject: [PATCH] auto_scale option for heteroscedastic noise --- GPy/models/sparse_GP.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/GPy/models/sparse_GP.py b/GPy/models/sparse_GP.py index 14c789b8..cbce9b62 100644 --- a/GPy/models/sparse_GP.py +++ b/GPy/models/sparse_GP.py @@ -200,13 +200,13 @@ class sparse_GP(GP): self.kern._set_params(p[self.Z.size:self.Z.size+self.kern.Nparam]) self.likelihood._set_params(p[self.Z.size+self.kern.Nparam:]) self._compute_kernel_matrices() - if self.auto_scale_factor: - self.scale_factor = np.sqrt(self.psi2.sum(0).mean()*self.likelihood.precision) #if self.auto_scale_factor: - # if self.likelihood.is_heteroscedastic: - # self.scale_factor = max(1,np.sqrt(self.psi2_beta_scaled.sum(0).mean())) - # else: - # self.scale_factor = np.sqrt(self.psi2.sum(0).mean()*self.likelihood.precision) + # self.scale_factor = np.sqrt(self.psi2.sum(0).mean()*self.likelihood.precision) + if self.auto_scale_factor: + if self.likelihood.is_heteroscedastic: + self.scale_factor = max(100,np.sqrt(self.psi2_beta_scaled.sum(0).mean())) + else: + self.scale_factor = np.sqrt(self.psi2.sum(0).mean()*self.likelihood.precision) self._computations() def _get_params(self):