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Plot function moved to GP model

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Ricardo Andrade 2013-03-11 11:39:48 +00:00
parent 24d7054174
commit 0ade786385
1 changed files with 2 additions and 13 deletions
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15
GPy/models/sparse_GP.py
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@ -180,8 +180,8 @@ class sparse_GP(GP):
if self.has_uncertain_inputs: if self.has_uncertain_inputs:
raise NotImplementedError, "EP approximation not implemented for uncertain inputs" raise NotImplementedError, "EP approximation not implemented for uncertain inputs"
else: else:
#self.likelihood.fit_DTC(self.Kmm,self.psi1) self.likelihood.fit_DTC(self.Kmm,self.psi1)
self.likelihood.fit_FITC(self.Kmm,self.psi1,self.psi0) #self.likelihood.fit_FITC(self.Kmm,self.psi1,self.psi0)
self._set_params(self._get_params()) # update the GP self._set_params(self._get_params()) # update the GP
def log_likelihood(self): def log_likelihood(self):
@ -240,14 +240,3 @@ class sparse_GP(GP):
var = Kxx - np.sum(Kx*np.dot(self.Kmmi - self.C/self.scale_factor**2, Kx),0) var = Kxx - np.sum(Kx*np.dot(self.Kmmi - self.C/self.scale_factor**2, Kx),0)
return mu,var[:,None] return mu,var[:,None]
def plot(self, *args, **kwargs):
"""
Plot the fitted model: just call the GP plot function and then add inducing inputs
"""
GP.plot(self,*args,**kwargs)
if self.Q==1:
if self.has_uncertain_inputs:
pb.errorbar(self.X[:,0], pb.ylim()[0]+np.zeros(self.N), xerr=2*np.sqrt(self.X_uncertainty.flatten()))
if self.Q==2:
pb.plot(self.Z[:,0],self.Z[:,1],'wo')