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New likelihood: HeteroscedasticGaussian

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This commit is contained in:
Ricardo 2015-09-02 13:29:33 +01:00
parent 7a5872e11d
commit f780693577
2 changed files with 4 additions and 3 deletions
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1
GPy/likelihoods/__init__.py
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@ -1,6 +1,7 @@
from .bernoulli import Bernoulli
from .exponential import Exponential
from .gaussian import Gaussian
from .gaussian import HeteroscedasticGaussian
from .gamma import Gamma
from .poisson import Poisson
from .student_t import StudentT

6
GPy/likelihoods/gaussian.py
View file

@ -326,7 +326,7 @@ class Gaussian(Likelihood):
dF_dtheta = -0.5/lik_var + 0.5*(np.square(Y) + np.square(m) + v - 2*m*Y)/(lik_var**2)
return F, dF_dmu, dF_dv, dF_dtheta.reshape(1, Y.shape[0], Y.shape[1])
class Heteroscedastic_Gaussian(Gaussian):
class HeteroscedasticGaussian(Gaussian):
def __init__(self, Y_metadata, gp_link=None, variance=1., name='het_Gauss'):
if gp_link is None:
gp_link = link_functions.Identity()
@ -335,7 +335,7 @@ class Heteroscedastic_Gaussian(Gaussian):
print("Warning, Exact inference is not implemeted for non-identity link functions,\
if you are not already, ensure Laplace inference_method is used")
super(Heteroscedastic_Gaussian, self).__init__(gp_link, np.ones(Y_metadata['output_index'].shape[0])*variance, name)
super(HeteroscedasticGaussian, self).__init__(gp_link, np.ones(Y_metadata['output_index'].shape[0])*variance, name)
def exact_inference_gradients(self, dL_dKdiag,Y_metadata=None):
return dL_dKdiag[Y_metadata['output_index']][:,0]
@ -351,4 +351,4 @@ class Heteroscedastic_Gaussian(Gaussian):
var += np.atleast_3d(np.eye(var.shape[0])*self.variance)
else:
var += self.variance
return mu, var
return mu, var