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Fixing bernoulli likelihood for Laplace, fixing Zep for EP, and starting working on quadrature limits

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This commit is contained in:
Alan Saul 2015-10-19 19:29:57 +01:00
parent 6b6938bd11
commit 5b4abf4c34
8 changed files with 70 additions and 39 deletions
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10
GPy/likelihoods/bernoulli.py
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@ -140,7 +140,7 @@ class Bernoulli(Likelihood):
Each y_i must be in {0, 1}
"""
#objective = (inv_link_f**y) * ((1.-inv_link_f)**(1.-y))
return np.where(y, inv_link_f, 1.-inv_link_f)
return np.where(y==1, inv_link_f, 1.-inv_link_f)
def logpdf_link(self, inv_link_f, y, Y_metadata=None):
"""
@ -179,7 +179,7 @@ class Bernoulli(Likelihood):
#grad = (y/inv_link_f) - (1.-y)/(1-inv_link_f)
#grad = np.where(y, 1./inv_link_f, -1./(1-inv_link_f))
ff = np.clip(inv_link_f, 1e-9, 1-1e-9)
denom = np.where(y, ff, -(1-ff))
denom = np.where(y==1, ff, -(1-ff))
return 1./denom
def d2logpdf_dlink2(self, inv_link_f, y, Y_metadata=None):
@ -205,7 +205,7 @@ class Bernoulli(Likelihood):
"""
#d2logpdf_dlink2 = -y/(inv_link_f**2) - (1-y)/((1-inv_link_f)**2)
#d2logpdf_dlink2 = np.where(y, -1./np.square(inv_link_f), -1./np.square(1.-inv_link_f))
arg = np.where(y, inv_link_f, 1.-inv_link_f)
arg = np.where(y==1, inv_link_f, 1.-inv_link_f)
ret = -1./np.square(np.clip(arg, 1e-9, 1e9))
if np.any(np.isinf(ret)):
stop
@ -230,7 +230,7 @@ class Bernoulli(Likelihood):
#d3logpdf_dlink3 = 2*(y/(inv_link_f**3) - (1-y)/((1-inv_link_f)**3))
state = np.seterr(divide='ignore')
# TODO check y \in {0, 1} or {-1, 1}
d3logpdf_dlink3 = np.where(y, 2./(inv_link_f**3), -2./((1.-inv_link_f)**3))
d3logpdf_dlink3 = np.where(y==1, 2./(inv_link_f**3), -2./((1.-inv_link_f)**3))
np.seterr(**state)
return d3logpdf_dlink3
@ -243,8 +243,6 @@ class Bernoulli(Likelihood):
p = self.predictive_mean(mu, var)
return [np.asarray(p>(q/100.), dtype=np.int32) for q in quantiles]
def samples(self, gp, Y_metadata=None):
"""
Returns a set of samples of observations based on a given value of the latent variable.