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work on likeluhoods and likelihoods tests

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James Hensman 2014-02-27 15:37:31 +00:00
parent 5cf792504a
commit 2876e5a07a
11 changed files with 186 additions and 222 deletions
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20
GPy/likelihoods/bernoulli.py
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@ -95,7 +95,7 @@ class Bernoulli(Likelihood):
return np.nan
#raise NotImplementedError
def pdf_link(self, link_f, y, extra_data=None):
def pdf_link(self, link_f, y, Y_metadata=None):
"""
Likelihood function given link(f)
@ -106,7 +106,7 @@ class Bernoulli(Likelihood):
:type link_f: Nx1 array
:param y: data
:type y: Nx1 array
:param extra_data: extra_data not used in bernoulli
:param Y_metadata: Y_metadata not used in bernoulli
:returns: likelihood evaluated for this point
:rtype: float
@ -118,7 +118,7 @@ class Bernoulli(Likelihood):
objective = np.where(y, link_f, 1.-link_f)
return np.exp(np.sum(np.log(objective)))
def logpdf_link(self, link_f, y, extra_data=None):
def logpdf_link(self, link_f, y, Y_metadata=None):
"""
Log Likelihood function given link(f)
@ -129,7 +129,7 @@ class Bernoulli(Likelihood):
:type link_f: Nx1 array
:param y: data
:type y: Nx1 array
:param extra_data: extra_data not used in bernoulli
:param Y_metadata: Y_metadata not used in bernoulli
:returns: log likelihood evaluated at points link(f)
:rtype: float
"""
@ -140,7 +140,7 @@ class Bernoulli(Likelihood):
np.seterr(**state)
return np.sum(objective)
def dlogpdf_dlink(self, link_f, y, extra_data=None):
def dlogpdf_dlink(self, link_f, y, Y_metadata=None):
"""
Gradient of the pdf at y, given link(f) w.r.t link(f)
@ -151,7 +151,7 @@ class Bernoulli(Likelihood):
:type link_f: Nx1 array
:param y: data
:type y: Nx1 array
:param extra_data: extra_data not used in bernoulli
:param Y_metadata: Y_metadata not used in bernoulli
:returns: gradient of log likelihood evaluated at points link(f)
:rtype: Nx1 array
"""
@ -162,7 +162,7 @@ class Bernoulli(Likelihood):
np.seterr(**state)
return grad
def d2logpdf_dlink2(self, link_f, y, extra_data=None):
def d2logpdf_dlink2(self, link_f, y, Y_metadata=None):
"""
Hessian at y, given link_f, w.r.t link_f the hessian will be 0 unless i == j
i.e. second derivative logpdf at y given link(f_i) link(f_j) w.r.t link(f_i) and link(f_j)
@ -175,7 +175,7 @@ class Bernoulli(Likelihood):
:type link_f: Nx1 array
:param y: data
:type y: Nx1 array
:param extra_data: extra_data not used in bernoulli
:param Y_metadata: Y_metadata not used in bernoulli
:returns: Diagonal of log hessian matrix (second derivative of log likelihood evaluated at points link(f))
:rtype: Nx1 array
@ -190,7 +190,7 @@ class Bernoulli(Likelihood):
np.seterr(**state)
return d2logpdf_dlink2
def d3logpdf_dlink3(self, link_f, y, extra_data=None):
def d3logpdf_dlink3(self, link_f, y, Y_metadata=None):
"""
Third order derivative log-likelihood function at y given link(f) w.r.t link(f)
@ -201,7 +201,7 @@ class Bernoulli(Likelihood):
:type link_f: Nx1 array
:param y: data
:type y: Nx1 array
:param extra_data: extra_data not used in bernoulli
:param Y_metadata: Y_metadata not used in bernoulli
:returns: third derivative of log likelihood evaluated at points link(f)
:rtype: Nx1 array
"""