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Trying to 'debug'

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Alan Saul 2013-03-14 15:30:22 +00:00
parent 3f114aa020
commit f9535c858a
3 changed files with 52 additions and 32 deletions
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25
python/likelihoods/Laplace.py
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@ -5,13 +5,13 @@ from GPy.util.linalg import jitchol
from functools import partial
from GPy.likelihoods.likelihood import likelihood
from GPy.util.linalg import pdinv,mdot
from scipy.stats import norm
class Laplace(likelihood):
"""Laplace approximation to a posterior"""
def __init__(self,data,likelihood_function):
def __init__(self, data, likelihood_function):
"""
Laplace Approximation
@ -42,7 +42,13 @@ class Laplace(likelihood):
GPy expects a likelihood to be gaussian, so need to caluclate the points Y^{squiggle} and Z^{squiggle}
that makes the posterior match that found by a laplace approximation to a non-gaussian likelihood
"""
z_hat = N(f_hat|f_hat, hess_hat) / self.height_unnormalised
#z_hat = N(f_hat|f_hat, hess_hat) / self.height_unnormalised
normalised_approx = norm(loc=self.f_hat, scale=self.hess_hat)
self.Z = normalised_approx.pdf(self.f_hat)/self.height_unnormalised
#self.Y =
#self.YYT =
#self.covariance_matrix =
#self.precision =
def fit_full(self, K):
"""
@ -51,11 +57,9 @@ class Laplace(likelihood):
:K: Covariance matrix
"""
f = np.zeros((self.N, 1))
print K.shape
print f.shape
print self.data.shape
#K = np.diag(np.ones(self.N))
(Ki, _, _, log_Kdet) = pdinv(K)
obj_constant = (0.5 * log_Kdet) - ((0.5 * self.N) * np.log(2*np.pi))
obj_constant = (0.5 * log_Kdet) - ((0.5 * self.N) * np.log(2 * np.pi))
#Find \hat(f) using a newton raphson optimizer for example
#TODO: Add newton-raphson as subclass of optimizer class
@ -77,11 +81,12 @@ class Laplace(likelihood):
return np.squeeze(res)
self.f_hat = sp.optimize.fmin_ncg(obj, f, fprime=obj_grad, fhess=obj_hess)
print self.f_hat
#At this point get the hessian matrix
self.hess_hat = obj_hess(f_hat)
self.hess_hat = obj_hess(self.f_hat)
#Need to add the constant as we previously were trying to avoid computing it (seems like a small overhead though...)
self.height_unnormalised = obj(f_hat) #FIXME: Is it -1?
self.height_unnormalised = obj(self.f_hat) #FIXME: Is it -1?
return _compute_GP_variables()
return self._compute_GP_variables()