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Fixed the z scalings

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This commit is contained in:
Alan Saul 2013-04-10 13:43:13 +01:00
parent e0c1e4a4df
commit 65481d7a73
2 changed files with 22 additions and 14 deletions
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8
python/examples/laplace_approximations.py
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@ -12,7 +12,7 @@ def timing():
deg_free = 10
real_sd = np.sqrt(real_var)
the_is = np.zeros(times)
X = np.linspace(0.0, 10.0, 500)[:, None]
X = np.linspace(0.0, 10.0, 300)[:, None]
for a in xrange(times):
Y = np.sin(X) + np.random.randn(*X.shape)*real_var
@ -22,8 +22,8 @@ def timing():
Yc[25] += 10
Yc[23] += 10
Yc[24] += 10
Yc[300] += 10
Yc[400] += 10000
Yc[250] += 10
#Yc[4] += 10000
edited_real_sd = real_sd
kernel1 = GPy.kern.rbf(X.shape[1])
@ -36,7 +36,7 @@ def timing():
m.optimize()
the_is[a] = m.likelihood.i
import ipdb; ipdb.set_trace() ### XXX BREAKPOINT
#import ipdb; ipdb.set_trace() ### XXX BREAKPOINT
print the_is
print np.mean(the_is)

28
python/likelihoods/Laplace.py
View file

@ -1,7 +1,7 @@
import numpy as np
import scipy as sp
import GPy
from scipy.linalg import cholesky, eig, inv, cho_solve
from scipy.linalg import cholesky, eig, inv, cho_solve, det
from numpy.linalg import cond
from GPy.likelihoods.likelihood import likelihood
from GPy.util.linalg import pdinv, mdot, jitchol, chol_inv
@ -134,15 +134,24 @@ class Laplace(likelihood):
y_W_f = mdot(Y_tilde.T, self.W, self.f_hat)
y_W_y = mdot(Y_tilde.T, self.W, Y_tilde)
ln_W_det = det_ln_diag(self.W)
Z_tilde = (self.NORMAL_CONST
- 0.5*self.ln_K_det
- 0.5*ln_W_det
- 0.5*self.ln_Ki_W_i_det
- 0.5*f_Ki_W_f
- 0.5*y_W_y
+ y_W_f
Z_tilde = (- self.NORMAL_CONST
+ 0.5*self.ln_K_det
+ 0.5*ln_W_det
+ 0.5*self.ln_Ki_W_i_det
+ 0.5*f_Ki_W_f
+ 0.5*y_W_y
- y_W_f
+ self.ln_z_hat
)
#Z_tilde = (self.NORMAL_CONST
#- 0.5*self.ln_K_det
#- 0.5*ln_W_det
#- 0.5*self.ln_Ki_W_i_det
#- 0.5*f_Ki_W_f
#- 0.5*y_W_y
#+ y_W_f
#+ self.ln_z_hat
#)
##Check it isn't singular!
if cond(self.W) > 1e14:
@ -191,8 +200,7 @@ class Laplace(likelihood):
self.f_Ki_f = np.dot(self.f_hat.T, a)
self.ln_K_det = pddet(self.K)
self.ln_z_hat = (self.NORMAL_CONST
- 0.5*self.f_Ki_f
self.ln_z_hat = (- 0.5*self.f_Ki_f
- 0.5*self.ln_K_det
+ 0.5*self.ln_Ki_W_i_det
+ self.likelihood_function.link_function(self.data, self.f_hat)