apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-06-11 15:15:15 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

A few typos

Browse source
This commit is contained in:
Alan Saul 2013-08-29 13:47:56 +01:00
parent 000491b25d
commit 54954c63f8
2 changed files with 9 additions and 2 deletions
Download patch file Download diff file Expand all files Collapse all files

2
GPy/examples/laplace_approximations.py
View file

@ -632,7 +632,7 @@ def gaussian_f_check():
plt.subplot(212)
m.optimize()
m.plot()
print "final optimised student t"
print "final optimised gaussian"
print m
print "real GP"
print mgp

9
GPy/likelihoods/Laplace.py
View file

@ -105,8 +105,15 @@ class Laplace(likelihood):
dL_dthetaL = np.zeros(num_params) # make space for one derivative for each likelihood parameter
for thetaL_i in range(num_params):
#Explicit
#dL_dthetaL_exp = np.sum(dlik_dthetaL[thetaL_i]) - 0.5*np.dot(np.diag(self.Ki_W_i), dlik_hess_dthetaL[thetaL_i])
#a = 0.5*np.dot(np.diag(self.Ki_W_i), dlik_hess_dthetaL[thetaL_i])
#d = dlik_hess_dthetaL[thetaL_i]
#e = pdinv(pdinv(self.K)[0] + np.diagflat(self.W))[0]
#b = 0.5*np.dot(np.diag(e).T, d)
#g = 0.5*(np.diag(self.K) - np.sum(cho_solve((self.B_chol, True), np.dot(np.diagflat(self.W_12),self.K))**2, 1))
#dL_dthetaL_exp = np.sum(dlik_dthetaL[thetaL_i]) - np.dot(g.T, dlik_hess_dthetaL[thetaL_i])
dL_dthetaL_exp = np.sum(dlik_dthetaL[thetaL_i]) - 0.5*np.dot(np.diag(self.Ki_W_i), dlik_hess_dthetaL[thetaL_i])
#dL_dthetaL_exp = np.sum(dlik_dthetaL[thetaL_i]) - 0.5*np.trace(mdot(self.Bi, self.K, dlik_hess_dthetaL[thetaL_i]))
#Implicit
df_hat_dthetaL = mdot(I_KW_i, self.K, dlik_grad_dthetaL[thetaL_i])
dL_dthetaL_imp = np.dot(dL_dfhat, df_hat_dthetaL)