apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-06-29 15:59:41 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

xrange fixes for Python 3

Browse source
This commit is contained in:
Mike Croucher 2015-03-07 07:49:59 +00:00
parent 5eeb2f18e9
commit cf1c382acd
14 changed files with 29 additions and 29 deletions
Download patch file Download diff file Expand all files Collapse all files

6
GPy/inference/latent_function_inference/posterior.py
View file

@ -107,7 +107,7 @@ class Posterior(object):
if self._precision is None:
cov = np.atleast_3d(self.covariance)
self._precision = np.zeros(cov.shape) # if one covariance per dimension
for p in xrange(cov.shape[-1]):
for p in range(cov.shape[-1]):
self._precision[:,:,p] = pdinv(cov[:,:,p])[0]
return self._precision
@ -125,7 +125,7 @@ class Posterior(object):
if self._woodbury_inv is not None:
winv = np.atleast_3d(self._woodbury_inv)
self._woodbury_chol = np.zeros(winv.shape)
for p in xrange(winv.shape[-1]):
for p in range(winv.shape[-1]):
self._woodbury_chol[:,:,p] = pdinv(winv[:,:,p])[2]
#Li = jitchol(self._woodbury_inv)
#self._woodbury_chol, _ = dtrtri(Li)
@ -160,7 +160,7 @@ class Posterior(object):
elif self._covariance is not None:
B = np.atleast_3d(self._K) - np.atleast_3d(self._covariance)
self._woodbury_inv = np.empty_like(B)
for i in xrange(B.shape[-1]):
for i in range(B.shape[-1]):
tmp, _ = dpotrs(self.K_chol, B[:,:,i])
self._woodbury_inv[:,:,i], _ = dpotrs(self.K_chol, tmp.T)
return self._woodbury_inv

2
GPy/inference/latent_function_inference/var_dtc_parallel.py
View file

@ -92,7 +92,7 @@ class VarDTC_minibatch(LatentFunctionInference):
psi0_full = 0.
YRY_full = 0.
for n_start in xrange(0,num_data,batchsize):
for n_start in range(0,num_data,batchsize):
n_end = min(batchsize+n_start, num_data)
if batchsize==num_data:
Y_slice = Y