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Commented out weave functions for Py3 support

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This commit is contained in:
Mike Croucher 2015-03-01 10:18:27 +00:00
parent a0dc90596c
commit 34103ca37c
1 changed files with 9 additions and 4 deletions
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13
GPy/kern/_src/stationary.py
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@ -8,10 +8,15 @@ from ...core.parameterization.transformations import Logexp
from ...util.linalg import tdot
from ... import util
import numpy as np
from scipy import integrate, weave
from scipy import integrate
from ...util.config import config # for assesing whether to use weave
from ...util.caching import Cache_this
try:
from scipy import weave
except ImportError:
config.set('weave', 'working', 'False')
class Stationary(Kern):
"""
Stationary kernels (covariance functions).
@ -167,9 +172,9 @@ class Stationary(Kern):
except:
print("\n Weave compilation failed. Falling back to (slower) numpy implementation\n")
config.set('weave', 'working', 'False')
self.lengthscale.gradient = np.array([np.einsum('ij,ij,...', tmp, np.square(X[:,q:q+1] - X2[:,q:q+1].T), -1./self.lengthscale[q]**3) for q in xrange(self.input_dim)])
self.lengthscale.gradient = np.array([np.einsum('ij,ij,...', tmp, np.square(X[:,q:q+1] - X2[:,q:q+1].T), -1./self.lengthscale[q]**3) for q in range(self.input_dim)])
else:
self.lengthscale.gradient = np.array([np.einsum('ij,ij,...', tmp, np.square(X[:,q:q+1] - X2[:,q:q+1].T), -1./self.lengthscale[q]**3) for q in xrange(self.input_dim)])
self.lengthscale.gradient = np.array([np.einsum('ij,ij,...', tmp, np.square(X[:,q:q+1] - X2[:,q:q+1].T), -1./self.lengthscale[q]**3) for q in range(self.input_dim)])
else:
r = self._scaled_dist(X, X2)
self.lengthscale.gradient = -np.sum(dL_dr*r)/self.lengthscale
@ -234,7 +239,7 @@ class Stationary(Kern):
#the lower memory way with a loop
ret = np.empty(X.shape, dtype=np.float64)
for q in xrange(self.input_dim):
for q in range(self.input_dim):
np.sum(tmp*(X[:,q][:,None]-X2[:,q][None,:]), axis=1, out=ret[:,q])
ret /= self.lengthscale**2