Python 3 fixes

GPy/util/block_matrices.py

@@ -100,10 +100,10 @@ def block_dot(A, B, diagonal=False):
         Dshape = D.shape
         if diagonal and (len(Cshape) == 1 or len(Dshape) == 1\
                 or C.shape[0] != C.shape[1] or D.shape[0] != D.shape[1]):
-            print "Broadcasting, C: {} D:{}".format(C.shape, D.shape)
+            print("Broadcasting, C: {} D:{}".format(C.shape, D.shape))
             return C*D
         else:
-            print "Dotting, C: {} C:{}".format(C.shape, D.shape)
+            print("Dotting, C: {} C:{}".format(C.shape, D.shape))
             return np.dot(C,D)
     dot = np.vectorize(f, otypes = [np.object])
     return dot(A,B)

GPy/util/choleskies.py

@@ -5,7 +5,7 @@ import numpy as np
 from . import linalg
 from .config import config
 
-import choleskies_cython
+from . import choleskies_cython
 
 def safe_root(N):
     i = np.sqrt(N)
@@ -59,12 +59,12 @@ def _backprop_gradient_pure(dL, L):
     """
     dL_dK = np.tril(dL).copy()
     N = L.shape[0]
-    for k in xrange(N - 1, -1, -1):
-        for j in xrange(k + 1, N):
-            for i in xrange(j, N):
+    for k in range(N - 1, -1, -1):
+        for j in range(k + 1, N):
+            for i in range(j, N):
                 dL_dK[i, k] -= dL_dK[i, j] * L[j, k]
                 dL_dK[j, k] -= dL_dK[i, j] * L[i, k]
-        for j in xrange(k + 1, N):
+        for j in range(k + 1, N):
             dL_dK[j, k] /= L[k, k]
             dL_dK[k, k] -= L[j, k] * dL_dK[j, k]
         dL_dK[k, k] /= (2 * L[k, k])

GPy/util/linalg.py

@@ -15,7 +15,7 @@ import warnings
 import os
 from .config import config
 import logging
-import linalg_cython
+from . import linalg_cython
 
 
 _scipyversion = np.float64((scipy.__version__).split('.')[:2])