Various Py3 related import fixes

GPy/core/model.py

@@ -13,6 +13,7 @@ import itertools
 import sys
 from .verbose_optimization import VerboseOptimization
 # import numdifftools as ndt
+from functools import reduce
 
 class Model(Parameterized):
     _fail_count = 0  # Count of failed optimization steps (see objective)

GPy/core/parameterization/param.py

@@ -6,6 +6,7 @@ import numpy
 np = numpy
 from .parameter_core import Parameterizable, adjust_name_for_printing, Pickleable
 from .observable_array import ObsAr
+from functools import reduce
 
 ###### printing
 __constraints_name__ = "Constraint"

GPy/models/mrd.py

@@ -82,7 +82,7 @@ class MRD(BayesianGPLVMMiniBatch):
         assert len(self.names) == len(self.Ylist), "one name per dataset, or None if Ylist is a dict"
 
         if inference_method is None:
-            self.inference_method = InferenceMethodList([VarDTC() for _ in xrange(len(self.Ylist))])
+            self.inference_method = InferenceMethodList([VarDTC() for _ in range(len(self.Ylist))])
         else:
             assert isinstance(inference_method, InferenceMethodList), "please provide one inference method per Y in the list and provide it as InferenceMethodList, inference_method given: {}".format(inference_method)
             self.inference_method = inference_method

GPy/testing/pickle_tests.py

@@ -34,7 +34,7 @@ class ListDictTestCase(unittest.TestCase):
         for k,v in d1.items():
             self.assertListEqual(list(v), list(d2[k]), msg)
     def assertArrayListEquals(self, l1, l2):
-        for a1, a2 in itertools.izip(l1,l2):
+        for a1, a2 in zip(l1,l2):
             np.testing.assert_array_equal(a1, a2)
 
 class Test(ListDictTestCase):