Python 3 fixes

GPy/inference/optimization/stochastics.py

@@ -40,7 +40,7 @@ class SparseGPMissing(StochasticStorage):
         bdict = {}
         #For N > 1000 array2string default crops
         opt = np.get_printoptions()
-        np.set_printoptions(threshold='nan')
+        np.set_printoptions(threshold=np.inf)
         for d in range(self.Y.shape[1]):
             inan = np.isnan(self.Y)[:, d]
             arr_str = np.array2string(inan, np.inf, 0, True, '', formatter={'bool':lambda x: '1' if x else '0'})
@@ -74,7 +74,7 @@ class SparseGPStochastics(StochasticStorage):
             bdict = {}
             if self.missing_data:
                 opt = np.get_printoptions()
-                np.set_printoptions(threshold='nan')
+                np.set_printoptions(threshold=np.inf)
                 for d in self.d:
                     inan = np.isnan(self.Y[:, d])
                     arr_str = np.array2string(inan,np.inf, 0,True, '',formatter={'bool':lambda x: '1' if x else '0'})

GPy/plotting/matplot_dep/models_plots.py

@@ -3,7 +3,7 @@
 
 import numpy as np
 from . import Tango
-from base_plots import gpplot, x_frame1D, x_frame2D,gperrors
+from .base_plots import gpplot, x_frame1D, x_frame2D,gperrors
 from ...models.gp_coregionalized_regression import GPCoregionalizedRegression
 from ...models.sparse_gp_coregionalized_regression import SparseGPCoregionalizedRegression
 from scipy import sparse
@@ -186,8 +186,8 @@ def plot_fit(model, plot_limits=None, which_data_rows='all',
         #optionally plot some samples
         if samples: #NOTE not tested with fixed_inputs
             Ysim = model.posterior_samples(Xgrid, samples, Y_metadata=Y_metadata)
-            print Ysim.shape
-            print Xnew.shape
+            print(Ysim.shape)
+            print(Xnew.shape)
             for yi in Ysim.T:
                 plots['posterior_samples'] = ax.plot(Xnew, yi[:,None], '#3300FF', linewidth=0.25)
                 #ax.plot(Xnew, yi[:,None], marker='x', linestyle='--',color=Tango.colorsHex['darkBlue']) #TODO apply this line for discrete outputs.

GPy/testing/misc_tests.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 import numpy as np
 import scipy as sp
 import GPy
@@ -18,8 +19,8 @@ class MiscTests(np.testing.TestCase):
             assert np.isinf(np.exp(self._lim_val_exp + 1))
             assert np.isfinite(GPy.util.misc.safe_exp(self._lim_val_exp + 1))
 
-            print w
-            print len(w)
+            print(w)
+            print(len(w))
             assert len(w)==1 # should have one overflow warning
 
     def test_safe_exp_lower(self):