manual merging

GPy/likelihoods/__init__.py

@@ -1,9 +1,10 @@
-from bernoulli import Bernoulli
-from exponential import Exponential
-from gaussian import Gaussian
-from gamma import Gamma
-from poisson import Poisson
-from student_t import StudentT
-from likelihood import Likelihood
-from mixed_noise import MixedNoise
-from binomial import Binomial
+from .bernoulli import Bernoulli
+from .exponential import Exponential
+from .gaussian import Gaussian
+from .gamma import Gamma
+from .poisson import Poisson
+from .student_t import StudentT
+from .likelihood import Likelihood
+from .mixed_noise import MixedNoise
+from .binomial import Binomial
+

GPy/likelihoods/bernoulli.py

@@ -2,10 +2,9 @@
 # Licensed under the BSD 3-clause license (see LICENSE.txt)
 
 import numpy as np
-from ..util.univariate_Gaussian import std_norm_cdf, std_norm_pdf
-
-import link_functions
-from likelihood import Likelihood
+from ..util.univariate_Gaussian import std_norm_pdf, std_norm_cdf
+from . import link_functions
+from .likelihood import Likelihood
 
 class Bernoulli(Likelihood):
     """

GPy/likelihoods/binomial.py

@@ -3,8 +3,8 @@
 
 import numpy as np
 from ..util.univariate_Gaussian import std_norm_pdf, std_norm_cdf
-import link_functions
-from likelihood import Likelihood
+from . import link_functions
+from .likelihood import Likelihood
 from scipy import special
 
 class Binomial(Likelihood):

GPy/likelihoods/exponential.py

@@ -5,8 +5,8 @@
 import numpy as np
 from scipy import stats,special
 import scipy as sp
-import link_functions
-from likelihood import Likelihood
+from . import link_functions
+from .likelihood import Likelihood
 
 class Exponential(Likelihood):
     """

GPy/likelihoods/gamma.py

@@ -6,8 +6,8 @@ import numpy as np
 from scipy import stats,special
 import scipy as sp
 from ..core.parameterization import Param
-import link_functions
-from likelihood import Likelihood
+from . import link_functions
+from .likelihood import Likelihood
 
 class Gamma(Likelihood):
     """

GPy/likelihoods/gaussian.py

@@ -13,8 +13,8 @@ James 11/12/13
 
 import numpy as np
 from scipy import stats, special
-import link_functions
-from likelihood import Likelihood
+from . import link_functions
+from .likelihood import Likelihood
 from ..core.parameterization import Param
 from ..core.parameterization.transformations import Logexp
 from scipy import stats
@@ -35,8 +35,8 @@ class Gaussian(Likelihood):
             gp_link = link_functions.Identity()
 
         if not isinstance(gp_link, link_functions.Identity):
-            print "Warning, Exact inference is not implemeted for non-identity link functions,\
-            if you are not already, ensure Laplace inference_method is used"
+            print("Warning, Exact inference is not implemeted for non-identity link functions,\
+            if you are not already, ensure Laplace inference_method is used")
 
         super(Gaussian, self).__init__(gp_link, name=name)
 

GPy/likelihoods/likelihood.py

@@ -4,7 +4,7 @@
 import numpy as np
 from scipy import stats,special
 import scipy as sp
-import link_functions
+from . import link_functions
 from ..util.misc import chain_1, chain_2, chain_3, blockify_dhess_dtheta, blockify_third, blockify_hessian, safe_exp
 from scipy.integrate import quad
 import warnings
@@ -254,8 +254,8 @@ class Likelihood(Parameterized):
         return mean
 
     def _conditional_mean(self, f):
-        """Quadrature calculation of the conditional mean: E(Y_star|f_star)"""
-        raise NotImplementedError, "implement this function to make predictions"
+        """Quadrature calculation of the conditional mean: E(Y_star|f)"""
+        raise NotImplementedError("implement this function to make predictions")
 
     def predictive_variance(self, mu,variance, predictive_mean=None, Y_metadata=None):
         """
@@ -604,7 +604,7 @@ class Likelihood(Parameterized):
         :param burnin: number of samples to use for burnin (will need modifying)
         :param Y_metadata: Y_metadata for pdf
         """
-        print "Warning, using MCMC for sampling y*, needs to be tuned!"
+        print("Warning, using MCMC for sampling y*, needs to be tuned!")
         if starting_loc is None:
             starting_loc = fNew
         from functools import partial
@@ -658,8 +658,8 @@ class Likelihood(Parameterized):
 
             #Show progress
             if i % int((burn_in+num_samples)*0.1) == 0:
-                print "{}% of samples taken ({})".format((i/int((burn_in+num_samples)*0.1)*10), i)
-                print "Last run accept ratio: ", accept_ratio[i]
+                print("{}% of samples taken ({})".format((i/int((burn_in+num_samples)*0.1)*10), i))
+                print("Last run accept ratio: ", accept_ratio[i])
 
-        print "Average accept ratio: ", np.mean(accept_ratio)
+        print("Average accept ratio: ", np.mean(accept_ratio))
         return chain_values

GPy/likelihoods/link_functions.py

@@ -177,7 +177,7 @@ class Heaviside(GPTransformation):
         return np.where(f>0, 1, 0)
 
     def dtransf_df(self,f):
-        raise NotImplementedError, "This function is not differentiable!"
+        raise NotImplementedError("This function is not differentiable!")
 
     def d2transf_df2(self,f):
-        raise NotImplementedError, "This function is not differentiable!"
+        raise NotImplementedError("This function is not differentiable!")

GPy/likelihoods/mixed_noise.py

@@ -3,9 +3,9 @@
 
 import numpy as np
 from scipy import stats, special
-import link_functions
-from likelihood import Likelihood
-from gaussian import Gaussian
+from . import link_functions
+from .likelihood import Likelihood
+from .gaussian import Gaussian
 from ..core.parameterization import Param
 from ..core.parameterization.transformations import Logexp
 from ..core.parameterization import Parameterized

GPy/likelihoods/poisson.py

@@ -5,8 +5,8 @@ from __future__ import division
 import numpy as np
 from scipy import stats,special
 import scipy as sp
-import link_functions
-from likelihood import Likelihood
+from . import link_functions
+from .likelihood import Likelihood
 
 class Poisson(Likelihood):
     """

GPy/likelihoods/student_t.py

@@ -4,10 +4,10 @@
 import numpy as np
 from scipy import stats, special
 import scipy as sp
-import link_functions
+from . import link_functions
 from scipy import stats, integrate
 from scipy.special import gammaln, gamma
-from likelihood import Likelihood
+from .likelihood import Likelihood
 from ..core.parameterization import Param
 from ..core.parameterization.transformations import Logexp