[docs] had to rename kern._src to kern.src. PLEASE CHECK YOUR CODE, if it is running smoothly

GPy/kern/__init__.py

@@ -1,31 +1,31 @@
 """
 Kernel module the kernels to sit in.
 
-.. automodule:: GPy.kern.src
+.. automodule:: .src
    :members:
    :private-members:
 """
-from . import _src as src
-from ._src.kern import Kern
-from ._src.rbf import RBF
-from ._src.linear import Linear, LinearFull
-from ._src.static import Bias, White, Fixed
-from ._src.brownian import Brownian
-from ._src.stationary import Exponential, OU, Matern32, Matern52, ExpQuad, RatQuad, Cosine
-from ._src.mlp import MLP
-from ._src.periodic import PeriodicExponential, PeriodicMatern32, PeriodicMatern52
-from ._src.standard_periodic import StdPeriodic
-from ._src.independent_outputs import IndependentOutputs, Hierarchical
-from ._src.coregionalize import Coregionalize
-from ._src.ODE_UY import ODE_UY
-from ._src.ODE_UYC import ODE_UYC
-from ._src.ODE_st import ODE_st
-from ._src.ODE_t import ODE_t
-from ._src.poly import Poly
-from ._src.eq_ode2 import EQ_ODE2
-from ._src.trunclinear import TruncLinear,TruncLinear_inf
-from ._src.splitKern import SplitKern,DEtime
-from ._src.splitKern import DEtime as DiffGenomeKern
-from ._src.spline import Spline
-from ._src.eq_ode2 import EQ_ODE2
-from ._src.basis_funcs import LinearSlopeBasisFuncKernel, BasisFuncKernel, ChangePointBasisFuncKernel, DomainKernel
+from .src.kern import Kern
+from .src.add import Add
+from .src.prod import Prod
+from .src.rbf import RBF
+from .src.linear import Linear, LinearFull
+from .src.static import Bias, White, Fixed
+from .src.brownian import Brownian
+from .src.stationary import Exponential, OU, Matern32, Matern52, ExpQuad, RatQuad, Cosine
+from .src.mlp import MLP
+from .src.periodic import PeriodicExponential, PeriodicMatern32, PeriodicMatern52
+from .src.standard_periodic import StdPeriodic
+from .src.independent_outputs import IndependentOutputs, Hierarchical
+from .src.coregionalize import Coregionalize
+from .src.ODE_UY import ODE_UY
+from .src.ODE_UYC import ODE_UYC
+from .src.ODE_st import ODE_st
+from .src.ODE_t import ODE_t
+from .src.poly import Poly
+from .src.eq_ode2 import EQ_ODE2
+from .src.trunclinear import TruncLinear,TruncLinear_inf
+from .src.splitKern import SplitKern,DEtime
+from .src.splitKern import DEtime as DiffGenomeKern
+from .src.spline import Spline
+from .src.basis_funcs import LinearSlopeBasisFuncKernel, BasisFuncKernel, ChangePointBasisFuncKernel, DomainKernel

GPy/kern/src/ODE_UY.py

@@ -2,10 +2,10 @@
 # Licensed under the BSD 3-clause license (see LICENSE.txt)
 
 from .kern import Kern
+from .independent_outputs import index_to_slices
 from ...core.parameterization import Param
 from ...core.parameterization.transformations import Logexp
 import numpy as np
-from .independent_outputs import index_to_slices
 
 class ODE_UY(Kern):
     def __init__(self, input_dim, variance_U=3., variance_Y=1., lengthscale_U=1., lengthscale_Y=1., active_dims=None, name='ode_uy'):

GPy/kern/src/__init__.py

@@ -0,0 +1 @@
+from . import psi_comp

GPy/kern/src/basis_funcs.py

@@ -1,9 +1,9 @@
 # #Copyright (c) 2012, Max Zwiessele (see AUTHORS.txt).
 # Licensed under the BSD 3-clause license (see LICENSE.txt)
+import numpy as np
 from .kern import Kern
 from ...core.parameterization.param import Param
 from ...core.parameterization.transformations import Logexp
-import numpy as np
 from ...util.caching import Cache_this
 from ...util.linalg import tdot, mdot
 

GPy/kern/src/independent_outputs.py

@@ -2,7 +2,7 @@
 # Licensed under the BSD 3-clause license (see LICENSE.txt)
 
 
-from .kern import Kern, CombinationKernel
+from .kern import CombinationKernel
 import numpy as np
 import itertools
 

GPy/kern/src/kern.py

@@ -3,9 +3,9 @@
 import sys
 import numpy as np
 from ...core.parameterization.parameterized import Parameterized
-from .kernel_slice_operations import KernCallsViaSlicerMeta
+from ...core.parameterization.observable_array import ObsAr
 from ...util.caching import Cache_this
-from GPy.core.parameterization.observable_array import ObsAr
+from .kernel_slice_operations import KernCallsViaSlicerMeta
 from functools import reduce
 import six
 
@@ -198,15 +198,6 @@ class Kern(Parameterized):
         from ...plotting.matplot_dep import kernel_plots
         kernel_plots.plot(self, x, fignum, ax, title, plot_limits, resolution, **mpl_kwargs)
 
-    def plot_ARD(self, *args, **kw):
-        """
-        See :class:`~GPy.plotting.matplot_dep.kernel_plots`
-        """
-        import sys
-        assert "matplotlib" in sys.modules, "matplotlib package has not been imported."
-        from ...plotting.matplot_dep import kernel_plots
-        return kernel_plots.plot_ARD(self,*args,**kw)
-
     def input_sensitivity(self, summarize=True):
         """
         Returns the sensitivity for each dimension of this kernel.

GPy/kern/src/linear.py

@@ -8,7 +8,6 @@ from ...util.linalg import tdot
 from ...core.parameterization import Param
 from ...core.parameterization.transformations import Logexp
 from ...util.caching import Cache_this
-from ...util.config import *
 from .psi_comp import PSICOMP_Linear
 
 class Linear(Kern):

GPy/kern/src/mlp.py

@@ -5,7 +5,6 @@ from .kern import Kern
 from ...core.parameterization import Param
 from ...core.parameterization.transformations import Logexp
 import numpy as np
-from ...util.linalg import tdot
 from ...util.caching import Cache_this
 four_over_tau = 2./np.pi
 

GPy/kern/src/periodic.py

@@ -8,7 +8,6 @@ from ...util.linalg import mdot
 from ...util.decorators import silence_errors
 from ...core.parameterization.param import Param
 from ...core.parameterization.transformations import Logexp
-from functools import reduce
 
 class Periodic(Kern):
     def __init__(self, input_dim, variance, lengthscale, period, n_freq, lower, upper, active_dims, name):

GPy/kern/src/psi_comp/__init__.py

@@ -2,13 +2,9 @@
 # Licensed under the BSD 3-clause license (see LICENSE.txt)
 
 from ....core.parameterization.parameter_core import Pickleable
-from GPy.util.caching import Cache_this
+from ....util.caching import Cache_this
 from ....core.parameterization import variational
-from . import rbf_psi_comp
-from . import ssrbf_psi_comp
-from . import sslinear_psi_comp
-from . import linear_psi_comp
-
+#from linear_psi_comp import LINEAr
 
 class PSICOMP(Pickleable):
         
@@ -22,6 +18,7 @@ class PSICOMP(Pickleable):
         pass
 
 from .gaussherm import PSICOMP_GH
+from . import rbf_psi_comp, linear_psi_comp, ssrbf_psi_comp, sslinear_psi_comp
 
 class PSICOMP_RBF(PSICOMP):
     @Cache_this(limit=10, ignore_args=(0,))
@@ -67,3 +64,5 @@ class PSICOMP_Linear(PSICOMP):
             raise ValueError("unknown distriubtion received for psi-statistics")
 
 
+from . import ssrbf_psi_gpucomp
+from rbf_psi_gpucomp import PSICOMP_RBF_GPU

GPy/kern/src/psi_comp/gaussherm.py

@@ -8,10 +8,12 @@ An approximated psi-statistics implementation based on Gauss-Hermite Quadrature
 import numpy as np
 
 from ....core.parameterization import Param
-from GPy.util.caching import Cache_this
+from ....util.caching import Cache_this
 from ....util.linalg import tdot
 from . import PSICOMP
 
+
+
 class PSICOMP_GH(PSICOMP):
     
     def __init__(self, degree=5, cache_K=True):

GPy/kern/src/psi_comp/rbf_psi_gpucomp.py

@@ -235,7 +235,6 @@ gpu_code = """
 class PSICOMP_RBF_GPU(PSICOMP_RBF):
 
     def __init__(self, threadnum=256, blocknum=30, GPU_direct=False):
-        from . import PSICOMP_RBF
         self.fall_back = PSICOMP_RBF()
         
         from pycuda.compiler import SourceModule

GPy/kern/src/rbf.py

@@ -4,11 +4,9 @@
 
 import numpy as np
 from .stationary import Stationary
-from .psi_comp import PSICOMP_RBF
-from .psi_comp.rbf_psi_gpucomp import PSICOMP_RBF_GPU
-from ...util.config import *
+from .psi_comp import PSICOMP_RBF, PSICOMP_RBF_GPU
 from ...core import Param
-from GPy.core.parameterization.transformations import Logexp
+from ...core.parameterization.transformations import Logexp
 
 class RBF(Stationary):
     """

GPy/kern/src/spline.py

@@ -5,6 +5,7 @@ import numpy as np
 from .kern import Kern
 from ...core.parameterization import Param
 from ...core.parameterization.transformations import Logexp
+
 class Spline(Kern):
     """
     Linear spline kernel. You need to specify 2 parameters: the variance and c.

GPy/kern/src/splitKern.py

@@ -3,7 +3,7 @@ A new kernel
 """
 
 import numpy as np
-from .kern import Kern,CombinationKernel
+from .kern import Kern, CombinationKernel
 from .independent_outputs import index_to_slices
 import itertools
 
@@ -13,7 +13,7 @@ class DEtime(Kern):
         self.idx_p = idx_p
         self.index_dim=index_dim
         self.kern = SplitKern(kernel,Xp, index_dim=index_dim)
-        super(DiffGenomeKern, self).__init__(input_dim=kernel.input_dim+1, active_dims=None, name=name)
+        super(DEtime, self).__init__(input_dim=kernel.input_dim+1, active_dims=None, name=name)
         self.add_parameter(self.kern)
     
     def K(self, X, X2=None):

GPy/kern/src/symbolic.py

@@ -1,7 +1,7 @@
 # Check Matthew Rocklin's blog post.
 import sympy as sym
 import numpy as np
-from .kern import Kern
+from GPy.kern.src import Kern
 from ...core.symbolic import Symbolic_core
 
 

GPy/kern/src/trunclinear.py

@@ -7,7 +7,6 @@ from .kern import Kern
 from ...core.parameterization import Param
 from ...core.parameterization.transformations import Logexp
 from ...util.caching import Cache_this
-from ...util.config import *
 
 class TruncLinear(Kern):
     """

GPy/models/ss_gplvm.py

@@ -9,7 +9,7 @@ from ..core.parameterization import Param
 from ..likelihoods import Gaussian
 from ..core.parameterization.variational import SpikeAndSlabPrior, SpikeAndSlabPosterior,VariationalPrior
 from ..inference.latent_function_inference.var_dtc_parallel import update_gradients, VarDTC_minibatch
-from ..kern._src.psi_comp.ssrbf_psi_gpucomp import PSICOMP_SSRBF_GPU
+from ..kern.src.psi_comp.ssrbf_psi_gpucomp import PSICOMP_SSRBF_GPU
 
 class IBPPosterior(SpikeAndSlabPosterior):
     '''

GPy/testing/pickle_tests.py

@@ -13,9 +13,9 @@ import tempfile
 from GPy.core.parameterization.param import Param
 from GPy.core.parameterization.observable_array import ObsAr
 from GPy.core.parameterization.priors import Gaussian
-from GPy.kern._src.rbf import RBF
-from GPy.kern._src.linear import Linear
-from GPy.kern._src.static import Bias, White
+from GPy.kern.src.rbf import RBF
+from GPy.kern.src.linear import Linear
+from GPy.kern.src.static import Bias, White
 from GPy.examples.dimensionality_reduction import mrd_simulation
 from GPy.core.parameterization.variational import NormalPosterior
 from GPy.models.gp_regression import GPRegression