kernel docs to kern.src

GPy/kern/__init__.py

@@ -1,10 +1,4 @@
-"""
-Kernel module the kernels to sit in.
 
-.. automodule:: .src
-   :members:
-   :private-members:
-"""
 from .src.kern import Kern
 from .src.add import Add
 from .src.prod import Prod

GPy/kern/src/__init__.py

@@ -1 +1,10 @@
+"""
+
+In terms of Gaussian Processes, a kernel is a function that specifies the degree of similarity between variables given their relative positions in parameter space. If known variables *x* and *x'* are close together then observed variables *y* and *y'* may also be similar, depending on the kernel function and its parameters.
+
+.. inheritance-diagram:: GPy.kern.src.kern.Kern
+   :top-classes: GPy.core.parameterization.parameterized.Parameterized
+
+"""
+
 from . import psi_comp

doc/source/index.rst

@@ -47,7 +47,7 @@ Several tutorials have been developed in the form of `Jupyter Notebooks <https:/
    GPy.core
    GPy.core.parameterization
    GPy.models
-   GPy.kern
+   GPy.kern.src
    GPy.likelihoods
    GPy.mappings
    GPy.examples