Started fixing docs

GPy/core/fitc.py

@@ -11,18 +11,20 @@ from sparse_gp import SparseGP
 
 class FITC(SparseGP):
     """
-    sparse FITC approximation
+
+    Sparse FITC approximation
 
     :param X: inputs
     :type X: np.ndarray (num_data x Q)
     :param likelihood: a likelihood instance, containing the observed data
     :type likelihood: GPy.likelihood.(Gaussian | EP)
-    :param kernel : the kernel (covariance function). See link kernels
+    :param kernel: the kernel (covariance function). See link kernels
     :type kernel: a GPy.kern.kern instance
     :param Z: inducing inputs (optional, see note)
     :type Z: np.ndarray (M x Q) | None
-    :param normalize_(X|Y) : whether to normalize the data before computing (predictions will be in original scales)
+    :param normalize_(X|Y): whether to normalize the data before computing (predictions will be in original scales)
     :type normalize_(X|Y): bool
+
     """
 
     def __init__(self, X, likelihood, kernel, Z, normalize_X=False):

GPy/core/mapping.py

@@ -49,6 +49,7 @@ class Mapping(Parameterized):
 
     def plot(self, plot_limits=None, which_data='all', which_parts='all', resolution=None, levels=20, samples=0, fignum=None, ax=None, fixed_inputs=[], linecol=Tango.colorsHex['darkBlue']):
         """
+
         Plot the mapping.
         
         Plots the mapping associated with the model.
@@ -79,8 +80,7 @@ class Mapping(Parameterized):
         :type fixed_inputs: a list of tuples
         :param linecol: color of line to plot.
         :type linecol:
-        :param levels: for 2D plotting, the number of contour levels to use
+        :param levels: for 2D plotting, the number of contour levels to use is ax is None, create a new figure
-        is ax is None, create a new figure
 
         """
         # TODO include samples

GPy/core/model.py

@@ -56,10 +56,11 @@ class Model(Parameterized):
 
     def set_prior(self, regexp, what):
         """
+
         Sets priors on the model parameters.
 
-        Notes
+        **Notes**
-        -----
+
         Asserts that the prior is suitable for the constraint. If the
         wrong constraint is in place, an error is raised.  If no
         constraint is in place, one is added (warning printed).
@@ -185,8 +186,8 @@ class Model(Parameterized):
         be handled silently.  If _all_ runs fail, the model is reset to the
         existing parameter values.
 
-        Notes
+        **Notes**
-        -----
+
         :param num_restarts: number of restarts to use (default 10)
         :type num_restarts: int
         :param robust: whether to handle exceptions silently or not (default False)
@@ -195,7 +196,9 @@ class Model(Parameterized):
         :type parallel: bool
         :param num_processes: number of workers in the multiprocessing pool
         :type numprocesses: int
-        **kwargs are passed to the optimizer. They can be:
+
+        \*\*kwargs are passed to the optimizer. They can be:
+
         :param max_f_eval: maximum number of function evaluations
         :type max_f_eval: int
         :param max_iters: maximum number of iterations
@@ -203,9 +206,7 @@ class Model(Parameterized):
         :param messages: whether to display during optimisation
         :type messages: bool
 
-        ..Note: If num_processes is None, the number of workes in the multiprocessing pool is automatically
+        .. note:: If num_processes is None, the number of workes in the multiprocessing pool is automatically set to the number of processors on the current machine.
-        set to the number of processors on the current machine.
-
 
         """
         initial_parameters = self._get_params_transformed()

doc/Makefile

@@ -2,7 +2,7 @@
 #
 
 # You can set these variables from the command line.
-SPHINXOPTS    =
+SPHINXOPTS    = -a -w log.txt -E
 SPHINXBUILD   = sphinx-build
 PAPER         =
 BUILDDIR      = _build