Fixed docstring warnings - could still be mistakes

This commit is contained in:
James McMurray 2013-09-20 13:38:20 +01:00
parent c36a6b341c
commit be3880c0bd
20 changed files with 261 additions and 144 deletions

View file

@ -14,6 +14,7 @@ import sys
class SVIGP(GPBase):
"""
Stochastic Variational inference in a Gaussian Process
:param X: inputs
@ -22,25 +23,26 @@ class SVIGP(GPBase):
:type Y: np.ndarray of observations (N x D)
:param batchsize: the size of a h
Additional kwargs are used as for a sparse GP. They include
Additional kwargs are used as for a sparse GP. They include:
:param q_u: canonical parameters of the distribution squasehd into a 1D array
:type q_u: np.ndarray
:param M : Number of inducing points (optional, default 10. Ignored if Z is not None)
:param M: Number of inducing points (optional, default 10. Ignored if Z is not None)
:type M: int
:param kernel : the kernel/covariance function. See link kernels
:param kernel: the kernel/covariance function. See link kernels
:type kernel: a GPy kernel
:param Z: inducing inputs (optional, see note)
:type Z: np.ndarray (M x Q) | None
:param X_uncertainty: The uncertainty in the measurements of X (Gaussian variance)
:type X_uncertainty: np.ndarray (N x Q) | None
:param Zslices: slices for the inducing inputs (see slicing TODO: link)
:param M : Number of inducing points (optional, default 10. Ignored if Z is not None)
:param M: Number of inducing points (optional, default 10. Ignored if Z is not None)
:type M: int
:param beta: noise precision. TODO> ignore beta if doing EP
:param beta: noise precision. TODO: ignore beta if doing EP
:type beta: float
: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
"""