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wrapping docstrings

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James Hensman 2014-01-28 14:45:00 +00:00
parent 1d2ecad6f9
commit 18a5c437e8
1 changed files with 26 additions and 10 deletions
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36
GPy/core/gp.py
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@ -98,11 +98,14 @@ class GP(Model):
:type Xnew: np.ndarray, Nnew x self.input_dim
:param which_parts: specifies which outputs kernel(s) to use in prediction
:type which_parts: ('all', list of bools)
:param full_cov: whether to return the full covariance matrix, or just the diagonal
:param full_cov: whether to return the full covariance matrix, or just
the diagonal
:type full_cov: bool
:returns: mean: posterior mean, a Numpy array, Nnew x self.input_dim
:returns: var: posterior variance, a Numpy array, Nnew x 1 if full_cov=False, Nnew x Nnew otherwise
:returns: lower and upper boundaries of the 95% confidence intervals, Numpy arrays, Nnew x self.input_dim
:returns: var: posterior variance, a Numpy array, Nnew x 1 if
full_cov=False, Nnew x Nnew otherwise
:returns: lower and upper boundaries of the 95% confidence intervals,
Numpy arrays, Nnew x self.input_dim
If full_cov and self.input_dim > 1, the return shape of var is Nnew x Nnew x self.input_dim. If self.input_dim == 1, the return shape is Nnew x Nnew.
@ -170,9 +173,13 @@ class GP(Model):
def plot_f(self, *args, **kwargs):
"""
Plot the GP's view of the world, where the data is normalized and before applying a likelihood.
This is a convenience function: arguments are passed to GPy.plotting.matplot_dep.models_plots.plot_f_fit
Plot the GP's view of the world, where the data is normalized and
before applying a likelihood.
This is a convenience function: arguments are passed to
GPy.plotting.matplot_dep.models_plots.plot_f_fit
"""
assert "matplotlib" in sys.modules, "matplotlib package has not been imported."
from ..plotting.matplot_dep import models_plots
@ -181,14 +188,19 @@ class GP(Model):
def plot(self, *args):
"""
Plot the posterior of the GP.
- In one dimension, the function is plotted with a shaded region identifying two standard deviations.
- In two dimsensions, a contour-plot shows the mean predicted function
- In higher dimensions, use fixed_inputs to plot the GP with some of the inputs fixed.
- In one dimension, the function is plotted with a shaded region
identifying two standard deviations.
- In two dimsensions, a contour-plot shows the mean predicted
function
- In higher dimensions, use fixed_inputs to plot the GP with some of
the inputs fixed.
Can plot only part of the data and part of the posterior functions
using which_data_rows which_data_ycols and which_parts
This is a convenience function: arguments are passed to GPy.plotting.matplot_dep.models_plots.plot_fit
This is a convenience function: arguments are passed to
GPy.plotting.matplot_dep.models_plots.plot_fit
"""
assert "matplotlib" in sys.modules, "matplotlib package has not been imported."
from ..plotting.matplot_dep import models_plots
@ -196,8 +208,12 @@ class GP(Model):
def _getstate(self):
"""
Get the current state of the class, here we return everything that is needed to recompute the model.
Get the current state of the class, here we return everything that is
needed to recompute the model.
"""
return Model._getstate(self) + [self.X,
self.num_data,
self.input_dim,