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1 change: 1 addition & 0 deletions docs/source/api/gp.rst
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Expand Up @@ -9,3 +9,4 @@ Gaussian Processes
gp/implementations
gp/mean
gp/cov
gp/util
9 changes: 9 additions & 0 deletions docs/source/api/gp/util.rst
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@@ -0,0 +1,9 @@
************
GP Utilities
************

.. automodule:: pymc.gp.util
.. autosummary::
:toctree: generated

plot_gp_dist
20 changes: 10 additions & 10 deletions pymc/gp/util.py
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Expand Up @@ -178,30 +178,30 @@ def plot_gp_dist(

Parameters
----------
ax: axes
ax : axes
Matplotlib axes.
samples: numpy.ndarray
samples : numpy.ndarray
Array of S posterior predictive sample from a GP.
Expected shape: (S, X)
x: numpy.ndarray
x : numpy.ndarray
Grid of X values corresponding to the samples.
Expected shape: (X,) or (X, 1), or (1, X)
plot_samples: bool
plot_samples : bool
Plot the GP samples along with posterior (defaults True).
palette: str
palette : str
Palette for coloring output (defaults to "Reds").
fill_alpha: float
fill_alpha : float
Alpha value for the posterior interval fill (defaults to 0.8).
samples_alpha: float
samples_alpha : float
Alpha value for the sample lines (defaults to 0.1).
fill_kwargs: dict
fill_kwargs : dict
Additional arguments for posterior interval fill (fill_between).
samples_kwargs: dict
samples_kwargs : dict
Additional keyword arguments for samples plot.

Returns
-------
ax: Matplotlib axes
ax : Matplotlib axes
"""
import matplotlib.pyplot as plt

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