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Merge branch 'devel' of github.com:SheffieldML/GPy into devel

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Alan Saul 2013-11-29 14:21:10 +00:00
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235
GPy/examples/regression.py
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@ -1,7 +1,6 @@
# Copyright (c) 2012, GPy authors (see AUTHORS.txt).
# Licensed under the BSD 3-clause license (see LICENSE.txt)
"""
Gaussian Processes regression examples
"""
@ -9,88 +8,107 @@ import pylab as pb
import numpy as np
import GPy
def coregionalization_toy2(max_iters=100):
def olympic_marathon_men(optimize=True, plot=True):
"""Run a standard Gaussian process regression on the Olympic marathon data."""
data = GPy.util.datasets.olympic_marathon_men()
# create simple GP Model
m = GPy.models.GPRegression(data['X'], data['Y'])
# set the lengthscale to be something sensible (defaults to 1)
m['rbf_lengthscale'] = 10
if optimize:
m.optimize('bfgs', max_iters=200)
if plot:
m.plot(plot_limits=(1850, 2050))
return m
def coregionalization_toy2(optimize=True, plot=True):
"""
A simple demonstration of coregionalization on two sinusoidal functions.
"""
#build a design matrix with a column of integers indicating the output
X1 = np.random.rand(50, 1) * 8
X2 = np.random.rand(30, 1) * 5
index = np.vstack((np.zeros_like(X1), np.ones_like(X2)))
X = np.hstack((np.vstack((X1, X2)), index))
#build a suitable set of observed variables
Y1 = np.sin(X1) + np.random.randn(*X1.shape) * 0.05
Y2 = np.sin(X2) + np.random.randn(*X2.shape) * 0.05 + 2.
Y = np.vstack((Y1, Y2))
#build the kernel
k1 = GPy.kern.rbf(1) + GPy.kern.bias(1)
k2 = GPy.kern.coregionalize(2,1)
k = k1**k2 #k = k1.prod(k2,tensor=True)
k = k1**k2
m = GPy.models.GPRegression(X, Y, kernel=k)
m.constrain_fixed('.*rbf_var', 1.)
# m.constrain_positive('.*kappa')
m.optimize('sim', messages=1, max_iters=max_iters)
pb.figure()
Xtest1 = np.hstack((np.linspace(0, 9, 100)[:, None], np.zeros((100, 1))))
Xtest2 = np.hstack((np.linspace(0, 9, 100)[:, None], np.ones((100, 1))))
mean, var, low, up = m.predict(Xtest1)
GPy.util.plot.gpplot(Xtest1[:, 0], mean, low, up)
mean, var, low, up = m.predict(Xtest2)
GPy.util.plot.gpplot(Xtest2[:, 0], mean, low, up)
pb.plot(X1[:, 0], Y1[:, 0], 'rx', mew=2)
pb.plot(X2[:, 0], Y2[:, 0], 'gx', mew=2)
if optimize:
m.optimize('bfgs', max_iters=100)
if plot:
m.plot(fixed_inputs=[(1,0)])
m.plot(fixed_inputs=[(1,1)], ax=pb.gca())
return m
def coregionalization_toy(max_iters=100):
"""
A simple demonstration of coregionalization on two sinusoidal functions.
"""
X1 = np.random.rand(50, 1) * 8
X2 = np.random.rand(30, 1) * 5
X = np.vstack((X1, X2))
Y1 = np.sin(X1) + np.random.randn(*X1.shape) * 0.05
Y2 = -np.sin(X2) + np.random.randn(*X2.shape) * 0.05
Y = np.vstack((Y1, Y2))
#FIXME: Needs recovering once likelihoods are consolidated
#def coregionalization_toy(optimize=True, plot=True):
# """
# A simple demonstration of coregionalization on two sinusoidal functions.
# """
# X1 = np.random.rand(50, 1) * 8
# X2 = np.random.rand(30, 1) * 5
# X = np.vstack((X1, X2))
# Y1 = np.sin(X1) + np.random.randn(*X1.shape) * 0.05
# Y2 = -np.sin(X2) + np.random.randn(*X2.shape) * 0.05
# Y = np.vstack((Y1, Y2))
#
# k1 = GPy.kern.rbf(1)
# m = GPy.models.GPMultioutputRegression(X_list=[X1,X2],Y_list=[Y1,Y2],kernel_list=[k1])
# m.constrain_fixed('.*rbf_var', 1.)
# m.optimize(max_iters=100)
#
# fig, axes = pb.subplots(2,1)
# m.plot(fixed_inputs=[(1,0)],ax=axes[0])
# m.plot(fixed_inputs=[(1,1)],ax=axes[1])
# axes[0].set_title('Output 0')
# axes[1].set_title('Output 1')
# return m
k1 = GPy.kern.rbf(1)
m = GPy.models.GPMultioutputRegression(X_list=[X1,X2],Y_list=[Y1,Y2],kernel_list=[k1])
m.constrain_fixed('.*rbf_var', 1.)
m.optimize(max_iters=max_iters)
fig, axes = pb.subplots(2,1)
m.plot(fixed_inputs=[(1,0)],ax=axes[0])
m.plot(fixed_inputs=[(1,1)],ax=axes[1])
axes[0].set_title('Output 0')
axes[1].set_title('Output 1')
return m
def coregionalization_sparse(max_iters=100):
def coregionalization_sparse(optimize=True, plot=True):
"""
A simple demonstration of coregionalization on two sinusoidal functions using sparse approximations.
"""
X1 = np.random.rand(500, 1) * 8
X2 = np.random.rand(300, 1) * 5
index = np.vstack((np.zeros_like(X1), np.ones_like(X2)))
X = np.hstack((np.vstack((X1, X2)), index))
Y1 = np.sin(X1) + np.random.randn(*X1.shape) * 0.05
Y2 = -np.sin(X2) + np.random.randn(*X2.shape) * 0.05
Y = np.vstack((Y1, Y2))
#fetch the data from the non sparse examples
m = coregionalization_toy2(optimize=False, plot=False)
X, Y = m.X, m.likelihood.Y
k1 = GPy.kern.rbf(1)
#construct a model
m = GPy.models.SparseGPRegression(X,Y)
m.constrain_fixed('iip_\d+_1') # don't optimize the inducing input indexes
m = GPy.models.SparseGPMultioutputRegression(X_list=[X1,X2],Y_list=[Y1,Y2],kernel_list=[k1],num_inducing=5)
m.constrain_fixed('.*rbf_var',1.)
#m.optimize(messages=1)
m.optimize_restarts(5, robust=True, messages=1, max_iters=max_iters, optimizer='bfgs')
if optimize:
m.optimize('bfgs', max_iters=100, messages=1)
if plot:
m.plot(fixed_inputs=[(1,0)])
m.plot(fixed_inputs=[(1,1)], ax=pb.gca())
fig, axes = pb.subplots(2,1)
m.plot_single_output(output=0,ax=axes[0],plot_limits=(-1,9))
m.plot_single_output(output=1,ax=axes[1],plot_limits=(-1,9))
axes[0].set_title('Output 0')
axes[1].set_title('Output 1')
return m
def epomeo_gpx(max_iters=100):
"""Perform Gaussian process regression on the latitude and longitude data from the Mount Epomeo runs. Requires gpxpy to be installed on your system to load in the data."""
def epomeo_gpx(optimize=True, plot=True):
"""
Perform Gaussian process regression on the latitude and longitude data
from the Mount Epomeo runs. Requires gpxpy to be installed on your system
to load in the data.
"""
data = GPy.util.datasets.epomeo_gpx()
num_data_list = []
for Xpart in data['X']:
@ -119,14 +137,17 @@ def epomeo_gpx(max_iters=100):
m.constrain_fixed('.*rbf_var', 1.)
m.constrain_fixed('iip')
m.constrain_bounded('noise_variance', 1e-3, 1e-1)
# m.optimize_restarts(5, robust=True, messages=1, max_iters=max_iters, optimizer='bfgs')
m.optimize(max_iters=max_iters,messages=True)
return m
def multiple_optima(gene_number=937, resolution=80, model_restarts=10, seed=10000, max_iters=300):
"""Show an example of a multimodal error surface for Gaussian process regression. Gene 939 has bimodal behaviour where the noisy mode is higher."""
"""
Show an example of a multimodal error surface for Gaussian process
regression. Gene 939 has bimodal behaviour where the noisy mode is
higher.
"""
# Contour over a range of length scales and signal/noise ratios.
length_scales = np.linspace(0.1, 60., resolution)
@ -175,12 +196,15 @@ def multiple_optima(gene_number=937, resolution=80, model_restarts=10, seed=1000
return m # (models, lls)
def _contour_data(data, length_scales, log_SNRs, kernel_call=GPy.kern.rbf):
"""Evaluate the GP objective function for a given data set for a range of signal to noise ratios and a range of lengthscales.
"""
Evaluate the GP objective function for a given data set for a range of
signal to noise ratios and a range of lengthscales.
:data_set: A data set from the utils.datasets director.
:length_scales: a list of length scales to explore for the contour plot.
:log_SNRs: a list of base 10 logarithm signal to noise ratios to explore for the contour plot.
:kernel: a kernel to use for the 'signal' portion of the data."""
:kernel: a kernel to use for the 'signal' portion of the data.
"""
lls = []
total_var = np.var(data['Y'])
@ -203,79 +227,58 @@ def _contour_data(data, length_scales, log_SNRs, kernel_call=GPy.kern.rbf):
return np.array(lls)
def olympic_100m_men(max_iters=100, kernel=None):
def olympic_100m_men(optimize=True, plot=True):
"""Run a standard Gaussian process regression on the Rogers and Girolami olympics data."""
data = GPy.util.datasets.olympic_100m_men()
# create simple GP Model
m = GPy.models.GPRegression(data['X'], data['Y'], kernel)
m = GPy.models.GPRegression(data['X'], data['Y'])
# set the lengthscale to be something sensible (defaults to 1)
if kernel==None:
m['rbf_lengthscale'] = 10
m['rbf_lengthscale'] = 10
# optimize
m.optimize(max_iters=max_iters)
if optimize:
m.optimize('bfgs', max_iters=200)
# plot
m.plot(plot_limits=(1850, 2050))
print(m)
if plot:
m.plot(plot_limits=(1850, 2050))
return m
def olympic_marathon_men(max_iters=100, kernel=None):
"""Run a standard Gaussian process regression on the Olympic marathon data."""
data = GPy.util.datasets.olympic_marathon_men()
# create simple GP Model
m = GPy.models.GPRegression(data['X'], data['Y'], kernel)
# set the lengthscale to be something sensible (defaults to 1)
if kernel==None:
m['rbf_lengthscale'] = 10
# optimize
m.optimize(max_iters=max_iters)
# plot
m.plot(plot_limits=(1850, 2050))
print(m)
return m
def toy_rbf_1d(optimizer='tnc', max_nb_eval_optim=100):
def toy_rbf_1d(optimize=True, plot=True):
"""Run a simple demonstration of a standard Gaussian process fitting it to data sampled from an RBF covariance."""
data = GPy.util.datasets.toy_rbf_1d()
# create simple GP Model
m = GPy.models.GPRegression(data['X'], data['Y'])
# optimize
m.optimize(optimizer, max_f_eval=max_nb_eval_optim)
# plot
m.plot()
print(m)
if optimize:
m.optimize('bfgs')
if plot:
m.plot()
return m
def toy_rbf_1d_50(max_iters=100):
def toy_rbf_1d_50(optimize=True, plot=True):
"""Run a simple demonstration of a standard Gaussian process fitting it to data sampled from an RBF covariance."""
data = GPy.util.datasets.toy_rbf_1d_50()
# create simple GP Model
m = GPy.models.GPRegression(data['X'], data['Y'])
# optimize
m.optimize(max_iters=max_iters)
if optimize:
m.optimize('bfgs')
if plot:
m.plot()
# plot
m.plot()
print(m)
return m
def toy_poisson_rbf_1d(optimizer='bfgs', max_nb_eval_optim=100):
def toy_poisson_rbf_1d(optimize=True, plot=True):
"""Run a simple demonstration of a standard Gaussian process fitting it to data sampled from an RBF covariance."""
x_len = 400
X = np.linspace(0, 10, x_len)[:, None]
f_true = np.random.multivariate_normal(np.zeros(x_len), GPy.kern.rbf(1).K(X))
Y = np.array([np.random.poisson(np.exp(f)) for f in f_true])[:,None]
Y = np.array([np.random.poisson(np.exp(f)) for f in f_true]).reshape(x_len,1)
noise_model = GPy.likelihoods.poisson()
likelihood = GPy.likelihoods.EP(Y,noise_model)
@ -283,14 +286,14 @@ def toy_poisson_rbf_1d(optimizer='bfgs', max_nb_eval_optim=100):
# create simple GP Model
m = GPy.models.GPRegression(X, Y, likelihood=likelihood)
# optimize
m.optimize(optimizer, max_f_eval=max_nb_eval_optim)
# plot
m.plot()
print(m)
if optimize:
m.optimize('bfgs')
if plot:
m.plot()
return m
def toy_poisson_rbf_1d_laplace(optimizer='bfgs', max_nb_eval_optim=100):
def toy_poisson_rbf_1d_laplace(optimize=True, plot=True):
"""Run a simple demonstration of a standard Gaussian process fitting it to data sampled from an RBF covariance."""
x_len = 30
X = np.linspace(0, 10, x_len)[:, None]
@ -303,13 +306,13 @@ def toy_poisson_rbf_1d_laplace(optimizer='bfgs', max_nb_eval_optim=100):
# create simple GP Model
m = GPy.models.GPRegression(X, Y, likelihood=likelihood)
# optimize
m.optimize(optimizer, max_f_eval=max_nb_eval_optim)
# plot
m.plot()
# plot the real underlying rate function
pb.plot(X, np.exp(f_true), '--k', linewidth=2)
print(m)
if optimize:
m.optimize(optimizer, max_f_eval=max_nb_eval_optim)
if plot:
m.plot()
# plot the real underlying rate function
pb.plot(X, np.exp(f_true), '--k', linewidth=2)
return m
@ -459,7 +462,7 @@ def sparse_GP_regression_2D(num_samples=400, num_inducing=50, max_iters=100):
print(m)
return m
def uncertain_inputs_sparse_regression(max_iters=100):
def uncertain_inputs_sparse_regression(optimize=True, plot=True):
"""Run a 1D example of a sparse GP regression with uncertain inputs."""
fig, axes = pb.subplots(1, 2, figsize=(12, 5))

46
GPy/models.py
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@ -1,23 +1,31 @@
'''
Created on 14 Nov 2013
GPy Models
==========
@author: maxz
Implementations for common models used in GP regression and classification.
The different models can be viewed in :mod:`GPy.models_modules`, which holds
detailed explanations for the different models.
:warning: This module is a convienince module for endusers to use. For developers
see :mod:`GPy.models_modules`, which holds the implementions for each model.
'''
from _models.bayesian_gplvm import BayesianGPLVM
from _models.gp_regression import GPRegression
from _models.gp_classification import GPClassification#; _gp_classification = gp_classification ; del gp_classification
from _models.sparse_gp_regression import SparseGPRegression#; _sparse_gp_regression = sparse_gp_regression ; del sparse_gp_regression
from _models.svigp_regression import SVIGPRegression#; _svigp_regression = svigp_regression ; del svigp_regression
from _models.sparse_gp_classification import SparseGPClassification#; _sparse_gp_classification = sparse_gp_classification ; del sparse_gp_classification
from _models.fitc_classification import FITCClassification#; _fitc_classification = fitc_classification ; del fitc_classification
from _models.gplvm import GPLVM#; _gplvm = gplvm ; del gplvm
from _models.bcgplvm import BCGPLVM#; _bcgplvm = bcgplvm; del bcgplvm
from _models.sparse_gplvm import SparseGPLVM#; _sparse_gplvm = sparse_gplvm ; del sparse_gplvm
from _models.warped_gp import WarpedGP#; _warped_gp = warped_gp ; del warped_gp
from _models.bayesian_gplvm import BayesianGPLVM#; _bayesian_gplvm = bayesian_gplvm ; del bayesian_gplvm
from _models.mrd import MRD#; _mrd = mrd; del mrd
from _models.gradient_checker import GradientChecker#; _gradient_checker = gradient_checker ; del gradient_checker
from _models.gp_multioutput_regression import GPMultioutputRegression#; _gp_multioutput_regression = gp_multioutput_regression ; del gp_multioutput_regression
from _models.sparse_gp_multioutput_regression import SparseGPMultioutputRegression#; _sparse_gp_multioutput_regression = sparse_gp_multioutput_regression ; del sparse_gp_multioutput_regression
from _models.gradient_checker import GradientChecker
__updated__ = '2013-11-28'
from models_modules.bayesian_gplvm import BayesianGPLVM
from models_modules.gp_regression import GPRegression
from models_modules.gp_classification import GPClassification#; _gp_classification = gp_classification ; del gp_classification
from models_modules.sparse_gp_regression import SparseGPRegression#; _sparse_gp_regression = sparse_gp_regression ; del sparse_gp_regression
from models_modules.svigp_regression import SVIGPRegression#; _svigp_regression = svigp_regression ; del svigp_regression
from models_modules.sparse_gp_classification import SparseGPClassification#; _sparse_gp_classification = sparse_gp_classification ; del sparse_gp_classification
from models_modules.fitc_classification import FITCClassification#; _fitc_classification = fitc_classification ; del fitc_classification
from models_modules.gplvm import GPLVM#; _gplvm = gplvm ; del gplvm
from models_modules.bcgplvm import BCGPLVM#; _bcgplvm = bcgplvm; del bcgplvm
from models_modules.sparse_gplvm import SparseGPLVM#; _sparse_gplvm = sparse_gplvm ; del sparse_gplvm
from models_modules.warped_gp import WarpedGP#; _warped_gp = warped_gp ; del warped_gp
from models_modules.bayesian_gplvm import BayesianGPLVM#; _bayesian_gplvm = bayesian_gplvm ; del bayesian_gplvm
from models_modules.mrd import MRD#; _mrd = mrd; del mrd
from models_modules.gradient_checker import GradientChecker#; _gradient_checker = gradient_checker ; del gradient_checker
from models_modules.gp_multioutput_regression import GPMultioutputRegression#; _gp_multioutput_regression = gp_multioutput_regression ; del gp_multioutput_regression
from models_modules.sparse_gp_multioutput_regression import SparseGPMultioutputRegression#; _sparse_gp_multioutput_regression = sparse_gp_multioutput_regression ; del sparse_gp_multioutput_regression
from models_modules.gradient_checker import GradientChecker

0
GPy/_models/__init__.py → GPy/models_modules/__init__.py
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52
GPy/_models/bayesian_gplvm.py → GPy/models_modules/bayesian_gplvm.py
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@ -12,6 +12,7 @@ from GPy.util import plot_latent, linalg
from .gplvm import GPLVM
from GPy.util.plot_latent import most_significant_input_dimensions
from matplotlib import pyplot
from GPy.core.model import Model
class BayesianGPLVM(SparseGP, GPLVM):
"""
@ -285,6 +286,57 @@ class BayesianGPLVM(SparseGP, GPLVM):
self.init = state.pop()
SparseGP.setstate(self, state)
class BayesianGPLVMWithMissingData(Model):
"""
Bayesian Gaussian Process Latent Variable Model with missing data support.
NOTE: Missing data is assumed to be missing at random!
This extension comes with a large memory and computing time deficiency.
Use only if fraction of missing data at random is higher than 60%.
Otherwise, try filtering data before using this extension.
Y can hold missing data as given by `missing`, standard is :class:`~numpy.nan`.
If likelihood is given for Y, this likelihood will be discarded, but the parameters
of the likelihood will be taken. Also every effort of creating the same likelihood
will be done.
:param likelihood_or_Y: observed data (np.ndarray) or GPy.likelihood
:type likelihood_or_Y: :class:`~numpy.ndarray` | :class:`~GPy.likelihoods.likelihood.likelihood` instance
:param int input_dim: latent dimensionality
:param init: initialisation method for the latent space
:type init: 'PCA' | 'random'
"""
def __init__(self, likelihood_or_Y, input_dim, X=None, X_variance=None, init='PCA', num_inducing=10,
Z=None, kernel=None, missing=np.nan, **kwargs):
if type(likelihood_or_Y) is np.ndarray:
likelihood = Gaussian(likelihood_or_Y)
else:
likelihood = likelihood_or_Y
if X == None:
X = self.initialise_latent(init, input_dim, likelihood.Y)
self.init = init
if X_variance is None:
X_variance = np.clip((np.ones_like(X) * 0.5) + .01 * np.random.randn(*X.shape), 0.001, 1)
if Z is None:
Z = np.random.permutation(X.copy())[:num_inducing]
assert Z.shape[1] == X.shape[1]
if kernel is None:
kernel = kern.rbf(input_dim) # + kern.white(input_dim)
SparseGP.__init__(self, X, likelihood, kernel, Z=Z, X_variance=X_variance, **kwargs)
self.ensure_default_constraints()
def _get_param_names(self):
X_names = sum([['X_%i_%i' % (n, q) for q in range(self.input_dim)] for n in range(self.num_data)], [])
S_names = sum([['X_variance_%i_%i' % (n, q) for q in range(self.input_dim)] for n in range(self.num_data)], [])
return (X_names + S_names + SparseGP._get_param_names(self))
pass
def latent_cost_and_grad(mu_S, kern, Z, dL_dpsi0, dL_dpsi1, dL_dpsi2):
"""

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GPy/_models/bcgplvm.py → GPy/models_modules/bcgplvm.py
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GPy/_models/fitc_classification.py → GPy/models_modules/fitc_classification.py
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GPy/_models/gp_classification.py → GPy/models_modules/gp_classification.py
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GPy/_models/gp_multioutput_regression.py → GPy/models_modules/gp_multioutput_regression.py
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GPy/_models/gp_regression.py → GPy/models_modules/gp_regression.py
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GPy/_models/gradient_checker.py → GPy/models_modules/gradient_checker.py
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GPy/_models/sparse_gp_classification.py → GPy/models_modules/sparse_gp_classification.py
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GPy/_models/sparse_gp_multioutput_regression.py → GPy/models_modules/sparse_gp_multioutput_regression.py
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GPy/_models/sparse_gp_regression.py → GPy/models_modules/sparse_gp_regression.py
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GPy/_models/sparse_gplvm.py → GPy/models_modules/sparse_gplvm.py
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GPy/_models/svigp_regression.py → GPy/models_modules/svigp_regression.py
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GPy/_models/warped_gp.py → GPy/models_modules/warped_gp.py
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65
doc/GPy.core.rst
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@ -1,102 +1,107 @@
GPy.core package
================
core Package
============
Submodules
----------
:mod:`core` Package
-------------------
GPy.core.domains module
-----------------------
.. automodule:: GPy.core
:members:
:undoc-members:
:show-inheritance:
:mod:`domains` Module
---------------------
.. automodule:: GPy.core.domains
:members:
:undoc-members:
:show-inheritance:
GPy.core.fitc module
--------------------
:mod:`fitc` Module
------------------
.. automodule:: GPy.core.fitc
:members:
:undoc-members:
:show-inheritance:
GPy.core.gp module
------------------
:mod:`gp` Module
----------------
.. automodule:: GPy.core.gp
:members:
:undoc-members:
:show-inheritance:
GPy.core.gp_base module
-----------------------
:mod:`gp_base` Module
---------------------
.. automodule:: GPy.core.gp_base
:members:
:undoc-members:
:show-inheritance:
GPy.core.mapping module
-----------------------
:mod:`mapping` Module
---------------------
.. automodule:: GPy.core.mapping
:members:
:undoc-members:
:show-inheritance:
GPy.core.model module
---------------------
:mod:`model` Module
-------------------
.. automodule:: GPy.core.model
:members:
:undoc-members:
:show-inheritance:
GPy.core.parameterized module
-----------------------------
:mod:`parameterized` Module
---------------------------
.. automodule:: GPy.core.parameterized
:members:
:undoc-members:
:show-inheritance:
GPy.core.priors module
----------------------
:mod:`priors` Module
--------------------
.. automodule:: GPy.core.priors
:members:
:undoc-members:
:show-inheritance:
GPy.core.sparse_gp module
-------------------------
:mod:`sparse_gp` Module
-----------------------
.. automodule:: GPy.core.sparse_gp
:members:
:undoc-members:
:show-inheritance:
GPy.core.svigp module
---------------------
:mod:`svigp` Module
-------------------
.. automodule:: GPy.core.svigp
:members:
:undoc-members:
:show-inheritance:
GPy.core.transformations module
-------------------------------
:mod:`transformations` Module
-----------------------------
.. automodule:: GPy.core.transformations
:members:
:undoc-members:
:show-inheritance:
:mod:`variational` Module
-------------------------
Module contents
---------------
.. automodule:: GPy.core
.. automodule:: GPy.core.variational
:members:
:undoc-members:
:show-inheritance:

45
doc/GPy.examples.rst
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@ -1,62 +1,59 @@
GPy.examples package
====================
examples Package
================
Submodules
----------
:mod:`examples` Package
-----------------------
GPy.examples.classification module
----------------------------------
.. automodule:: GPy.examples
:members:
:undoc-members:
:show-inheritance:
:mod:`classification` Module
----------------------------
.. automodule:: GPy.examples.classification
:members:
:undoc-members:
:show-inheritance:
GPy.examples.dimensionality_reduction module
--------------------------------------------
:mod:`dimensionality_reduction` Module
--------------------------------------
.. automodule:: GPy.examples.dimensionality_reduction
:members:
:undoc-members:
:show-inheritance:
GPy.examples.laplace_approximations module
------------------------------------------
:mod:`laplace_approximations` Module
------------------------------------
.. automodule:: GPy.examples.laplace_approximations
:members:
:undoc-members:
:show-inheritance:
GPy.examples.regression module
------------------------------
:mod:`regression` Module
------------------------
.. automodule:: GPy.examples.regression
:members:
:undoc-members:
:show-inheritance:
GPy.examples.stochastic module
------------------------------
:mod:`stochastic` Module
------------------------
.. automodule:: GPy.examples.stochastic
:members:
:undoc-members:
:show-inheritance:
GPy.examples.tutorials module
-----------------------------
:mod:`tutorials` Module
-----------------------
.. automodule:: GPy.examples.tutorials
:members:
:undoc-members:
:show-inheritance:
Module contents
---------------
.. automodule:: GPy.examples
:members:
:undoc-members:
:show-inheritance:

39
doc/GPy.inference.rst
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@ -1,62 +1,51 @@
GPy.inference package
=====================
inference Package
=================
Submodules
----------
GPy.inference.conjugate_gradient_descent module
-----------------------------------------------
:mod:`conjugate_gradient_descent` Module
----------------------------------------
.. automodule:: GPy.inference.conjugate_gradient_descent
:members:
:undoc-members:
:show-inheritance:
GPy.inference.gradient_descent_update_rules module
--------------------------------------------------
:mod:`gradient_descent_update_rules` Module
-------------------------------------------
.. automodule:: GPy.inference.gradient_descent_update_rules
:members:
:undoc-members:
:show-inheritance:
GPy.inference.optimization module
---------------------------------
:mod:`optimization` Module
--------------------------
.. automodule:: GPy.inference.optimization
:members:
:undoc-members:
:show-inheritance:
GPy.inference.samplers module
-----------------------------
:mod:`samplers` Module
----------------------
.. automodule:: GPy.inference.samplers
:members:
:undoc-members:
:show-inheritance:
GPy.inference.scg module
------------------------
:mod:`scg` Module
-----------------
.. automodule:: GPy.inference.scg
:members:
:undoc-members:
:show-inheritance:
GPy.inference.sgd module
------------------------
:mod:`sgd` Module
-----------------
.. automodule:: GPy.inference.sgd
:members:
:undoc-members:
:show-inheritance:
Module contents
---------------
.. automodule:: GPy.inference
:members:
:undoc-members:
:show-inheritance:

161
doc/GPy.kern.parts.rst
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@ -1,262 +1,275 @@
GPy.kern.parts package
======================
parts Package
=============
Submodules
----------
:mod:`parts` Package
--------------------
GPy.kern.parts.Brownian module
------------------------------
.. automodule:: GPy.kern.parts
:members:
:undoc-members:
:show-inheritance:
:mod:`Brownian` Module
----------------------
.. automodule:: GPy.kern.parts.Brownian
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.Matern32 module
------------------------------
:mod:`Matern32` Module
----------------------
.. automodule:: GPy.kern.parts.Matern32
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.Matern52 module
------------------------------
:mod:`Matern52` Module
----------------------
.. automodule:: GPy.kern.parts.Matern52
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.ODE_1 module
---------------------------
:mod:`ODE_1` Module
-------------------
.. automodule:: GPy.kern.parts.ODE_1
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.bias module
--------------------------
:mod:`ODE_UY` Module
--------------------
.. automodule:: GPy.kern.parts.ODE_UY
:members:
:undoc-members:
:show-inheritance:
:mod:`bias` Module
------------------
.. automodule:: GPy.kern.parts.bias
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.coregionalize module
-----------------------------------
:mod:`coregionalize` Module
---------------------------
.. automodule:: GPy.kern.parts.coregionalize
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.eq_ode1 module
-----------------------------
:mod:`eq_ode1` Module
---------------------
.. automodule:: GPy.kern.parts.eq_ode1
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.exponential module
---------------------------------
:mod:`exponential` Module
-------------------------
.. automodule:: GPy.kern.parts.exponential
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.finite_dimensional module
----------------------------------------
:mod:`finite_dimensional` Module
--------------------------------
.. automodule:: GPy.kern.parts.finite_dimensional
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.fixed module
---------------------------
:mod:`fixed` Module
-------------------
.. automodule:: GPy.kern.parts.fixed
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.gibbs module
---------------------------
:mod:`gibbs` Module
-------------------
.. automodule:: GPy.kern.parts.gibbs
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.hetero module
----------------------------
:mod:`hetero` Module
--------------------
.. automodule:: GPy.kern.parts.hetero
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.hierarchical module
----------------------------------
:mod:`hierarchical` Module
--------------------------
.. automodule:: GPy.kern.parts.hierarchical
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.independent_outputs module
-----------------------------------------
:mod:`independent_outputs` Module
---------------------------------
.. automodule:: GPy.kern.parts.independent_outputs
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.kernpart module
------------------------------
:mod:`kernpart` Module
----------------------
.. automodule:: GPy.kern.parts.kernpart
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.linear module
----------------------------
:mod:`linear` Module
--------------------
.. automodule:: GPy.kern.parts.linear
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.mlp module
-------------------------
:mod:`mlp` Module
-----------------
.. automodule:: GPy.kern.parts.mlp
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.periodic_Matern32 module
---------------------------------------
:mod:`periodic_Matern32` Module
-------------------------------
.. automodule:: GPy.kern.parts.periodic_Matern32
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.periodic_Matern52 module
---------------------------------------
:mod:`periodic_Matern52` Module
-------------------------------
.. automodule:: GPy.kern.parts.periodic_Matern52
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.periodic_exponential module
------------------------------------------
:mod:`periodic_exponential` Module
----------------------------------
.. automodule:: GPy.kern.parts.periodic_exponential
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.poly module
--------------------------
:mod:`poly` Module
------------------
.. automodule:: GPy.kern.parts.poly
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.prod module
--------------------------
:mod:`prod` Module
------------------
.. automodule:: GPy.kern.parts.prod
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.prod_orthogonal module
-------------------------------------
:mod:`prod_orthogonal` Module
-----------------------------
.. automodule:: GPy.kern.parts.prod_orthogonal
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.rational_quadratic module
----------------------------------------
:mod:`rational_quadratic` Module
--------------------------------
.. automodule:: GPy.kern.parts.rational_quadratic
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.rbf module
-------------------------
:mod:`rbf` Module
-----------------
.. automodule:: GPy.kern.parts.rbf
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.rbf_inv module
-----------------------------
:mod:`rbf_inv` Module
---------------------
.. automodule:: GPy.kern.parts.rbf_inv
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.rbfcos module
----------------------------
:mod:`rbfcos` Module
--------------------
.. automodule:: GPy.kern.parts.rbfcos
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.spline module
----------------------------
:mod:`spline` Module
--------------------
.. automodule:: GPy.kern.parts.spline
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.symmetric module
-------------------------------
:mod:`symmetric` Module
-----------------------
.. automodule:: GPy.kern.parts.symmetric
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.sympykern module
-------------------------------
:mod:`sympy_helpers` Module
---------------------------
.. automodule:: GPy.kern.parts.sympy_helpers
:members:
:undoc-members:
:show-inheritance:
:mod:`sympykern` Module
-----------------------
.. automodule:: GPy.kern.parts.sympykern
:members:
:undoc-members:
:show-inheritance:
GPy.kern.parts.white module
---------------------------
:mod:`white` Module
-------------------
.. automodule:: GPy.kern.parts.white
:members:
:undoc-members:
:show-inheritance:
Module contents
---------------
.. automodule:: GPy.kern.parts
:members:
:undoc-members:
:show-inheritance:

55
doc/GPy.kern.rst
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@ -1,5 +1,29 @@
GPy.kern package
================
kern Package
============
:mod:`kern` Package
-------------------
.. automodule:: GPy.kern
:members:
:undoc-members:
:show-inheritance:
:mod:`constructors` Module
--------------------------
.. automodule:: GPy.kern.constructors
:members:
:undoc-members:
:show-inheritance:
:mod:`kern` Module
------------------
.. automodule:: GPy.kern.kern
:members:
:undoc-members:
:show-inheritance:
Subpackages
-----------
@ -8,30 +32,3 @@ Subpackages
GPy.kern.parts
Submodules
----------
GPy.kern.constructors module
----------------------------
.. automodule:: GPy.kern.constructors
:members:
:undoc-members:
:show-inheritance:
GPy.kern.kern module
--------------------
.. automodule:: GPy.kern.kern
:members:
:undoc-members:
:show-inheritance:
Module contents
---------------
.. automodule:: GPy.kern
:members:
:undoc-members:
:show-inheritance:

53
doc/GPy.likelihoods.noise_models.rst
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@ -1,78 +1,75 @@
GPy.likelihoods.noise_models package
====================================
noise_models Package
====================
Submodules
----------
:mod:`noise_models` Package
---------------------------
GPy.likelihoods.noise_models.bernoulli_noise module
---------------------------------------------------
.. automodule:: GPy.likelihoods.noise_models
:members:
:undoc-members:
:show-inheritance:
:mod:`bernoulli_noise` Module
-----------------------------
.. automodule:: GPy.likelihoods.noise_models.bernoulli_noise
:members:
:undoc-members:
:show-inheritance:
GPy.likelihoods.noise_models.exponential_noise module
-----------------------------------------------------
:mod:`exponential_noise` Module
-------------------------------
.. automodule:: GPy.likelihoods.noise_models.exponential_noise
:members:
:undoc-members:
:show-inheritance:
GPy.likelihoods.noise_models.gamma_noise module
-----------------------------------------------
:mod:`gamma_noise` Module
-------------------------
.. automodule:: GPy.likelihoods.noise_models.gamma_noise
:members:
:undoc-members:
:show-inheritance:
GPy.likelihoods.noise_models.gaussian_noise module
--------------------------------------------------
:mod:`gaussian_noise` Module
----------------------------
.. automodule:: GPy.likelihoods.noise_models.gaussian_noise
:members:
:undoc-members:
:show-inheritance:
GPy.likelihoods.noise_models.gp_transformations module
------------------------------------------------------
:mod:`gp_transformations` Module
--------------------------------
.. automodule:: GPy.likelihoods.noise_models.gp_transformations
:members:
:undoc-members:
:show-inheritance:
GPy.likelihoods.noise_models.noise_distributions module
-------------------------------------------------------
:mod:`noise_distributions` Module
---------------------------------
.. automodule:: GPy.likelihoods.noise_models.noise_distributions
:members:
:undoc-members:
:show-inheritance:
GPy.likelihoods.noise_models.poisson_noise module
-------------------------------------------------
:mod:`poisson_noise` Module
---------------------------
.. automodule:: GPy.likelihoods.noise_models.poisson_noise
:members:
:undoc-members:
:show-inheritance:
GPy.likelihoods.noise_models.student_t_noise module
---------------------------------------------------
:mod:`student_t_noise` Module
-----------------------------
.. automodule:: GPy.likelihoods.noise_models.student_t_noise
:members:
:undoc-members:
:show-inheritance:
Module contents
---------------
.. automodule:: GPy.likelihoods.noise_models
:members:
:undoc-members:
:show-inheritance:

135
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@ -1,5 +1,69 @@
GPy.likelihoods package
=======================
likelihoods Package
===================
:mod:`likelihoods` Package
--------------------------
.. automodule:: GPy.likelihoods
:members:
:undoc-members:
:show-inheritance:
:mod:`ep` Module
----------------
.. automodule:: GPy.likelihoods.ep
:members:
:undoc-members:
:show-inheritance:
:mod:`ep_mixed_noise` Module
----------------------------
.. automodule:: GPy.likelihoods.ep_mixed_noise
:members:
:undoc-members:
:show-inheritance:
:mod:`gaussian` Module
----------------------
.. automodule:: GPy.likelihoods.gaussian
:members:
:undoc-members:
:show-inheritance:
:mod:`gaussian_mixed_noise` Module
----------------------------------
.. automodule:: GPy.likelihoods.gaussian_mixed_noise
:members:
:undoc-members:
:show-inheritance:
:mod:`laplace` Module
---------------------
.. automodule:: GPy.likelihoods.laplace
:members:
:undoc-members:
:show-inheritance:
:mod:`likelihood` Module
------------------------
.. automodule:: GPy.likelihoods.likelihood
:members:
:undoc-members:
:show-inheritance:
:mod:`noise_model_constructors` Module
--------------------------------------
.. automodule:: GPy.likelihoods.noise_model_constructors
:members:
:undoc-members:
:show-inheritance:
Subpackages
-----------
@ -8,70 +72,3 @@ Subpackages
GPy.likelihoods.noise_models
Submodules
----------
GPy.likelihoods.ep module
-------------------------
.. automodule:: GPy.likelihoods.ep
:members:
:undoc-members:
:show-inheritance:
GPy.likelihoods.ep_mixed_noise module
-------------------------------------
.. automodule:: GPy.likelihoods.ep_mixed_noise
:members:
:undoc-members:
:show-inheritance:
GPy.likelihoods.gaussian module
-------------------------------
.. automodule:: GPy.likelihoods.gaussian
:members:
:undoc-members:
:show-inheritance:
GPy.likelihoods.gaussian_mixed_noise module
-------------------------------------------
.. automodule:: GPy.likelihoods.gaussian_mixed_noise
:members:
:undoc-members:
:show-inheritance:
GPy.likelihoods.laplace module
------------------------------
.. automodule:: GPy.likelihoods.laplace
:members:
:undoc-members:
:show-inheritance:
GPy.likelihoods.likelihood module
---------------------------------
.. automodule:: GPy.likelihoods.likelihood
:members:
:undoc-members:
:show-inheritance:
GPy.likelihoods.noise_model_constructors module
-----------------------------------------------
.. automodule:: GPy.likelihoods.noise_model_constructors
:members:
:undoc-members:
:show-inheritance:
Module contents
---------------
.. automodule:: GPy.likelihoods
:members:
:undoc-members:
:show-inheritance:

33
doc/GPy.mappings.rst
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@ -1,38 +1,35 @@
GPy.mappings package
====================
mappings Package
================
Submodules
----------
:mod:`mappings` Package
-----------------------
GPy.mappings.kernel module
--------------------------
.. automodule:: GPy.mappings
:members:
:undoc-members:
:show-inheritance:
:mod:`kernel` Module
--------------------
.. automodule:: GPy.mappings.kernel
:members:
:undoc-members:
:show-inheritance:
GPy.mappings.linear module
--------------------------
:mod:`linear` Module
--------------------
.. automodule:: GPy.mappings.linear
:members:
:undoc-members:
:show-inheritance:
GPy.mappings.mlp module
-----------------------
:mod:`mlp` Module
-----------------
.. automodule:: GPy.mappings.mlp
:members:
:undoc-members:
:show-inheritance:
Module contents
---------------
.. automodule:: GPy.mappings
:members:
:undoc-members:
:show-inheritance:

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@ -1,134 +0,0 @@
GPy.models package
==================
Submodules
----------
GPy.models.bayesian_gplvm module
--------------------------------
.. automodule:: GPy.models.bayesian_gplvm
:members:
:undoc-members:
:show-inheritance:
GPy.models.bcgplvm module
-------------------------
.. automodule:: GPy.models.bcgplvm
:members:
:undoc-members:
:show-inheritance:
GPy.models.fitc_classification module
-------------------------------------
.. automodule:: GPy.models.fitc_classification
:members:
:undoc-members:
:show-inheritance:
GPy.models.gp_classification module
-----------------------------------
.. automodule:: GPy.models.gp_classification
:members:
:undoc-members:
:show-inheritance:
GPy.models.gp_multioutput_regression module
-------------------------------------------
.. automodule:: GPy.models.gp_multioutput_regression
:members:
:undoc-members:
:show-inheritance:
GPy.models.gp_regression module
-------------------------------
.. automodule:: GPy.models.gp_regression
:members:
:undoc-members:
:show-inheritance:
GPy.models.gplvm module
-----------------------
.. automodule:: GPy.models.gplvm
:members:
:undoc-members:
:show-inheritance:
GPy.models.gradient_checker module
----------------------------------
.. automodule:: GPy.models.gradient_checker
:members:
:undoc-members:
:show-inheritance:
GPy.models.mrd module
---------------------
.. automodule:: GPy.models.mrd
:members:
:undoc-members:
:show-inheritance:
GPy.models.sparse_gp_classification module
------------------------------------------
.. automodule:: GPy.models.sparse_gp_classification
:members:
:undoc-members:
:show-inheritance:
GPy.models.sparse_gp_multioutput_regression module
--------------------------------------------------
.. automodule:: GPy.models.sparse_gp_multioutput_regression
:members:
:undoc-members:
:show-inheritance:
GPy.models.sparse_gp_regression module
--------------------------------------
.. automodule:: GPy.models.sparse_gp_regression
:members:
:undoc-members:
:show-inheritance:
GPy.models.sparse_gplvm module
------------------------------
.. automodule:: GPy.models.sparse_gplvm
:members:
:undoc-members:
:show-inheritance:
GPy.models.svigp_regression module
----------------------------------
.. automodule:: GPy.models.svigp_regression
:members:
:undoc-members:
:show-inheritance:
GPy.models.warped_gp module
---------------------------
.. automodule:: GPy.models.warped_gp
:members:
:undoc-members:
:show-inheritance:
Module contents
---------------
.. automodule:: GPy.models
:members:
:undoc-members:
:show-inheritance:

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@ -0,0 +1,131 @@
models_modules Package
======================
:mod:`models_modules` Package
-----------------------------
.. automodule:: GPy.models_modules
:members:
:undoc-members:
:show-inheritance:
:mod:`bayesian_gplvm` Module
----------------------------
.. automodule:: GPy.models_modules.bayesian_gplvm
:members:
:undoc-members:
:show-inheritance:
:mod:`bcgplvm` Module
---------------------
.. automodule:: GPy.models_modules.bcgplvm
:members:
:undoc-members:
:show-inheritance:
:mod:`fitc_classification` Module
---------------------------------
.. automodule:: GPy.models_modules.fitc_classification
:members:
:undoc-members:
:show-inheritance:
:mod:`gp_classification` Module
-------------------------------
.. automodule:: GPy.models_modules.gp_classification
:members:
:undoc-members:
:show-inheritance:
:mod:`gp_multioutput_regression` Module
---------------------------------------
.. automodule:: GPy.models_modules.gp_multioutput_regression
:members:
:undoc-members:
:show-inheritance:
:mod:`gp_regression` Module
---------------------------
.. automodule:: GPy.models_modules.gp_regression
:members:
:undoc-members:
:show-inheritance:
:mod:`gplvm` Module
-------------------
.. automodule:: GPy.models_modules.gplvm
:members:
:undoc-members:
:show-inheritance:
:mod:`gradient_checker` Module
------------------------------
.. automodule:: GPy.models_modules.gradient_checker
:members:
:undoc-members:
:show-inheritance:
:mod:`mrd` Module
-----------------
.. automodule:: GPy.models_modules.mrd
:members:
:undoc-members:
:show-inheritance:
:mod:`sparse_gp_classification` Module
--------------------------------------
.. automodule:: GPy.models_modules.sparse_gp_classification
:members:
:undoc-members:
:show-inheritance:
:mod:`sparse_gp_multioutput_regression` Module
----------------------------------------------
.. automodule:: GPy.models_modules.sparse_gp_multioutput_regression
:members:
:undoc-members:
:show-inheritance:
:mod:`sparse_gp_regression` Module
----------------------------------
.. automodule:: GPy.models_modules.sparse_gp_regression
:members:
:undoc-members:
:show-inheritance:
:mod:`sparse_gplvm` Module
--------------------------
.. automodule:: GPy.models_modules.sparse_gplvm
:members:
:undoc-members:
:show-inheritance:
:mod:`svigp_regression` Module
------------------------------
.. automodule:: GPy.models_modules.svigp_regression
:members:
:undoc-members:
:show-inheritance:
:mod:`warped_gp` Module
-----------------------
.. automodule:: GPy.models_modules.warped_gp
:members:
:undoc-members:
:show-inheritance:

27
doc/GPy.rst
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@ -1,6 +1,22 @@
GPy package
GPy Package
===========
:mod:`GPy` Package
------------------
.. automodule:: GPy.__init__
:members:
:undoc-members:
:show-inheritance:
:mod:`models` Module
--------------------
.. automodule:: GPy.models
:members:
:undoc-members:
:show-inheritance:
Subpackages
-----------
@ -12,14 +28,7 @@ Subpackages
GPy.kern
GPy.likelihoods
GPy.mappings
GPy.models
GPy.models_modules
GPy.testing
GPy.util
Module contents
---------------
.. automodule:: GPy
:members:
:undoc-members:
:show-inheritance:

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doc/GPy.testing.rst
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@ -1,134 +1,131 @@
GPy.testing package
===================
testing Package
===============
Submodules
----------
:mod:`testing` Package
----------------------
GPy.testing.bcgplvm_tests module
--------------------------------
.. automodule:: GPy.testing
:members:
:undoc-members:
:show-inheritance:
:mod:`bcgplvm_tests` Module
---------------------------
.. automodule:: GPy.testing.bcgplvm_tests
:members:
:undoc-members:
:show-inheritance:
GPy.testing.bgplvm_tests module
-------------------------------
:mod:`bgplvm_tests` Module
--------------------------
.. automodule:: GPy.testing.bgplvm_tests
:members:
:undoc-members:
:show-inheritance:
GPy.testing.cgd_tests module
----------------------------
:mod:`cgd_tests` Module
-----------------------
.. automodule:: GPy.testing.cgd_tests
:members:
:undoc-members:
:show-inheritance:
GPy.testing.examples_tests module
---------------------------------
:mod:`examples_tests` Module
----------------------------
.. automodule:: GPy.testing.examples_tests
:members:
:undoc-members:
:show-inheritance:
GPy.testing.gp_transformation_tests module
------------------------------------------
:mod:`gp_transformation_tests` Module
-------------------------------------
.. automodule:: GPy.testing.gp_transformation_tests
:members:
:undoc-members:
:show-inheritance:
GPy.testing.gplvm_tests module
------------------------------
:mod:`gplvm_tests` Module
-------------------------
.. automodule:: GPy.testing.gplvm_tests
:members:
:undoc-members:
:show-inheritance:
GPy.testing.kernel_tests module
-------------------------------
:mod:`kernel_tests` Module
--------------------------
.. automodule:: GPy.testing.kernel_tests
:members:
:undoc-members:
:show-inheritance:
GPy.testing.likelihoods_tests module
------------------------------------
:mod:`likelihoods_tests` Module
-------------------------------
.. automodule:: GPy.testing.likelihoods_tests
:members:
:undoc-members:
:show-inheritance:
GPy.testing.mapping_tests module
--------------------------------
:mod:`mapping_tests` Module
---------------------------
.. automodule:: GPy.testing.mapping_tests
:members:
:undoc-members:
:show-inheritance:
GPy.testing.mrd_tests module
----------------------------
:mod:`mrd_tests` Module
-----------------------
.. automodule:: GPy.testing.mrd_tests
:members:
:undoc-members:
:show-inheritance:
GPy.testing.prior_tests module
------------------------------
:mod:`prior_tests` Module
-------------------------
.. automodule:: GPy.testing.prior_tests
:members:
:undoc-members:
:show-inheritance:
GPy.testing.psi_stat_expectation_tests module
---------------------------------------------
:mod:`psi_stat_expectation_tests` Module
----------------------------------------
.. automodule:: GPy.testing.psi_stat_expectation_tests
:members:
:undoc-members:
:show-inheritance:
GPy.testing.psi_stat_gradient_tests module
------------------------------------------
:mod:`psi_stat_gradient_tests` Module
-------------------------------------
.. automodule:: GPy.testing.psi_stat_gradient_tests
:members:
:undoc-members:
:show-inheritance:
GPy.testing.sparse_gplvm_tests module
-------------------------------------
:mod:`sparse_gplvm_tests` Module
--------------------------------
.. automodule:: GPy.testing.sparse_gplvm_tests
:members:
:undoc-members:
:show-inheritance:
GPy.testing.unit_tests module
-----------------------------
:mod:`unit_tests` Module
------------------------
.. automodule:: GPy.testing.unit_tests
:members:
:undoc-members:
:show-inheritance:
Module contents
---------------
.. automodule:: GPy.testing
:members:
:undoc-members:
:show-inheritance:

29
doc/GPy.util.latent_space_visualizations.controllers.rst
View file

@ -1,30 +1,27 @@
GPy.util.latent_space_visualizations.controllers package
========================================================
controllers Package
===================
Submodules
----------
:mod:`controllers` Package
--------------------------
GPy.util.latent_space_visualizations.controllers.axis_event_controller module
-----------------------------------------------------------------------------
.. automodule:: GPy.util.latent_space_visualizations.controllers
:members:
:undoc-members:
:show-inheritance:
:mod:`axis_event_controller` Module
-----------------------------------
.. automodule:: GPy.util.latent_space_visualizations.controllers.axis_event_controller
:members:
:undoc-members:
:show-inheritance:
GPy.util.latent_space_visualizations.controllers.imshow_controller module
-------------------------------------------------------------------------
:mod:`imshow_controller` Module
-------------------------------
.. automodule:: GPy.util.latent_space_visualizations.controllers.imshow_controller
:members:
:undoc-members:
:show-inheritance:
Module contents
---------------
.. automodule:: GPy.util.latent_space_visualizations.controllers
:members:
:undoc-members:
:show-inheritance:

20
doc/GPy.util.latent_space_visualizations.rst
View file

@ -1,5 +1,13 @@
GPy.util.latent_space_visualizations package
============================================
latent_space_visualizations Package
===================================
:mod:`latent_space_visualizations` Package
------------------------------------------
.. automodule:: GPy.util.latent_space_visualizations
:members:
:undoc-members:
:show-inheritance:
Subpackages
-----------
@ -7,11 +15,5 @@ Subpackages
.. toctree::
GPy.util.latent_space_visualizations.controllers
GPy.util.latent_space_visualizations.views
Module contents
---------------
.. automodule:: GPy.util.latent_space_visualizations
:members:
:undoc-members:
:show-inheritance:

343
doc/GPy.util.rst
View file

@ -1,5 +1,181 @@
GPy.util package
================
util Package
============
:mod:`util` Package
-------------------
.. automodule:: GPy.util
:members:
:undoc-members:
:show-inheritance:
:mod:`Tango` Module
-------------------
.. automodule:: GPy.util.Tango
:members:
:undoc-members:
:show-inheritance:
:mod:`block_matrices` Module
----------------------------
.. automodule:: GPy.util.block_matrices
:members:
:undoc-members:
:show-inheritance:
:mod:`classification` Module
----------------------------
.. automodule:: GPy.util.classification
:members:
:undoc-members:
:show-inheritance:
:mod:`config` Module
--------------------
.. automodule:: GPy.util.config
:members:
:undoc-members:
:show-inheritance:
:mod:`datasets` Module
----------------------
.. automodule:: GPy.util.datasets
:members:
:undoc-members:
:show-inheritance:
:mod:`decorators` Module
------------------------
.. automodule:: GPy.util.decorators
:members:
:undoc-members:
:show-inheritance:
:mod:`erfcx` Module
-------------------
.. automodule:: GPy.util.erfcx
:members:
:undoc-members:
:show-inheritance:
:mod:`linalg` Module
--------------------
.. automodule:: GPy.util.linalg
:members:
:undoc-members:
:show-inheritance:
:mod:`ln_diff_erfs` Module
--------------------------
.. automodule:: GPy.util.ln_diff_erfs
:members:
:undoc-members:
:show-inheritance:
:mod:`misc` Module
------------------
.. automodule:: GPy.util.misc
:members:
:undoc-members:
:show-inheritance:
:mod:`mocap` Module
-------------------
.. automodule:: GPy.util.mocap
:members:
:undoc-members:
:show-inheritance:
:mod:`multioutput` Module
-------------------------
.. automodule:: GPy.util.multioutput
:members:
:undoc-members:
:show-inheritance:
:mod:`netpbmfile` Module
------------------------
.. automodule:: GPy.util.netpbmfile
:members:
:undoc-members:
:show-inheritance:
:mod:`pca` Module
-----------------
.. automodule:: GPy.util.pca
:members:
:undoc-members:
:show-inheritance:
:mod:`plot` Module
------------------
.. automodule:: GPy.util.plot
:members:
:undoc-members:
:show-inheritance:
:mod:`plot_latent` Module
-------------------------
.. automodule:: GPy.util.plot_latent
:members:
:undoc-members:
:show-inheritance:
:mod:`squashers` Module
-----------------------
.. automodule:: GPy.util.squashers
:members:
:undoc-members:
:show-inheritance:
:mod:`symbolic` Module
----------------------
.. automodule:: GPy.util.symbolic
:members:
:undoc-members:
:show-inheritance:
:mod:`univariate_Gaussian` Module
---------------------------------
.. automodule:: GPy.util.univariate_Gaussian
:members:
:undoc-members:
:show-inheritance:
:mod:`visualize` Module
-----------------------
.. automodule:: GPy.util.visualize
:members:
:undoc-members:
:show-inheritance:
:mod:`warping_functions` Module
-------------------------------
.. automodule:: GPy.util.warping_functions
:members:
:undoc-members:
:show-inheritance:
Subpackages
-----------
@ -8,166 +184,3 @@ Subpackages
GPy.util.latent_space_visualizations
Submodules
----------
GPy.util.Tango module
---------------------
.. automodule:: GPy.util.Tango
:members:
:undoc-members:
:show-inheritance:
GPy.util.classification module
------------------------------
.. automodule:: GPy.util.classification
:members:
:undoc-members:
:show-inheritance:
GPy.util.config module
----------------------
.. automodule:: GPy.util.config
:members:
:undoc-members:
:show-inheritance:
GPy.util.datasets module
------------------------
.. automodule:: GPy.util.datasets
:members:
:undoc-members:
:show-inheritance:
GPy.util.decorators module
--------------------------
.. automodule:: GPy.util.decorators
:members:
:undoc-members:
:show-inheritance:
GPy.util.erfcx module
---------------------
.. automodule:: GPy.util.erfcx
:members:
:undoc-members:
:show-inheritance:
GPy.util.linalg module
----------------------
.. automodule:: GPy.util.linalg
:members:
:undoc-members:
:show-inheritance:
GPy.util.ln_diff_erfs module
----------------------------
.. automodule:: GPy.util.ln_diff_erfs
:members:
:undoc-members:
:show-inheritance:
GPy.util.misc module
--------------------
.. automodule:: GPy.util.misc
:members:
:undoc-members:
:show-inheritance:
GPy.util.mocap module
---------------------
.. automodule:: GPy.util.mocap
:members:
:undoc-members:
:show-inheritance:
GPy.util.multioutput module
---------------------------
.. automodule:: GPy.util.multioutput
:members:
:undoc-members:
:show-inheritance:
GPy.util.netpbmfile module
--------------------------
.. automodule:: GPy.util.netpbmfile
:members:
:undoc-members:
:show-inheritance:
GPy.util.plot module
--------------------
.. automodule:: GPy.util.plot
:members:
:undoc-members:
:show-inheritance:
GPy.util.plot_latent module
---------------------------
.. automodule:: GPy.util.plot_latent
:members:
:undoc-members:
:show-inheritance:
GPy.util.squashers module
-------------------------
.. automodule:: GPy.util.squashers
:members:
:undoc-members:
:show-inheritance:
GPy.util.symbolic module
------------------------
.. automodule:: GPy.util.symbolic
:members:
:undoc-members:
:show-inheritance:
GPy.util.univariate_Gaussian module
-----------------------------------
.. automodule:: GPy.util.univariate_Gaussian
:members:
:undoc-members:
:show-inheritance:
GPy.util.visualize module
-------------------------
.. automodule:: GPy.util.visualize
:members:
:undoc-members:
:show-inheritance:
GPy.util.warping_functions module
---------------------------------
.. automodule:: GPy.util.warping_functions
:members:
:undoc-members:
:show-inheritance:
Module contents
---------------
.. automodule:: GPy.util
:members:
:undoc-members:
:show-inheritance:

3
doc/index.rst
View file

@ -15,6 +15,9 @@ For a quick start, you can have a look at one of the tutorials:
You may also be interested by some examples in the GPy/examples folder.
The detailed Developers Documentation is listed below
=====================================================
Contents:
.. toctree::

2
setup.py
View file

@ -18,7 +18,7 @@ setup(name = 'GPy',
license = "BSD 3-clause",
keywords = "machine-learning gaussian-processes kernels",
url = "http://sheffieldml.github.com/GPy/",
packages = ['GPy', 'GPy.core', 'GPy.kern', 'GPy.util', 'GPy._models', 'GPy.inference', 'GPy.examples', 'GPy.likelihoods', 'GPy.testing', 'GPy.util.latent_space_visualizations', 'GPy.util.latent_space_visualizations.controllers', 'GPy.likelihoods.noise_models', 'GPy.kern.parts', 'GPy.mappings'],
packages = ['GPy', 'GPy.core', 'GPy.kern', 'GPy.util', 'GPy.models_modules', 'GPy.inference', 'GPy.examples', 'GPy.likelihoods', 'GPy.testing', 'GPy.util.latent_space_visualizations', 'GPy.util.latent_space_visualizations.controllers', 'GPy.likelihoods.noise_models', 'GPy.kern.parts', 'GPy.mappings'],
package_dir={'GPy': 'GPy'},
package_data = {'GPy': ['GPy/examples', 'gpy_config.cfg']},
py_modules = ['GPy.__init__'],