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Merge branch 'master' of github.com:SheffieldML/GPy

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Alan Saul 2013-03-11 12:41:15 +00:00
commit 71c47cceee
10 changed files with 83 additions and 34 deletions
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7
GPy/__init__.py
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@ -9,3 +9,10 @@ import util
import examples
from core import priors
import likelihoods
import testing
from numpy.testing import Tester
from nose.tools import nottest
@nottest
def tests():
Tester(testing).test(verbose=10)

3
GPy/testing/bgplvm_tests.py
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@ -12,6 +12,7 @@ class BGPLVMTests(unittest.TestCase):
k = GPy.kern.rbf(Q) + GPy.kern.white(Q, 0.00001)
K = k.K(X)
Y = np.random.multivariate_normal(np.zeros(N),K,D).T
Y -= Y.mean(axis=0)
k = GPy.kern.bias(Q) + GPy.kern.white(Q, 0.00001)
m = GPy.models.Bayesian_GPLVM(Y, Q, kernel = k, M=M)
m.constrain_positive('(rbf|bias|noise|white|S)')
@ -24,6 +25,7 @@ class BGPLVMTests(unittest.TestCase):
k = GPy.kern.rbf(Q) + GPy.kern.white(Q, 0.00001)
K = k.K(X)
Y = np.random.multivariate_normal(np.zeros(N),K,D).T
Y -= Y.mean(axis=0)
k = GPy.kern.linear(Q) + GPy.kern.white(Q, 0.00001)
m = GPy.models.Bayesian_GPLVM(Y, Q, kernel = k, M=M)
m.constrain_positive('(linear|bias|noise|white|S)')
@ -36,6 +38,7 @@ class BGPLVMTests(unittest.TestCase):
k = GPy.kern.rbf(Q) + GPy.kern.white(Q, 0.00001)
K = k.K(X)
Y = np.random.multivariate_normal(np.zeros(N),K,D).T
Y -= Y.mean(axis=0)
k = GPy.kern.rbf(Q) + GPy.kern.white(Q, 0.00001)
m = GPy.models.Bayesian_GPLVM(Y, Q, kernel = k, M=M)
m.constrain_positive('(rbf|bias|noise|white|S)')

1
GPy/testing/kernel_tests.py
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@ -13,7 +13,6 @@ class KernelTests(unittest.TestCase):
X = np.random.rand(5,5)
Y = np.ones((5,1))
m = GPy.models.GP_regression(X,Y,K)
print m
self.assertTrue(m.checkgrad())
def test_coregionalisation(self):

11
GPy/testing/unit_tests.py
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@ -192,17 +192,6 @@ class GradientTests(unittest.TestCase):
m.approximate_likelihood()
self.assertTrue(m.checkgrad())
def test_warped_GP(self):
xmin, xmax = 1, 2.5*np.pi
b, C, SNR = 1, 0, 0.1
X = np.linspace(xmin, xmax, 500)
y = b*X + C + 1*np.sin(X)
y += 0.05*np.random.randn(len(X))
X, y = X[:, None], y[:, None]
m = GPy.models.warpedGP(X, y, warping_terms = 3)
m.constrain_positive('(tanh_a|tanh_b|rbf|white|bias)')
self.assertTrue(m.checkgrad())
if __name__ == "__main__":
print "Running unit tests, please be (very) patient..."

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16
doc/GPy.examples.rst
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@ -73,6 +73,22 @@ examples Package
:undoc-members:
:show-inheritance:
:mod:`tuto_GP_regression` Module
--------------------------------
.. automodule:: GPy.examples.tuto_GP_regression
:members:
:undoc-members:
:show-inheritance:
:mod:`tuto_kernel_overview` Module
----------------------------------
.. automodule:: GPy.examples.tuto_kernel_overview
:members:
:undoc-members:
:show-inheritance:
:mod:`uncertain_input_GP_regression_demo` Module
------------------------------------------------

28
doc/GPy.kern.rst
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@ -49,6 +49,14 @@ kern Package
:undoc-members:
:show-inheritance:
:mod:`coregionalise` Module
---------------------------
.. automodule:: GPy.kern.coregionalise
:members:
:undoc-members:
:show-inheritance:
:mod:`exponential` Module
-------------------------
@ -113,18 +121,18 @@ kern Package
:undoc-members:
:show-inheritance:
:mod:`product` Module
---------------------
:mod:`prod` Module
------------------
.. automodule:: GPy.kern.product
.. automodule:: GPy.kern.prod
:members:
:undoc-members:
:show-inheritance:
:mod:`product_orthogonal` Module
--------------------------------
:mod:`prod_orthogonal` Module
-----------------------------
.. automodule:: GPy.kern.product_orthogonal
.. automodule:: GPy.kern.prod_orthogonal
:members:
:undoc-members:
:show-inheritance:
@ -145,6 +153,14 @@ kern Package
:undoc-members:
:show-inheritance:
:mod:`symmetric` Module
-----------------------
.. automodule:: GPy.kern.symmetric
:members:
:undoc-members:
:show-inheritance:
:mod:`sympykern` Module
-----------------------

41
doc/kernel_implementation.rst
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@ -3,15 +3,36 @@
List of implemented kernels
***************************
The :math:`\checkmark` symbol represents the functions that have been implemented for each kernel.
The following table shows the implemented kernels in GPy and gives the details of the implemented function for each kernel.
.. |tick|
.. |tick| image:: tick.png
====== =========== === ======= =========== =============== ======= =========== ====== ====== =======
==================== =========== ====== ======= =========== =============== ======= =========== ====== ====== =======
NAME get/set K Kdiag dK_dtheta dKdiag_dtheta dK_dX dKdiag_dX psi0 psi1 psi2
====== =========== === ======= =========== =============== ======= =========== ====== ====== =======
rbf \\checkmark y
====== =========== === ======= =========== =============== ======= =========== ====== ====== =======
==================== =========== ====== ======= =========== =============== ======= =========== ====== ====== =======
bias |tick| |tick| |tick| |tick| |tick| |tick| |tick| |tick| |tick| |tick|
-------------------- ----------- ------ ------- ----------- --------------- ------- ----------- ------ ------ -------
Brownian |tick| |tick| |tick| |tick| |tick| |tick| |tick|
-------------------- ----------- ------ ------- ----------- --------------- ------- ----------- ------ ------ -------
exponential |tick| |tick| |tick| |tick| |tick| |tick| |tick|
-------------------- ----------- ------ ------- ----------- --------------- ------- ----------- ------ ------ -------
finite_dimensional |tick| |tick| |tick| |tick| |tick|
-------------------- ----------- ------ ------- ----------- --------------- ------- ----------- ------ ------ -------
linear |tick| |tick| |tick| |tick| |tick| |tick| |tick| |tick| |tick|
-------------------- ----------- ------ ------- ----------- --------------- ------- ----------- ------ ------ -------
Matern32 |tick| |tick| |tick| |tick| |tick| |tick| |tick|
-------------------- ----------- ------ ------- ----------- --------------- ------- ----------- ------ ------ -------
Matern52 |tick| |tick| |tick| |tick| |tick| |tick| |tick|
-------------------- ----------- ------ ------- ----------- --------------- ------- ----------- ------ ------ -------
periodic_exponential |tick| |tick| |tick| |tick| |tick|
-------------------- ----------- ------ ------- ----------- --------------- ------- ----------- ------ ------ -------
periodic_Matern32 |tick| |tick| |tick| |tick| |tick|
-------------------- ----------- ------ ------- ----------- --------------- ------- ----------- ------ ------ -------
periodic_Matern52 |tick| |tick| |tick| |tick| |tick|
-------------------- ----------- ------ ------- ----------- --------------- ------- ----------- ------ ------ -------
rbf |tick| |tick| |tick| |tick| |tick| |tick| |tick| |tick| |tick| |tick|
-------------------- ----------- ------ ------- ----------- --------------- ------- ----------- ------ ------ -------
spline |tick| |tick| |tick| |tick| |tick| |tick|
-------------------- ----------- ------ ------- ----------- --------------- ------- ----------- ------ ------ -------
white |tick| |tick| |tick| |tick| |tick| |tick| |tick| |tick| |tick| |tick|
==================== =========== ====== ======= =========== =============== ======= =========== ====== ====== =======
.. |tick| image:: Figures/tick.png

2
doc/tuto_kernel_overview.rst
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@ -39,7 +39,7 @@ return::
Implemented kernels
===================
Many kernels are already implemented in GPy. A comprehensive list can be found `here <kernel_implementation.html>`_ . The following figure gives a summary of most of them:
Many kernels are already implemented in GPy. A comprehensive list can be found `here <kernel_implementation.html>`_ and the following figure gives a summary of most of them:
.. figure:: Figures/tuto_kern_overview_allkern.png
:align: center

6
setup.py
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@ -3,8 +3,6 @@
import os
from setuptools import setup
#from numpy.distutils.core import Extension, setup
#from sphinx.setup_command import BuildDoc
# Version number
version = '0.1.3'
@ -14,12 +12,12 @@ def read(fname):
setup(name = 'GPy',
version = version,
author = 'James Hensman, Nicolo Fusi, Ricardo Andrade, Nicolas Durrande, Alan Saul, Neil D. Lawrence',
author = read('AUTHORS.txt'),
author_email = "james.hensman@gmail.com",
description = ("The Gaussian Process Toolbox"),
license = "BSD 3-clause",
keywords = "machine-learning gaussian-processes kernels",
url = "http://ml.sheffield.ac.uk/GPy/",
url = "http://sheffieldml.github.com/GPy/",
packages = ['GPy', 'GPy.core', 'GPy.kern', 'GPy.util', 'GPy.models', 'GPy.inference', 'GPy.examples', 'GPy.likelihoods'],
package_dir={'GPy': 'GPy'},
package_data = {'GPy': ['GPy/examples']},