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added GPy.tests(), removed some useless tests

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This commit is contained in:
Nicolo Fusi 2013-03-11 12:33:03 +00:00
parent 2b7f0999bc
commit e32afa11e5
5 changed files with 11 additions and 17 deletions
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5
GPy/__init__.py
View file

@ -9,3 +9,8 @@ import util
import examples
from core import priors
import likelihoods
import testing
from numpy.testing import Tester
def tests():
Tester(testing).test(verbose=10)

5
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)')
@ -36,13 +38,14 @@ 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)')
m.randomize()
self.assertTrue(m.checkgrad())
if __name__ == "__main__":
print "Running unit tests, please be (very) patient..."
unittest.main()

1
GPy/testing/kernel_tests.py
View file

@ -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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@ -177,17 +177,6 @@ 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..."

6
setup.py
View file

@ -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']},