apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-06-14 15:25:15 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

changing all parameterized objects to be compatible with the new parameterization

Browse source
This commit is contained in:
Max Zwiessele 2013-10-25 15:29:04 +01:00
parent e1bee4536a
commit d3721b76a8
21 changed files with 645 additions and 529 deletions
Download patch file Download diff file Expand all files Collapse all files

10
GPy/testing/parameter_testing.py
View file

@ -31,10 +31,10 @@ class Test(unittest.TestCase):
self.Y = numpy.random.multivariate_normal(numpy.zeros(self.N), K + numpy.eye(self.N) * .2, self.D).T
self.bgplvm = BayesianGPLVM(Gaussian(self.Y, variance=self.noise_variance), self.Q, self.X, self.X_variance, kernel=self.kern)
self.bgplvm.ensure_default_constraints(warning=False)
self.bgplvm.tie_params("noise_variance|white_variance")
self.bgplvm.constrain_fixed("rbf_var", warning=False)
# self.bgplvm = BayesianGPLVM(Gaussian(self.Y, variance=self.noise_variance), self.Q, self.X, self.X_variance, kernel=self.kern)
# self.bgplvm.ensure_default_constraints(warning=False)
# self.bgplvm.tie_params("noise_variance|white_variance")
# self.bgplvm.constrain_fixed("rbf_var", warning=False)
self.parameter = Parameterized([
Parameterized([
Param('X', self.X),
@ -110,7 +110,7 @@ class Test(unittest.TestCase):
self.parameter[''].unconstrain()
self.parameter.X.constrain_positive()
self.parameter.X[:,numpy.s_[0::2]].unconstrain_positive()
assert(numpy.alltrue(self.parameter._constraints_.indices()[0] == numpy.r_[1:self.N*self.Q:2]))
assert(numpy.alltrue(self.parameter.constraints.indices()[0] == numpy.r_[1:self.N*self.Q:2]))
def testNdarrayFunc(self):
assert(numpy.alltrue(self.parameter.X * self.parameter.X == self.X * self.X))