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working on psi cross terms

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Nicolo Fusi 2013-03-11 14:03:23 +00:00
parent 84119a19b3
commit 05ca5cfe6d
3 changed files with 30 additions and 6 deletions
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26
GPy/testing/bgplvm_tests.py
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@ -45,6 +45,32 @@ class BGPLVMTests(unittest.TestCase):
m.randomize()
self.assertTrue(m.checkgrad())
def test_rbf_bias_kern(self):
N, M, Q, D = 10, 3, 2, 4
X = np.random.rand(N, Q)
k = GPy.kern.rbf(Q) + GPy.kern.bias(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.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)')
m.randomize()
self.assertTrue(m.checkgrad())
def test_linear_bias_kern(self):
N, M, Q, D = 10, 3, 2, 4
X = np.random.rand(N, Q)
k = GPy.kern.linear(Q) + GPy.kern.bias(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.bias(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)')
m.randomize()
self.assertTrue(m.checkgrad())
if __name__ == "__main__":
print "Running unit tests, please be (very) patient..."