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[VarDTC] reverted SparseGP to previous state, updated BGPLVM accordingly

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This commit is contained in:
Max Zwiessele 2014-11-03 11:16:34 +00:00
parent 70afcd3ddd
commit 6b3888f163
5 changed files with 655 additions and 253 deletions
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6
GPy/testing/model_tests.py
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@ -112,7 +112,7 @@ class MiscTests(unittest.TestCase):
def test_missing_data(self):
from GPy import kern
from GPy.models import BayesianGPLVM
from GPy.models.bayesian_gplvm_minibatch import BayesianGPLVMMiniBatch
from GPy.examples.dimensionality_reduction import _simulate_matern
D1, D2, D3, N, num_inducing, Q = 13, 5, 8, 400, 3, 4
@ -124,12 +124,12 @@ class MiscTests(unittest.TestCase):
Ymissing[inan] = np.nan
k = kern.Linear(Q, ARD=True) + kern.White(Q, np.exp(-2)) # + kern.bias(Q)
m = BayesianGPLVM(Ymissing, Q, init="random", num_inducing=num_inducing,
m = BayesianGPLVMMiniBatch(Ymissing, Q, init="random", num_inducing=num_inducing,
kernel=k, missing_data=True)
assert(m.checkgrad())
k = kern.RBF(Q, ARD=True) + kern.White(Q, np.exp(-2)) # + kern.bias(Q)
m = BayesianGPLVM(Ymissing, Q, init="random", num_inducing=num_inducing,
m = BayesianGPLVMMiniBatch(Ymissing, Q, init="random", num_inducing=num_inducing,
kernel=k, missing_data=True)
assert(m.checkgrad())