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gradients now lazy instantiated

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Max Zwiessele 2014-02-20 08:38:14 +00:00
parent 1c3fe0c51e
commit 46f59f9f64
2 changed files with 11 additions and 3 deletions
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3
GPy/examples/dimensionality_reduction.py
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@ -296,11 +296,12 @@ def bgplvm_simulation_missing_data(optimize=True, verbose=1,
k = kern.linear(Q, ARD=True)# + kern.white(Q, _np.exp(-2)) # + kern.bias(Q)
inan = _np.random.binomial(1, .6, size=Y.shape).astype(bool)
m = BayesianGPLVM(Y, Q, init="random", num_inducing=num_inducing, kernel=k)
m = BayesianGPLVM(Y.copy(), Q, init="random", num_inducing=num_inducing, kernel=k)
m.inference_method = VarDTCMissingData()
m.Y[inan] = _np.nan
m.q.variance *= .1
m.parameters_changed()
m.Yreal = Y
if optimize:
print "Optimizing model:"