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all parameters in memory

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Max Zwiessele 2014-03-10 08:21:13 +00:00
parent f7223ea377
commit 546d5dfff3
9 changed files with 135 additions and 103 deletions
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16
GPy/examples/dimensionality_reduction.py
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@ -324,14 +324,14 @@ def mrd_simulation(optimize=True, verbose=True, plot=True, plot_sim=True, **kw):
D1, D2, D3, N, num_inducing, Q = 60, 20, 36, 60, 6, 5
_, _, Ylist = _simulate_sincos(D1, D2, D3, N, num_inducing, Q, plot_sim)
likelihood_list = [Gaussian(x, normalize=True) for x in Ylist]
k = kern.Linear(Q, ARD=True) + kern.Bias(Q, _np.exp(-2)) + kern.White(Q, _np.exp(-2))
m = MRD(likelihood_list, input_dim=Q, num_inducing=num_inducing, kernels=k, initx="", initz='permute', **kw)
m.ensure_default_constraints()
for i, bgplvm in enumerate(m.bgplvms):
m['{}_noise'.format(i)] = bgplvm.likelihood.Y.var() / 500.
#Ylist = [Ylist[0]]
k = [kern.Linear(Q, ARD=True) + kern.White(Q, 1e-4) for _ in range(len(Ylist))]
m = MRD(Ylist, input_dim=Q, num_inducing=num_inducing, kernel=k, initx="", initz='permute', **kw)
m['.*noise'] = [Y.var()/500. for Y in Ylist]
#for i, Y in enumerate(Ylist):
# m['.*Y_{}.*Gaussian.*noise'.format(i)] = Y.var(1) / 500.
if optimize:
print "Optimizing Model:"