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dim reduction examples clearer and init not as much black magic anymore

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This commit is contained in:
Max Zwiessele 2014-02-05 09:09:02 +00:00
parent cdd3732fce
commit dcf9c34b20
1 changed files with 4 additions and 4 deletions
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8
GPy/examples/dimensionality_reduction.py
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@ -261,12 +261,12 @@ def bgplvm_simulation(optimize=True, verbose=1,
from GPy import kern
from GPy.models import BayesianGPLVM
D1, D2, D3, N, num_inducing, Q = 15, 5, 8, 30, 3, 10
D1, D2, D3, N, num_inducing, Q = 49, 30, 10, 12, 3, 10
_, _, Ylist = _simulate_sincos(D1, D2, D3, N, num_inducing, Q, plot_sim)
Y = Ylist[0]
k = kern.linear(Q, ARD=True)
m = BayesianGPLVM(Y, Q, init="PCA", num_inducing=num_inducing, kernel=k)
m.X_variance = m.X_variance * .1
m.X_variance = m.X_variance * .7
m['noise'] = Y.var() / 100.
if optimize:
@ -292,8 +292,8 @@ def mrd_simulation(optimize=True, verbose=True, plot=True, plot_sim=True, **kw):
m.ensure_default_constraints()
for i, bgplvm in enumerate(m.bgplvms):
m['{}_noise'.format(i)] = bgplvm.likelihood.Y.var() / 500.
bgplvm.X_variance = bgplvm.X_variance * .1
m['{}_noise'.format(i)] = 1 #bgplvm.likelihood.Y.var() / 500.
bgplvm.X_variance = bgplvm.X_variance #* .1
if optimize:
print "Optimizing Model:"
m.optimize(messages=verbose, max_iters=8e3, gtol=.1)