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demo changed, bgplvm still broken

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Max Zwiessele 2013-04-18 17:59:01 +01:00
parent 865e9df255
commit 10703e4774
3 changed files with 113 additions and 92 deletions
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12
GPy/examples/dimensionality_reduction.py
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@ -170,26 +170,30 @@ def bgplvm_simulation(burnin='scg', plot_sim=False, max_f_eval=12):
from GPy import kern
reload(mrd); reload(kern)
Y = Ylist[1]
k = kern.linear(Q, ARD=True) + kern.bias(Q, .0001) + kern.white(Q, .1)
k = kern.linear(Q, ARD=True) + kern.white(Q, .00001) # + kern.bias(Q)
m = Bayesian_GPLVM(Y, Q, init="PCA", M=M, kernel=k)
m.set('noise', Y.var() / 100.)
# m.set('noise',)
# m.auto_scale_factor = True
# m.scale_factor = 1.
m.ensure_default_constraints()
if burnin:
print "initializing beta"
cstr = "noise"
m.unconstrain(cstr); m.constrain_fixed(cstr)
m.unconstrain(cstr); m.constrain_fixed(cstr, Y.var() / 100.)
m.optimize(burnin, messages=1, max_f_eval=max_f_eval)
print "releasing beta"
cstr = "noise"
m.unconstrain(cstr); m.constrain_positive(cstr)
true_X = np.hstack((slist[1], slist[3], 0. * np.ones((N, Q - 2))))
m.set('X_\d', true_X)
m.constrain_fixed("X_\d")
# # cstr = 'variance'
# # m.unconstrain(cstr), m.constrain_bounded(cstr, 1e-10, 1.)