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simulation data changes

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This commit is contained in:
Max Zwiessele 2013-04-16 12:37:31 +01:00
parent 350497c726
commit aaf51f0e19
2 changed files with 29 additions and 38 deletions
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34
GPy/examples/dimensionality_reduction.py
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@ -118,13 +118,13 @@ def mrd_simulation(plot_sim=False):
# Y2 -= Y2.mean(0)
# make_params = lambda ard: np.hstack([[1], ard, [1, .3]])
D1, D2, D3, N, M, Q = 50, 100, 8, 200, 2, 5
x = np.linspace(0, 8 * np.pi, N)[:, None]
D1, D2, D3, N, M, Q = 50, 100, 8, 300, 2, 6
x = np.linspace(0, 4 * np.pi, N)[:, None]
s1 = np.vectorize(lambda x: np.sin(x))
s2 = np.vectorize(lambda x: np.cos(x))
s3 = np.vectorize(lambda x:-np.exp(-np.cos(2 * x)))
sS = np.vectorize(lambda x: x * np.sin(2 * x))
s2 = np.vectorize(lambda x: x * np.cos(x))
sS = np.vectorize(lambda x:-np.exp(-np.cos(2 * x)))
s3 = np.vectorize(lambda x: np.sin(2 * x))
s1 = s1(x)
s2 = s2(x)
@ -161,16 +161,16 @@ def mrd_simulation(plot_sim=False):
Y2 += .5 * np.random.randn(*Y2.shape)
Y3 += .5 * np.random.randn(*Y3.shape)
# Y1 -= Y1.mean(0)
# Y2 -= Y2.mean(0)
# Y3 -= Y3.mean(0)
Y1 -= Y1.mean(0)
Y2 -= Y2.mean(0)
Y3 -= Y3.mean(0)
# Y1 /= Y1.std(0)
# Y2 /= Y2.std(0)
# Y3 /= Y3.std(0)
Y1 /= Y1.std(0)
Y2 /= Y2.std(0)
Y3 /= Y3.std(0)
Slist = [s1, s2, sS]
Ylist = [Y1, Y2]
Ylist = [Y1]
if plot_sim:
import pylab
@ -190,20 +190,22 @@ def mrd_simulation(plot_sim=False):
pylab.tight_layout()
# k = kern.rbf(Q, ARD=True) + kern.bias(Q) + kern.white(Q)
k = kern.linear(Q, ARD=True) + kern.bias(Q) + kern.white(Q)
m = mrd.MRD(*Ylist, Q=Q, M=M, kernel=k, initx="concat", _debug=False)
k = kern.linear(Q, ARD=True) + kern.bias(Q, .01) + kern.white(Q, .1)
m = mrd.MRD(*Ylist, Q=Q, M=M, kernel=k, initx="concat", initz='permute', _debug=False)
m.ensure_default_constraints()
ardvar = 5. / (m.X.max(axis=0) - m.X.min(axis=0))
for i, Y in enumerate(Ylist):
m.set('{}_noise'.format(i + 1), Y.var() / 100.)
# import ipdb;ipdb.set_trace()
cstr = "variance"
m.unconstrain(cstr); m.constrain_bounded(cstr, 1e-15, 1.)
m.unconstrain(cstr); m.constrain_bounded(cstr, 1e-12, 1.)
# print "initializing beta"
# cstr = "noise"
# m.unconstrain(cstr); m.constrain_fixed(cstr)
# import ipdb;ipdb.set_trace()
# m.optimize('scg', messages=1, max_f_eval=200)
#
# print "releasing beta"