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Merge branch 'wgps_improvements' of https://github.com/beckdaniel/GPy into beckdaniel-wgps_improvements

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mzwiessele 2016-08-03 13:27:52 +01:00
commit 9be51df4f1
5 changed files with 261 additions and 242 deletions
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31
GPy/examples/regression.py
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@ -550,3 +550,34 @@ def parametric_mean_function(max_iters=100, optimize=True, plot=True):
return m
def warped_gp_cubic_sine(max_iters=100):
"""
A test replicating the cubic sine regression problem from
Snelson's paper.
"""
X = (2 * np.pi) * np.random.random(151) - np.pi
Y = np.sin(X) + np.random.normal(0,0.2,151)
Y = np.array([np.power(abs(y),float(1)/3) * (1,-1)[y<0] for y in Y])
X = X[:, None]
Y = Y[:, None]
warp_k = GPy.kern.RBF(1)
warp_f = GPy.util.warping_functions.TanhFunction(n_terms=2)
warp_m = GPy.models.WarpedGP(X, Y, kernel=warp_k, warping_function=warp_f)
warp_m['.*\.d'].constrain_fixed(1.0)
m = GPy.models.GPRegression(X, Y)
m.optimize_restarts(parallel=False, robust=True, num_restarts=5, max_iters=max_iters)
warp_m.optimize_restarts(parallel=False, robust=True, num_restarts=5, max_iters=max_iters)
#m.optimize(max_iters=max_iters)
#warp_m.optimize(max_iters=max_iters)
print(warp_m)
print(warp_m['.*warp.*'])
warp_m.predict_in_warped_space = False
warp_m.plot(title="Warped GP - Latent space")
warp_m.predict_in_warped_space = True
warp_m.plot(title="Warped GP - Warped space")
m.plot(title="Standard GP")
warp_m.plot_warping()
pb.show()