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beckdaniel/gist:5489270

Created April 30, 2013 14:57
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gistfile1.txt
import numpy as np
import GPy as gp
X = np.random.uniform(-3.,3.,(2000,17))
Y = np.sin(X) + np.random.randn(2000,17)*0.05
kernel = gp.kern.rbf(D=17, variance=1., lengthscale=1.)
m = gp.models.GP_regression(X,Y,kernel,normalize_X=True,normalize_Y=True)
m.constrain_positive('')
m.optimize()
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