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manual merging

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This commit is contained in:
James Hensman 2014-03-10 08:37:59 +00:00
commit a6eae08934
48 changed files with 1907 additions and 1082 deletions
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20
GPy/examples/non_gaussian.py
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@ -30,7 +30,7 @@ def student_t_approx(optimize=True, plot=True):
#Yc = Yc/Yc.max()
#Add student t random noise to datapoints
deg_free = 5
deg_free = 1
print "Real noise: ", real_std
initial_var_guess = 0.5
edited_real_sd = initial_var_guess
@ -47,9 +47,9 @@ def student_t_approx(optimize=True, plot=True):
m1['.*white'].constrain_fixed(1e-5)
m1.randomize()
##Gaussian GP model on corrupt data
#Gaussian GP model on corrupt data
m2 = GPy.models.GPRegression(X, Yc.copy(), kernel=kernel2)
m1['.*white'].constrain_fixed(1e-5)
m2['.*white'].constrain_fixed(1e-5)
m2.randomize()
#Student t GP model on clean data
@ -59,10 +59,6 @@ def student_t_approx(optimize=True, plot=True):
m3['.*t_noise'].constrain_bounded(1e-6, 10.)
m3['.*white'].constrain_fixed(1e-5)
m3.randomize()
debug = True
#TODO: remove
return m3
#Student t GP model on corrupt data
t_distribution = GPy.likelihoods.StudentT(deg_free=deg_free, sigma2=edited_real_sd)
@ -71,6 +67,16 @@ def student_t_approx(optimize=True, plot=True):
m4['.*t_noise'].constrain_bounded(1e-6, 10.)
m4['.*white'].constrain_fixed(1e-5)
m4.randomize()
print m4
debug=True
if debug:
m4.optimize(messages=1)
import pylab as pb
pb.plot(m4.X, m4.inference_method.f_hat)
pb.plot(m4.X, m4.Y, 'rx')
m4.plot()
print m4
return m4
if optimize:
optimizer='scg'