apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-05-15 06:52:39 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

Merge branch 'params' of github.com:SheffieldML/GPy into params

Browse source
This commit is contained in:
Max Zwiessele 2014-03-13 12:30:27 +00:00
commit 0d343cf0ca
2 changed files with 32 additions and 2 deletions
Download patch file Download diff file Expand all files Collapse all files

30
GPy/examples/coreg_example.py Normal file
View file

@ -0,0 +1,30 @@
import numpy as np
import pylab as pb
import GPy
pb.ion()
X1 = 100 * np.random.rand(100)[:,None]
X2 = 100 * np.random.rand(100)[:,None]
#X1.sort()
#X2.sort()
Y1 = np.sin(X1/10.) + np.random.rand(100)[:,None]
Y2 = np.cos(X2/10.) + np.random.rand(100)[:,None]
Mlist = [GPy.kern.Matern32(1,lengthscale=20.,name="Mat")]
kern = GPy.util.multioutput.LCM(input_dim=1,num_outputs=12,kernels_list=Mlist,name='H')
m = GPy.models.GPCoregionalizedRegression(X_list=[X1,X2], Y_list=[Y1,Y2], kernel=kern)
m.optimize()
fig = pb.figure()
ax0 = fig.add_subplot(211)
ax1 = fig.add_subplot(212)
slices = GPy.util.multioutput.get_slices([Y1,Y2])
m.plot(fixed_inputs=[(1,0)],which_data_rows=slices[0],ax=ax0)
m.plot(fixed_inputs=[(1,1)],which_data_rows=slices[1],ax=ax1)

4
GPy/util/multioutput.py
View file

@ -54,8 +54,8 @@ def ICM(input_dim, num_outputs, kernel, W_rank=1,W=None,kappa=None,name='X'):
kernel.input_dim = input_dim
warnings.warn("kernel's input dimension overwritten to fit input_dim parameter.")
#K = kernel.prod(GPy.kern.Coregionalize(input_dim, num_outputs,W_rank,W,kappa,name='B'),tensor=True,name=name)
K = kernel.prod(GPy.kern.Coregionalize(input_dim, num_outputs,W_rank,W,kappa,name='B'),name=name)
K = kernel.prod(GPy.kern.Coregionalize([input_dim], num_outputs,W_rank,W,kappa,name='B'),name=name)
#K = kernel ** GPy.kern.Coregionalize(input_dim, num_outputs,W_rank,W,kappa, name= 'B')
K['.*variance'] = 1.
K['.*variance'].fix()
return K