apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-05-01 15:52:39 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

debugging BGPLVM

Browse source
This commit is contained in:
Nicolo Fusi 2013-02-15 16:31:51 +00:00
parent 151c426a3a
commit bf2d641112
3 changed files with 21 additions and 19 deletions
Download patch file Download diff file Expand all files Collapse all files

18
GPy/examples/BGPLVM_demo.py
View file

@ -6,23 +6,21 @@ import pylab as pb
import GPy
np.random.seed(123344)
N = 10
M = 3
Q = 4
D = 5
N = 3
M = 2
Q = 2
D = 4
#generate GPLVM-like data
X = np.random.rand(N, Q)
k = GPy.kern.rbf(Q) + GPy.kern.white(Q, 0.00001)
K = k.K(X)
Y = np.random.multivariate_normal(np.zeros(N),K,D).T
<<<<<<< HEAD
k = GPy.kern.rbf(Q) + GPy.kern.rbf(Q) + GPy.kern.white(Q)
# k = GPy.kern.linear(Q, ARD = True) + GPy.kern.white(Q, 0.00001)
=======
k = GPy.kern.bias(Q) #+ GPy.kern.white(Q)
# k = GPy.kern.rbf(Q) + GPy.kern.rbf(Q) + GPy.kern.white(Q)
# k = GPy.kern.rbf(Q) + GPy.kern.bias(Q) + GPy.kern.white(Q, 0.00001)
k = GPy.kern.rbf(Q, ARD = False) + GPy.kern.white(Q, 0.00001)
>>>>>>> master
# k = GPy.kern.rbf(Q, ARD = False) + GPy.kern.white(Q, 0.00001)
m = GPy.models.Bayesian_GPLVM(Y, Q, kernel = k, M=M)
m.constrain_positive('(rbf|bias|noise|white|S)')
# m.constrain_fixed('S', 1)

4
GPy/examples/oil_flow_demo.py
View file

@ -41,9 +41,9 @@ m.constrain_positive('(rbf|bias|S|linear|white|noise)')
# m.unconstrain('white')
# m.constrain_bounded('white', 1e-6, 10.0)
# plot_oil(m.X, np.array([1,1]), labels, 'PCA initialization')
m.optimize(messages = True)
# m.optimize(messages = True)
# m.optimize('tnc', messages = True)
plot_oil(m.X, m.kern.parts[0].lengthscale, labels, 'B-GPLVM')
# plot_oil(m.X, m.kern.parts[0].lengthscale, labels, 'B-GPLVM')
# # pb.figure()
# m.plot()
# pb.title('PCA initialisation')