apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-05-24 14:15:14 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

all kernels working fine with the psi statistics now

Browse source
This commit is contained in:
Nicolo Fusi 2013-02-15 18:08:40 +00:00
parent 16d9536027
commit de665361a7
5 changed files with 14 additions and 18 deletions
Download patch file Download diff file Expand all files Collapse all files

6
GPy/examples/BGPLVM_demo.py
View file

@ -6,8 +6,8 @@ import pylab as pb
import GPy
np.random.seed(123344)
N = 3
M = 2
N = 10
M = 3
Q = 2
D = 4
#generate GPLVM-like data
@ -16,7 +16,7 @@ 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
k = GPy.kern.bias(Q) #+ GPy.kern.white(Q)
k = GPy.kern.linear(Q, ARD = True) + 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)

4
GPy/examples/oil_flow_demo.py
View file

@ -32,7 +32,7 @@ Y -= Y.mean(axis=0)
# Y /= Y.std(axis=0)
Q = 5
k = GPy.kern.linear(Q, ARD = False) + GPy.kern.white(Q)
k = GPy.kern.linear(Q, ARD = True) + GPy.kern.white(Q)
m = GPy.models.Bayesian_GPLVM(Y, Q, kernel = k, M = 20)
m.constrain_positive('(rbf|bias|S|linear|white|noise)')
@ -41,7 +41,7 @@ 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')
# # pb.figure()