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BGPLVM test for crossterms

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Max Zwiessele 2013-11-06 15:26:09 +00:00
parent ddf106dd32
commit d2d1d58db3
1 changed files with 8 additions and 5 deletions
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13
GPy/examples/dimensionality_reduction.py
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@ -12,10 +12,10 @@ from GPy.likelihoods.gaussian import Gaussian
default_seed = np.random.seed(123344)
def BGPLVM(seed=default_seed):
N = 5
num_inducing = 4
Q = 3
D = 2
N = 13
num_inducing = 5
Q = 6
D = 25
# generate GPLVM-like data
X = np.random.rand(N, Q)
lengthscales = np.random.rand(Q)
@ -25,9 +25,12 @@ def BGPLVM(seed=default_seed):
Y = np.random.multivariate_normal(np.zeros(N), K, D).T
lik = Gaussian(Y, normalize=True)
k = GPy.kern.rbf_inv(Q, .5, np.ones(Q) * 2., ARD=True) + GPy.kern.bias(Q) + GPy.kern.white(Q)
# k = GPy.kern.rbf_inv(Q, .5, np.ones(Q) * 2., ARD=True) + GPy.kern.bias(Q) + GPy.kern.white(Q)
# k = GPy.kern.linear(Q) + GPy.kern.bias(Q) + GPy.kern.white(Q, 0.00001)
# k = GPy.kern.rbf(Q, ARD = False) + GPy.kern.white(Q, 0.00001)
# k = GPy.kern.rbf(Q, .5, np.ones(Q) * 2., ARD=True) + GPy.kern.rbf(Q, .3, np.ones(Q) * .2, ARD=True)
k = GPy.kern.rbf(Q, .5, np.ones(Q) * 2., ARD=True) + GPy.kern.linear(Q, np.ones(Q) * .2, ARD=True)
# k = GPy.kern.rbf(Q, .5, 2., ARD=0) + GPy.kern.rbf(Q, .3, .2, ARD=0)
m = GPy.models.BayesianGPLVM(lik, Q, kernel=k, num_inducing=num_inducing)
m.lengthscales = lengthscales