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[SSGPLVM] add plotting class

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This commit is contained in:
Zhenwen Dai 2014-04-08 15:26:34 +01:00
parent 01860455af
commit 5cfc250ad1
9 changed files with 96 additions and 10 deletions
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9
GPy/models/ss_gplvm.py
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@ -30,9 +30,12 @@ class SSGPLVM(SparseGP):
def __init__(self, Y, input_dim, X=None, X_variance=None, init='PCA', num_inducing=10,
Z=None, kernel=None, inference_method=None, likelihood=None, name='Spike-and-Slab GPLVM', group_spike=False, **kwargs):
if X == None: # The mean of variational approximation (mu)
if X == None:
from ..util.initialization import initialize_latent
X = initialize_latent(init, input_dim, Y)
X, fracs = initialize_latent(init, input_dim, Y)
else:
fracs = np.ones(input_dim)
self.init = init
if X_variance is None: # The variance of the variational approximation (S)
@ -52,7 +55,7 @@ class SSGPLVM(SparseGP):
likelihood = Gaussian()
if kernel is None:
kernel = kern.SSRBF(input_dim)
kernel = kern.RBF(input_dim, lengthscale=fracs, ARD=True) # + kern.white(input_dim)
pi = np.empty((input_dim))
pi[:] = 0.5