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Fixed some tests

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This commit is contained in:
Alan Saul 2013-12-16 17:17:47 +00:00
parent 5db256a841
commit 10fcb4027b
2 changed files with 4 additions and 4 deletions
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4
GPy/examples/dimensionality_reduction.py
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@ -41,7 +41,7 @@ def bgplvm_test_model(seed=default_seed, optimize=False, verbose=1, plot=False):
# randomly obstruct data with percentage p
p = .8
Y_obstruct = Y.copy()
Y_obstruct[np.random.uniform(size=(Y.shape)) < p] = np.nan
Y_obstruct[_np.random.uniform(size=(Y.shape)) < p] = _np.nan
#===========================================================================
m2 = GPy.models.BayesianGPLVMWithMissingData(Y_obstruct, input_dim, kernel=k, num_inducing=num_inducing)
m.lengthscales = lengthscales
@ -52,7 +52,7 @@ def bgplvm_test_model(seed=default_seed, optimize=False, verbose=1, plot=False):
pb.title('PCA initialisation')
m2.plot()
pb.title('PCA initialisation')
if optimize:
m.optimize('scg', messages=verbose)
m2.optimize('scg', messages=verbose)

4
GPy/models_modules/sparse_gplvm.py
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@ -6,7 +6,7 @@ import numpy as np
import pylab as pb
import sys, pdb
from sparse_gp_regression import SparseGPRegression
from gplvm import GPLVM
from gplvm import GPLVM, initialise_latent
# from .. import kern
# from ..core import model
# from ..util.linalg import pdinv, PCA
@ -24,7 +24,7 @@ class SparseGPLVM(SparseGPRegression, GPLVM):
"""
def __init__(self, Y, input_dim, kernel=None, init='PCA', num_inducing=10):
X = self.initialise_latent(init, input_dim, Y)
X = initialise_latent(init, input_dim, Y)
SparseGPRegression.__init__(self, X, Y, kernel=kernel, num_inducing=num_inducing)
self.ensure_default_constraints()