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added sparsegp with missing data

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Max Zwiessele 2014-02-18 15:52:33 +00:00
parent e96d40b4cc
commit d0c563ff0a
19 changed files with 572 additions and 325 deletions
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8
GPy/examples/regression.py
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@ -361,7 +361,7 @@ def toy_ARD_sparse(max_iters=1000, kernel_type='linear', num_samples=300, D=4, o
kernel = GPy.kern.rbf_inv(X.shape[1], ARD=1)
else:
kernel = GPy.kern.rbf(X.shape[1], ARD=1)
kernel += GPy.kern.bias(X.shape[1])
#kernel += GPy.kern.bias(X.shape[1])
X_variance = np.ones(X.shape) * 0.5
m = GPy.models.SparseGPRegression(X, Y, kernel, X_variance=X_variance)
# len_prior = GPy.priors.inverse_gamma(1,18) # 1, 25
@ -434,10 +434,14 @@ def sparse_GP_regression_1D(num_samples=400, num_inducing=5, max_iters=100, opti
return m
def sparse_GP_regression_2D(num_samples=400, num_inducing=50, max_iters=100, optimize=True, plot=True):
def sparse_GP_regression_2D(num_samples=400, num_inducing=50, max_iters=100, optimize=True, plot=True, nan=False):
"""Run a 2D example of a sparse GP regression."""
np.random.seed(1234)
X = np.random.uniform(-3., 3., (num_samples, 2))
Y = np.sin(X[:, 0:1]) * np.sin(X[:, 1:2]) + np.random.randn(num_samples, 1) * 0.05
if nan:
inan = np.random.binomial(1,.2,size=Y.shape)
Y[inan] = np.nan
# construct kernel
rbf = GPy.kern.rbf(2)