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Merge branch 'params' of github.com:SheffieldML/GPy into params

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Conflicts:
	GPy/likelihoods/gaussian.py
This commit is contained in:
Max Zwiessele 2014-03-18 15:49:10 +00:00
commit 79ba989b31
10 changed files with 189 additions and 36 deletions
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21
GPy/core/parameterization/variational.py
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@ -126,6 +126,27 @@ class SpikeAndSlabPosterior(VariationalPosterior):
super(SpikeAndSlabPosterior, self).__init__(means, variances, name)
self.gamma = Param("binary_prob",binary_prob, Logistic(1e-10,1.-1e-10))
self.add_parameter(self.gamma)
def __getitem__(self, s):
if isinstance(s, (int, slice, tuple, list, np.ndarray)):
import copy
n = self.__new__(self.__class__, self.name)
dc = self.__dict__.copy()
dc['mean'] = self.mean[s]
dc['variance'] = self.variance[s]
dc['binary_prob'] = self.binary_prob[s]
dc['_parameters_'] = copy.copy(self._parameters_)
n.__dict__.update(dc)
n._parameters_[dc['mean']._parent_index_] = dc['mean']
n._parameters_[dc['variance']._parent_index_] = dc['variance']
n._parameters_[dc['binary_prob']._parent_index_] = dc['binary_prob']
n.ndim = n.mean.ndim
n.shape = n.mean.shape
n.num_data = n.mean.shape[0]
n.input_dim = n.mean.shape[1] if n.ndim != 1 else 1
return n
else:
return super(VariationalPrior, self).__getitem__(s)
def plot(self, *args):
"""