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output_dim instead of input_dim

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Ricardo 2013-06-05 15:19:05 +01:00
parent f60c8ab899
commit b535cf2e30
1 changed files with 5 additions and 5 deletions
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10
GPy/likelihoods/gaussian.py
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@ -24,8 +24,8 @@ class Gaussian(likelihood):
# Don't scale outputs which have zero variance to zero. # Don't scale outputs which have zero variance to zero.
self._scale[np.nonzero(self._scale == 0.)] = 1.0e-3 self._scale[np.nonzero(self._scale == 0.)] = 1.0e-3
else: else:
self._offset = np.zeros((1, self.input_dim)) self._offset = np.zeros((1, self.output_dim))
self._scale = np.ones((1, self.input_dim)) self._scale = np.ones((1, self.output_dim))
self.set_data(data) self.set_data(data)
@ -35,7 +35,7 @@ class Gaussian(likelihood):
def set_data(self, data): def set_data(self, data):
self.data = data self.data = data
self.N, D = data.shape self.N, D = data.shape
assert D == self.input_dim assert D == self.output_dim
self.Y = (self.data - self._offset) / self._scale self.Y = (self.data - self._offset) / self._scale
if D > self.N: if D > self.N:
self.YYT = np.dot(self.Y, self.Y.T) self.YYT = np.dot(self.Y, self.Y.T)
@ -68,9 +68,9 @@ class Gaussian(likelihood):
""" """
mean = mu * self._scale + self._offset mean = mu * self._scale + self._offset
if full_cov: if full_cov:
if self.input_dim > 1: if self.output_dim > 1:
raise NotImplementedError, "TODO" raise NotImplementedError, "TODO"
# Note. for input_dim>1, we need to re-normalise all the outputs independently. # Note. for output_dim>1, we need to re-normalise all the outputs independently.
# This will mess up computations of diag(true_var), below. # This will mess up computations of diag(true_var), below.
# note that the upper, lower quantiles should be the same shape as mean # note that the upper, lower quantiles should be the same shape as mean
# Augment the output variance with the likelihood variance and rescale. # Augment the output variance with the likelihood variance and rescale.