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more gradient based tomfoolery

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James Hensman 2014-01-24 14:15:32 +00:00
parent 7b5e8a9ffc
commit c1a416debc
4 changed files with 4 additions and 6 deletions
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3
GPy/core/model.py
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@ -33,7 +33,8 @@ class Model(Parameterized):
#def dK_d(self, param, dL_dK, X, X2)
g = np.zeros(self.size)
try:
[g.__setitem__(s, self.gradient_mapping[p]().flat) for p, s in itertools.izip(self._parameters_, self._param_slices_) if not p.is_fixed]
#[g.__setitem__(s, self.gradient_mapping[p]().flat) for p, s in itertools.izip(self._parameters_, self._param_slices_) if not p.is_fixed]
[g.__setitem__(s, p.gradient.flat) for p, s in itertools.izip(self._parameters_, self._param_slices_) if not p.is_fixed]
except KeyError:
raise KeyError, 'Gradient for {} not defined, please specify gradients for parameters to optimize'.format(p.name)
return g