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Modified gradient_checker to allow for variable 'f'

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Alan Saul 2013-09-11 11:54:47 +01:00
parent 1dd83291fe
commit 64e65b846d
1 changed files with 15 additions and 15 deletions
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8
GPy/models/gradient_checker.py
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@ -81,8 +81,8 @@ class GradientChecker(Model):
# self._param_names.extend(map(lambda nameshape: ('_'.join(nameshape)).strip('_'), itertools.izip(itertools.repeat(name), itertools.imap(lambda t: '_'.join(map(str, t)), itertools.product(*map(lambda xi: range(xi), shape)))))) # self._param_names.extend(map(lambda nameshape: ('_'.join(nameshape)).strip('_'), itertools.izip(itertools.repeat(name), itertools.imap(lambda t: '_'.join(map(str, t)), itertools.product(*map(lambda xi: range(xi), shape))))))
self.args = args self.args = args
self.kwargs = kwargs self.kwargs = kwargs
self.f = f self._f = f
self.df = df self._df = df
def _get_x(self): def _get_x(self):
if len(self.names) > 1: if len(self.names) > 1:
@ -90,10 +90,10 @@ class GradientChecker(Model):
return [self.__getattribute__(self.names[0])] + list(self.args) return [self.__getattribute__(self.names[0])] + list(self.args)
def log_likelihood(self): def log_likelihood(self):
return float(numpy.sum(self.f(*self._get_x(), **self.kwargs))) return float(numpy.sum(self._f(*self._get_x(), **self.kwargs)))
def _log_likelihood_gradients(self): def _log_likelihood_gradients(self):
return numpy.atleast_1d(self.df(*self._get_x(), **self.kwargs)).flatten() return numpy.atleast_1d(self._df(*self._get_x(), **self.kwargs)).flatten()
def _get_params(self): def _get_params(self):