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Changed the gradients (perhaps for the worse)

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Alan Saul 2013-09-09 11:54:32 +01:00
parent 54954c63f8
commit f943cf9ddb
1 changed files with 6 additions and 5 deletions
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11
GPy/likelihoods/likelihood_functions.py
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@ -523,7 +523,7 @@ class gaussian(likelihood_function):
"""
assert y.shape == f.shape
s2_i = (1.0/self._variance)*self.I
grad = np.dot(s2_i, y) - np.dot(s2_i, f)
grad = np.dot(s2_i, y) - 0.5*np.dot(s2_i, f)
return grad
def d2lik_d2f(self, y, f, extra_data=None):
@ -541,7 +541,7 @@ class gaussian(likelihood_function):
"""
assert y.shape == f.shape
s2_i = (1.0/self._variance)*self.I
hess = np.diag(-s2_i)[:, None] # FIXME: CAREFUL THIS MAY NOT WORK WITH MULTIDIMENSIONS?
hess = 0.5*np.diag(-s2_i)[:, None] # FIXME: CAREFUL THIS MAY NOT WORK WITH MULTIDIMENSIONS?
return hess
def d3lik_d3f(self, y, f, extra_data=None):
@ -560,7 +560,8 @@ class gaussian(likelihood_function):
"""
assert y.shape == f.shape
e = y - f
dlik_dsigma = -0.5*self.N/self._variance - 0.5*np.trace(np.dot(e.T, np.dot(self.I, e)))
s_4 = 1.0/(self._variance**2)
dlik_dsigma = -0.5*self.N*1/self._variance + 0.5*s_4*np.trace(np.dot(e.T, np.dot(self.I, e)))
return dlik_dsigma
def dlik_df_dstd(self, y, f, extra_data=None):
@ -569,7 +570,7 @@ class gaussian(likelihood_function):
"""
assert y.shape == f.shape
s_4 = 1.0/(self._variance**2)
dlik_grad_dsigma = -np.dot(s_4, np.dot(self.I, y)) + np.dot(s_4, np.dot(self.I, f))
dlik_grad_dsigma = -np.dot(s_4, np.dot(self.I, y)) + 0.5*np.dot(s_4, np.dot(self.I, f))
return dlik_grad_dsigma
def d2lik_d2f_dstd(self, y, f, extra_data=None):
@ -579,7 +580,7 @@ class gaussian(likelihood_function):
$$\frac{d}{d\sigma}(\frac{d^{2}p(y_{i}|f_{i})}{d^{2}f}) = \frac{2\sigma v(v + 1)(\sigma^2 v - 3(y-f)^2)}{((y-f)^2 + \sigma^2 v)^3}$$
"""
assert y.shape == f.shape
dlik_hess_dsigma = np.diag((1.0/(self._variance**2))*self.I)[:, None]
dlik_hess_dsigma = 0.5*np.diag((1.0/(self._variance**2))*self.I)[:, None]
return dlik_hess_dsigma
def _gradients(self, y, f, extra_data=None):