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42 lines
1 KiB
Python
42 lines
1 KiB
Python
# Copyright (c) 2012, GPy authors (see AUTHORS.txt).
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# Licensed under the BSD 3-clause license (see LICENSE.txt)
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from kernpart import kernpart
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import numpy as np
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import hashlib
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class fixed(kernpart):
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def __init__(self,D,K,variance=1.):
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"""
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:param D: the number of input dimensions
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:type D: int
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:param variance: the variance of the kernel
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:type variance: float
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"""
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self.D = D
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self.fixed_K = K
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self.Nparam = 1
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self.name = 'fixed'
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self._set_params(np.array([variance]).flatten())
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def _get_params(self):
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return self.variance
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def _set_params(self,x):
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assert x.shape==(1,)
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self.variance = x
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def _get_param_names(self):
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return ['variance']
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def K(self,X,X2,target):
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target += self.variance * self.fixed_K
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def dK_dtheta(self,partial,X,X2,target):
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target += (partial * self.fixed_K).sum()
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def dK_dX(self, partial,X, X2, target):
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pass
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def dKdiag_dX(self,partial,X,target):
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pass
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