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Merge branch 'params' of github.com:SheffieldML/GPy into params

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James Hensman 2014-02-17 12:05:31 +00:00
commit 65a2c2a320
9 changed files with 112 additions and 14 deletions
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3
GPy/kern/parts/bias.py
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@ -14,7 +14,8 @@ class Bias(Kernpart):
:type variance: float
"""
super(Bias, self).__init__(input_dim, name)
self.variance = Param("variance", variance)
from ...core.parameterization.transformations import Logexp
self.variance = Param("variance", variance, Logexp())
self.add_parameter(self.variance)
def K(self,X,X2,target):

2
GPy/kern/parts/linear.py
View file

@ -61,7 +61,7 @@ class Linear(Kernpart):
def update_gradients_full(self, dL_dK, X):
#self.variances.gradient[:] = 0
self._param_grad_helper(dL_dK, X, self.variances.gradient)
self._param_grad_helper(dL_dK, X, None, self.variances.gradient)
def update_gradients_sparse(self, dL_dKmm, dL_dKnm, dL_dKdiag, X, Z):
tmp = dL_dKdiag[:, None] * X ** 2

4
GPy/kern/parts/rbf.py
View file

@ -265,7 +265,7 @@ class RBF(Kernpart):
}
"""
num_data, num_inducing, input_dim = X.shape[0], X.shape[0], self.input_dim
X, dvardLdK = param_to_array(X, dvardLdK)
X, dvardLdK, var_len3 = param_to_array(X, dvardLdK, var_len3)
weave.inline(code, arg_names=['num_data', 'num_inducing', 'input_dim', 'X', 'target', 'dvardLdK', 'var_len3'], type_converters=weave.converters.blitz, **self.weave_options)
else:
code = """
@ -282,7 +282,7 @@ class RBF(Kernpart):
}
"""
num_data, num_inducing, input_dim = X.shape[0], X2.shape[0], self.input_dim
X, X2, dvardLdK = param_to_array(X, X2, dvardLdK)
X, X2, dvardLdK, var_len3 = param_to_array(X, X2, dvardLdK, var_len3)
weave.inline(code, arg_names=['num_data', 'num_inducing', 'input_dim', 'X', 'X2', 'target', 'dvardLdK', 'var_len3'], type_converters=weave.converters.blitz, **self.weave_options)
return target