physbo.gp.cov.gauss module¶
-
class
physbo.gp.cov.gauss.
gauss
(num_dim, width=3, scale=1, ard=False, max_width=1000000.0, min_width=1e-06, max_scale=1000000.0, min_scale=1e-06)[ソース]¶ ベースクラス:
object
gaussian kernel
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cat_params
(width, scale)[ソース]¶ Taking the logarithm of width and scale parameters and concatinate them into one ndarray
- パラメータ
width (int) --
scale (int) --
- 戻り値
params -- Parameters
- 戻り値の型
numpy.ndarray
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decomp_params
(params)[ソース]¶ decompose the parameters defined on the log region into width and scale parameters
- パラメータ
params (numpy.ndarray) -- parameters
- 戻り値
width (float)
scale (float)
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get_cand_params
(X, t)[ソース]¶ Getting candidate parameters.
- パラメータ
X (numpy.ndarray) -- N x d dimensional matrix. Each row of X denotes the d-dimensional feature vector of search candidate.
t (numpy.ndarray) -- N dimensional array. The negative energy of each search candidate (value of the objective function to be optimized).
- 戻り値
params
- 戻り値の型
numpy.ndarray
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get_cov
(X, Z=None, params=None, diag=False)[ソース]¶ compute the covariant matrix :param X: N x d dimensional matrix. Each row of X denotes the d-dimensional feature vector of search candidate. :type X: numpy.ndarray :param Z: N x d dimensional matrix. Each row of Z denotes the d-dimensional feature vector of search candidate. :type Z: numpy.ndarray :param params: Parameters :type params: numpy.ndarray :param diag: If X is the diagonalization matrix, true. :type diag: bool
- 戻り値
G -- covariant matrix
- 戻り値の型
numpy.ndarray
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get_grad
(X, params=None)[ソース]¶ Getting gradiant values of X
- パラメータ
X (numpy.ndarray) -- N x d dimensional matrix. Each row of X denotes the d-dimensional feature vector of search candidate.
params (numpy.ndarray) --
- 戻り値
grad
- 戻り値の型
numpy.ndarray
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get_params_bound
()[ソース]¶ Getting boundary array.
- 戻り値
bound -- A num_params-dimensional array with the tuple (min_params, max_params).
- 戻り値の型
list
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load
(file_name)[ソース]¶ Recovering the Gaussian kernel from file :param file_name: file name to load the information of the kernel :type file_name: str
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prepare
(params=None)[ソース]¶ Setting parameters
- パラメータ
params (numpy.ndarray) -- parameters
- 戻り値
params (numpy.ndarray)
width (int)
scale (int)
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rand_expans
(num_basis, params=None)[ソース]¶ Kernel Expansion
- パラメータ
num_basis (int) -- total number of basis
params (numpy.ndarray) -- Parameters
- 戻り値
- 戻り値の型
tupple (W, b, amp)
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save
(file_name)[ソース]¶ save the gaussian kernel
- パラメータ
file_name (str) -- file name to save the information of the kernel
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set_params
(params)[ソース]¶ set kernel parameters
- パラメータ
params (numpy.ndarray) -- Parameters for optimization.
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supp_params
(params)[ソース]¶ Set maximum (minimum) values for parameters when the parameter is greater(less) than this value.
- パラメータ
params (numpy.ndarray) -- Parameters for optimization. Array of real elements of size (n,), where ‘n’ is the number of independent variables.
- 戻り値
params
- 戻り値の型
numpy.ndarray
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