physbo.gp.core.prior module¶
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class
physbo.gp.core.prior.
prior
(mean, cov)[ソース]¶ ベースクラス:
object
prior of gaussian process
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cat_params
(mean_params, cov_params)[ソース]¶ - パラメータ
mean_params (numpy.ndarray) -- Mean values of parameters
cov_params (numpy.ndarray) -- Covariance matrix of parameters
- 戻り値
- 戻り値の型
numpy.ndarray
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decomp_params
(params)[ソース]¶ decomposing the parameters to those of mean values and covariance matrix for priors
- パラメータ
params (numpy.ndarray) -- parameters
- 戻り値
mean_params (numpy.ndarray)
cov_params (numpy.ndarray)
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get_cov
(X, Z=None, params=None, diag=False)[ソース]¶ Calculating the variance-covariance matrix of priors
- 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.
Z (numpy.ndarray) -- N x d dimensional matrix. Each row of Z denotes the d-dimensional feature vector of tests.
params (numpy.ndarray) -- Parameters.
diag (bool) -- If X is the diagonalization matrix, true.
- 戻り値
- 戻り値の型
numpy.ndarray
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get_grad_cov
(X, params=None)[ソース]¶ Calculating the covariance matrix priors
- 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) -- Parameters.
- 戻り値
- 戻り値の型
numpy.ndarray
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get_grad_mean
(num_data, params=None)[ソース]¶ Calculating the gradiant of mean values of priors
- パラメータ
num_data (int) -- Total number of data
params (numpy.ndarray) -- Parameters
- 戻り値
- 戻り値の型
numpy.ndarray
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get_mean
(num_data, params=None)[ソース]¶ Calculating the mean value of priors
- パラメータ
num_data (int) -- Total number of data
params (numpy.ndarray) -- Parameters
- 戻り値
- 戻り値の型
float
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sampling
(X, N=1)[ソース]¶ Sampling from GP prior
- 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.
N (int) --
- 戻り値
- 戻り値の型
float
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set_cov_params
(params)[ソース]¶ Setting parameters for covariance matrix of priors
- パラメータ
params (numpy.ndarray) -- Parameters
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