physbo.gp.core.prior module¶

class physbo.gp.core.prior.prior(mean, cov)[source]¶

Bases: object

prior of gaussian process

cat_params(mean_params, cov_params)[source]¶

Parameters

mean_params (numpy.ndarray) – Mean values of parameters
cov_params (numpy.ndarray) – Covariance matrix of parameters

Returns

Return type

numpy.ndarray

decomp_params(params)[source]¶

decomposing the parameters to those of mean values and covariance matrix for priors

Parameters

params (numpy.ndarray) – parameters

Returns

mean_params (numpy.ndarray)
cov_params (numpy.ndarray)

get_cov(X, Z=None, params=None, diag=False)[source]¶

Calculating the variance-covariance matrix of priors

Parameters

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.

Returns

Return type

numpy.ndarray

get_grad_cov(X, params=None)[source]¶

Calculating the covariance matrix priors

Parameters

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.

Returns

Return type

numpy.ndarray

get_grad_mean(num_data, params=None)[source]¶

Calculating the gradiant of mean values of priors

Parameters

num_data (int) – Total number of data
params (numpy.ndarray) – Parameters

Returns

Return type

numpy.ndarray

get_mean(num_data, params=None)[source]¶

Calculating the mean value of priors

Parameters

num_data (int) – Total number of data
params (numpy.ndarray) – Parameters

Returns

Return type

float

sampling(X, N=1)[source]¶

Sampling from GP prior

Parameters

X (numpy.ndarray) – N x d dimensional matrix. Each row of X denotes the d-dimensional feature vector of search candidate.
N (int) –

Returns

Return type

float

set_cov_params(params)[source]¶

Setting parameters for covariance matrix of priors

Parameters: params (numpy.ndarray) – Parameters

set_mean_params(params)[source]¶

Setting parameters for mean values of priors

Parameters: params (numpy.ndarray) – Parameters

set_params(params)[source]¶

Setting parameters

Parameters: params (numpy.ndarray) – Parameters.