physbo.gp.inf.exact module

physbo.gp.inf.exact.eval_marlik(gp, X, t, params=None)

Evaluating marginal likelihood.

パラメータ

• gp (physbo.gp.core.model) --

• 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).

• params (numpy.ndarray) -- Parameters.

戻り値

marlik -- Marginal likelihood.

戻り値の型

float

physbo.gp.inf.exact.get_grad_marlik(gp, X, t, params=None)

Evaluating gradiant of marginal likelihood.

パラメータ

• gp (physbo.gp.core.model) --

• 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).

• params (numpy.ndarray) -- Parameters.

戻り値

grad_marlik -- Gradiant of marginal likelihood.

戻り値の型

numpy.ndarray

physbo.gp.inf.exact.get_post_fcov(gp, X, Z, params=None, diag=True)

Calculating the covariance of posterior

パラメータ

• gp (physbo.gp.core.model) --

• 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

physbo.gp.inf.exact.get_post_fmean(gp, X, Z, params=None)

Calculating the mean of posterior

パラメータ

• gp (physbo.gp.core.model) --

• 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.

戻り値

戻り値の型

numpy.ndarray

physbo.gp.inf.exact.prepare(gp, X, t, params=None)

パラメータ

• gp (physbo.gp.core.model) --

• 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).

• params (numpy.ndarray) -- Parameters.

戻り値

stats

戻り値の型

tupple