physbo.blm.prior.gauss module

class physbo.blm.prior.gauss.cov_const(params=None)

ベースクラス: object

isotropic variance-covariance

All elements have the same variance and are independent with each other

params

half of log of covariance

Type

float

sigma2

covariance

Type

float

prec

precision (= inv. of covariance)

Type

float

get_cov(nbasis, params=None)

computes the covariance

パラメータ

• nbasis (int) -- the number of components

• params (float) -- half of log of variance (default: self.params)

戻り値

nbasis-by-n-basis covariance matrix

戻り値の型

numpy.ndarray

get_prec(nbasis, params=None)

computes the precision

パラメータ

• nbasis (int) -- the number of components

• params (float) -- half of log of variance (default: self.params)

戻り値

nbasis-by-n-basis precision matrix

戻り値の型

numpy.ndarray

set_params(params)

sets params

パラメータ

params (float) -- half of log of variance

class physbo.blm.prior.gauss.gauss(nbasis, cov=None)

ベースクラス: object

Gaussian prior

nbasis

number of components

Type

int

cov

covariance

Type

cov_const

get_cov(params=None)

calculates the variance-covariance matrix of priors

パラメータ

params (float) -- half of log of variance (default: self.cov.params)

戻り値

戻り値の型

numpy.ndarray

get_mean(params=None)

calculates the mean value of priors

パラメータ

params (float) -- half of log of variance (not used)

戻り値

戻り値の型

numpy.ndarray

get_prec(params=None)

calculates the precise matrix of priors

パラメータ

params (float) -- half of log of variance (default: self.cov.params)

戻り値

戻り値の型

numpy.ndarray

set_params(params)

sets params

パラメータ

params (float) -- half of log of variance