physbo.blm.prior.gauss module

class physbo.blm.prior.gauss.cov_const(params=None)[ソース]

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)[ソース]

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)[ソース]

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)[ソース]

sets params

パラメータ:params (float) -- half of log of variance
class physbo.blm.prior.gauss.gauss(nbasis, cov=None)[ソース]

Gaussian prior

nbasis

number of components

Type:int
cov

covariance

Type:cov_const
get_cov(params=None)[ソース]

calculates the variance-covariance matrix of priors

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)[ソース]

calculates the mean value of priors

params: float
half of log of variance (not used)
戻り値:
戻り値の型:numpy.ndarray
get_prec(params=None)[ソース]

calculates the precise matrix of priors

params: float
half of log of variance (default: self.cov.params)
戻り値:
戻り値の型:numpy.ndarray
set_params(params)[ソース]

sets params

params: float
half of log of variance