physbo.blm.lik.gauss module

class physbo.blm.lik.gauss.gauss(linear, cov)[source]

Bases: object

Gaussian

linear
cov

covariance

Type:

blm.lik.cov

stats
get_basis(X)[source]

calculates value of basis function at input

Parameters:

X (numpy.ndarray) – input

See also

blm.basis.fourier.get_basis

get_cov(N, params=None)[source]

Returns covariance matrix

Parameters:

  • N (int) – dimension

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

Returns:

NxN covariance matrix

Return type:

numpy.ndarray

get_mean(X, Psi=None, params=None, bias=None)[source]

calculates mean value

Parameters:

  • X (numpy.ndarray) – raw input

  • Psi (numpy.ndarray) – value of feature maps

  • params (numpy.ndarray) – weight

  • bias (float) – bias

See also

blm.basis.fourier.get_mean

get_prec(N, params=None)[source]

Returns precision matrix

Parameters:

  • N (int) – dimension

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

Returns:

NxN precision matrix

Return type:

numpy.ndarray

sampling(fmean)[source]

draws samples

Parameters:

fmean (numpy.ndarray) – means of samples

Returns:

samples

Return type:

numpy.ndarray

set_bias(bias)[source]

sets bias

set_params(params)[source]

sets parameters