physbo.blm.lik package
Module contents
- class physbo.blm.lik.Cov(params=None)[ソース]
ベースクラス:
object
Covariance
- params
half of log of variance
- Type:
float
- nparams
number of parameters
- Type:
int
- sigma2
variance
- Type:
float
- prec
inv. of variance
- Type:
float
- get_cov(N, params=None)[ソース]
compute the covariance of prior
- パラメータ:
N (int) -- dimension
params -- half of log of variance (default: self.params)
- 戻り値:
NxN covariance matrix
- 戻り値の型:
numpy.ndarray
- class physbo.blm.lik.Gauss(linear, cov)[ソース]
ベースクラス:
object
Gaussian
- linear
linear kernel
- Type:
- cov
covariance
- Type:
- stats
- get_basis(X)[ソース]
calculates value of basis function at input
- パラメータ:
X (numpy.ndarray) -- input
参考
physbo.blm.basis.fourier.get_basis
- get_cov(N, params=None)[ソース]
Returns covariance matrix
- パラメータ:
N (int) -- dimension
params (float) -- half of log of variance (default: self.cov.params)
- 戻り値:
NxN covariance matrix
- 戻り値の型:
numpy.ndarray
- get_mean(X, Psi=None, params=None, bias=None)[ソース]
calculates mean value
- パラメータ:
X (numpy.ndarray) -- raw input
Psi (numpy.ndarray) -- value of feature maps
params (numpy.ndarray) -- weight
bias (float) -- bias
参考
physbo.blm.basis.fourier.get_mean
- get_prec(N, params=None)[ソース]
Returns precision matrix
- パラメータ:
N (int) -- dimension
params (float) -- half of log of variance (default: self.cov.params)
- 戻り値:
NxN precision matrix
- 戻り値の型:
numpy.ndarray
- class physbo.blm.lik.Linear(basis, params=None, bias=None)[ソース]
ベースクラス:
object
- basis
basis for random feature map
- nbasis
number of basis
- Type:
int
- bias
- params
- get_mean(X, Psi=None, params=None, bias=None)[ソース]
calculate mean values
- パラメータ:
X (numpy.ndarray) -- input as an N-by-d matrix
Psi (numpy.ndarray) -- feature maps
Psi(X)
as an N-by-l matrix (default: self.get_basis(X))params (numpy.ndarray) -- weight as a vector with size l (default: self.params)
bias (float) -- (default: self.bias)
- 戻り値:
Psi * params + bias
- 戻り値の型:
numpy.ndarray