ParameterTransformer

class pyvbmc.parameter_transformer.ParameterTransformer(D: int, lb_orig: ndarray = None, ub_orig: ndarray = None, plb_orig: ndarray = None, pub_orig: ndarray = None, scale: ndarray = None, rotation_matrix: ndarray = None, transform_type='logit')

A class used to enable transforming of variables from unconstrained to constrained space and vice versa.

Parameters:

Dint

The dimension of the space.

lb_orignp.ndarray, optional

The lower bounds of the space. lb_orig and ub_orig define a set of strict lower and upper bounds for each parameter, given in the original space. By default None.

ub_orignp.ndarray, optional

The upper bounds of the space. lb_orig and ub_orig define a set of strict lower and upper bounds for each parameter, given in the original space. By default None.

plb_orignp.ndarray, optional

The plausible lower bounds such that lb_orig < plb_orig < pub_orig < ub_orig. plb_orig and pub_orig represent a “plausible” range for each parameter, given in the original space. By default None.

pub_orignp.ndarray, optional

The plausible upper bounds such that lb_orig < plb_orig < pub_orig < ub_orig. plb_orig and pub_orig represent a “plausible” range for each parameter, given in the original space. By default None.

bounded_transform_typestr, optional

A string indicating the type of transform for bounded variables: one of [“logit”, (“norminv” || “probit”), “student4”]. Default “logit”.

__call__(x: ndarray)

Performs direct transform of original variables x into unconstrained variables u.

Parameters:

xnp.ndarray

A N x D array, where N is the number of input data and D is the number of dimensions

Returns:

unp.ndarray

The variables transformed to unconstrained variables.

inverse(u: ndarray)

Performs inverse transform of unconstrained variables u into variables x in the original space

Parameters:

unp.ndarray

The unconstrained variables that will be transformed.

Returns:

xnp.ndarray

The original variables which result of the transformation.

log_abs_det_jacobian(u: ndarray)

log_abs_det_jacobian(u) returns the log absolute value of the determinant of the Jacobian of the parameter transformation evaluated at u, that is :math: log |D du(g^-1(u))|.

Parameters:

unp.ndarray

The points where the log determinant of the Jacobian should be evaluated (in transformed space).

Returns:

pnp.ndarray

The log absolute determinant of the Jacobian.