Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __reduce__, __reduce_ex__, __setattr__, __sizeof__, __subclasshook__

Static Methods

[hide private]

a new object with type S, a subtype of T

__new__(cls, mu_indices=None, var_indices=None)
Do not use, not officially supported!

source code

Class Variables

[hide private]

_instances = []

Inherited from Transformation: domain

Inherited from Transformation (private): _instance

Properties

[hide private]

Inherited from object: __class__

Method Details

[hide private]

new(cls, mu_indices=None, var_indices=None)
Static Method

source code

Do not use, not officially supported!

Returns: a new object with type S, a subtype of T
Overrides: object.__new__

init(self, mu_indices, var_indices)
(Constructor)

source code

x.__init__(...) initializes x; see help(type(x)) for signature

Overrides: object.__init__: (inherited documentation)

df(opt_param)_dopt_param evaluated at self.f(opt_param)=model_param, times the gradient dL_dmodel_param,

i.e.: define

.. math:

   rac{rac{\partial L}{\partial f}\left(\left.\partial f(x)}{\partial x}
ight|_{x=f^{-1}(f)
ight)}

Overrides: Transformation.gradfactor: (inherited documentation)

initialize(self, f)

source code

produce a sensible initial value for f(x)

Overrides: Transformation.initialize: (inherited documentation)

str(self)
(Informal representation operator)

source code

str(x)

Overrides: object.__str__: (inherited documentation)

Class NormalTheta

__new__(cls, mu_indices=None, var_indices=None) Static Method

__init__(self, mu_indices, var_indices) (Constructor)

f(self, theta)

finv(self, muvar)

gradfactor(self, muvar, dmuvar)

initialize(self, f)

__str__(self) (Informal representation operator)

new(cls, mu_indices=None, var_indices=None)
Static Method

init(self, mu_indices, var_indices)
(Constructor)

str(self)
(Informal representation operator)