Package paramz :: Module transformations :: Class LogexpNeg
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Class LogexpNeg

source code


Instance Methods [hide private]
 
f(self, x) source code
 
finv(self, f) source code
 
gradfactor(self, f, df)
df(opt_param)_dopt_param evaluated at self.f(opt_param)=model_param, times the gradient dL_dmodel_param,
source code
 
initialize(self, f)
produce a sensible initial value for f(x)
source code
 
__str__(self)
str(x)
source code

Inherited from Transformation: __repr__, gradfactor_non_natural, log_jacobian, log_jacobian_grad, plot

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

Static Methods [hide private]

Inherited from Transformation: __new__

Class Variables [hide private]
  domain = 'positive'
hash(x)

Inherited from Transformation (private): _instance

Properties [hide private]

Inherited from object: __class__

Method Details [hide private]

f(self, x)

source code 
Overrides: Transformation.f

finv(self, f)

source code 
Overrides: Transformation.finv

gradfactor(self, f, df)

source code 

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)