Class NegativeExponent

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Instance Methods

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f(self, x)

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finv(self, f)

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

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initialize(self, f)
produce a sensible initial value for f(x)

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__str__(self)
str(x)

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Inherited from Exponent: log_jacobian, log_jacobian_grad

Inherited from Transformation: __repr__, gradfactor_non_natural, plot

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

Static Methods

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Inherited from Transformation: __new__

Class Variables

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domain = 'negative'
hash(x)

Inherited from Transformation (private): _instance

Properties

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Inherited from object: __class__

Method Details

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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)

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produce a sensible initial value for f(x)

Overrides: Transformation.initialize: (inherited documentation)

str(self)
(Informal representation operator)

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str(x)

Overrides: object.__str__: (inherited documentation)

Class NegativeExponent

f(self, x)

finv(self, f)

gradfactor(self, f, df)

initialize(self, f)

__str__(self) (Informal representation operator)

str(self)
(Informal representation operator)