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Package parsimony :: Package functions :: Module losses :: Class LinearFunction
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Class LinearFunction

source code

                        object --+        
                                 |        
               properties.Function --+    
                                     |    
          properties.CompositeFunction --+
                                         |
                            object --+   |
                                     |   |
                   properties.Gradient --+
                                         |
                            object --+   |
                                     |   |
properties.LipschitzContinuousGradient --+
                                         |
                            object --+   |
                                     |   |
                   properties.StepSize --+
                                         |
                                        LinearFunction

A linear function.

Instance Methods [hide private]
 
__init__(self, a)
Parameters ---------- a : Numpy array (p-by-1).		 source code
 
reset(self)
Free any cached computations from previous use of this Function.		 source code
 
f(self, x)
Function value.		 source code
 
grad(self, x)
Gradient of the function at beta.		 source code
 
L(self)
Lipschitz constant of the gradient.		 source code
 
step(self, beta=None, index=0)
The step size to use in descent methods.		 source code

Inherited from properties.Function: get_params, set_params

Inherited from properties.Gradient: approx_grad

Inherited from properties.LipschitzContinuousGradient: approx_L

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

Class Variables [hide private]
  __abstractmethods__ = frozenset([])

Inherited from properties.CompositeFunction: __metaclass__

Inherited from properties.Function (private): _abc_cache, _abc_negative_cache, _abc_negative_cache_version, _abc_registry

Properties [hide private]

Inherited from object: __class__

Method Details [hide private]

__init__(self, a)
(Constructor)

source code  

Parameters
----------
a : Numpy array (p-by-1). The slope.
Overrides: object.__init__

reset(self)

source code 

Free any cached computations from previous use of this Function.

From the interface "Function".

Overrides: properties.Function.reset

f(self, x)

source code  
Function value.

From the interface "Function".

Parameters
----------
beta : Numpy array. Regression coefficient vector. The point at which
        to evaluate the function.
Overrides: properties.Function.f

grad(self, x)

source code  
Gradient of the function at beta.

From the interface "Gradient".

Parameters
----------
x : The point at which to evaluate the gradient.
Overrides: properties.Gradient.grad

L(self)

source code  
Lipschitz constant of the gradient.

From the interface "LipschitzContinuousGradient".

Examples
--------
>>> import numpy as np
>>> from parsimony.functions.losses import LinearFunction
>>>
>>> np.random.seed(42)
>>> a = np.random.rand(10, 15)
>>> f = LinearFunction(a)
>>> L = f.L()
>>> L_ = f.approx_L((15, 1), 10)
>>> L >= L_
True
>>> L - L_
0.0
Overrides: properties.LipschitzContinuousGradient.L

step(self, beta=None, index=0)

source code 

The step size to use in descent methods.

Overrides: properties.StepSize.step

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