CloudFitter

Abstract base class for all point cloud fitting algorithms

Note that all concrete point cloud fitters must inherit from CloudFitter!

How to make a concrete CloudFitter class: - define a class that inherits from CloudFitter - make sure all functions with @abstractmethod are implemented in your class - it is recommended to start each overriding function with a call to super(), but this is not strictly necessary

See also the existing examples!

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[class] CloudFitter

comments:

abstract base class for all point cloud fitting algorithms  
note that all concrete point cloud fitters must inherit from CloudFitter!  
how to make a concrete CloudFitter class:  
- define a class that inherits from CloudFitter  
- make sure all functions with @abstractmethod are implemented in your class  
- it is recommended to start each overriding function with a call to super(), but this is not strictly necessary  
see also the existing examples!  

⤷ __init__

full signature:

def __init__( self )  

comments:

empty intializer  
this is an @abstractmethod and must be overridden in any concrete deriving class!  

⤷ fit

full signature:

def fit( self, points )  

comments:

input arguments:  
- points: 2D numpy array of shape (npoints,ndims)  

⤷ pdf

full signature:

def pdf( self, points )  

comments:

evaluate the pdf (probability density function) at given points  
this is an @abstractmethod and must be overridden in any concrete deriving class!  
input arguments:  
- points: a 2D numpy array of shape (npoints,ndims)  
output: a 1D array of shape (npoints)  

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