LogNormalFitter

Class for fitting a log-normal distribution to a point cloud

A log-normal distribution is constructed by fitting a normal distribution to the logarithm of the point coordinates.

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[class] LogNormalFitter

comments:

class for fitting a log-normal distribution to a point cloud  
parameters:  
- mean: multidim mean of underlying normal  
- cov: multidim covariance matrix of underlying normal  
- mvn: scipy.stats multivariate_normal object built from the mean and cov  

⤷ __init__

full signature:

def __init__(self)  

comments:

empty constructor  

⤷ fit

full signature:

def fit(self, points)  

comments:

fit to a set of points  
input arguments:  
- points: a np array of shape (npoints,ndims)  

⤷ pdf

full signature:

def pdf(self,points)  

comments:

get pdf at points  

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