lsst.meas.algorithms g691b785e4b+f9c6776e6c
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Public Member Functions | List of all members
lsst.meas.algorithms.noise_covariance.CorrelationMatrix Class Reference

Public Member Functions

tuple[int, int] shape (self)
 
float __call__ (self, int x, int y)
 

Detailed Description

A class holding correlation coefficients for a set of background pixels.

CorrelationMatrix is a dataclass that is initialized with a numpy ndarray
and provides some convenience methods for accessing the matrix elements.
A CorrelationMatrix instance is callable wth two integer values x and y,
which returns the <I(m,n) I(m+x, n+y) / sqrt( V(m,n) V(m+x,n+y) )>, where
I is the image, V is the variance plane and < > denotes the expectation
operator.

Parameters
----------
array : `numpy.ndarray`
    The matrix of correlation coefficients.

Definition at line 41 of file noise_covariance.py.

Member Function Documentation

◆ __call__()

float lsst.meas.algorithms.noise_covariance.CorrelationMatrix.__call__ (   self,
int  x,
int  y 
)

Definition at line 64 of file noise_covariance.py.

◆ shape()

tuple[int, int] lsst.meas.algorithms.noise_covariance.CorrelationMatrix.shape (   self)
The shape of the correlation matrix.

Definition at line 60 of file noise_covariance.py.


The documentation for this class was generated from the following file: