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lsst.meas.algorithms g511c235543+401ba1f5a0
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Public Member Functions | |
| tuple[int, int] | shape (self) |
| float | __call__ (self, int x, int y) |
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.
| float lsst.meas.algorithms.noise_covariance.CorrelationMatrix.__call__ | ( | self, | |
| int | x, | ||
| int | y | ||
| ) |
Definition at line 64 of file noise_covariance.py.
| 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.