lsst.meas.algorithms g555ede804d+8467fca4bb
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Public Member Functions | |
tuple[int, int] | shape (self) |
float | __call__ (self, int x, int y) |
Static Public Attributes | |
np | array .ndarray |
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.
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static |
Definition at line 57 of file noise_covariance.py.