pyacs.lib.glinalg.make_normal_system

Form the normal system for least-squares.

pyacs.lib.glinalg.make_normal_system.make_normal_system(A, d, inv_Cd)[source]

Form the normal system for A x = d with data covariance Cd.

Normal system: (A.T inv(Cd) A) x = A.T inv(Cd) d.

Parameters:

A (numpy.ndarray) – Design matrix.
d (array_like) – Observation vector.
inv_Cd (numpy.ndarray) – Inverse of data covariance matrix.

Returns:

N (numpy.ndarray) – A.T inv(Cd) A.
Nd (numpy.ndarray) – A.T inv(Cd) d (column vector).