pyacs.lib.glinalg.ls

Solve least-squares problem.

pyacs.lib.glinalg.ls.ls(G, d, verbose=False)[source]

Solve the least-squares problem min |Gx - d|**2.

Parameters:

  • G (numpy.ndarray) – m x n design matrix.

  • d (numpy.ndarray) – m observation vector.

  • verbose (bool, optional) – If True, print chi2, rank, singular values. Default is False.

Returns:

  • numpy.ndarray – Solution vector of length n. Note: variable name in code is m.

  • float – Chi-square (residual sum of squares). Only first return value is used in code.

Notes

Solved via numpy.linalg.lstsq.