skrf.calibration.calibrationAlgorithms.one_port_nls

skrf.calibration.calibrationAlgorithms.one_port_nls(measured, ideals)

one port non-linear least squares.

Parameters :

measured : list of Network objects or numpy.ndarray

a list of the measured reflection coefficients. The elements of the list can either a kxnxn numpy.ndarray, representing a s-matrix, or list of 1-port Network objects.

ideals : list of Network objects or numpy.ndarray

a list of the ideal reflection coefficients. The elements of the list can either a kxnxn numpy.ndarray, representing a s-matrix, or list of 1-port Network objects.

Returns :

output : a dictionary

a dictionary containing the following keys:

• ‘error coeffcients’: dictionary containing standard error coefficients
• ‘residuals’: a matrix of residuals from the least squared calculation. see numpy.linalg.lstsq() for more info
• ‘cov_x’: covariance matrix

Notes

Uses scipy.optmize.leastsq() for non-linear least squares calculation