- Normalization.__init__(measured, ideals, sloppy_input=False, is_reciprocal=True, name=None, self_calibration=False, *args, **kwargs)¶
About the order of supplied standards,
If the measured and ideals parameters are lists of Networks and sloppy_input=False, then their elements must align. However, if the measured and ideals are dictionaries, or sloppy_input=True, then we will try to align them for you based on the names of the networks (see func:`align_measured_ideals).
You do not want to use this sloppy_input feature if the calibration depends on the standard order (like TRL).
measured (list/dict of
Networkobjects) – Raw measurements of the calibration standards. The order must align with the ideals parameter ( or use sloppy_input)
ideals (list/dict of
Networkobjects) – Predicted ideal response of the calibration standards. The order must align with ideals list ( or use sloppy_input)
sloppy_input (Boolean.) – Allows ideals and measured lists to be ‘aligned’ based on the network names.
is_reciprocal (Boolean) – enables the reciprocity assumption on the calculation of the error_network, which is only relevant for one-port calibrations.
name (string) – the name of this calibration instance, like ‘waveguide cal’ this is just for convenience [None].
self_calibration (Boolean) – True if there are less ideals than measurements. Used in self-calibration such as LMR, LRRM, where some of the standards can be unknown.
*args (key-word arguments) – stored in self.kwargs, which may be used by sub-classes most likely in run.
**kwargs (key-word arguments) – stored in self.kwargs, which may be used by sub-classes most likely in run.