- class skrf.calibration.deembedding.OpenShort(dummy_open, dummy_short, name=None, *args, **kwargs)[source]¶
Remove open parasitics followed by short parasitics.
This is a commonly used de-embedding method for on-wafer applications.
A deembedding object is created with two dummy measurements: dummy_open and dummy_short. When
Deembedding.deembed()is applied, Open de-embedding is applied to the short dummy because the measurement results for the short dummy contains parallel parasitics. Then the Y-parameters of the dummy_open are subtracted from the DUT measurement, followed by subtraction of Z-parameters of dummy-short which is previously de-embedded.
This method is applicable only when there is a-priori knowledge of the equivalent circuit model of the parasitic network to be de-embedded, where the series parasitics are closest to device under test, followed by the parallel parasitics. For more information, see 
>>> import skrf as rf >>> from skrf.calibration import OpenShort
Create network objects for dummy structures and dut
>>> op = rf.Network('open_ckt.s2p') >>> sh = rf.Network('short_ckt.s2p') >>> dut = rf.Network('full_ckt.s2p')
Create de-embedding object
>>> dm = OpenShort(dummy_open = op, dummy_short = sh, name = 'test_openshort')
Remove parasitics to get the actual device network
>>> realdut = dm.deembed(dut)
Open-Short De-embedding Initializer
Perform the de-embedding calculation