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 1



M. C. A. M. Koolen, J. A. M. Geelen and M. P. J. G. Versleijen, “An improved de-embedding technique for on-wafer high frequency characterization”, IEEE 1991 Bipolar Circuits and Technology Meeting, pp. 188-191, Sep. 1991.


>>> 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