def test_sparam_conversion_vs_sdefinition(self):
'''
Check that power-wave or pseudo-waves scattering parameters definitions
give same results for real characteristic impedances
'''
f0 = rf.Frequency(75.8, npoints=1, unit='GHz')
s_ref = npy.array([[ # random values
[-0.1000 -0.2000j, -0.3000 +0.4000j],
[-0.3000 +0.4000j, 0.5000 -0.6000j]]])
ntw = rf.Network(frequency=f0, s=s_ref, z0=50, name='dut')
# renormalize s parameter according one of the definition.
# As characteristic impedances are all real, should be all equal
npy.testing.assert_allclose(ntw.s, s_ref)
npy.testing.assert_allclose(rf.renormalize_s(ntw.s, 50, 50, s_def='power'), s_ref)
npy.testing.assert_allclose(rf.renormalize_s(ntw.s, 50, 50, s_def='pseudo'), s_ref)
npy.testing.assert_allclose(rf.renormalize_s(ntw.s, 50, 50, s_def='traveling'), s_ref)
# also check Z and Y matrices, just in case
z_ref = npy.array([[
[18.0000 -16.0000j, 20.0000 + 40.0000j],
[20.0000 +40.0000j, 10.0000 -80.0000j]]])
npy.testing.assert_allclose(ntw.z, z_ref, atol=1e-4)
y_ref = npy.array([[
[0.0251 +0.0023j, 0.0123 -0.0066j],
[0.0123 -0.0066j, 0.0052 +0.0055j]]])
npy.testing.assert_allclose(ntw.y, y_ref, atol=1e-4)
# creating network by specifying s-params definition
ntw_power = rf.Network(frequency=f0, s=s_ref, z0=50, s_def='power')
ntw_pseudo = rf.Network(frequency=f0, s=s_ref, z0=50, s_def='pseudo')
ntw_legacy = rf.Network(frequency=f0, s=s_ref, z0=50, s_def='traveling')
self.assertTrue(ntw_power == ntw_pseudo)
self.assertTrue(ntw_power == ntw_legacy)
def test_sparam_conversion_with_complex_char_impedance(self):
'''
Renormalize a 2-port network wrt to complex characteristic impedances
using power-waves definition of s-param
Example based on scikit-rf issue #313
'''
f0 = rf.Frequency(75.8, npoints=1, unit='GHz')
s0 = npy.array([[-0.194 - 0.228j, -0.721 + 0.160j],
[-0.721 + 0.160j, +0.071 - 0.204j]])
ntw = rf.Network(frequency=f0, s=s0, z0=50, name='dut')
# complex characteristic impedance to renormalize to
zdut = 100 + 10j
# reference solutions obtained from ANSYS Circuit or ADS (same res)
# case 1: z0=[50, zdut]
s_ref = npy.array(
[[[-0.01629813 - 0.29764199j, -0.6726785 + 0.24747539j],
[-0.6726785 + 0.24747539j, -0.30104687 - 0.10693578j]]])
npy.testing.assert_allclose(rf.z2s(ntw.z, z0=[50, zdut]), s_ref)
npy.testing.assert_allclose(
rf.renormalize_s(ntw.s, [50, 50], [50, zdut]), s_ref)
# case 2: z0=[zdut, zdut]
s_ref = npy.array([[[
-0.402829859501534 - 0.165007172677339j,
-0.586542065592524 + 0.336098534178339j
],
[
-0.586542065592524 + 0.336098534178339j,
-0.164707376748782 - 0.21617153431756j
]]])
npy.testing.assert_allclose(rf.z2s(ntw.z, z0=[zdut, zdut]), s_ref)
npy.testing.assert_allclose(
rf.renormalize_s(ntw.s, [50, 50], [zdut, zdut]), s_ref)
# Compararing Z and Y matrices from reference ones (from ADS)
# Z or Y matrices do not depend of characteristic impedances.
# Precision is 1e-4 due to rounded results in ADS export files
z_ref = npy.array([[[34.1507 - 65.6786j, -37.7994 + 73.7669j],
[-37.7994 + 73.7669j, 55.2001 - 86.8618j]]])
npy.testing.assert_allclose(ntw.z, z_ref, atol=1e-4)
y_ref = npy.array([[[0.0926 + 0.0368j, 0.0770 + 0.0226j],
[0.0770 + 0.0226j, 0.0686 + 0.0206j]]])
npy.testing.assert_allclose(ntw.y, y_ref, atol=1e-4)
def setUp(self):
self.f0 = rf.Frequency(75.8, npoints=1, unit='GHz')
# initial s-param values of A 2 ports network
self.s0 = np.array([ # dummy values
[-0.1000 -0.2000j, -0.3000 +0.4000j],
[-0.3000 +0.4000j, 0.5000 -0.6000j]]).reshape(-1,2,2)
# build initial network (under z0=50)
self.ntw0 = rf.Network(frequency=self.f0, s=self.s0, z0=50, name='dut')
# complex characteristic impedance to renormalize to
self.zdut = 100 + 10j
# reference solutions obtained from ANSYS Circuit or ADS (same res)
# when z0=[50, zdut]
self.z_ref = np.array([ # not affected by z0
[18.0000 -16.0000j, 20.0000 +40.0000j],
[20.0000 +40.0000j, 10.0000 -80.0000j]]).reshape(-1,2,2)
self.y_ref = np.array([ # not affected by z0
[0.0251 +0.0023j, 0.0123 -0.0066j],
[0.0123 -0.0066j, 0.0052 +0.0055j]]).reshape(-1,2,2)
self.s_ref = np.array([ # renormalized s (power-waves)
[-0.1374 -0.2957j, -0.1995 +0.5340j],
[-0.1995 +0.5340j, -0.0464 -0.7006j]]).reshape(-1,2,2)
# Creating equivalent reference circuit
port1 = rf.Circuit.Port(self.f0, z0=50, name='port1')
port2 = rf.Circuit.Port(self.f0, z0=50, name='port2')
ntw0 = rf.Network(frequency=self.f0, z0=50, s=self.s0, name='dut')
cnx = [ # z0=[50,50]
[(port1, 0), (ntw0, 0)],
[(ntw0, 1), (port2, 0)]
]
self.cir = rf.Circuit(cnx)
# Creating equivalent circuit with z0 real
port2_real = rf.Circuit.Port(self.f0, z0=100, name='port2')
cnx_real = [ # z0=[50,100]
[(port1, 0), (ntw0, 0)],
[(ntw0, 1), (port2_real, 0)]
]
self.cir_real = rf.Circuit(cnx_real)
# Creating equivalent circuit with z0 complex
port2_complex = rf.Circuit.Port(self.f0, z0=self.zdut, name='port2')
cnx_complex = [ # z0=[50,zdut]
[(port1, 0), (ntw0, 0)],
[(ntw0, 1), (port2_complex, 0)]
]
self.cir_complex = rf.Circuit(cnx_complex)
# references for each s-param definition
self.s_legacy = rf.renormalize_s(self.s0, [50,50], [50,self.zdut],
s_def='traveling')
self.s_power = rf.renormalize_s(self.s0, [50,50], [50,self.zdut],
s_def='power')
self.s_pseudo = rf.renormalize_s(self.s0, [50,50], [50,self.zdut],
s_def='pseudo')
# for real values, should be = whatever s-param definition
self.s_real = rf.renormalize_s(self.s0, [50,50], [50,100])
