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@maxanier
Created April 6, 2023 12:53
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De-embeding/Extracting Passives - Scikit-RF - Library/Playground
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{
"cells": [
{
"cell_type": "code",
"execution_count": 70,
"metadata": {},
"outputs": [],
"source": [
"# Import library files\n",
"\n",
"import sys\n",
"sys.path.insert(0,'/home/sage/notebooks/Util')\n",
"\n",
"from PassivesLibrary import InductorData, TLData\n",
"from NetworkLibrary import ManualS2P, NetworkS2P\n",
"from skrf import Network, Frequency\n",
"from matplotlib import pyplot as plt \n",
"import skrf as rf\n",
"import numpy as np\n"
]
},
{
"cell_type": "code",
"execution_count": 71,
"metadata": {},
"outputs": [],
"source": [
"name_ind_dut = \"PA1_Chip2_inductor4\" #\"pa1_sim_ind4_full\" #\n",
"name_ind_fixture =\"PA1_Chip2_reference_thru\" # \"pa1_sim_thru_only\" #\n",
"\n",
"name_tl_dut = \"sparam_pa2_ic2_tl1\"\n",
"name_tl_fixture = \"sparam_pa2_ic2_through\""
]
},
{
"cell_type": "code",
"execution_count": 72,
"metadata": {},
"outputs": [],
"source": [
"ind_meas= Network('Data/'+name_ind_dut+\".s2p\")\n",
"ind_fix = Network('Data/'+name_ind_fixture+\".s2p\")\n",
"\n",
"tl_meas = Network('Data/'+name_tl_dut+\".s2p\")\n",
"tl_fix = Network('Data/'+name_tl_fixture+\".s2p\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Inductors\n"
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[1.7517790903993267e-10, 17.552015269428722]"
]
},
"execution_count": 73,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ind_T_net = NetworkS2P.deembed_T(ind_meas, ind_fix)\n",
"ind_T = InductorData.calculateInductance(ind_T_net, \"T\")\n",
"ind_T.valueAt(60e9)"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[1.7391714468909724e-10, 15.735979561400477]"
]
},
"execution_count": 74,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ind_wang_net = NetworkS2P.deembed_wang2022(ind_meas, ind_fix)\n",
"ind_wang = InductorData.calculateInductance(ind_wang_net, \"Wang\")\n",
"ind_wang.valueAt(60e9)"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[-1.651183488901912e-10, 32.69591590897411]"
]
},
"execution_count": 75,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ind_ito_net = NetworkS2P.deembed_ito2008(ind_meas, ind_fix)\n",
"ind_ito = InductorData.calculateInductance(ind_ito_net,\"Ito\")\n",
"ind_ito.valueAt(60e9)"
]
},
{
"cell_type": "code",
"execution_count": 76,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[1.4604285862135812e-10, 23.801094721584526]"
]
},
"execution_count": 76,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ind_splitpi_net = NetworkS2P.deembed_splitpi(ind_meas, ind_fix)\n",
"ind_splitpi = InductorData.calculateInductance(ind_splitpi_net, \"SplitPi\")\n",
"ind_splitpi.valueAt(60e9)"
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[2.0986944277049284e-10, 14.008107849733106]"
]
},
"execution_count": 77,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ind_splittee_net = NetworkS2P.deembed_splittee(ind_meas, ind_fix)\n",
"ind_splittee = InductorData.calculateInductance(ind_splittee_net, \"SplitTee\")\n",
"ind_splittee.valueAt(60e9)"
]
},
{
"cell_type": "code",
"execution_count": 78,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[1.4724099162233888e-10, 29.787904327972292]"
]
},
"execution_count": 78,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ind_splitpi_man_net = NetworkS2P.deembed_splitpi_man(ind_meas, ind_fix)\n",
"ind_splitpi_man = InductorData.calculateInductance(ind_splitpi_man_net, \"SplitPiMan\")\n",
"ind_splitpi_man.valueAt(60e9)"
]
},
{
"cell_type": "code",
"execution_count": 79,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x7f225dac1550>"
]
},
"execution_count": 79,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 1440x504 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig=plt.figure(figsize=(20,7))\n",
"a1 = fig.add_axes([0,0,1,1])\n",
"a1.set_ylim(0,300e-12)\n",
"plt.xlabel(\"Frequency\") \n",
"plt.ylabel(\"Inductance\")\n",
"a1.plot(ind_T.f, ind_T.L, label=\"T\")\n",
"a1.plot(ind_wang.f, ind_wang.L, label=\"Wang\")\n",
"a1.plot(ind_ito.f, ind_ito.L, label=\"Ito\")\n",
"a1.plot(ind_splitpi.f, ind_splitpi.L, label=\"SplitPi\")\n",
"a1.plot(ind_splitpi_man.f, ind_splitpi_man.L, label=\"SplitPiMan\")\n",
"a1.plot(ind_splittee.f, ind_splittee.L, label=\"SplitTee\")\n",
"a1.legend()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Transmissionline"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[73.45918979516456, 329.3707335830435]"
]
},
"execution_count": 80,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tl_T_net = NetworkS2P.deembed_T(tl_meas, tl_fix)\n",
"tl_T = TLData.fromSParam(tl_T_net, 390e-6, \"T\")\n",
"tl_T.valueAt(60e9)"
]
},
{
"cell_type": "code",
"execution_count": 81,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[72.57218738776861, 345.36613558678]"
]
},
"execution_count": 81,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tl_wang_net = NetworkS2P.deembed_wang2022(tl_meas, tl_fix)\n",
"tl_wang = TLData.fromSParam(tl_wang_net, 390e-6, \"Wang\")\n",
"tl_wang.valueAt(60e9)"
]
},
{
"cell_type": "code",
"execution_count": 82,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[65.28881476590682, -2375.5462394561837]"
]
},
"execution_count": 82,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tl_ito_net = NetworkS2P.deembed_ito2008(tl_meas, tl_fix)\n",
"tl_ito = TLData.fromSParam(tl_ito_net, 390e-6, \"Ito\")\n",
"tl_ito.valueAt(60e9)"
]
},
{
"cell_type": "code",
"execution_count": 83,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[69.14112933600389, 363.9013846687261]"
]
},
"execution_count": 83,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tl_splitpi_net = NetworkS2P.deembed_splitpi(tl_meas, tl_fix)\n",
"tl_splitpi = TLData.fromSParam(tl_splitpi_net, 390e-6, \"SplitPi\")\n",
"tl_splitpi.valueAt(60e9)"
]
},
{
"cell_type": "code",
"execution_count": 84,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[68.15465598914787, -911.5558717096484]"
]
},
"execution_count": 84,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tl_splitpi_man_net = NetworkS2P.deembed_splitpi_man(tl_meas, tl_fix)\n",
"tl_splitpi_man = TLData.fromSParam(tl_splitpi_man_net, 390e-6, \"SplitPiMan\")\n",
"tl_splitpi_man.valueAt(60e9)"
]
},
{
"cell_type": "code",
"execution_count": 85,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[73.45918979516456, 329.3707335830435]"
]
},
"execution_count": 85,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tl_splittee_net = NetworkS2P.deembed_T(tl_meas, tl_fix)\n",
"tl_splittee = TLData.fromSParam(tl_splittee_net, 390e-6, \"SplitTee\")\n",
"tl_splittee.valueAt(60e9)"
]
},
{
"cell_type": "code",
"execution_count": 86,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x7f225d715ba8>"
]
},
"execution_count": 86,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 1440x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig=plt.figure(figsize=(20,5))\n",
"a1 = fig.add_axes([0,0,1,1])\n",
"a1.set_ylim(0,100)\n",
"plt.xlabel(\"Frequency\") \n",
"plt.ylabel(\"Impedance\")\n",
"a1.plot(tl_T.f, tl_T.Zc, label=\"T\")\n",
"a1.plot(tl_wang.f, tl_wang.Zc, label=\"Wang\")\n",
"a1.plot(tl_ito.f, tl_ito.Zc, label=\"Ito\")\n",
"a1.plot(tl_splitpi.f, tl_splitpi.Zc, label=\"SplitPi\")\n",
"a1.plot(tl_splittee.f, tl_splittee.Zc, label=\"SplitTee\")\n",
"a1.plot(tl_splitpi_man.f, tl_splitpi_man.Zc, label=\"SplitPiMan\")\n",
"a1.legend()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
from skrf import Network, Frequency
import skrf as rf
import numpy as np
import scipy.linalg as sp_alg
from skrf.calibration import SplitPi, SplitTee
class ManualS2P:
"""Collection of functions dealing with single frequency 2-port scattering parameters represented by np.matrix"""
def s2t(S_source: np.matrix) -> np.matrix:
"""Convert single S-parameter matrix to (Scattering) Transfer matrix."""
#https://en.wikipedia.org/wiki/Scattering_parameters#Scattering_transfer_parameters
S_source_det= np.linalg.det(S_source)
return np.matrix([[-S_source_det/S_source[1,0] , S_source[0,0]/S_source[1,0]],[-S_source[1,1]/S_source[1,0] , 1/S_source[1,0]]] )
def chop_in_half_t(T_combined: np.matrix) -> np.matrix:
"""Takes symmetric recipocal (Scattering) Transfer matrix and splits it at the virtual symmetry (in the center)"""
return sp_alg.sqrtm(T_combined)
def deembed_t(T_combined: np.matrix, T_pre: np.matrix, T_post: np.matrix) -> np.matrix:
"""Takes (Scattering) Transfer matrix and removes given parts from input and output"""
return np.dot(np.dot(np.linalg.inv(T_pre) , T_combined), np.linalg.inv(T_post))
def t2s(T_source: np.matrix) -> np.matrix:
"""Convert single (Scattering) Transfer matrix to S-parameter matrix."""
#https://en.wikipedia.org/wiki/Scattering_parameters#Scattering_transfer_parameters
T_source_det = np.linalg.det(T_source)
return np.matrix([[T_source[0,1]/T_source[1,1], T_source_det/T_source[1,1]] , [ 1/T_source[1,1] , - T_source[1,0] / T_source[1,1]]])
class NetworkS2P:
"""Collection of functions dealing with 2-port scattering parameters over frequency represented with scikit-rf """
def deembed_T(combined: Network, thru: Network) -> Network:
"""Deembeds network
Given a 2-port network that is connected using an identical/symmetrical passive structure at in- and output
and the 2-port network of that combined in- and output structure, the original network is deembeded.
Assuming T_thru = T_half * T_half
Assuming T_combined = T_half * T_dut * T_half
De-embedding: T_dut = T_half^{-1} * T_half * T_dut * T_half * T_half^{-1}
Uses skrf magic.
"""
thru_half = rf.network.chopinhalf(thru)
return thru_half.inv ** combined ** thru_half.inv
def chop_in_half_manual(full: Network) -> Network:
"""Splits a passive network in the virtual center.
Network is assumed to formed of two symmetrical parts and must be reciprocal.
"""
# Manual version of https://scikit-rf.readthedocs.io/en/v0.18.1/api/generated/skrf.network.chopinhalf.html
half_t = np.array([sp_alg.sqrtm(np.matrix(x)) for x in full.t[:]])
half_s = rf.t2s(half_t)
return Network(frequency=full.f/1e9, s=half_s)
def deembed_T_manual(combined: Network, thru: Network) -> Network:
"""Deembeds network
Given a 2-port network that is connected using an identical/symmetrical passive structure at in- and output
and the 2-port network of that combined in- and output structure, the original network is deembeded.
Assuming T_thru = T_half * T_half
Assuming T_combined = T_half * T_dut * T_half
De-embedding: T_dut = T_half^{-1} * T_half * T_dut * T_half * T_half^{-1}
Manual version of #deembed (which uses skrf)
"""
thru_half = NetworkS2P.chop_in_half_manual(thru)
deembeded_t = np.array([ManualS2P.deembed_t(combined.t[i],thru_half.t[i],thru_half.t[i]) for i in range(combined.t[:,0,0].size) ])
deembeded_s = rf.t2s(deembeded_t)
return Network(frequency=combined.f/1e9, s=deembeded_s)
def deembed_wang2022(combined: Network, thru: Network) -> Network:
"""De-embeds network based on Wang2022 approach
https://doi.org/10.1109/LMWC.2022.3173970
Intended to remove a series-shunt fixture.
Based on ABCD parameters
Assuming A_thru = A_left * A_right
Assuming A_combined = A_left * A_dut * A_right
De-embedding A_dut = A_left^{-1} * A_left * A_dut * A_right * A_right^{-1}
Originally, the proposed method requires an ideal length transmission line between pad and DUT, but results are ok even with a different length
"""
wang_A = []
for i in range(len(combined.f)):
x = thru.a[i]
k = x[0,0]**2 - x[0,1]*x[1,0]
a = (x[0,0]+np.sqrt(k)) * np.sqrt((x[0,0]-np.sqrt(k))/(2*x[0,1]*x[1,0]))
b = np.sqrt(x[0,1]*(x[0,0]-np.sqrt(k))/2/x[1,0])
c = np.sqrt(x[1,0]*(x[0,0]-np.sqrt(k))/2/x[0,1])
At = [[a,b],[c,a]]
At_inv = np.linalg.inv(At)
A = np.dot(np.dot(At_inv, combined.a[i]),At_inv)
wang_A.append(A)
return Network(frequency=combined.f/1e9, s=rf.a2s(np.array(wang_A)))
def deembed_ito2008(combined: Network, thru: Network) -> Network:
"""De-embeds network based on Ito2008 approach. Doesn't seem to work
https://doi.org/10.1109/MWSYM.2008.4633183
Splits thru into left and right based on Y parameters and de-embeds based on T parameters.
Assuming Y_half = ?
Assuming T_combined = T_half * T_dut * T_half
De-embedding: T_dut = T_half^{-1} * T_half * T_dut * T_half * T_half^{-1}
"""
ito_y_left = np.array([[ [x[0,0] - x[1,0] , 2*x[1,0]], [2*x[1,0], -2*x[1,0]] ] for x in thru.y[:]])
ito_y_right = np.array([[ [-2*x[0,1] , 2*x[0,1]], [2*x[0,1], x[1,1] - x[0,1]]] for x in thru.y[:]])
ito_left = Network(frequency=thru.f/1e9, s=rf.y2s(ito_y_left))
ito_right = Network(frequency=thru.f/1e9, s=rf.y2s(ito_y_right))
ito_left_t = rf.s2t(ito_left.s)
ito_right_t = rf.s2t(ito_right.s)
ito_t = []
for i in range(len(combined.f)):
ito_t.append(ManualS2P.deembed_t(ito_left_t[i], combined.t[i], ito_right_t[i]))
ito_t = np.array(ito_t)
return Network(frequency=combined.f/1e9, s=rf.t2s(ito_t))
def deembed_splitpi(combined: Network, thru: Network) -> Network:
"""De-embeds network based on Nan2007 approach. Implemented in scikit-rf
https://doi.org/10.1109/RFIC.2007.380889
Intended to remove a shunt-series fixture.
Assuming A_left, Aright=?
Assuming A_combined = A_left * A_dut * A_right
De-embedding A_dut = A_left^{-1} * A_left * A_dut * A_right * A_right^{-1}
"""
return SplitPi(dummy_thru = thru).deembed(combined)
def deembed_splittee(combined: Network, thru: Network) -> Network:
"""De-embeds network based on Kobrinksi2005 approach. Implemented in scikit-rf
https://doi.org/10.1109/TADVP.2004.841672
Intended to remove a series-shunt fixture.
Assuming A_left, Aright=?
Assuming A_combined = A_left * A_dut * A_right
De-embedding A_dut = A_left^{-1} * A_left * A_dut * A_right * A_right^{-1}
"""
return SplitTee(dummy_thru = thru).deembed(combined)
def deembed_splitpi_man(combined: Network, thru: Network) -> Network:
"""De-embeds network based on Nan2007 approach
https://doi.org/10.1109/RFIC.2007.380889
Intended to remove a shunt-series fixture.
Assuming A_left = [[1,z],[y,1+y*z]], A_right = [[1+y*z, z],[y, 1]]
Extracting z and y from Y-Param assuming shunt-series-shunt thru.
Assuming A_combined = A_left * A_dut * A_right
De-embedding A_dut = A_left^{-1} * A_left * A_dut * A_right * A_right^{-1}
"""
nan_A = []
for i in range(len(combined.f)):
x = thru.y[i]
y = x[0,0]+x[0,1]
z = - 1/2/x[0,1]
A_left = [[1,z],[y,1+y*z]]
A_right = [[1+y*z, z],[y, 1]]
A_left_inv = np.linalg.inv(A_left)
A_right_inv = np.linalg.inv(A_right)
A = np.dot(np.dot(A_left_inv, combined.a[i]),A_right_inv)
nan_A.append(A)
return Network(frequency=combined.f/1e9, s=rf.a2s(np.array(nan_A)))
import numpy as np
from matplotlib import pyplot as plt
from skrf import Network, Frequency
import skrf as rf
class InductorData:
"""Represents measured/simulated inductor data composed of L and Q over frequency"""
def __init__(self, f, L, Q, name="Inductor"):
self.f_min = np.min(f)
self.f_max = np.max(f)
self.f = f
self.L = L
self.Q = Q
self.name = name
if self.f[0] == 0: #Inductance at 0Hz does not make any sense and might be NaN
self.L[0] = 0
def valueAt(self, f, Interpolate=True):
if f > self.f_max or f < self.f_min:
raise RuntimeError("Frequency out of bounds", f, self.f_max, self.f_min)
if Interpolate:
return [np.interp(f, self.f, self.L), np.interp(f, self.f, self.Q)]
else:
idx = (np.abs(self.f - f)).argmin()
return [self.L[idx] , self.Q[idx]]
def plot(self):
fig=plt.figure(figsize=(20,5))
a1 = fig.add_axes([0,0,1,1])
a1.set_ylim(0,np.max(self.L[1:]))
plt.title(self.name)
plt.xlabel("Frequency")
plt.ylabel("Inductance")
a1.plot(self.f, self.L)
a2 = a1.twinx()
a2.set_ylim(0,np.max(self.Q))
a2.plot(self.f, self.Q)
def savetxt(self, filepath):
np.savetxt(filepath, np.transpose([self.f, self.L, self.Q]), delimiter=',',fmt='%.5e')
def calculateDiffIndWeird(Sind: Network, name="Differential Inductance"):
"""Accepts a scikit-rf 2 port network and calculates the differential inductance based on Okada2010 10.5772/8435"""
Sdiff = (Sind.s[:,0,0]-Sind.s[:,0,1]-Sind.s[:,1,0]+Sind.s[:,1,1])/2
Zdiff = 2 * 50 * (1+Sdiff)/(1-Sdiff)
Ldiff = 1/2/np.pi/(Sind.f+1e-12)*np.imag(Zdiff)
Qdiff = np.imag(Zdiff)/np.real(Zdiff)
return InductorData(Sind.f, Ldiff, Qdiff, name)
def calculateInductance(Sind: Network, name="Inductor"):
"""Accepts a scikit-rf 2 port network and calculates inductance based on Y-parameter"""
ls = -np.imag(1/Sind.y[:,0,1])/2/3.14/Sind.f
q = np.imag(1/Sind.y[:,0,1])/np.real(1/Sind.y[:,0,1])
return InductorData(Sind.f, ls, q, name)
class TLData:
"""Represents a transmission line over frequency
"""
def __init__(self, f, Zc, Att, name="CPW"):
"""
Att: attenuation in dB per meter
"""
self.f_min = np.min(f)
self.f_max = np.max(f)
self.f = f
self.Zc = Zc
self.Att = Att
self.name = name
def valueAt(self, f, Interpolate=True):
if f > self.f_max or f < self.f_min:
raise RuntimeError("Frequency out of bounds", f, self.f_max, self.f_min)
if Interpolate:
return [np.interp(f, self.f, self.Zc), np.interp(f, self.f, self.Att)]
else:
idx = (np.abs(self.f - f)).argmin()
return [self.Zc[idx] , self.Att[idx]]
def savetxt(self, filepath):
np.savetxt(filepath, np.transpose([self.f, self.Zc, self.Att]), delimiter=',',fmt='%.5e')
def plot(self):
fig=plt.figure(figsize=(20,5))
a1 = fig.add_axes([0,0,1,1])
a1.set_ylim(0,np.max(self.Zc[1:]))
plt.title(self.name)
plt.xlabel("Frequency")
plt.ylabel("Impedance")
a1.plot(self.f, self.Zc)
a2 = a1.twinx()
a2.set_ylim(0,np.max(self.Att))
a2.plot(self.f, self.Att)
def fromSParam(Sind: Network, length, name="TL"):
zc = np.sqrt(Sind.z[:,0,0]/ Sind.y[:,0,0])
gamma = 1/length * np.arctanh(1/zc/Sind.y[:,0,0])
alpha = np.real(gamma)
att = 20*alpha*np.log10(np.exp(1))
return TLData(Sind.f, np.abs(zc), att, name=name)
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