265 lines
6.3 KiB
Python
265 lines
6.3 KiB
Python
# coding: utf-8
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from __future__ import print_function, division, unicode_literals
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import numpy as np
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import uncertainties.umath as um
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import matplotlib.pyplot as plt
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from lab import *
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##
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## Impedence of an inductor (I)
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## (all SI units)
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## measured quantities
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R = ufloat(996, 4) # resistor
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Rl = ufloat(19.9, 0.1) # internal resistance (inductor)
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# frequency
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nu = array(60, 100, 200, 500, 800, 1.2e3, 1.6e3, 2e3, 3e3, 5e3,
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10e3, 15e3, 20e3, 30e3, 40e3, 50e3, 80e3, 100e3, 200e3, 300e3)
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# V input
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Va = array(9.60, 9.60, 9.60, 9.60, 9.60, 9.60, 9.60, 9.80, 9.80, 9.80,
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9.80, 9.60, 9.60, 9.80, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0)/2
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# V output
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Vb = array(9.40, 9.40, 9.20, 9.20, 9.20, 9.20, 9.20, 9.40, 9.20, 9.20,
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8.30, 7.45, 6.81, 5.77, 5.20, 4.63, 3.45, 2.96, 1.73, 1.21)/2
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# time offset Va - Vb
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Oab = -array(100e-6, 80e-6, 20e-6, 20e-6, 12e-6, 8e-6, 8e-6, 8e-6, 6e-6, 3e-6,
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4.5e-6, 4.1e-6, 3.9e-6, 3.5e-6, 3.1e-6, 2.8e-6, 2.1e-6, 1.8e-6, 1.1e-6, 780e-9)
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# time offset I - V
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Oiv = array( 3e-4, 2.1e-4, 1e-4, 65e-6, 88e-6, 80e-6, 78e-6, 72e-6, 56e-6, 40e-6,
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22e-6, 16.1e-6, 12.2e-6, 8.2e-6, 6.1e-6, 4.9e-6, 3.1e-6, 2.5e-6, 1.26e-6, 840e-9)
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## derived quantities
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om = 2*np.pi*nu # angular frequency
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I = Vb/R.n # output current
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Vab = Va - Vb # tension drop
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Fab = om * Oab # phase difference Vᵢ - Vₒ
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Fiv = om * Oiv # phase difference I - Vₒ
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Z = Vab/I * np.exp(1j*Fiv) # impedance
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H1 = Vab/Vb * np.exp(1j*Fab) # transfer function ΔV→Vb
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H2 = Vb/Va * np.exp(1j*Fab) # transfer function Va→Vb
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## estimate uncertainties
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Evb, Eva = ufloat(Vb[0], 0.15), ufloat(Va[0], 0.15)
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# uncertainties Oiv
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sigmaOiv = array(5e-4, 5e-4, 5e-4, 1e-06, 1e-06, 1e-06, 1e-06, 1e-06, 1e-06, 1e-06,
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1e-06, 1e-07, 1e-07, 1e-07, 1e-07, 1e-07, 1e-07, 1e-07, 5e-08, 5e-08)
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# uncertainties Oab
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sigmaOab = array(5e-06, 5e-06, 5e-06, 5e-06, 2e-06, 2e-06, 2e-06, 2e-06, 2e-06, 2e-06,
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2e-07, 2e-07, 2e-07, 2e-07, 2e-07, 2e-07, 2e-07, 2e-07, 2e-07, 2e-08)
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# phase uncertainties
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sigmaFiv = sigmaOiv * 2*np.pi*nu
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sigmaFab = sigmaOab * 2*np.pi*nu
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# magnitude ucnertainties
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sigmaZ = (R*(Eva-Evb)/Evb).s
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sigmaH1 = ((Eva-Evb)/Evb).s
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sigmaH2 = ((Evb-Eva)/Evb).s
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## plot and fit Z(ν)
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plt.figure(4)
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plt.clf()
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# magnitude
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plt.subplot(2, 1, 1)
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plt.title('impedance (RL circuit)')
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plt.xscale('log')
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plt.ylabel('magnitude (kΩ)')
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plt.scatter(nu, abs(Z)/1e3, color="#36913d")
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x = np.arange(nu.min()-10, nu.max()+2e3, 10)
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# fit |Z|(ω) = √(Rl² + (iωL)²)
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f = lambda x, Rl, L: np.sqrt(Rl**2 + (2*np.pi*L * x)**2)
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f, (Rlo, L1) = curve(nu, abs(Z), f, sigmaZ, guess=[Rl.n, 0.04], method='trf')
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plt.plot(x, f(x)/1e3, color="#36913d")
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alpha = check_measures(Rl, Rlo)
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beta = chi_squared_fit(nu, abs(Z), f, sigmaZ)
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print(mformat('''
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# fit magnitude Z
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L₁: {} H
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Rlₒ₁: {} Ω
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compatibility test Rl/Rlₒ₁:
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α={:.2f}, α>ε: {}
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χ² test:
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β={:.2f}, β>ε: {}
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''', L1, Rlo,
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alpha, alpha>epsilon,
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beta, beta>epsilon))
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# phase
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plt.subplot(2, 1, 2)
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plt.xscale('log')
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plt.xlabel('frequency (Hz)')
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plt.ylabel('phase (rad)')
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plt.scatter(nu, Fiv, color="#33859d")
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# fit ∠Z(ω) = arctan(ωL/Rl)
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f = lambda x, Rl, L: np.arctan(2*np.pi*x*L/Rl)
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f, (Rlo2, L2) = curve(nu, Fiv, f, sigmaFiv, guess=[Rl.n, L1.n])
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plt.plot(x, f(x), color="#245361")
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plt.show()
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alpha = check_measures(Rl, Rlo2)
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beta = chi_squared_fit(nu, Fiv, f, sigmaFiv)
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print(mformat('''
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# fit phase Z
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L₂: {} H
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Rlₒ₂: {} Ω
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compatibility test Rl/Rlₒ₂:
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α={:.2f}, α>ε: {}
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χ² test:
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β={:.2f}, β>ε: {}
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''', L2, Rlo2,
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alpha, alpha>epsilon,
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beta, beta>epsilon))
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## plot, fit H₁(ν)
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plt.figure(5)
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plt.clf()
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# magnitude
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plt.subplot(2,1,1)
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plt.title('transmission function 1')
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plt.xscale('log')
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plt.ylabel('amplitude (Vout-Vin / Vout)')
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plt.scatter(nu, abs(H1), color="#2e3340")
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# fit |H₁|(ω) = √(Rl² + (iωL)²)/R
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f = lambda x, R, L: np.sqrt(Rl.n**2 + (2*np.pi*L*x)**2)/R
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f, (Ro1, L1) = curve(nu, abs(H1), f, sigmaH1, guess=[R.n, L1.n]) # NB. does not converge adding Rl
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plt.plot(x, f(x), color="#61778d")
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alpha = check_measures(R, Ro1)
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beta = chi_squared_fit(nu, abs(H1), f, sigmaH1)
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print(mformat('''
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# fit magnitude H₁
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L₁: {} H
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Rₒ₁: {} Ω
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compatibility test R/Rₒ₁:
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α={:.2f}, α>ε: {}
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χ² test:
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γ={:.2f}, γ>ε: {}
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''', L1, Ro1,
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alpha, alpha>epsilon,
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beta, beta>epsilon))
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# phase
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plt.subplot(2,1,2)
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plt.xscale('log')
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plt.xlabel('frequency (Hz)')
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plt.ylabel('phase (rad)')
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plt.scatter(nu, Fab, color="#a54242")
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# fit ∠H₁(ω) = arctan(-ωL/(R+Rl))
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f = lambda x, Re, L: np.arctan(-2*np.pi*L/Re * x)
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f, (Re, L2) = curve(nu, Fab, f, sigmaFab, guess=[Rl.n+R.n, L1.n])
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plt.plot(x, f(x), color='#cc6666')
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plt.show()
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alpha = check_measures(Rl+R, Re)
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beta = chi_squared_fit(nu, Fab, f, 2*sigmaFab)
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print(mformat('''
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# fit phase H₁
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L₂: {} H
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Re: {} Ω
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compatibility test (Rl+R)/Re:
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α={:.2f}, α>ε: {}
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χ² test:
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β={:.2f}, γ>ε: {}
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''', L2, Re,
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alpha, alpha>epsilon,
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beta, beta>epsilon))
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## plot, fit H₂(ν)
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plt.figure(6)
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plt.clf()
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# magnitude
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plt.subplot(2,1,1)
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plt.title('transmission function 2')
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plt.xscale('log')
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plt.ylabel('amplitude (Vout / Vin)')
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plt.scatter(nu, abs(H2), color='#845336')
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# fit |H₂|(ω) = R/√((Rl+R)² + (ωL)²) ≈ 1/√(1 + (iωL)²)
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f = lambda x, R, L: 1/np.sqrt(1 + (2*np.pi*L*x/R)**2)
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f, (Ro1, L1) = curve(nu, abs(H2), f, sigmaH2, guess=[R.n, L1.n])
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plt.plot(x, f(x), color="#8c4f4a")
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alpha = check_measures(R, Ro1)
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beta = chi_squared_fit(nu, abs(H2), f, sigmaH2)
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print(mformat('''
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# fit magnitude H₂
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L₁: {} H
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Rₒ₁: {} Ω
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compatibility test R/Rₒ₁:
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α={:.2f}, α>ε: {}
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χ² test:
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γ={:.2f}, γ>ε: {}
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''', L1, Ro1,
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alpha, alpha>epsilon,
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beta, beta>epsilon))
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# phase
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plt.subplot(2,1,2)
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plt.xscale('log')
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plt.xlabel('frequency (Hz)')
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plt.ylabel('phase (rad)')
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plt.scatter(nu, Fab, color='#5c6652')
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# fit ∠H₁(ω) = arctan(-ωL/(R+Rl))
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f = lambda x, Re, L: np.arctan(-2*np.pi*L/Re * x)
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f, (Re, L2) = curve(nu, Fab, f, sigmaFab, guess=[Rl.n+R.n, L1.n])
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plt.plot(x, f(x), color='#718062')
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plt.show()
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alpha = check_measures(Rl+R, Re)
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beta = chi_squared_fit(nu, Fab, f, 2*sigmaFab)
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print(mformat('''
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# fit phase H₂
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L₂: {} H
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Re: {} Ω
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compatibility test (Rl+R)/Re:
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α={:.2f}, α>ε: {}
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χ² test:
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β={:.2f}, γ>ε: {}
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''', L2, Re,
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alpha, alpha>epsilon,
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beta, beta>epsilon))
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plt.show()
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