def test_plot_nyquist():
frequencies = [1000.0, 1.0, 0.01]
Z = np.array([1, 2, 3]) + 1j * np.array([2, 3, 4])
_, ax = plt.subplots()
ax = plot_nyquist(ax, frequencies, Z)
xs, ys = ax.lines[0].get_xydata().T
assert (xs == Z.real).all() and (ys == -Z.imag).all()
"pulse_params": {
"centers": centers,
"pots": pots,
"widths": widths
},
"eis_params": {
"start_freq": start_freq,
"end_freq": end_freq,
"points": points,
},
"eis_results": eis_exp,
"pulse_results": pulse_exp,
}
ana_results[sno] = {"randles": copy(res_randles), "rrc": copy(res_rrc)}
import matplotlib.pyplot as plt
from impedance.plotting import plot_nyquist
fig, ax = plt.subplots(figsize=(5, 5))
plot_nyquist(ax, frequencies, Z)
plot_nyquist(ax, frequencies, RRC.predict(frequencies))
plot_nyquist(ax, frequencies, randles.predict(frequencies))
plt.show()
fig, ax = plt.subplots(3, 3)
ax = ax.flatten()
for i in range(9):
ax[i].plot(np.array(pulse_exp["data"])[:, i])
plt.show()
]
# ФИТТИНГ
Z_fitB = circuitB.predict(frequencies)
# Погрешность
res_meas_real = (Z - circuitB.predict(frequencies)).real / np.abs(Z)
res_meas_imag = (Z - circuitB.predict(frequencies)).imag / np.abs(Z)
# ploting
plt.figure(figsize=(6, 6))
ax1 = plt.subplot(221)
ax2 = plt.subplot(222)
ax3 = plt.subplot(223)
ax4 = plt.subplot(224)
#GRAFS
plot_bode(axes=(ax1, ax2), f=frequencies, Z=Z, fmt='o')
plot_bode(axes=(ax1, ax2), f=frequencies, Z=Z_fitB)
plot_nyquist(ax3, frequencies, Z, fmt='o')
plot_nyquist(ax3, frequencies, Z_fitB)
#ERROR
ax4.plot(frequencies,
res_meas_real,
'-',
label=r'$\Delta_{\mathrm{Real}}$')
ax4.plot(frequencies,
res_meas_imag,
'-',
label=r'$\Delta_{\mathrm{Imag}}$')
ax4.set_title('Measurement Model Error', fontsize=12)
ax4.tick_params(axis='both', which='major', labelsize=12)
ax4.set_ylabel('$\Delta$ $(\%)$', fontsize=10)
ax4.set_xlabel('$f$ [Hz]', fontsize=10)
ax4.set_xscale('log')
del connection
pstat.SetCell(GamryCOM.CellOff)
pstat.Close()
import matplotlib.pyplot as plt
plt.scatter(np.array(Zreal),-np.array(Zimag),c=np.log(Zfreq))
plt.colorbar()
plt.axis('equal')
plt.show()
from impedance.circuits import CustomCircuit
frequencies = np.array(Zfreq)
Z = np.array(Zreal)+1j*np.array(Zimag)
circuit = 'R0-p(R1,C1)'
guess = [np.min(Z.real),np.max(Z.real),10**-6]
circuit_mod = CustomCircuit(circuit,initial_guess=guess)
circuit_mod.fit(frequencies, Z)
Z_fit = circuit_mod.predict(frequencies)
import matplotlib.pyplot as plt
from impedance.plotting import plot_nyquist
fig, ax = plt.subplots()
plot_nyquist(ax, frequencies, Z, fmt='o')
plot_nyquist(ax, frequencies, Z_fit, fmt='-')
plt.legend(['Data', 'Fit'])
plt.show()