def plot1D(self, data, fig):
vnafreqs = self.vnafreqs
plt.figure(fig.number)
plt.clf()
fig.suptitle(self.image_filename + '\n' + self.data_filename + '/' +
self.expNum)
ax1 = fig.add_subplot(221)
ax1.plot(np.real(data), np.imag(data))
ax1.set_xlabel('Re(a)')
ax1.set_ylabel('Im(a)')
ax1.ticklabel_format(useOffset=False)
ax2 = fig.add_subplot(222)
ax2.plot(vnafreqs * 1e-9, np.abs(data))
ax2.set_xlabel('VNA freq (GHz)')
ax2.set_ylabel('|a|')
ax2.ticklabel_format(useOffset=False)
ax3 = fig.add_subplot(223)
ax3.plot(vnafreqs * 1e-9, np.angle(data, deg=True))
ax3.set_xlabel('VNA freq (GHz)')
ax3.set_ylabel('angle(a)')
ax3.ticklabel_format(useOffset=False)
ax4 = fig.add_subplot(224)
ax4.plot(vnafreqs * 1e-9, 20 * np.log(np.abs(data)) / np.log(10))
ax4.set_xlabel('VNA freq (GHz)')
ax4.set_ylabel('20 log|a|')
ax4.ticklabel_format(useOffset=False)
if self.fitdata and len(self.fitparams) > 0:
popt = self.fitparams
data_fit = af.complex_a_out(vnafreqs, *popt)
ax1.plot(np.real(data_fit), np.imag(data_fit), '--')
ax2.plot(vnafreqs * 1e-9, np.abs(data_fit), '--')
ax3.plot(vnafreqs * 1e-9, np.angle(data_fit, deg=True), '--')
ax4.plot(vnafreqs * 1e-9,
20 * np.log(np.abs(data_fit)) / np.log(10))
plt.show()
self.saveimage(fig, self.image_filename)
plt.pause(0.1)
def plot1D(self, data, fig):
vnafreqs = self.vnafreqs
plt.figure(fig.number)
plt.clf()
fig.suptitle(self.image_filename+'\n'+self.data_filename+'/'+self.expNum)
ax1 = fig.add_subplot(221)
ax1.plot(np.real(data), np.imag(data))
ax1.set_xlabel('Re(a)')
ax1.set_ylabel('Im(a)')
ax1.ticklabel_format(useOffset=False)
ax2 = fig.add_subplot(222)
ax2.plot(vnafreqs*1e-9, np.abs(data))
ax2.set_xlabel('VNA freq (GHz)')
ax2.set_ylabel('|a|')
ax2.ticklabel_format(useOffset=False)
ax3 = fig.add_subplot(223)
ax3.plot(vnafreqs*1e-9, np.angle(data, deg=True))
ax3.set_xlabel('VNA freq (GHz)')
ax3.set_ylabel('angle(a)')
ax3.ticklabel_format(useOffset=False)
ax4 = fig.add_subplot(224)
ax4.plot(vnafreqs*1e-9, 20 * np.log(np.abs(data)) / np.log(10))
ax4.set_xlabel('VNA freq (GHz)')
ax4.set_ylabel('20 log|a|')
ax4.ticklabel_format(useOffset=False)
if self.fitdata and len(self.fitparams)>0:
popt = self.fitparams
data_fit = af.complex_a_out(vnafreqs, *popt)
ax1.plot(np.real(data_fit),np.imag(data_fit),'--')
ax2.plot(vnafreqs*1e-9,np.abs(data_fit),'--')
ax3.plot(vnafreqs*1e-9,np.angle(data_fit, deg=True),'--')
ax4.plot(vnafreqs*1e-9, 20 * np.log(np.abs(data_fit)) / np.log(10))
plt.show()
self.saveimage(fig, self.image_filename)
plt.pause(0.1)
ki_fit = np.zeros(genpoints)
f_0_guess = 13052250602
kc_guess = 18736539
ki_guess = 5465667
for n in range(genpoints):
data_n = data_complex[n]
popt = af.fit_complex_a_out(vna_freqs,
data_n,
f_0=None,
kc=kc_guess,
ki=ki_guess)
freqs_fit[n] = popt[0]
kc_fit[n] = popt[1]
ki_fit[n] = popt[2]
if debug_fits:
data_n_fit = af.complex_a_out(vna_freqs, *popt)
fig, ax = plt.subplots(2, 2)
ax[0, 0].plot(vna_freqs, np.abs(data_n_fit))
ax[0, 0].plot(vna_freqs, np.abs(data_n))
ax[1, 0].plot(vna_freqs, np.angle(data_n_fit))
ax[1, 0].plot(vna_freqs, np.angle(data_n))
ax[1, 1].plot(np.real(data_n_fit), np.imag(data_n_fit))
ax[1, 1].plot(np.real(data_n_fit), np.imag(data_n))
fig, ax = plt.subplots(3, 1)
ax[0].plot(genfreqs * 1e-9, freqs_fit * 1e-9)
ax[0].set_ylabel('Freq (GHz)')
ax[0].ticklabel_format(useOffset=False)
ax[1].plot(genfreqs * 1e-9, kc_fit * 1e-6)
ax[1].set_ylabel('kc (MHz)')
ax[1].ticklabel_format(useOffset=False)
#
freqs_fit = np.zeros(genpoints)
kc_fit = np.zeros(genpoints)
ki_fit = np.zeros(genpoints)
f_0_guess = 13052250602
kc_guess = 18736539
ki_guess = 5465667
for n in range(genpoints):
data_n = data_complex[n]
popt = af.fit_complex_a_out(vna_freqs, data_n, f_0=None, kc=kc_guess, ki=ki_guess)
freqs_fit[n]=popt[0]
kc_fit[n]=popt[1]
ki_fit[n]=popt[2]
if debug_fits:
data_n_fit = af.complex_a_out(vna_freqs, *popt)
fig, ax = plt.subplots(2,2)
ax[0,0].plot(vna_freqs, np.abs(data_n_fit))
ax[0,0].plot(vna_freqs, np.abs(data_n))
ax[1,0].plot(vna_freqs, np.angle(data_n_fit))
ax[1,0].plot(vna_freqs, np.angle(data_n))
ax[1,1].plot(np.real(data_n_fit),np.imag(data_n_fit))
ax[1,1].plot(np.real(data_n_fit),np.imag(data_n))
fig, ax =plt.subplots(3,1)
ax[0].plot(genfreqs*1e-9, freqs_fit*1e-9)
ax[0].set_ylabel('Freq (GHz)')
ax[0].ticklabel_format(useOffset=False)
ax[1].plot(genfreqs*1e-9, kc_fit*1e-6)
ax[1].set_ylabel('kc (MHz)')
ax[1].ticklabel_format(useOffset=False)
