label=r"$-f_{sig}(t)\ \sin(\omega t)$",
)
plot(t * 1e6, 1e-6 * full_wave.real, "b-", alpha=0.8, marker="None", linewidth=2, label=r"$f_{sig}(t)\ \cos(\omega t)$")
xlabel("Time ($\mu s$)", fontsize=14)
ylabel("V", fontsize=14)
xlim(4, 6)
subplot(212)
output = np.fft.fft(full_wave)
plot(1e-6 * unfuckup(np.fft.fftfreq(len(full_wave), 1.0 / f_sample)), 1e-18 * unfuckup(abs(output) ** 2), "-")
LO_freq = lofreq / 256.0 * 200
ylim(1e-5, ylim()[1] * 10)
bleh = ylim()
semilogy([0, 0], bleh, "k:")
text(-9, 1, r"$%.3f MHz$" % (-LO_freq - 6), fontsize=16)
text(-4, 0.1, r"$%.3f MHz$" % (-LO_freq), fontsize=16)
text(3, 1, r"$%.3f MHz$" % (-LO_freq + 6), fontsize=16)
ylim(*bleh)
# legend(loc=2, fontsize=14)
xlim(-15, 15)
xlabel("Frequency (MHz)", fontsize=14)
ylabel("Power", fontsize=14)
subplot(211)
tfilt, vfilt = fourier_filter(output, 200e6, kill_freqs=(-3.125e6, -9.125e6), kill_radius=5)
plot(tfilt * 1e6, 1e-6 * vfilt.real, "k-", linewidth=5, label="Re[Filtered]")
plot(tfilt * 1e6, 1e-6 * vfilt.imag, "k-", linewidth=5, alpha=0.5, label="Im[Filtered]")
xlim(3.9, 5.1)
legend(fontsize=14)
subplot(211)
text(-3.9, 0.4, r"$-4.1 MHz$", fontsize=14)
text(-1.3, 0.6, r"$-0.1 MHz$", fontsize=14)
text(0.3, 0.6, r"$0.1 MHz$", fontsize=14)
text(2.9, 0.4, r"$4.1 MHz$", fontsize=14)
subplot(212)
text(-3.8, 0.4, r"$-3.9 MHz$", fontsize=14)
text(-1.3, 0.6, r"$-0.1 MHz$", fontsize=14)
text(0.3, 0.6, r"$0.1 MHz$", fontsize=14)
text(2.9, 0.4, r"$3.9 MHz$", fontsize=14)
ylim(0, 0.9)
# now the fourier filtered waveform
figure(3)
subplot(121)
t, v = fourier_filter(np.fft.fft(data_p), 1.0 / dt, kill_freqs=(4.1e6, -4.1e6), kill_radius=5)
plot(t * 1e6, v, "-", color="Orange", linewidth=2)
xlabel(r"Time ($\mu s$)", fontsize=14)
ylabel("V", fontsize=14)
xlim(100, 120)
ylim(-0.25, 0.25)
subplot(122)
t, v = fourier_filter(np.fft.fft(data_m), 1.0 / dt, kill_freqs=(3.9e6, -3.9e6), kill_radius=5)
plot(t * 1e6, v, "-", color="Blue", linewidth=2)
xlabel(r"Time ($\mu s$)", fontsize=14)
xlim(100, 120)
ylim(-0.25, 0.25)
gca().set_yticklabels([], visible=False)
