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Fourier SNR: change markers with sampling frequency
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parent
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commit
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1 changed files with 38 additions and 5 deletions
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@ -217,18 +217,35 @@ if __name__ == "__main__":
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# plot the snrs
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fig, axs2 = plt.subplots()
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fig.basefname="signal_to_noise_vs_N"
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axs2.set_title("A: {:.2e}, $\\sigma$: {:.2e}".format(sine_amp, noise_sigma))
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axs2.set_xlabel("$N = T*f_s$")
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axs2.set_ylabel("SNR")
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mycolors = {}
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myshapes = { 250: '^', 500: 'v' }
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for i, (f_sample, f_sine, t_lengths) in enumerate(fs_iter):
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if f_sine in mycolors.keys():
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color = mycolors[f_sine]
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else:
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color = None
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if f_sample in myshapes.keys():
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marker = myshapes[f_sample]
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else:
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marker = 'x'
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# plot the means
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l = axs2.plot(t_lengths*f_sample, np.mean(my_snrs[i], axis=-1), marker='*', ls='none', label='f:{}MHz, fs:{}MHz'.format(f_sine, f_sample), markeredgecolor='black')
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l = axs2.plot(t_lengths*f_sample, np.mean(my_snrs[i], axis=-1), color=color, marker=marker, ls='none', label='f:{}MHz, fs:{}MHz'.format(f_sine, f_sample), markeredgecolor='black', mew=0.1)
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color = l[0].get_color()
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mycolors[f_sine] = color
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myshapes[f_sample] = l[0].get_marker()
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for k, t_length in enumerate(t_lengths):
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t_length = np.repeat(t_length * f_sample, my_snrs.shape[-1])
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axs2.plot(t_length, my_snrs[i,k], ls='none', color=color, marker='o', alpha=max(0.01, 1/my_snrs.shape[-1]))
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if True:
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for k, t_length in enumerate(t_lengths):
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t_length = np.repeat(t_length * f_sample, my_snrs.shape[-1])
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axs2.plot(t_length, my_snrs[i,k], ls='none', color=color, marker='o', alpha=max(0.01, 1/my_snrs.shape[-1]))
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axs2.legend()
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@ -236,14 +253,30 @@ if __name__ == "__main__":
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# plot snrs vs T
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fig, axs3 = plt.subplots()
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fig.basefname="signal_to_noise_vs_T"
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axs3.set_title("A: {:.2e}, $\\sigma$: {:.2e}".format(sine_amp, noise_sigma))
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axs3.set_xlabel("time [us]")
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axs3.set_ylabel("SNR")
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#mycolors = {}
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#myshapes = { 250: '^', 500: 'v' }
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for i, (f_sample, f_sine, t_lengths) in enumerate(fs_iter):
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if f_sine in mycolors.keys():
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color = mycolors[f_sine]
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else:
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color = None
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if f_sample in myshapes.keys():
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marker = myshapes[f_sample]
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else:
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marker = 'x'
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# plot the means
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l = axs3.plot(t_lengths, np.mean(my_snrs[i], axis=-1), marker='o', ls='none', label='f:{}MHz, fs:{}MHz'.format(f_sine, f_sample), markeredgecolor='black', markeredgewidth=1)
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l = axs3.plot(t_lengths, np.mean(my_snrs[i], axis=-1), color=color, marker=marker, ls='none', label='f:{}MHz, fs:{}MHz'.format(f_sine, f_sample), markeredgecolor='black', mew=1)
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color = l[0].get_color()
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mycolors[f_sine] = color
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myshapes[f_sample] = l[0].get_marker()
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for k, t_length in enumerate(t_lengths):
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t_length = np.repeat(t_length , my_snrs.shape[-1])
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