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ZH: figures showing baseline diff reconstruction in time domain
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parent
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commit
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1 changed files with 36 additions and 22 deletions
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@ -160,11 +160,11 @@ if __name__ == "__main__":
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##############################
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##############################
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# Compare actual time shifts #
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# Compare actual time shifts #
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##############################
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##############################
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antenna_time_shifts = { a.name: a.attrs['clock_offset'] for a in sorted(antennas, key=lambda a: int(a.name)) }
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actual_antenna_time_shifts = { a.name: a.attrs['clock_offset'] for a in sorted(antennas, key=lambda a: int(a.name)) }
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if True:
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if True:
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actual_phase_shifts = [ -1*lib.phase_mod(2*np.pi*f_beacon*v) for k,v in antenna_time_shifts.items() ]
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actual_antenna_phase_shifts = [ -1*lib.phase_mod(2*np.pi*f_beacon*v) for k,v in actual_antenna_time_shifts.items() ]
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antenna_names = [int(k)-1 for k,v in antenna_time_shifts.items() ]
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antenna_names = [int(k)-1 for k,v in actual_antenna_time_shifts.items() ]
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for i in range(2):
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for i in range(2):
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plot_residuals = i == 1
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plot_residuals = i == 1
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@ -179,7 +179,7 @@ if __name__ == "__main__":
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secax.set_xlabel('Time $\\Delta\\varphi/(2\\pi f_{beac})$ [ns]')
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secax.set_xlabel('Time $\\Delta\\varphi/(2\\pi f_{beac})$ [ns]')
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if plot_residuals:
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if plot_residuals:
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phase_residuals = lib.phase_mod(mean_sigma_phase - actual_phase_shifts)
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phase_residuals = lib.phase_mod(mean_sigma_phase - actual_antenna_phase_shifts)
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fig.suptitle("Difference between Measured and Actual phases\n for Antenna $i$")
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fig.suptitle("Difference between Measured and Actual phases\n for Antenna $i$")
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axs[-1].set_xlabel("Antenna Phase Residual $\\Delta_\\varphi$")
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axs[-1].set_xlabel("Antenna Phase Residual $\\Delta_\\varphi$")
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else:
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else:
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@ -193,7 +193,7 @@ if __name__ == "__main__":
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axs[i].hist(phase_residuals, bins='sqrt', alpha=0.8, color=colors[0])
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axs[i].hist(phase_residuals, bins='sqrt', alpha=0.8, color=colors[0])
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else:
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else:
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axs[i].hist(mean_sigma_phase, bins='sqrt', density=False, alpha=0.8, color=colors[0], ls='solid' , histtype='step', label='Measured')
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axs[i].hist(mean_sigma_phase, bins='sqrt', density=False, alpha=0.8, color=colors[0], ls='solid' , histtype='step', label='Measured')
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axs[i].hist(actual_phase_shifts, bins='sqrt', density=False, alpha=0.8, color=colors[1], ls='dashed', histtype='step', label='Actual')
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axs[i].hist(actual_antenna_phase_shifts, bins='sqrt', density=False, alpha=0.8, color=colors[1], ls='dashed', histtype='step', label='Actual')
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i=1
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i=1
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@ -202,7 +202,7 @@ if __name__ == "__main__":
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axs[i].plot(phase_residuals, np.arange(N_ant), alpha=0.6, ls='none', marker='x', color=colors[0])
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axs[i].plot(phase_residuals, np.arange(N_ant), alpha=0.6, ls='none', marker='x', color=colors[0])
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else:
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else:
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axs[i].errorbar(mean_sigma_phase, np.arange(N_ant), yerr=std_sigma_phase, marker='4', alpha=0.7, ls='none', color=colors[0], label='Measured')
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axs[i].errorbar(mean_sigma_phase, np.arange(N_ant), yerr=std_sigma_phase, marker='4', alpha=0.7, ls='none', color=colors[0], label='Measured')
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axs[i].plot(actual_phase_shifts, antenna_names, ls='none', marker='3', alpha=0.8, color=colors[1], label='Actual')
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axs[i].plot(actual_antenna_phase_shifts, antenna_names, ls='none', marker='3', alpha=0.8, color=colors[1], label='Actual')
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axs[i].legend()
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axs[i].legend()
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fig.tight_layout()
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fig.tight_layout()
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@ -217,31 +217,45 @@ if __name__ == "__main__":
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##########################
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##########################
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##########################
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##########################
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actual_time_shifts = []
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actual_baseline_time_shifts = []
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for i,b in enumerate(basenames):
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for i,b in enumerate(basenames):
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actual_time_shift = lib.phase_mod(lib.phase_mod(antenna_time_shifts[b[0]]*2*np.pi*f_beacon) - lib.phase_mod(antenna_time_shifts[b[1]]*2*np.pi*f_beacon))
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actual_baseline_time_shift = actual_antenna_time_shifts[b[0]] - actual_antenna_time_shifts[b[1]]
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actual_time_shifts.append(actual_time_shift)
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actual_baseline_time_shifts.append(actual_baseline_time_shift)
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# unpack mean_sigma_phase back into a list of time diffs
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# unpack mean_sigma_phase back into a list of time diffs
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measured_time_diffs = []
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measured_baseline_time_diffs = []
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for i,b in enumerate(basenames):
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for i,b in enumerate(basenames):
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time0, time1 = mean_sigma_phase[name2idx(b[0])], mean_sigma_phase[name2idx(b[1])]
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phase0, phase1 = mean_sigma_phase[name2idx(b[0])], mean_sigma_phase[name2idx(b[1])]
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measured_time_diffs.append(time1 - time0)
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measured_baseline_time_diffs.append(lib.phase_mod(phase1 - phase0)/(2*np.pi*f_beacon))
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# Make a plot
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# Make a plot
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if True:
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if True:
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for i in range(2):
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fig, ax = plt.subplots()
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fig, ax = plt.subplots()
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ax.set_title("Baseline Time difference reconstruction" + ( '' if i == 0 else ' (wrapped time)'))
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ax.set_xlabel("Baseline no.")
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ax.set_xlabel("Baseline no.")
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ax.set_ylabel("$\\Delta t$[ns]")
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ax.set_ylabel("Time $\\Delta t$ [ns]")
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if True:
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forward = lambda x: x/(2*np.pi*f_beacon)
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inverse = lambda x: 2*np.pi*x*f_beacon
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secax = ax.secondary_yaxis('right', functions=(inverse, forward))
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secax.set_ylabel('Phase $\\Delta \\varphi$ [rad]')
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if True: # indicate single beacon period span
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if True: # indicate single beacon period span
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ax.plot((-1, -1), (0, 1/f_beacon), marker='3', ms=10, label='1/f_beacon')
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ax.plot((-1, -1), (-1/(2*f_beacon), 1/(2*f_beacon)), marker='3', ms=10, label='1/f_beacon')
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ax.plot(np.arange(N_base), actual_time_shifts, marker='+', label='actual time shifts')
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if i == 0:
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ax.plot(np.arange(N_base), measured_time_diffs, marker='x', label='calculated')
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ax.plot(np.arange(N_base), actual_baseline_time_shifts, marker='+', label='actual time shifts')
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else:
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ax.plot(np.arange(N_base), (actual_baseline_time_shifts+1/(2*f_beacon))%(1/f_beacon) - 1/(2*f_beacon), marker='+', label='actual time shifts')
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ax.plot(np.arange(N_base), measured_baseline_time_diffs, marker='x', label='calculated')
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ax.legend()
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ax.legend()
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if fig_dir:
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if fig_dir:
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fig.savefig(path.join(fig_dir, __file__ + f".calculated_shifts.pdf"))
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extra_name = ''
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if i == 1:
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extra_name = '.wrapped'
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fig.savefig(path.join(fig_dir, __file__ + f".time_comparison{extra_name}.pdf"))
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if show_plots:
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if show_plots:
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plt.show()
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plt.show()
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