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ZH: apply block_filter before determining SNRs
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1 changed files with 25 additions and 6 deletions
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@ -11,7 +11,7 @@ import h5py
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import matplotlib.pyplot as plt
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import matplotlib.pyplot as plt
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import numpy as np
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import numpy as np
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from earsim import REvent
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from earsim import REvent, block_filter
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import aa_generate_beacon as beacon
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import aa_generate_beacon as beacon
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import lib
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import lib
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@ -49,29 +49,48 @@ if __name__ == "__main__":
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beacon_amp = np.max(txdata['amplitudes'])# mu V/m
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beacon_amp = np.max(txdata['amplitudes'])# mu V/m
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if True: # Apply filter to raw beacon/noise to compare with Filtered Traces
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myfilter = lambda x: block_filter(x, dt, pb[0], pb[1])
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else: # Compare raw beacon/noise with Filtered Traces
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myfilter = lambda x: x
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##
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##
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## Beacon vs Noise SNR
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## Beacon vs Noise SNR
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##
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##
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if True:
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if True:
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beacon_snrs = [ lib.signal_to_noise(beacon_amp*ant.beacon, ant.noise, samplerate=1/dt, signal_band=beacon_pb) for ant in antennas ]
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beacon_snrs = [ lib.signal_to_noise(myfilter(beacon_amp*ant.beacon), myfilter(ant.noise), samplerate=1/dt, signal_band=beacon_pb) for ant in antennas ]
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fig, ax = plt.subplots()
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fig, ax = plt.subplots()
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ax.set_title("Maximum Beacon SNR")
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ax.set_title("Maximum Beacon/Noise SNR")
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ax.set_xlabel("Antenna no.")
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ax.set_xlabel("Antenna no.")
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ax.set_ylabel("SNR")
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ax.set_ylabel("SNR")
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ax.plot([ int(ant.name) for ant in antennas], beacon_snrs, 'o', ls='none')
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ax.plot([ int(ant.name) for ant in antennas], beacon_snrs, 'o', ls='none')
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if fig_dir:
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if fig_dir:
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fig.savefig(path.join(fig_dir, path.basename(__file__) + f".beacon_snr.pdf"))
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fig.savefig(path.join(fig_dir, path.basename(__file__) + f".beacon_vs_noise_snr.pdf"))
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##
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##
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## Beacon vs Total SNR
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##
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if True:
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beacon_snrs = [ lib.signal_to_noise(myfilter(beacon_amp*ant.beacon), ant.E_AxB, samplerate=1/dt, signal_band=beacon_pb) for ant in antennas ]
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fig, ax = plt.subplots()
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ax.set_title("Maximum Beacon/Total SNR")
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ax.set_xlabel("Antenna no.")
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ax.set_ylabel("SNR")
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ax.plot([ int(ant.name) for ant in antennas], beacon_snrs, 'o', ls='none')
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if fig_dir:
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fig.savefig(path.join(fig_dir, path.basename(__file__) + f".beacon_vs_total_snr.pdf"))
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##
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## Airshower signal vs Noise SNR
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## Airshower signal vs Noise SNR
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##
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##
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if True:
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if True:
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shower_snrs = [ lib.signal_to_noise(ant.E_AxB, ant.noise, samplerate=1/dt, signal_band=pb) for ant in antennas ]
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shower_snrs = [ lib.signal_to_noise(ant.E_AxB, myfilter(ant.noise), samplerate=1/dt, signal_band=pb) for ant in antennas ]
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fig, ax = plt.subplots()
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fig, ax = plt.subplots()
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ax.set_title("Total (Signal+Beacon+Noise) SNR")
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ax.set_title("Total (Signal+Beacon+Noise)/Noise SNR")
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ax.set_xlabel("Antenna no.")
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ax.set_xlabel("Antenna no.")
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ax.set_ylabel("SNR")
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ax.set_ylabel("SNR")
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ax.plot([ int(ant.name) for ant in antennas], shower_snrs, 'o', ls='none')
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ax.plot([ int(ant.name) for ant in antennas], shower_snrs, 'o', ls='none')
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