Convert ^M ...
Jeff Moe
parent
1a1fa72796
commit
d1bbf48030
198
CygnusRFI.py
198
CygnusRFI.py
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@ -1,99 +1,99 @@
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#!/usr/bin/env python
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import os
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import sys
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import argparse
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from time import sleep
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# Define argparse arguments
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parser = argparse.ArgumentParser()
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parser.add_argument("-b", "--bandwidth", type=str, required=True)
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parser.add_argument("-c", "--channels", type=str, default=1024)
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parser.add_argument("-t", "--t_int", type=str, default=0.1)
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parser.add_argument("-d", "--duration", type=str, required=True)
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parser.add_argument("-f", "--fmin", type=float, required=True)
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parser.add_argument("-F", "--fmax", type=float, required=True)
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args = parser.parse_args()
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bandwidth=args.bandwidth
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channels=args.channels
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t_int=args.t_int
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duration=args.duration
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fmin=args.fmin
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fmax=args.fmax
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#Define GRC observation parameters
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bandwidth = str(bandwidth)
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channels = str(channels)
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t_int = str(t_int)
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duration = str(duration)
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fmin = float(fmin)
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fmax = float(fmax)
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nbins = str(int(float(t_int) * float(bandwidth)/float(channels)))
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#Delete pre-existing observation.dat file
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for file_name in os.listdir('.'):
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if file_name.endswith('.dat'):
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try:
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os.remove(file_name)
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except OSError:
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pass
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try:
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os.remove('rfi_plot.png')
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except OSError:
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pass
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print('\n\033[1;33;48m+=================================================================+')
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print('\033[1;33;48m| \033[1;36;48mCygnusRFI\033[1;33;48m:\033[1;32;48m An open-source Radio Frequency Interference analyzer\033[1;33;48m |')
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print('\033[1;33;48m+=================================================================+')
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sleep(0.5)
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print('\n\033[1;33;48m\033[4;33;48mRFI Measurement Parameters:\033[0;32;48m')
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sleep(0.15)
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print(('\033[1;32;48mFrequency range to scan: \033[1;36;48m'+str(float(fmin)/1000000)+'-'+str(float(fmax)/1000000)+' MHz'))
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sleep(0.15)
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print(('\033[1;32;48mBandwidth per spectrum: \033[1;36;48m'+str(float(bandwidth)/1000000)+' MHz'))
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sleep(0.15)
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print(('\033[1;32;48mIntegration time per spectrum: \033[1;36;48m'+duration+' sec'))
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sleep(0.15)
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print(('\033[1;32;48mNumber of channels per spectrum (FFT Size should be a power of 2): \033[1;36;48m'+str(channels)))
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sleep(0.15)
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print(('\033[1;32;48mIntegration time per FFT sample: \033[1;36;48m'+t_int+' sec'))
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sleep(0.5)
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print(("\n\033[1;32;48mEstimated completion time: \033[1;36;48m"+str(float(duration)*float(fmax-fmin)/float(bandwidth))+" sec"))
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sleep(0.5)
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#proceed = eval(input("\n\033[1;36;48mProceed to measurement? [Y/n]: \033[1;33;48m"))
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proceed = 'Y'
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if proceed.lower() != 'n' and proceed.lower() != 'no':
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print('\n\033[1;33;48m+=================================================================+')
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print('\033[1;33;48m| [+] \033[1;32;48m Starting measurement...\033[1;33;48m |')
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print('\033[1;33;48m+=================================================================+\n')
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q=0
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for freq in range(int(fmin), int(fmax), int(float(bandwidth))):
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print(("\033[1;33;48m\n---------------------------------------------------------------------------\n \033[1;33;48m[*] \033[1;32;48mCurrently monitoring f_center = "+str(0.000001*freq)+" +/- "+str(float(float(bandwidth)*0.000001)/2)+" MHz (iteration: "+str(q)+")...\n\033[1;33;48m---------------------------------------------------------------------------"))
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#Define observation frequency
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f_center = str(freq)
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#Execute top_block.py with parameters
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print('\033[0m')
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sys.argv = ['top_block.py', '--c-freq='+f_center, '--samp-rate='+bandwidth, '--nchan='+channels, '--nbin='+nbins, '--obs-time='+duration]
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exec(compile(open('top_block.py', "rb").read(), 'top_block.py', 'exec'))
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os.rename('observation.dat', str(q)+'.dat')
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q = q+1
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print('\n\033[1;33;48m+=================================================================+')
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print('\033[1;33;48m| \033[1;32;48mMeasurement finished!\033[1;33;48m |')
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print('\033[1;33;48m+=================================================================+\n')
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f_center = str(fmin)
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sys.argv = ['rfi_plotter.py', 'freq='+f_center, 'samp_rate='+bandwidth, 'nchan='+channels, 'nbin='+nbins, 'n='+str(q), 'dur='+duration, 'fminimum='+str(fmin), 'fmaximum='+str(fmax)]
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exec(compile(open('rfi_plotter.py', "rb").read(), 'rfi_plotter.py', 'exec'))
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print('\033[1;32;48mYour data has been saved as \033[1;36;48mrfi_plot.png\033[1;32;48m.')
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else:
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print('\n\033[1;31;48m[!] Exiting...\n')
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#!/usr/bin/env python
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import os
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import sys
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import argparse
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from time import sleep
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# Define argparse arguments
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parser = argparse.ArgumentParser()
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parser.add_argument("-b", "--bandwidth", type=str, required=True)
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parser.add_argument("-c", "--channels", type=str, default=1024)
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parser.add_argument("-t", "--t_int", type=str, default=0.1)
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parser.add_argument("-d", "--duration", type=str, required=True)
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parser.add_argument("-f", "--fmin", type=float, required=True)
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parser.add_argument("-F", "--fmax", type=float, required=True)
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args = parser.parse_args()
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bandwidth=args.bandwidth
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channels=args.channels
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t_int=args.t_int
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duration=args.duration
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fmin=args.fmin
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fmax=args.fmax
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#Define GRC observation parameters
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bandwidth = str(bandwidth)
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channels = str(channels)
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t_int = str(t_int)
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duration = str(duration)
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fmin = float(fmin)
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fmax = float(fmax)
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nbins = str(int(float(t_int) * float(bandwidth)/float(channels)))
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#Delete pre-existing observation.dat file
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for file_name in os.listdir('.'):
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if file_name.endswith('.dat'):
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try:
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os.remove(file_name)
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except OSError:
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pass
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try:
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os.remove('rfi_plot.png')
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except OSError:
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pass
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print('\n\033[1;33;48m+=================================================================+')
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print('\033[1;33;48m| \033[1;36;48mCygnusRFI\033[1;33;48m:\033[1;32;48m An open-source Radio Frequency Interference analyzer\033[1;33;48m |')
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print('\033[1;33;48m+=================================================================+')
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sleep(0.5)
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print('\n\033[1;33;48m\033[4;33;48mRFI Measurement Parameters:\033[0;32;48m')
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sleep(0.15)
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print(('\033[1;32;48mFrequency range to scan: \033[1;36;48m'+str(float(fmin)/1000000)+'-'+str(float(fmax)/1000000)+' MHz'))
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sleep(0.15)
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print(('\033[1;32;48mBandwidth per spectrum: \033[1;36;48m'+str(float(bandwidth)/1000000)+' MHz'))
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sleep(0.15)
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print(('\033[1;32;48mIntegration time per spectrum: \033[1;36;48m'+duration+' sec'))
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sleep(0.15)
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print(('\033[1;32;48mNumber of channels per spectrum (FFT Size should be a power of 2): \033[1;36;48m'+str(channels)))
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sleep(0.15)
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print(('\033[1;32;48mIntegration time per FFT sample: \033[1;36;48m'+t_int+' sec'))
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sleep(0.5)
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print(("\n\033[1;32;48mEstimated completion time: \033[1;36;48m"+str(float(duration)*float(fmax-fmin)/float(bandwidth))+" sec"))
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sleep(0.5)
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#proceed = eval(input("\n\033[1;36;48mProceed to measurement? [Y/n]: \033[1;33;48m"))
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proceed = 'Y'
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if proceed.lower() != 'n' and proceed.lower() != 'no':
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print('\n\033[1;33;48m+=================================================================+')
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print('\033[1;33;48m| [+] \033[1;32;48m Starting measurement...\033[1;33;48m |')
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print('\033[1;33;48m+=================================================================+\n')
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q=0
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for freq in range(int(fmin), int(fmax), int(float(bandwidth))):
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print(("\033[1;33;48m\n---------------------------------------------------------------------------\n \033[1;33;48m[*] \033[1;32;48mCurrently monitoring f_center = "+str(0.000001*freq)+" +/- "+str(float(float(bandwidth)*0.000001)/2)+" MHz (iteration: "+str(q)+")...\n\033[1;33;48m---------------------------------------------------------------------------"))
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#Define observation frequency
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f_center = str(freq)
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#Execute top_block.py with parameters
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print('\033[0m')
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sys.argv = ['top_block.py', '--c-freq='+f_center, '--samp-rate='+bandwidth, '--nchan='+channels, '--nbin='+nbins, '--obs-time='+duration]
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exec(compile(open('top_block.py', "rb").read(), 'top_block.py', 'exec'))
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os.rename('observation.dat', str(q)+'.dat')
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q = q+1
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print('\n\033[1;33;48m+=================================================================+')
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print('\033[1;33;48m| \033[1;32;48mMeasurement finished!\033[1;33;48m |')
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print('\033[1;33;48m+=================================================================+\n')
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f_center = str(fmin)
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sys.argv = ['rfi_plotter.py', 'freq='+f_center, 'samp_rate='+bandwidth, 'nchan='+channels, 'nbin='+nbins, 'n='+str(q), 'dur='+duration, 'fminimum='+str(fmin), 'fmaximum='+str(fmax)]
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exec(compile(open('rfi_plotter.py', "rb").read(), 'rfi_plotter.py', 'exec'))
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print('\033[1;32;48mYour data has been saved as \033[1;36;48mrfi_plot.png\033[1;32;48m.')
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else:
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print('\n\033[1;31;48m[!] Exiting...\n')
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182
rfi_plotter.py
182
rfi_plotter.py
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@ -1,91 +1,91 @@
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#!/usr/bin/env python
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try:
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import matplotlib
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matplotlib.use('Agg')
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import numpy as np
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import matplotlib.pyplot as plt
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plt.rcParams.update({'font.size': 32})
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import argparse
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from matplotlib.gridspec import GridSpec
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parser = argparse.ArgumentParser()
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parser.add_argument('freq')
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parser.add_argument('samp_rate')
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parser.add_argument('nchan')
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parser.add_argument('nbin')
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parser.add_argument('n')
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parser.add_argument('dur')
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parser.add_argument('fminimum')
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parser.add_argument('fmaximum')
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args = parser.parse_args()
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def decibel(x):
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return 10.0*np.log10(x)
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#return x
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if __name__ == "__main__":
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#Observation parameters
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exec(args.freq)
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exec(args.samp_rate)
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exec(args.nchan)
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exec(args.nbin)
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exec(args.n)
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exec(args.dur)
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exec(args.fminimum)
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exec(args.fmaximum)
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frequency=freq
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#Load data
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z=1000*(np.fromfile("0.dat", dtype="float32").reshape(-1, nchan)/nbin)
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allarrays=[]
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#N = amount of .dat files
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for i in range(int(n)):
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final = 1000*(np.fromfile(str(i)+".dat", dtype="float32").reshape(-1, nchan)/nbin)
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allarrays.append(final)
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z_final = np.concatenate(allarrays,axis=1)
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#Number of sub-integrations
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nsub = z_final.shape[0]
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#Compute average spectrum
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zmean = np.mean(z_final, axis=0)
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#Compute time axis
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tint = float(nbin*nchan)/samp_rate
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t = tint*np.arange(nsub)
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#Compute frequency axis (convert to MHz)
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allfreq=[]
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for i in range(int(n)):
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freq = np.linspace((frequency+samp_rate*i)-0.5*samp_rate, (frequency+samp_rate*i)+0.5*samp_rate, nchan, endpoint=False)*1e-6
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allfreq.append(freq)
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freq = np.concatenate(allfreq)
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#Initialize plot
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fig = plt.figure(figsize=(5*n,20.25))
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gs = GridSpec(1,1)
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#Plot average spectrum
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ax1 = fig.add_subplot(gs[0,0])
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ax1.plot(freq, decibel(zmean), '#3182bd')
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ax1.fill_between(freq, decibel(zmean), color='#deebf7')
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ax1.set_xlim(np.min(freq), np.max(freq)) #np.min(freq), np.max(freq)
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ax1.set_ylim(np.amin(decibel(zmean))-0.5, np.amin(decibel(zmean))+15)
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ax1.ticklabel_format(useOffset=False)
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ax1.set_xlabel("Frequency (MHz)", labelpad=25)
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ax1.set_ylabel("Relative Power (dB)", labelpad=25)
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try:
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ax1.set_title("\nAveraged RFI Spectrum", pad=25)
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except:
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ax1.set_title("\nAveraged RFI Spectrum")
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ax1.annotate('Frequency range scanned: '+str(float(fminimum)/1000000)+'-'+str(float(fmaximum)/1000000)+' MHz ($\\Delta\\nu$ = '+str(float((fmaximum)-float(fminimum))/1000000)+' MHz)\nBandwidth per spectrum: '+str(float(samp_rate)/1000000)+' MHz\nIntegration time per spectrum: '+str(dur)+" sec\nNumber of channels per spectrum (FFT size): "+str(nchan), xy=(17, 1179), xycoords='axes points', size=32, ha='left', va='top', color='brown')
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ax1.grid()
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plt.tight_layout()
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plt.savefig("rfi_plot.png")
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except Exception as e:
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print(e)
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pass
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#!/usr/bin/env python
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try:
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import matplotlib
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matplotlib.use('Agg')
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import numpy as np
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import matplotlib.pyplot as plt
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plt.rcParams.update({'font.size': 32})
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import argparse
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from matplotlib.gridspec import GridSpec
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parser = argparse.ArgumentParser()
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parser.add_argument('freq')
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parser.add_argument('samp_rate')
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parser.add_argument('nchan')
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parser.add_argument('nbin')
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parser.add_argument('n')
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parser.add_argument('dur')
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parser.add_argument('fminimum')
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parser.add_argument('fmaximum')
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args = parser.parse_args()
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def decibel(x):
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return 10.0*np.log10(x)
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#return x
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if __name__ == "__main__":
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#Observation parameters
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exec(args.freq)
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exec(args.samp_rate)
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exec(args.nchan)
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exec(args.nbin)
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exec(args.n)
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exec(args.dur)
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exec(args.fminimum)
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exec(args.fmaximum)
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frequency=freq
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#Load data
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z=1000*(np.fromfile("0.dat", dtype="float32").reshape(-1, nchan)/nbin)
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allarrays=[]
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#N = amount of .dat files
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for i in range(int(n)):
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final = 1000*(np.fromfile(str(i)+".dat", dtype="float32").reshape(-1, nchan)/nbin)
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allarrays.append(final)
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z_final = np.concatenate(allarrays,axis=1)
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#Number of sub-integrations
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nsub = z_final.shape[0]
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#Compute average spectrum
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zmean = np.mean(z_final, axis=0)
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#Compute time axis
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tint = float(nbin*nchan)/samp_rate
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t = tint*np.arange(nsub)
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#Compute frequency axis (convert to MHz)
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allfreq=[]
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for i in range(int(n)):
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freq = np.linspace((frequency+samp_rate*i)-0.5*samp_rate, (frequency+samp_rate*i)+0.5*samp_rate, nchan, endpoint=False)*1e-6
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allfreq.append(freq)
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freq = np.concatenate(allfreq)
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#Initialize plot
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fig = plt.figure(figsize=(5*n,20.25))
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gs = GridSpec(1,1)
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#Plot average spectrum
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ax1 = fig.add_subplot(gs[0,0])
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ax1.plot(freq, decibel(zmean), '#3182bd')
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ax1.fill_between(freq, decibel(zmean), color='#deebf7')
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ax1.set_xlim(np.min(freq), np.max(freq)) #np.min(freq), np.max(freq)
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ax1.set_ylim(np.amin(decibel(zmean))-0.5, np.amin(decibel(zmean))+15)
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ax1.ticklabel_format(useOffset=False)
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ax1.set_xlabel("Frequency (MHz)", labelpad=25)
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ax1.set_ylabel("Relative Power (dB)", labelpad=25)
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try:
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ax1.set_title("\nAveraged RFI Spectrum", pad=25)
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except:
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ax1.set_title("\nAveraged RFI Spectrum")
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ax1.annotate('Frequency range scanned: '+str(float(fminimum)/1000000)+'-'+str(float(fmaximum)/1000000)+' MHz ($\\Delta\\nu$ = '+str(float((fmaximum)-float(fminimum))/1000000)+' MHz)\nBandwidth per spectrum: '+str(float(samp_rate)/1000000)+' MHz\nIntegration time per spectrum: '+str(dur)+" sec\nNumber of channels per spectrum (FFT size): "+str(nchan), xy=(17, 1179), xycoords='axes points', size=32, ha='left', va='top', color='brown')
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ax1.grid()
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plt.tight_layout()
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plt.savefig("rfi_plot.png")
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except Exception as e:
|
||||
print(e)
|
||||
pass
|
||||
|
|
|
|||
Loading…
Reference in New Issue