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#!/usr/bin/env python3
'''plot frame sync debug files'''
import argparse, os, sys
import numpy as np, matplotlib.pyplot as plt
def main(argv=None):
p = argparse.ArgumentParser(description=__doc__)
p.add_argument('sources', nargs='+', help='input files')
p.add_argument('-export', default=None, action='store_true', help='export figure')
p.add_argument('-nodisplay', action='store_true', help='disable display')
args = p.parse_args()
for fname in args.sources:
filename = framesync64_plot(fname,args.export,args.nodisplay)
def framesync64_plot(filename,export=None,nodisplay=True):
# open file and read values
fid = open(filename,'rb')
buf = np.fromfile(fid, count=1440, dtype=np.csingle)
tau_hat = np.fromfile(fid, count= 1, dtype=np.single)
dphi_hat = np.fromfile(fid, count= 1, dtype=np.single)
phi_hat = np.fromfile(fid, count= 1, dtype=np.single)
gamma_hat = np.fromfile(fid, count= 1, dtype=np.single)
evm = np.fromfile(fid, count= 1, dtype=np.single)
payload_rx = np.fromfile(fid, count= 630, dtype=np.csingle)
payload_sym = np.fromfile(fid, count= 600, dtype=np.csingle)
payload_dec = np.fromfile(fid, count= 72, dtype=np.int8)
# compute smooth spectral response in dB
nfft = 2400
f = np.arange(nfft)/nfft-0.5
psd = np.abs(np.fft.fftshift(np.fft.fft(buf, nfft)))**2
m = int(0.01*nfft)
w = np.hamming(2*m+1)
h = np.concatenate((w[m:], np.zeros(nfft-2*m-1), w[:m])) / (sum(w) * nfft)
H = np.fft.fft(h)
psd = 10*np.log10( np.real(np.fft.ifft(H * np.fft.fft(psd))) )
# plot impulse and spectral responses
fig, _ax = plt.subplots(2,2,figsize=(12,12))
ax = _ax.flatten()
t = np.arange(len(buf))
qpsk = np.exp(0.5j*np.pi*(np.arange(4)+0.5)) # payload constellation
ax[0].plot(t,np.real(buf), t,np.imag(buf))
ax[0].set_title('Raw I/Q Samples')
ax[1].plot(f,psd)
ax[1].set(xlim=(-0.5,0.5))
ax[1].set_title('Power Spectral Density')
ax[2].plot(np.real(payload_rx), np.imag(payload_rx), '.')
ax[2].set_title('RX Payload Syms')
ax[3].plot(np.real(payload_sym), np.imag(payload_sym), '.')
ax[3].set_title('Synchronized Payload Syms')
for _ax in ax[2:]:
_ax.set(xlim=(-1.3,1.3), ylim=(-1.3,1.3))
_ax.plot(np.real(qpsk),np.imag(qpsk),'rx')
_ax.set_xlabel('Real')
_ax.set_ylabel('Imag')
for _ax in ax:
_ax.grid(True)
title = '%s, tau:%9.6f, dphi:%9.6f, phi:%9.6f, rssi:%6.3f dB, evm:%6.3f' % \
(filename, tau_hat, dphi_hat, phi_hat, 20*np.log10(gamma_hat), evm)
print(title)
fig.suptitle(title)
if not nodisplay:
plt.show()
if export is not None:
fig.savefig(os.path.splitext(filename)[0]+'.png',bbox_inches='tight')
plt.close()
if __name__ == '__main__':
sys.exit(main())
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