Created
August 9, 2018 21:35
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DSLWP-B waterfall script
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#!/usr/bin/env python3 | |
import numpy as np | |
from scipy.fftpack import fft, fftshift | |
from scipy.signal import blackman | |
import matplotlib.pyplot as plt | |
# Parameters | |
N = 2**13 | |
averaging = 4 | |
samp_rate = 40000 | |
freq = 2400 | |
span = 1000 | |
hz_per_bin = samp_rate/N | |
centre_bin = int(np.round(freq/hz_per_bin)) | |
span_bin = int(np.ceil(span/hz_per_bin)) | |
samples = np.fromfile('/tmp/dslwp_photo.c64', dtype=np.complex64) | |
total_transforms = len(samples)//(N//2) - 1 | |
lines = total_transforms//averaging | |
window = blackman(N) | |
waterfall = np.empty((lines, 2*span_bin), dtype=np.float32) | |
for line in range(lines): | |
transforms = np.zeros((averaging, 2*span_bin), dtype=np.float32) | |
for transform in range(averaging): | |
start = (line * averaging + transform)*N//2 | |
x = samples[start : start+N] | |
f = fft(x * window)[centre_bin - span_bin : centre_bin + span_bin] | |
transforms[transform,:] = np.real(f)**2 + np.imag(f)**2 | |
waterfall[line,:] = 10*np.log10(np.average(transforms, axis=0)) - 20*np.log10(N) | |
plt.imsave('dslwp.png', waterfall[:,::-1].T, vmin = -125, vmax=-95, cmap='viridis', origin='bottom') |
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