right_stft=right_stft,
beta=beta,
method=est_method)
left_nulls.append(ln)
left_peaks.append(lp)
right_nulls.append(rn)
right_peaks.append(rp)
#
# Encapsulate & Plot data
#
fig_data = {}
# Zoom: Find max / min frequency present in the signal (less than some tolerance)
l_ylim = apreset.ylim_zoom(f,
left_stft,
absence_tol=freq_absence_tol,
max_offset=1.1)
r_ylim = apreset.ylim_zoom(f,
right_stft,
absence_tol=freq_absence_tol,
max_offset=1.1)
azi_fig_params = {
"options": ["grid"],
"plot_type": "pcolormesh",
"xlabel": "Azimuth",
"ylabel": "Frequency"
}
azi_line_options = [{"vmin": 0, "shading": 'gouraud', "cmap": "plasma"}]
# Subplots for both channels
Zxxf[:looff, :toff] = low
Zxxf[hioff:, toff:] = high
# Compute Inverse STFT
trec, xrec = signal.istft(Zxxf,
samp_rate,
window=window,
nperseg=window_length,
noverlap=noverlap)
#
# Encapsulate data
#
# Zoom: Find max / min frequency present in the signal (less than some tolerance)
ylim = apreset.ylim_zoom(f, Zxx, absence_tol=freq_absence_tol)
stft_fig_params = {
"line_options": [{
"vmin": 0,
"vmax": Zxx_max,
"shading": 'gouraud'
}],
"options": ["grid"],
"plot_type": "pcolormesh",
"xlabel": "Time (s)",
"ylabel": "Frequency (Hz)",
"ylim": ylim,
"yscale": "log",
"tickers": {
"yaxis": {