def plot_cwt_spectrogram(self, canvas: MatplotlibCanvas):
tr = ObspyUtil.get_tracer_from_file(self.file_selector.file_path)
ts, te = self.get_time_window()
tr.trim(starttime=ts, endtime=te)
tr.detrend(type="demean")
fs = tr.stats.sampling_rate
f_min = 1. / self.spectrum_box.win_bind.value if self.filter.min_freq == 0 else self.filter.min_freq
f_max = self.filter.max_freq
ObspyUtil.filter_trace(tr, self.filter.filter_value, f_min, f_max)
nf = 40
tt = int(self.spectrum_box.win_bind.value *
self.tracer_stats.Sampling_rate)
wmin = self.spectrum_box.w1_bind.value
wmax = self.spectrum_box.w2_bind.value
npts = len(tr.data)
[ba, nConv, frex,
half_wave] = ccwt_ba_fast(npts, self.tracer_stats.Sampling_rate,
f_min, f_max, wmin, wmax, tt, nf)
cf, sc, scalogram = cwt_fast(tr.data, ba, nConv, frex, half_wave, fs)
#scalogram = ccwt(tr.data, self.tracer_stats.Sampling_rate, f_min, f_max, wmin, wmax, tt, nf)
scalogram = np.abs(scalogram)**2
t = np.linspace(0, self.tracer_stats.Delta * npts, npts)
scalogram2 = 10 * (np.log10(scalogram / np.max(scalogram)))
x, y = np.meshgrid(t, np.linspace(f_min, f_max, scalogram2.shape[0]))
max_cwt = np.max(scalogram2)
min_cwt = np.min(scalogram2)
canvas.plot(t[0:len(t) - 1],
cf,
0,
clear_plot=False,
is_twinx=True,
color="red",
linewidth=0.5)
norm = Normalize(vmin=min_cwt, vmax=max_cwt)
canvas.plot_contour(x,
y,
scalogram2,
axes_index=1,
clabel="Power [dB]",
levels=100,
cmap=plt.get_cmap("jet"),
norm=norm)
canvas.set_xlabel(1, "Time (s)")
def trace(self):
return ObspyUtil.get_tracer_from_file(self.file_selector.file_path)