def process(self, wave):
wave.check_mono()
if wave.sample_rate != self.sr:
raise Exception("Wrong sample rate")
n = int(np.ceil(2 * wave.num_frames / float(self.w_len)))
m = (n + 1) * self.w_len / 2
swindow = self.make_signal_window(n)
win_ratios = [self.window / swindow[t * self.w_len / 2 :
t * self.w_len / 2 + self.w_len]
for t in range(n)]
wave = wave.zero_pad(0, int(m - wave.num_frames))
wave = audio.Wave(signal.hilbert(wave), wave.sample_rate)
result = np.zeros((self.n_bins, n))
for b in range(self.n_bins):
w = self.widths[b]
wc = 1 / np.square(w + 1)
filter = self.filters[b]
band = fftfilt(filter, wave.zero_pad(0, int(2 * w))[:,0])
band = band[int(w) : int(w + m), np.newaxis]
for t in range(n):
frame = band[t * self.w_len / 2:
t * self.w_len / 2 + self.w_len,:] * win_ratios[t]
result[b, t] = wc * np.real(np.conj(np.dot(frame.conj().T, frame)))
return audio.Spectrogram(result, self.sr, self.w_len, self.w_len / 2)
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