def walk(self, N=64, freq_base=A2, freq_max=C8,  start=0, end=None, each=True, combine=False, twin=0.020, thop=0.010, gamma=10, cof=4000):
        samplerate = self.audio.samplerate
        cstep = int(np.ceil(thop*samplerate))
        cwin = int(np.ceil(twin*samplerate))
        Y = np.zeros((0,N))
        if combine:
            assert 0 < thop <= twin
            assert 0 < cstep <= cwin
        for y in super(Y3, self).walk(N,freq_base,freq_max,start,end,each=False,combine=False,gamma=gamma,cof=cof):
            y[...,1:] = np.diff(y,1,1)
            if not combine:
                if each:
                    for v in y: yield v
                else:
                    yield y
            else:
                Y = np.append(Y, y, 0)
                while Y.shape[0] >= cwin:
                    wf, Y = Y[:cwin], Y[cstep:]
                    yield np.sqrt(np.mean(np.square(wf), 0))
        if combine and Y.shape[0] > 0:
            yield np.sqrt(np.mean(np.square(Y), 0))
dataset/ETHPy150Open dongying/dear/dear/spectrum/auditory.py/Y3.walk/original