recursive_cc.py 文件源码

python
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项目:backtrackbb 作者: BackTrackBB 项目源码 文件源码
def local_CC(sig1, sig2, t_lag, fs):
    """
    Calculation of Local-CC after Hale 2006.

    Output = H3 - non-smoothed LCC
          C - smoothed LCC (after Gussian smoothing)
          t_lag - array of t_lag times
    """
    l_max = int(t_lag*fs)
    h3 = np.zeros((2*l_max, len(sig1)), sig1.dtype)
    c = np.zeros((2*l_max, len(sig1)), sig1.dtype)
##
    t_lag = sp.linspace(-l_max/fs, l_max/fs, 2*l_max, endpoint=False)
##
##
    for l in xrange(-l_max, l_max):
        l_f = int(floor(l/2.))
        l_g = int(ceil(l/2.))
        h3[l+l_max] = (__shift2(sig1, l_f) * __shift2(sig2, -l_g) +
                       __shift2(sig1, l_g) * __shift2(sig2, -l_f))/2
        c[l+l_max] = Gaussian1D(h3[l+l_max], 10, padding=0)

#------------------not sure which formula for h3 is correct--------------------
#             h3[l+l_max]=(shift2(sig1,-l_f)*shift2(sig2,l_g) +\
#                    shift2(sig1,-l_g)*shift2(sig2,l_f))/2
#
    return c, h3, t_lag
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