recursive_cc.py 文件源码

def __gausscoeff(s):
    """Python implementation of the algorithm by Young & Vliet, 1995."""
    if s < .5:
        raise ValueError('Sigma for Gaussian filter must be >0.5 samples')
    q = 0.98711*s - 0.96330 if s > 0.5 else 3.97156 \
        - 4.14554*np.sqrt(1.0 - 0.26891*s)
    b = np.zeros(4)
    b[0] = 1.57825 + 2.44413*q + 1.4281*q**2 + 0.422205*q**3
    b[1] = 2.44413*q + 2.85619*q**2 + 1.26661*q**3
    b[2] = -(1.4281*q**2 + 1.26661*q**3)
    b[3] = 0.422205*q**3
    B = 1.0 - ((b[1] + b[2] + b[3])/b[0])
    # convert to a format compatible with lfilter's
    # difference equation
    B = np.array([B])
    A = np.ones(4)
    A[1:] = -b[1:]/b[0]
    return B, A