def rc2poly(kr, r0=None):
    """convert reflection coefficients to prediction filter polynomial

    :param k: reflection coefficients




    """
    # Initialize the recursion
    from .levinson import levup
    p = len(kr)              #% p is the order of the prediction polynomial.
    a = numpy.array([1, kr[0]])           #% a is a true polynomial.
    e = numpy.zeros(len(kr))

    if r0 is None:
        e0 = 0
    else:
        e0 = r0

    e[0] = e0 * (1. - numpy.conj(numpy.conjugate(kr[0])*kr[0]))

    # Continue the recursion for k=2,3,...,p, where p is the order of the
    # prediction polynomial.

    for k in range(1, p):
        [a, e[k]] = levup(a, kr[k], e[k-1])

    efinal = e[-1]
    return a, efinal
def rc2poly(kr, r0=None):
    """convert reflection coefficients to prediction filter polynomial

    :param k: reflection coefficients




    """
    # Initialize the recursion
    from .levinson import levup
    p = len(kr)              #% p is the order of the prediction polynomial.
    a = numpy.array([1, kr[0]])           #% a is a true polynomial.
    e = numpy.zeros(len(kr))

    if r0 is None:
        e0 = 0
    else:
        e0 = r0

    e[0] = e0 * (1. - numpy.conj(numpy.conjugate(kr[0])*kr[0]))

    # Continue the recursion for k=2,3,...,p, where p is the order of the
    # prediction polynomial.

    for k in range(1, p):
        [a, e[k]] = levup(a, kr[k], e[k-1])

    efinal = e[-1]
    return a, efinal
def rc2poly ( kr , r0 = None ) : # Initialize the recursion from . levinson import levup p = len ( kr ) #% p is the order of the prediction polynomial. a = numpy . array ( [ 1 , kr [ 0 ] ] ) #% a is a true polynomial. e = numpy . zeros ( len ( kr ) ) if r0 is None : e0 = 0 else : e0 = r0 e [ 0 ] = e0 * ( 1. - numpy . conj ( numpy . conjugate ( kr [ 0 ] ) * kr [ 0 ] ) ) # Continue the recursion for k=2,3,...,p, where p is the order of the # prediction polynomial. for k in range ( 1 , p ) : [ a , e [ k ] ] = levup ( a , kr [ k ] , e [ k - 1 ] ) efinal = e [ - 1 ] return a , efinal
convert reflection coefficients to prediction filter polynomial

    :param k: reflection coefficients
convert reflection coefficients to prediction filter polynomial