helper.py 文件源码

def nufft_r(om, N, J, K, alpha, beta):
    '''
    equation (30) of Fessler's paper

    '''
    def iterate_sum(rr, alf, r1):
        rr = rr + alf * r1
        return rr
    def iterate_l1(L, alpha, arg, beta, K, N, rr):
        oversample_ratio = (1.0 * K / N)
        import time
        t0=time.time()
        for l1 in range(-L, L + 1):
            alf = alpha[abs(l1)] * 1.0
    #         if l1 < 0:
    #             alf = numpy.conj(alf)
        #             r1 = numpy.sinc(1.0*(arg+1.0*l1*beta)/(1.0*K/N))
            input_array = (arg + 1.0 * l1 * beta) / oversample_ratio
            r1 = dirichlet(input_array)
            rr = iterate_sum(rr, alf, r1)
        return rr

    M = numpy.size(om)  # 1D size
    gam = 2.0 * numpy.pi / (K * 1.0)
    nufft_offset0 = nufft_offset(om, J, K)  # om/gam -  nufft_offset , [M,1]
    dk = 1.0 * om / gam - nufft_offset0  # om/gam -  nufft_offset , [M,1]
    arg = outer_sum(-numpy.arange(1, J + 1) * 1.0, dk)
    L = numpy.size(alpha) - 1
#     print('alpha',alpha)
    rr = numpy.zeros((J, M), dtype=numpy.float32)
    rr = iterate_l1(L, alpha, arg, beta, K, N, rr)
    return (rr, arg)