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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def cvm_unif_fix1(statistic):
 """ Approximates the first-term of the small sample count Gotze expansion. After equation 1.10 (with coefficients pulled out as csa / csb). """

    args = fix1_args / statistic
    kvs = kv((.25, .75, 1.25), args[:, :, newaxis])
    gs, hs = exp(-args) * tensordot(((1, 1, 0), (2, 3, -1)), kvs, axes=(1, 2))
    a = dot((7, 16, 7), fix1_csa * gs).sum() / statistic ** 1.5
    b = dot((1, 0, 24), fix1_csb * hs).sum() / statistic ** 2.5
    return cvm_unif_inf(statistic) / 12 - a - b