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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 moving_delta_tajima_d(ac1, ac2, size, start=0, stop=None, step=None):
 """Compute the difference in Tajima's D between two populations in moving windows. Parameters ac1 : array_like, int, shape (n_variants, n_alleles) Allele counts array for the first population. ac2 : array_like, int, shape (n_variants, n_alleles) Allele counts array for the second population. size : int The window size (number of variants). start : int, optional The index at which to start. stop : int, optional The index at which to stop. step : int, optional The number of variants between start positions of windows. If not given, defaults to the window size, i.e., non-overlapping windows. Returns ------- delta_d : ndarray, float, shape (n_windows,) Standardized delta Tajima's D. See Also -------- allel.stats.diversity.moving_tajima_d """


    d1 = moving_tajima_d(ac1, size=size, start=start, stop=stop, step=step)
    d2 = moving_tajima_d(ac2, size=size, start=start, stop=stop, step=step)
    delta = d1 - d2
    delta_z = (delta - np.mean(delta)) / np.std(delta)
    return delta_z