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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 cdf_single(z, N, normalization, dH=1, dK=3):
 """Cumulative distribution for the Lomb-Scargle periodogram Compute the expected cumulative distribution of the periodogram for the null hypothesis - i.e. data consisting of Gaussian noise. Parameters z : array-like the periodogram value N : int the number of data points from which the periodogram was computed normalization : string The periodogram normalization. Must be one of ['standard', 'model', 'log', 'psd'] dH, dK : integers (optional) The number of parameters in the null hypothesis and the model Returns ------- cdf : np.ndarray The expected cumulative distribution function Notes ----- For normalization='psd', the distribution can only be computed for periodograms constructed with errors specified. All expressions used here are adapted from Table 1 of Baluev 2008 [1]_. References .. [1] Baluev, R.V. MNRAS 385, 1279 (2008) """

    return 1 - fap_single(z, N, normalization=normalization, dH=dH, dK=dK)