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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 AIC_compare(aic_list):
 """ Calculates delta AIC and AIC weights from a list of AIC values Parameters aic_list : iterable AIC values from set of candidat models Returns tuple First element contains the delta AIC values, second element contains the relative AIC weights. Notes ----- AIC weights can be interpreted as the probability that a given model is the best model in the set. Examples -------- (array([ 0. , 19.11806518]), array([ 9.99929444e-01, 7.05560486e-05])) """


    aic_values = np.array(aic_list)
    minimum = np.min(aic_values)
    delta = aic_values - minimum
    values = np.exp(-delta / 2)
    weights = values / np.sum(values)

    return delta, weights