<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def _solve_k_from_mu(data, k_array, nll, *args):
 """ For given args, return k_agg from searching some k_range. Parameters data : array k_range : array nll : function args : Returns -------- :float Minimum k_agg """

    # TODO: See if a root finder like fminbound would work with Decimal used in
    # logpmf method (will this work with arrays?)

    nll_array = np.zeros(len(k_array))

    for i in range(len(k_array)):
        nll_array[i] = nll(data, k_array[i], *args)

    min_nll_idx = np.argmin(nll_array)

    return k_array[min_nll_idx]