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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 compute_mga_entropy_stat(mga_vec, codon_pos, stat_func=np.mean, default_val=0.0):
 """Compute MGA entropy conservation statistic Parameters mga_vec : np.array numpy vector containing MGA Entropy conservation scores for residues codon_pos : list of int position of codon in protein sequence stat_func : function, default=np.mean function that calculates a statistic default_val : float default value to return if there are no mutations Returns ------- score_stat : float MGA entropy score statistic for provided mutation list """

    # return default value if VEST scores are missing
    if mga_vec is None:
        return default_val

    # fetch scores
    myscores = fetch_mga_scores(mga_vec, codon_pos)

    # calculate mean score
    if myscores is not None and len(myscores):
        score_stat = stat_func(myscores)
    else:
        score_stat = default_val

    return score_stat