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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 fetch_mga_scores(mga_vec, codon_pos, default_mga=None):
 """Get MGAEntropy scores from pre-computed scores in array. 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 default_mga: float or None, default=None value to use if MGA entropy score not available for a given mutation. Drop mutations if no default specified. Returns ------- mga_ent_scores : np.array score results for MGA entropy conservation """

    # keep only positions in range of MGAEntropy scores
    len_mga = len(mga_vec)
    good_codon_pos = [p for p in codon_pos if p < len_mga]

    # get MGAEntropy scores
    if good_codon_pos:
        mga_ent_scores = mga_vec[good_codon_pos]
    else:
        mga_ent_scores = None

    return mga_ent_scores