def encodeCodon(seq_vec, ignore_stop_codons=True, maxlen=None, seq_align="start", encode_type="one_hot"):
    """Convert the Codon sequence into 1-hot-encoding numpy array

    # Arguments
        seq_vec: List of strings/DNA sequences
        ignore_stop_codons: boolean; if True, STOP_CODONS are omitted from one-hot encoding.
        maxlen: Maximum sequence length. See `pad_sequences` for more detail
        seq_align: How to align the sequences of variable lengths. See `pad_sequences` for more detail
        encode_type: can be `"one_hot"` or `token` for token encoding of codons (incremental integer ).

    # Returns
        numpy.ndarray of shape `(len(seq_vec), maxlen / 3, 61 if ignore_stop_codons else 64)`
    """
    if ignore_stop_codons:
        vocab = CODONS
        neutral_vocab = STOP_CODONS + ["NNN"]
    else:
        vocab = CODONS + STOP_CODONS
        neutral_vocab = ["NNN"]

    # replace all U's with A's?
    seq_vec = [str(seq).replace("U", "T") for seq in seq_vec]

    return encodeSequence(seq_vec,
                          vocab=vocab,
                          neutral_vocab=neutral_vocab,
                          maxlen=maxlen,
                          seq_align=seq_align,
                          pad_value="NNN",
                          encode_type=encode_type)
Convert the Codon sequence into 1-hot-encoding numpy array

    # Arguments
        seq_vec: List of strings/DNA sequences
        ignore_stop_codons: boolean; if True, STOP_CODONS are omitted from one-hot encoding.
        maxlen: Maximum sequence length. See `pad_sequences` for more detail
        seq_align: How to align the sequences of variable lengths. See `pad_sequences` for more detail
        encode_type: can be `"one_hot"` or `token` for token encoding of codons (incremental integer ).

    # Returns
        numpy.ndarray of shape `(len(seq_vec), maxlen / 3, 61 if ignore_stop_codons else 64)`