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src/h/y/hy454-0.4.4/lib/hy454/_preprocessing.py   hy454(Download)
from Bio.SeqRecord import SeqRecord
 
from BioExt import _GAP, enumerate_by_codon
 
from fakemp import farmout, farmworker
def from_positional(datastruct):
    records = []
    gapcdn = _GAP * 3
    maxlen = 0
    for poscdns in datastruct.values():
        prev = 0
        for pos, cdn in poscdns:
            seqstr += _GAP * (pos - prev) + cdn
            prev = pos + 3
        seqstr += _GAP * (maxlen - prev)
def to_positional(msa):
    datastruct = {}
    gapcdn = _GAP * 3
    for seq in msa:
        seqdata = []

src/h/y/hy454-0.4.4/lib/hy454/_graph.py   hy454(Download)
from matplotlib.transforms import Affine2D
 
from BioExt import _GAP, _STOP
 
from ._basefont import Basefont
            # frac to get the majorities
            counts = Counter(alignment[:, col].upper())
            if _GAP in counts:
                del counts[_GAP]
            # grab the count of the most common variant
    if mode & COVERAGE:
        for i, col in enumerate(range(n0, N)):
            heights[i] = sum(frac for p in alignment[:, col] if p != _GAP)
 
    # labels
_DNA_ALPHABET = Gapped(ambiguous_dna)
_RNA_ALPHABET = Gapped(ambiguous_rna)
_AMINO_ALPHABET = HasStopCodon(Gapped(extended_protein, gap_char=_GAP), stop_symbol=_STOP)
 
def _fix_ambigs(pwm, alphabet):