def precomputeRepeatGenerators(self, realigner):
RX = RepeatGenerator(
None,
realigner.repeat_width,
realigner.cons_count,
)
RY = RepeatGenerator(
None,
realigner.repeat_width,
realigner.cons_count
)
for rt, ch in [('trf', 'R'), ('original_repeats', 'r'), ('hmm', 'h')]:
if rt in realigner.annotations:
RX.addRepeats(realigner.annotations[rt][realigner.X_name])
RY.addRepeats(realigner.annotations[rt][realigner.Y_name])
realigner.drawer.add_repeat_finder_annotation(
'X',
ch,
realigner.annotations[rt][realigner.X_name],
(255, 0, 0, 255)
)
realigner.drawer.add_repeat_finder_annotation(
'Y',
ch,
realigner.annotations[rt][realigner.Y_name],
(255, 0, 0, 255)
)
if 'trf_cons' in realigner.annotations:
x_len = len(realigner.X)
y_len = len(realigner.Y)
cons = list((
realigner.annotations['trf_cons'][realigner.X_name] |
realigner.annotations['trf_cons'][realigner.Y_name]
))
if len(cons) > 0:
RX.addRepeats([
Repeat(i, j, 0, cons[i % len(cons)], "")
for i in range(x_len) for j in range(i + 1, x_len)
])
RY.addRepeats([
Repeat(i, j, 0, cons[i % len(cons)], "")
for i in range(y_len) for j in range(i + 1, y_len)
])
RX.buildRepeatDatabase()
RY.buildRepeatDatabase()
self.addRepeatGenerator(RX, RY)
def expectation_generator(args, model, alignment_filename, annotations):
for aln in Fasta.load(alignment_filename,
args.alignment_regexp,
Alignment,
sequence_selectors=args.sequence_regexp):
if len(aln.sequences) < 2:
sys.stderr.write("ERROR: not enough sequences in file\n")
raise "ERROR: not enough sequences in file"
seq1, seq2 = tuple(map(Fasta.alnToSeq, aln.sequences[:2]))
positionGenerator = list(AlignmentBeamGenerator(aln, args.beam_width))
RX = RepeatGenerator(None, args.repeat_width)
RY = RepeatGenerator(None, args.repeat_width)
for rt in ['trf', 'original_repeats']:
if rt in annotations:
RX.addRepeats(annotations[rt][aln.names[0]])
RY.addRepeats(annotations[rt][aln.names[1]])
RX.buildRepeatDatabase()
RY.buildRepeatDatabase()
if 'Repeat' in model.statenameToID:
model.states[model.statenameToID['Repeat']].addRepeatGenerator(
RX, RY)
(transitions, emissions), probability = model.getBaumWelchCounts(
seq1,
0,
len(seq1),
seq2,
0,
len(seq2),
positionGenerator=positionGenerator)
yield {
"probability": probability,
"transitions": transitions,
"emissions": emissions,
}