def __call__(self, garray):
if callable(self.gsize):
gsize = self.gsize()
seqs = self.gsize.seqs
else:
gsize = self.gsize
seqs = self.seqs
order = self.order
dtype = garray.typecode
bar = Bar('Loading sequences', max=len(gsize))
for region, seq in zip(gsize, seqs):
indarray = np.asarray(seq2ind(seq), dtype=dtype)
if order > 1:
# for higher order motifs, this part is used
filter_ = np.asarray([
pow(len(seq.seq.alphabet.letters), i) for i in range(order)
])
indarray = np.convolve(indarray, filter_, mode='valid')
garray[region, 0] = indarray.reshape(-1, 1)
bar.next()
bar.finish()
def __call__(self, garray):
if callable(self.gsize):
gsize = self.gsize()
seqs = self.gsize.seqs
else:
gsize = self.gsize
seqs = self.seqs
order = self.order
bar = Bar('Loading sequences', max=len(gsize))
for region, seq in zip(gsize, seqs):
indarray = np.asarray(seq2ind(seq))
if order > 1:
# for higher order motifs, this part is used
filter_ = np.asarray([
pow(len(seq.seq.alphabet.letters), i) for i in range(order)
])
indarray = np.convolve(indarray, filter_, mode='valid')
# the specific type int8 is not irrelevant, as long as
# the negative values are maintained correctly.
indarray[indarray < np.iinfo('int8').min] = np.iinfo(
'int8').min
garray[region, 0] = indarray.reshape(-1, 1)
bar.next()
bar.finish()
def _seq_loader(cover, seqs, order):
print('Convert sequences to index array')
for seq in seqs:
if cover._full_genome_stored:
interval = GenomicInterval(seq.id, 0,
len(seq) - order + 1, '.')
else:
interval = GenomicInterval(
*_str_to_iv(seq.id, template_extension=0))
indarray = np.asarray(seq2ind(seq), dtype=dtype)
if order > 1:
# for higher order motifs, this part is used
filter_ = np.asarray([
pow(len(seq.seq.alphabet.letters), i)
for i in range(order)
])
indarray = np.convolve(indarray, filter_, mode='valid')
cover[interval, 0] = indarray
def __call__(self, garray):
seqs = self.seqs
order = self.order
dtype = garray.typecode
print('Convert sequences to index array')
for seq in seqs:
if garray._full_genome_stored:
interval = GenomicInterval(seq.id, 0,
len(seq) - order + 1, '.')
else:
interval = GenomicInterval(*_str_to_iv(seq.id,
template_extension=0))
indarray = np.asarray(seq2ind(seq), dtype=dtype)
if order > 1:
# for higher order motifs, this part is used
filter_ = np.asarray([pow(len(seq.seq.alphabet.letters),
i) for i in range(order)])
indarray = np.convolve(indarray, filter_, mode='valid')
garray[interval, 0] = indarray.reshape(-1, 1)