def _do_pileups(
self,
mids,
chrom,
expected=False,
):
if expected:
data = None
logging.debug("Doing expected")
else:
data = self.get_data(
chrom
) # self.CoolSnipper.select(self.regions[chrom], self.regions[chrom])
max_right = self.matsizes[chrom]
mymap = self.make_outmap()
if self.coverage_norm:
coverage = self.get_coverage(data)
cov_start = np.zeros(mymap.shape[0])
cov_end = np.zeros(mymap.shape[1])
n = 0
for stBin, endBin, stPad, endPad in mids:
rot_flip = False
rot = False
if stBin > endBin:
stBin, stPad, endBin, endPad = endBin, endPad, stBin, stPad
if self.anchor is None:
rot_flip = True
else:
rot = True
if self.rescale:
stPad = stPad + int(round(self.rescale_pad * 2 * stPad))
endPad = endPad + int(round(self.rescale_pad * 2 * endPad))
else:
stPad, endPad = self.pad_bins, self.pad_bins
lo_left = stBin - stPad
hi_left = stBin + stPad + 1
lo_right = endBin - endPad
hi_right = endBin + endPad + 1
if lo_left < 0 or hi_right > max_right:
continue
if (self.mindist <= abs(endBin - stBin) * self.resolution <
self.maxdist or self.CC.local):
if not expected:
try:
newmap = data[lo_left:hi_left,
lo_right:hi_right].toarray()
except (IndexError, ValueError):
continue
else:
newmap = self.get_expected_matrix(chrom,
(lo_left, hi_left),
(lo_right, hi_right))
# if (
# newmap.shape != mymap.shape and not self.rescale
# ): # AFAIK only happens at ends of chroms
# height, width = newmap.shape
# h, w = mymap.shape
# x = w - width
# y = h - height
# newmap = np.pad(
# newmap, [(y, 0), (0, x)], "constant"
# ) # Padding to adjust to the right shape
if self.rescale:
if newmap.size == 0 or np.all(np.isnan(newmap)):
newmap = np.zeros(
(self.rescale_size, self.rescale_size))
else:
newmap = numutils.zoom_array(
newmap, (self.rescale_size, self.rescale_size))
if rot_flip:
newmap = np.rot90(np.flipud(newmap), 1)
elif rot:
newmap = np.rot90(newmap, -1)
mymap = np.nansum([mymap, newmap], axis=0)
if self.coverage_norm and not expected and (self.balance is
False):
new_cov_start = coverage[lo_left:hi_left]
new_cov_end = coverage[lo_right:hi_right]
if self.rescale:
if len(new_cov_start) == 0:
new_cov_start = np.zeros(self.rescale_size)
if len(new_cov_end) == 0:
new_cov_end = np.zeros(self.rescale_size)
new_cov_start = numutils.zoom_array(
new_cov_start, (self.rescale_size, ))
new_cov_end = numutils.zoom_array(
new_cov_end, (self.rescale_size, ))
else:
l = len(new_cov_start)
r = len(new_cov_end)
new_cov_start = np.pad(new_cov_start,
(mymap.shape[0] - l, 0),
"constant")
new_cov_end = np.pad(new_cov_end,
(0, mymap.shape[1] - r),
"constant")
cov_start += np.nan_to_num(new_cov_start)
cov_end += +np.nan_to_num(new_cov_end)
n += 1
if self.CC.local:
mymap = np.triu(mymap, 0)
mymap += np.rot90(np.fliplr(np.triu(mymap, 1)))
return mymap, n, cov_start, cov_end
def _do_pileups(
self,
mids,
chrom,
expected=False,
):
mymap = self.make_outmap()
cov_start = np.zeros(mymap.shape[0])
cov_end = np.zeros(mymap.shape[1])
num = np.zeros_like(mymap)
n = 0
try:
mids_row1 = next(mids)
except StopIteration:
logging.info(f"Nothing to sum up in chromosome {chrom}")
return mymap, mymap, cov_start, cov_end, n
else:
mids = itertools.chain([mids_row1], mids)
if expected:
data = None
logging.debug("Doing expected")
else:
data = self.get_data(
chrom
) # self.CoolSnipper.select(self.regions[chrom], self.regions[chrom])
max_right = self.matsizes[chrom]
if self.coverage_norm:
coverage = self.get_coverage(data)
for stBin, endBin, stPad, endPad in mids:
rot_flip = False
rot = False
if stBin >= endBin:
stBin, stPad, endBin, endPad = endBin, endPad, stBin, stPad
if self.anchor is None:
rot_flip = True
else:
rot = True
if self.rescale:
stPad = stPad + int(round(self.rescale_pad * 2 * stPad))
endPad = endPad + int(round(self.rescale_pad * 2 * endPad))
else:
stPad, endPad = self.pad_bins, self.pad_bins
lo_left = stBin - stPad
hi_left = stBin + stPad + 1
lo_right = endBin - endPad
hi_right = endBin + endPad + 1
if lo_left < 0 or hi_right > max_right:
continue
diag = hi_left - lo_right
if not expected:
try:
newmap = data[lo_left:hi_left, lo_right:hi_right].toarray()
except (IndexError, ValueError):
continue
else:
newmap = self.get_expected_matrix(chrom, (lo_left, hi_left),
(lo_right, hi_right))
# if (
# newmap.shape != mymap.shape and not self.rescale
# ): # AFAIK only happens at ends of chroms
# height, width = newmap.shape
# h, w = mymap.shape
# x = w - width
# y = h - height
# newmap = np.pad(
# newmap, [(y, 0), (0, x)], "constant"
# ) # Padding to adjust to the right shape
newmap = newmap.astype(float)
if not self.local:
ignore_indices = np.tril_indices_from(
newmap, diag - (stPad * 2 + 1) - 1 + self.ignore_diags)
newmap[ignore_indices] = np.nan
else:
newmap = np.triu(newmap, self.ignore_diags)
newmap += np.triu(newmap, 1).T
if self.rescale:
if newmap.size == 0 or np.all(np.isnan(newmap)):
newmap = np.zeros((self.rescale_size, self.rescale_size))
else:
newmap = numutils.zoom_array(
newmap, (self.rescale_size, self.rescale_size))
if rot_flip:
newmap = np.rot90(np.flipud(newmap), 1)
elif rot:
newmap = np.rot90(newmap, -1)
mymap = np.nansum([mymap, newmap], axis=0)
if self.coverage_norm and not expected and (self.balance is False):
new_cov_start = coverage[lo_left:hi_left]
new_cov_end = coverage[lo_right:hi_right]
if self.rescale:
if len(new_cov_start) == 0:
new_cov_start = np.zeros(self.rescale_size)
if len(new_cov_end) == 0:
new_cov_end = np.zeros(self.rescale_size)
new_cov_start = numutils.zoom_array(
new_cov_start, (self.rescale_size, ))
new_cov_end = numutils.zoom_array(new_cov_end,
(self.rescale_size, ))
else:
l = len(new_cov_start)
r = len(new_cov_end)
new_cov_start = np.pad(new_cov_start,
(mymap.shape[0] - l, 0), "constant")
new_cov_end = np.pad(new_cov_end, (0, mymap.shape[1] - r),
"constant")
cov_start += np.nan_to_num(new_cov_start)
cov_end += +np.nan_to_num(new_cov_end)
num += np.isfinite(newmap).astype(int)
n += 1
return mymap, num, cov_start, cov_end, n
def _do_pileups(mids, data, binsize, pad, expected, mindist, maxdist, local,
balance, cov_norm, rescale, rescale_pad, rescale_size,
coverage, anchor):
mymap = make_outmap(pad, rescale, rescale_size)
cov_start = np.zeros(mymap.shape[0])
cov_end = np.zeros(mymap.shape[1])
n = 0
for stBin, endBin, stPad, endPad in mids:
rot_flip = False
rot = False
if stBin > endBin:
stBin, stPad, endBin, endPad = endBin, endPad, stBin, stPad
if anchor is None:
rot_flip = True
else:
rot = True
if rescale:
stPad = stPad + int(round(rescale_pad*2*stPad))
endPad = endPad + int(round(rescale_pad*2*endPad))
else:
stPad = pad
endPad = pad
lo_left = stBin - stPad
hi_left = stBin + stPad + 1
lo_right = endBin - endPad
hi_right = endBin + endPad + 1
if mindist <= abs(endBin - stBin)*binsize < maxdist or local:
if expected is False:
try:
newmap = np.nan_to_num(data[lo_left:hi_left,
lo_right:hi_right].toarray())
except (IndexError, ValueError) as e:
continue
else:
newmap = get_expected_matrix((lo_left, hi_left),
(lo_right, hi_right),
expected, local)
if newmap.shape != mymap.shape and not rescale: #AFAIK only happens at ends of chroms
height, width = newmap.shape
h, w = mymap.shape
x = w - width
y = h - height
newmap = np.pad(newmap, [(y, 0), (0, x)], 'constant') #Padding to adjust to the right shape
if rescale:
if newmap.size==0:
newmap = np.zeros((rescale_size, rescale_size))
else:
newmap = numutils.zoom_array(newmap, (rescale_size,
rescale_size))
if rot_flip:
newmap = np.rot90(np.flipud(newmap), -1)
elif rot:
newmap = np.rot90(newmap, -1)
mymap += np.nan_to_num(newmap)
if cov_norm and (expected is False) and (balance is False):
new_cov_start = coverage[lo_left:hi_left]
new_cov_end = coverage[lo_right:hi_right]
if rescale:
if len(new_cov_start)==0:
new_cov_start = np.zeros(rescale_size)
if len(new_cov_end)==0:
new_cov_end = np.zeros(rescale_size)
new_cov_start = numutils.zoom_array(new_cov_start,
(rescale_size,))
new_cov_end = numutils.zoom_array(new_cov_end,
(rescale_size,))
else:
l = len(new_cov_start)
r = len(new_cov_end)
new_cov_start = np.pad(new_cov_start, (mymap.shape[0]-l, 0),
'constant')
new_cov_end = np.pad(new_cov_end,
(0, mymap.shape[1]-r), 'constant')
cov_start += np.nan_to_num(new_cov_start)
cov_end += +np.nan_to_num(new_cov_end)
n += 1
if local:
mymap = np.triu(mymap, 0)
mymap += np.rot90(np.fliplr(np.triu(mymap, 1)))
return mymap, n, cov_start, cov_end