def __mul__(self, other):
dmat = Sparse3DMatrix.__mul__(self, other)
dmat.num_loci, dmat.num_haplotypes, dmat.num_reads = dmat.shape
if isinstance(
other,
(np.ndarray, csc_matrix, csr_matrix, coo_matrix, lil_matrix)):
dmat.hname = self.hname
dmat.rname = copy.copy(self.rname)
dmat.rid = copy.copy(self.rid)
dmat.num_groups = 0
else:
dmat.__copy_names(self)
dmat.__copy_group_info(self)
return dmat
def bundle(
self,
reset=False,
shallow=False): # Copies the original matrix (Use lots of memory)
"""
Returns ``AlignmentPropertyMatrix`` object in which loci are bundled using grouping information.
:param reset: whether to reset the values at the loci
:param shallow: whether to copy all the meta data
"""
if self.finalized:
# if self.num_groups > 0:
if self.groups is not None and self.gname is not None:
grp_conv_mat = lil_matrix((self.num_loci, self.num_groups))
for i in xrange(self.num_groups):
grp_conv_mat[self.groups[i], i] = 1.0
grp_align = Sparse3DMatrix.__mul__(
self, grp_conv_mat) # The core of the bundling
grp_align.num_loci = self.num_groups
grp_align.num_haplotypes = self.num_haplotypes
grp_align.num_reads = self.num_reads
grp_align.shape = (grp_align.num_loci,
grp_align.num_haplotypes,
grp_align.num_reads)
grp_align.count = self.count
if not shallow:
grp_align.lname = copy.copy(self.gname)
grp_align.hname = self.hname
grp_align.rname = copy.copy(self.rname)
grp_align.sname = copy.copy(self.sname)
grp_align.lid = dict(
zip(grp_align.lname, np.arange(grp_align.num_loci)))
grp_align.rid = copy.copy(self.rid)
grp_align.sid = copy.copy(self.sid)
if reset:
grp_align.reset()
return grp_align
else:
raise RuntimeError(
'No group information is available for bundling.')
else:
raise RuntimeError('The matrix is not finalized.')