def _compressed_sparse_stack(blocks, axis):
"""Fast path for stacking CSR/CSC matrices
(i) vstack for CSR, (ii) hstack for CSC.
"""
other_axis = 1 if axis == 0 else 0
data = cupy.concatenate([b.data for b in blocks])
constant_dim = blocks[0].shape[other_axis]
idx_dtype = sputils.get_index_dtype(arrays=[b.indptr for b in blocks],
maxval=max(data.size, constant_dim))
indices = cupy.empty(data.size, dtype=idx_dtype)
indptr = cupy.empty(sum(b.shape[axis]
for b in blocks) + 1, dtype=idx_dtype)
last_indptr = idx_dtype(0)
sum_dim = 0
sum_indices = 0
for b in blocks:
if b.shape[other_axis] != constant_dim:
raise ValueError(
'incompatible dimensions for axis %d' % other_axis)
indices[sum_indices:sum_indices+b.indices.size] = b.indices
sum_indices += b.indices.size
idxs = slice(sum_dim, sum_dim + b.shape[axis])
indptr[idxs] = b.indptr[:-1]
indptr[idxs] += last_indptr
sum_dim += b.shape[axis]
last_indptr += b.indptr[-1]
indptr[-1] = last_indptr
if axis == 0:
return csr.csr_matrix((data, indices, indptr),
shape=(sum_dim, constant_dim))
else:
return csc.csc_matrix((data, indices, indptr),
shape=(constant_dim, sum_dim))
def tocsr(self, copy=False):
"""Converts the matrix to Compressed Sparse Row format.
Args:
copy (bool): If ``False``, it shares data arrays as much as
possible. Actually this option is ignored because all
arrays in a matrix cannot be shared in coo to csr conversion.
Returns:
cupyx.scipy.sparse.csr_matrix: Converted matrix.
"""
if self.nnz == 0:
return csr.csr_matrix(self.shape, dtype=self.dtype)
self.sum_duplicates()
# copy is ignored because coosort method breaks an original.
x = self.copy()
cusparse.coosort(x)
return cusparse.coo2csr(x)
def tocsr(self, copy=False):
"""Converts the matrix to Compressed Sparse Row format.
Args:
copy (bool): If ``False``, it shares data arrays as much as
possible. Actually this option is ignored because all
arrays in a matrix cannot be shared in coo to csr conversion.
Returns:
cupyx.scipy.sparse.csr_matrix: Converted matrix.
"""
if self.nnz == 0:
return csr.csr_matrix(self.shape, dtype=self.dtype)
# copy is silently ignored (in line with SciPy) because both
# sum_duplicates and coosort change the underlying data
x = self.copy()
x.sum_duplicates()
cusparse.coosort(x, 'r')
x = cusparse.coo2csr(x)
x.has_canonical_format = True
return x