def _get_submatrix(self, major=None, minor=None, copy=False):
"""Return a submatrix of this matrix.
major, minor: None or slice with step 1
"""
M, N = self._swap(*self.shape)
i0, i1 = self._process_slice(major, M)
j0, j1 = self._process_slice(minor, N)
is_major_full = i0 == 0 and i1 == M
is_minor_full = j0 == 0 and j1 == N
if is_major_full and is_minor_full:
return self.copy() if copy else self
indptr, indices, data = self.indptr, self.indices, self.data
if not is_major_full:
indptr, indices, data = _index._get_csr_submatrix_major_axis(
indptr, indices, data, i0, i1)
if not is_minor_full:
indptr, indices, data = _index._get_csr_submatrix_minor_axis(
indptr, indices, data, j0, j1)
shape = self._swap(i1 - i0, j1 - j0)
return self.__class__((data, indices, indptr),
shape=shape,
dtype=self.dtype,
copy=False)
def _major_slice(self, idx, copy=False):
"""Index along the major axis where idx is a slice object.
"""
if idx == slice(None):
return self.copy() if copy else self
M, N = self._swap(*self.shape)
start, stop, step = idx.indices(M)
M = len(range(start, stop, step))
new_shape = self._swap(M, N)
if M == 0 or self.nnz == 0:
return self.__class__(new_shape)
if step == 1:
indptr, indices, data = _index._get_csr_submatrix_major_axis(
self.indptr, self.indices, self.data, start, stop)
else:
rows = cupy.arange(start,
start + M * step,
step,
dtype=self.indptr.dtype)
indptr, indices, data = _index._csr_row_index(
rows, self.indptr, self.indices, self.data)
return self.__class__((data, indices, indptr),
shape=new_shape,
copy=False)
def _get_intXint(self, row, col):
major, minor = self._swap(row, col)
indptr, indices, data = _index._get_csr_submatrix_major_axis(
self.indptr, self.indices, self.data, major, major + 1)
indptr, indices, data = _index._get_csr_submatrix_minor_axis(
indptr, indices, data, minor, minor + 1)
return data.sum(dtype=self.dtype)
def _get_intXint(self, row, col):
major, minor = self._swap(row, col)
data, indices, _ = _index._get_csr_submatrix_major_axis(
self.data, self.indices, self.indptr, major, major + 1)
dtype = data.dtype
res = cupy.zeros((), dtype=dtype)
if dtype.kind == 'c':
_index._compress_getitem_complex_kern(
data.real, data.imag, indices, minor, res.real, res.imag)
else:
_index._compress_getitem_kern(data, indices, minor, res)
return res
def getrow(self, i):
"""Returns a copy of row i of the matrix, as a (1 x n)
CSR matrix (row vector).
Args:
i (integer): Row
Returns:
cupyx.scipy.sparse.csr_matrix: Sparse matrix with single row
"""
M, N = self.shape
i = _index._normalize_index(i, M, 'index')
indptr, indices, data = _index._get_csr_submatrix_major_axis(
self.indptr, self.indices, self.data, i, i + 1)
return csr_matrix((data, indices, indptr),
shape=(1, N),
dtype=self.dtype,
copy=False)
def _major_slice(self, idx, copy=False):
"""Index along the major axis where idx is a slice object.
"""
M, N = self._swap(*self.shape)
start, stop, step = idx.indices(M)
if start == 0 and stop == M and step == 1:
return self.copy() if copy else self
M = len(range(start, stop, step))
new_shape = self._swap(M, N)
if step == 1:
if M == 0 or self.nnz == 0:
return self.__class__(new_shape, dtype=self.dtype)
return self.__class__(_index._get_csr_submatrix_major_axis(
self.data, self.indices, self.indptr, start, stop),
shape=new_shape,
copy=copy)
rows = cupy.arange(start, stop, step, dtype=self.indptr.dtype)
return self._major_index_fancy(rows)
