def tocsc(self, copy=False): """Converts the matrix to Compressed Sparse Column 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 dia to csc conversion. Returns: cupy.sparse.csc_matrix: Converted matrix. """ if self.data.size == 0: return csc.csc_matrix(self.shape, dtype=self.dtype) num_rows, num_cols = self.shape num_offsets, offset_len = self.data.shape row, mask = core.ElementwiseKernel( 'int32 offset_len, int32 offsets, int32 num_rows, ' 'int32 num_cols, T data', 'int32 row, bool mask', ''' int offset_inds = i % offset_len; row = offset_inds - offsets; mask = (row >= 0 && row < num_rows && offset_inds < num_cols && data != 0); ''', 'dia_tocsc')(offset_len, self.offsets[:, None], num_rows, num_cols, self.data) indptr = cupy.zeros(num_cols + 1, dtype='i') indptr[1:offset_len + 1] = cupy.cumsum(mask.sum(axis=0)) indptr[offset_len + 1:] = indptr[offset_len] indices = row.T[mask.T].astype('i', copy=False) data = self.data.T[mask.T] return csc.csc_matrix((data, indices, indptr), shape=self.shape, dtype=self.dtype)
def transpose(self, axes=None, copy=False): """Returns a transpose matrix. Args: axes: This option is not supported. copy (bool): If ``True``, a returned matrix shares no data. Otherwise, it shared data arrays as much as possible. Returns: cupy.sparse.spmatrix: Transpose matrix. """ if axes is not None: raise ValueError( 'Sparse matrices do not support an \'axes\' parameter because ' 'swapping dimensions is the only logical permutation.') shape = self.shape[1], self.shape[0] return csc.csc_matrix( (self.data, self.indices, self.indptr), shape=shape, copy=copy)