bsparse.sparse.COO

class COO(rows, cols, data, shape=None, dtype=None, symmetry=None)

A sparse matrix in coordinate format.

The COO class represents a sparse matrix using three arrays:

• rows: contains the row coordinates of the non-zero elements.

• cols: contains the column coordinates of the non-zero elements.

• data: contains the values of the non-zero elements.

During instantiation, the matrix is sorted (lexicographically) by rows and columns.

Duplicate elements are not allowed.

Parameters:

rowsarray_like

The row coordinates of the non-zero elements.

colsarray_like

The column coordinates of the non-zero elements.

dataarray_like

The values of the non-zero elements.

shapetuple, optional

The shape of the matrix. If not given, it is inferred from the row and column indices.

dtypenumpy.dtype, optional

The data type of the matrix elements. If not given, it is inferred from the data array.

symmetrystr, optional

The symmetry of the matrix. If not given, no symmetry is assumed. This is only applicable for square matrices, where possible values are 'symmetric' and 'hermitian'. Note that when setting a symmetry, the lower triangular part of the matrix is discarded.

Examples

>>> rows = [0, 1, 2, 2, 3]
>>> cols = [1, 2, 2, 3, 4]
>>> data = [1, 2, 3, 4, 5]
>>> coo = COO(rows, cols, data, shape=(4, 5))
>>> coo.toarray()
array([[0, 1, 0, 0, 0],
       [0, 0, 2, 0, 0],
       [0, 0, 3, 4, 0],
       [0, 0, 0, 0, 5]])

Attributes:

rowsndarray

The row coordinates of the non-zero elements.

colsndarray

The column coordinates of the non-zero elements.

datandarray

The values of the diagonals.

shapetuple[int, int]

The shape of the matrix.

dtypedtype

The data type of the matrix elements.

symmetrystr

The symmetry of the matrix.

nnzint

The number of stored elements in the matrix.

TCOO

The transpose of the matrix.

HCOO

The conjugate transpose of the matrix.

Methods

astype(dtype)	Returns a copy of the matrix with a different data type.
conj()	The complex conjugate of the matrix.
conjugate()	The complex conjugate of the matrix.
copy()	Returns a copy of the matrix.
diagonal([offset])	Returns the diagonal of the matrix.
from_array(arr[, symmetry])	Creates a sparse matrix from a dense numpy.ndarray.
from_sparray(mat[, symmetry])	Creates a sparse matrix from a scipy.sparse.sparray.
save_npz(filename)	Saves the matrix as .npz archive.
toarray()	Converts the matrix to a dense numpy.ndarray.
tocoo()	Converts the matrix to coordinate storage.
tocsr()	Converts the matrix to compressed row storage.
todia()	Converts the matrix to diagonal storage.