bsparse.sparse.CSR

class CSR(rowptr, cols, data, shape=None, dtype=None, symmetry=None)

A sparse matrix in Compressed Sparse Row format.

The CSR class represents a sparse matrix using three arrays:

• rowptr: contains the index of the first element of each row.

• cols: contains the column indices of each non-zero element.

• data: contains the values of each non-zero element.

Parameters:

rowptrarray_like

The index of the first element of each row.

colsarray_like

The column indices of each non-zero element.

dataarray_like

The values of each non-zero element.

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

>>> rowptr = [0, 2, 3, 5]
>>> cols = [0, 2, 1, 0, 2]
>>> data = [1, 2, 3, 4, 5]
>>> csr = CSR(rowptr, cols, data, shape=(3, 3))
>>> csr.toarray()
array([[1, 0, 2],
       [0, 3, 0],
       [4, 0, 5]])

Attributes:

rowptrndarray

The index of the first element of each row.

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.

symmetrystr

The symmetry of the matrix.

nnzint

The number of non-zero elements in the matrix.

TCSR

The transpose of the matrix.

HCSR

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 COO format.
tocsr()	Converts the matrix to CSR format.
todia()	Converts the matrix to DIA format.