scipy.sparse.load_npz¶

scipy.sparse.load_npz(file)[source]¶

Load a sparse matrix from a file using .npz format.

Parameters

filestr or file-like object: Either the file name (string) or an open file (file-like object) where the data will be loaded.

Returns

resultcsc_matrix, csr_matrix, bsr_matrix, dia_matrix or coo_matrix: A sparse matrix containing the loaded data.

Raises

IOError: If the input file does not exist or cannot be read.

See also

scipy.sparse.save_npz: Save a sparse matrix to a file using .npz format.
numpy.load: Load several arrays from a .npz archive.

Examples

Store sparse matrix to disk, and load it again:

>>> import scipy.sparse
>>> sparse_matrix = scipy.sparse.csc_matrix(np.array([[0, 0, 3], [4, 0, 0]]))
>>> sparse_matrix
<2x3 sparse matrix of type '<class 'numpy.int64'>'
   with 2 stored elements in Compressed Sparse Column format>
>>> sparse_matrix.todense()
matrix([[0, 0, 3],
        [4, 0, 0]], dtype=int64)

>>> scipy.sparse.save_npz('/tmp/sparse_matrix.npz', sparse_matrix)
>>> sparse_matrix = scipy.sparse.load_npz('/tmp/sparse_matrix.npz')

>>> sparse_matrix
<2x3 sparse matrix of type '<class 'numpy.int64'>'
    with 2 stored elements in Compressed Sparse Column format>
>>> sparse_matrix.todense()
matrix([[0, 0, 3],
        [4, 0, 0]], dtype=int64)

scipy.sparse.save_npz scipy.sparse.find