scipy.sparse.save_npz¶

scipy.sparse.save_npz(file, matrix, compressed=True)[source]¶

Save a sparse matrix to 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 saved. If file is a string, the .npz extension will be appended to the file name if it is not already there.
matrix: spmatrix (format: ``csc``, ``csr``, ``bsr``, ``dia`` or coo``): The sparse matrix to save.
compressedbool, optional: Allow compressing the file. Default: True

See also

scipy.sparse.load_npz: Load a sparse matrix from a file using .npz format.
numpy.savez: Save several arrays into a .npz archive.
numpy.savez_compressed: Save several arrays into a compressed .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.random scipy.sparse.load_npz