scipy.sparse.

save_npz#

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

Save a sparse matrix or array 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 or sparray: The sparse matrix or array to save. Supported formats: csc, csr, bsr, dia or coo.
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 numpy as np
>>> import scipy as sp
>>> sparse_matrix = sp.sparse.csc_matrix([[0, 0, 3], [4, 0, 0]])
>>> sparse_matrix
<Compressed Sparse Column sparse matrix of dtype 'int64'
    with 2 stored elements and shape (2, 3)>
>>> sparse_matrix.toarray()
array([[0, 0, 3],
       [4, 0, 0]], dtype=int64)

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

>>> sparse_matrix
<Compressed Sparse Column sparse matrix of dtype 'int64'
    with 2 stored elements and shape (2, 3)>
>>> sparse_matrix.toarray()
array([[0, 0, 3],
       [4, 0, 0]], dtype=int64)