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.toarray()
array([[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.toarray()
array([[0, 0, 3],
       [4, 0, 0]], dtype=int64)