scipy 1.8.0 Pypi GitHub Homepage
Other Docs
ParametersBackRef
save_npz(file, matrix, compressed=True)

Parameters

file : str 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.

compressed : bool, optional

Allow compressing the file. Default: True

Save a sparse matrix to a file using .npz format.

See Also

numpy.savez

Save several arrays into a .npz archive.

numpy.savez_compressed

Save several arrays into a compressed .npz archive.

scipy.sparse.load_npz

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

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)
See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.sparse._matrix_io.save_npz scipy.sparse._matrix_io.load_npz

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


GitHub : /scipy/sparse/_matrix_io.py#11
type: <class 'function'>
Commit: