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
orcoo
.- 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)