scipy.sparse.
save_npz#
- scipy.sparse.save_npz(file, matrix, compressed=True)[source]#
- Save a sparse matrix or array to a file using - .npzformat.- 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 - .npzextension 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,- diaor- coo.
- compressedbool, optional
- Allow compressing the file. Default: True 
 
 - See also - scipy.sparse.load_npz
- Load a sparse matrix from a file using - .npzformat.
- numpy.savez
- Save several arrays into a - .npzarchive.
- numpy.savez_compressed
- Save several arrays into a compressed - .npzarchive.
 - 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)