scipy.sparse.save_npz¶
- scipy.sparse.save_npz(file, matrix, compressed=True)[source]¶
Save a sparse matrix to a file using .npz format.
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
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 '<type 'numpy.int64'>' with 2 stored elements in Compressed Sparse Column format> >>> sparse_matrix.todense() matrix([[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 '<type 'numpy.int64'>' with 2 stored elements in Compressed Sparse Column format> >>> sparse_matrix.todense() matrix([[0, 0, 3], [4, 0, 0]], dtype=int64)