Skip to main content
`Ctrl`+`K`
scipy.sparse.

# save_npz

scipy.sparse.save_npz(file, matrix, compressed=True)

  Save a sparse matrix or array 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 or sparray

      The sparse matrix or array to save. Supported formats: `csc`, `csr`, `bsr`, `dia` or `coo`.

    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 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)