# scipy.sparse.save_npz

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

  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 '<class '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 '<class '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.random scipy.sparse.load_npz