# scipy.sparse.load_npz

scipy.sparse.load_npz(file)

  Load a sparse matrix from 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 loaded.

  Returns
    result csc_matrix, csr_matrix, bsr_matrix, dia_matrix or coo_matrix

      A sparse matrix containing the loaded data.

  Raises
    IOError

      If the input file does not exist or cannot be read.

  See also

  `scipy.sparse.save_npz`

    Save a sparse matrix to a file using `.npz` format.

  `numpy.load`

    Load several arrays from a `.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.save_npz scipy.sparse.find