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# numpy.ravel_multi_index

`numpy.``ravel_multi_index`(multi_index, dims, mode='raise', order='C')

  Converts a tuple of index arrays into an array of flat indices, applying boundary modes to the multi-index.

  Parameters : | multi_index : tuple of array_like A tuple of integer arrays, one array for each dimension. dims : tuple of ints The shape of array into which the indices from `multi_index` apply. mode : {‘raise’, ‘wrap’, ‘clip’}, optional Specifies how out-of-bounds indices are handled. Can specify either one mode or a tuple of modes, one mode per index. ‘raise’ – raise an error (default) ‘wrap’ – wrap around ‘clip’ – clip to the range In ‘clip’ mode, a negative index which would normally wrap will clip to 0 instead. order : {‘C’, ‘F’}, optional Determines whether the multi-index should be viewed as indexing in C (row-major) order or FORTRAN (column-major) order.
  Returns : | raveled_indices : ndarray An array of indices into the flattened version of an array of dimensions `dims`.

  See also

  `unravel_index`

  Notes

  New in version 1.6.0.

  Examples

      >>> arr = np.array([[3,6,6],[4,5,1]])
      >>> np.ravel_multi_index(arr, (7,6))
      array([22, 41, 37])
      >>> np.ravel_multi_index(arr, (7,6), order='F')
      array([31, 41, 13])
      >>> np.ravel_multi_index(arr, (4,6), mode='clip')
      array([22, 23, 19])
      >>> np.ravel_multi_index(arr, (4,4), mode=('clip','wrap'))
      array([12, 13, 13])

      >>> np.ravel_multi_index((3,1,4,1), (6,7,8,9))
      1621

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