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# numpy.ravel

`numpy.``ravel`(a, order='C')

  Return a flattened array.

  A 1-d array, containing the elements of the input, is returned. A copy is made only if needed.

  Parameters: | a : array_like Input array. The elements in a are read in the order specified by order, and packed as a 1-dimensional array. order : {‘C’,’F’}, optional The elements of a are read in this order. It can be either ‘C’ for row-major order, or F for column-major order. By default, row-major order is used.
  Returns: | 1d_array : ndarray Output of the same dtype as a, and of shape `(a.size(),)` (or `(np.prod(a.shape),)`).

  See also

  `ndarray.flat`
    1-D iterator over an array.
  `ndarray.flatten`
    1-D array copy of the elements of an array in row-major order.

  Notes

  In row-major order, the row index varies the slowest, and the column index the quickest. This can be generalised to multiple dimensions, where row-major order implies that the index along the first axis varies slowest, and the index along the last quickest. The opposite holds for Fortran-, or column-major, mode.

  Examples

  If an array is in C-order (default), then ravel is equivalent to `reshape(-1)`:

      >>> x = np.array([[1, 2, 3], [4, 5, 6]])
      >>> print x.reshape(-1)
      [1  2  3  4  5  6]

      >>> print np.ravel(x)
      [1  2  3  4  5  6]

  When flattening using Fortran-order, however, we see

      >>> print np.ravel(x, order='F')
      [1 4 2 5 3 6]

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