def argsort(self, axis=-<NUM_LIT:1>, kind='<STR_LIT>', order=None):
index_array = np.core.fromnumeric._wrapit(self, '<STR_LIT>', axis,<EOL>kind, order)<EOL>index_array = index_array.view(np.ndarray)<EOL>return index_array<EOL>
Returns the indices that would sort an array.

.. note::

        This method wraps `numpy.argsort`.  This documentation is 
        modified from that of `numpy.argsort`.

Perform an indirect sort along the given axis using the algorithm 
specified by the `kind` keyword.  It returns an array of indices of the 
same shape as the original array that index data along the given axis 
in sorted order.

**Parameters**

        **axis** : int or None, optional

                Axis along which to sort.  The default is -1 (the last 
                axis). If `None`, the flattened array is used.

        **kind** : {'quicksort', 'mergesort', 'heapsort'}, optional

                Sorting algorithm.

        **order** : list, optional

                This argument specifies which fields to compare first, 
                second, etc.  Not all fields need be specified.

**Returns**

        **index_array** : ndarray, int

                Array of indices that sort the tabarray along the 
                specified axis.  In other words, ``a[index_array]`` 
                yields a sorted `a`.

        **See Also**

                sort : Describes sorting algorithms used.
                lexsort : Indirect stable sort with multiple keys.
                ndarray.sort : Inplace sort.

        **Notes**

                See `numpy.sort` for notes on the different sorting 
                algorithms.

        **Examples**

                Sorting with keys:

                >>> x = tabarray([(1, 0), (0, 1)], dtype=[('x', '<i4'), ('y', '<i4')])
                >>> x
                tabarray([(1, 0), (0, 1)], 
                      dtype=[('x', '<i4'), ('y', '<i4')])

                >>> x.argsort(order=('x','y'))
                array([1, 0])

                >>> x.argsort(order=('y','x'))
                array([0, 1])