parameters: (m)
return_statement: return m[:, ::-1]
docstring: Flip array in the left/right direction.
  
      Flip the entries in each row in the left/right direction.
      Columns are preserved, but appear in a different order than before.
  
      Parameters
      ----------
      m : array_like
          Input array.
  
      Returns
      -------
      f : ndarray
          A view of `m` with the columns reversed.  Since a view
          is returned, this operation is :math:`\\mathcal O(1)`.
  
      See Also
      --------
      flipud : Flip array in the up/down direction.
      rot90 : Rotate array counterclockwise.
  
      Notes
      -----
      Equivalent to A[:,::-1]. Does not require the array to be
      two-dimensional.
  
      Examples
      --------
      >>> A = np.diag([1.,2.,3.])
      >>> A
      array([[ 1.,  0.,  0.],
             [ 0.,  2.,  0.],
             [ 0.,  0.,  3.]])
      >>> np.fliplr(A)
      array([[ 0.,  0.,  1.],
             [ 0.,  2.,  0.],
             [ 3.,  0.,  0.]])
  
      >>> A = np.random.randn(2,3,5)
      >>> np.all(np.fliplr(A)==A[:,::-1,...])
      True
docstring_summary: Flip array in the left/right direction.
docstring_tokens: Flip array in the left / right direction .
function: def fliplr(m):
      """
      Flip array in the left/right direction.
  
      Flip the entries in each row in the left/right direction.
      Columns are preserved, but appear in a different order than before.
  
      Parameters
      ----------
      m : array_like
          Input array.
  
      Returns
      -------
      f : ndarray
          A view of `m` with the columns reversed.  Since a view
          is returned, this operation is :math:`\\mathcal O(1)`.
  
      See Also
      --------
      flipud : Flip array in the up/down direction.
      rot90 : Rotate array counterclockwise.
  
      Notes
      -----
      Equivalent to A[:,::-1]. Does not require the array to be
      two-dimensional.
  
      Examples
      --------
      >>> A = np.diag([1.,2.,3.])
      >>> A
      array([[ 1.,  0.,  0.],
             [ 0.,  2.,  0.],
             [ 0.,  0.,  3.]])
      >>> np.fliplr(A)
      array([[ 0.,  0.,  1.],
             [ 0.,  2.,  0.],
             [ 3.,  0.,  0.]])
  
      >>> A = np.random.randn(2,3,5)
      >>> np.all(np.fliplr(A)==A[:,::-1,...])
      True
  
      """
      m = asanyarray(m)
      if m.ndim < 2:
          raise ValueError("Input must be >= 2-d.")
      return m[:, ::-1]
function_tokens: def fliplr ( m ) : m = asanyarray ( m ) if m . ndim < 2 : raise ValueError ( "Input must be >= 2-d." ) return m [ : , : : - 1 ]