parameters: (v, k=0)
return_statement: return _api_internal.diagflat(v, k)
docstring: Create a two-dimensional array with the flattened input as a diagonal.
  
      Parameters
      ----------
      v : array_like
          Input data, which is flattened and set as the `k`-th
          diagonal of the output.
      k : int, optional
          Diagonal to set; 0, the default, corresponds to the "main" diagonal,
          a positive (negative) `k` giving the number of the diagonal above
          (below) the main.
  
      Returns
      -------
      out : ndarray
          The 2-D output array.
  
      See Also
      --------
      diag : MATLAB work-alike for 1-D and 2-D arrays.
      diagonal : Return specified diagonals.
      trace : Sum along diagonals.
  
      Examples
      --------
      >>> np.diagflat([[1,2], [3,4]])
      array([[1, 0, 0, 0],
             [0, 2, 0, 0],
             [0, 0, 3, 0],
             [0, 0, 0, 4]])
      >>> np.diagflat([1,2], 1)
      array([[0, 1, 0],
             [0, 0, 2],
             [0, 0, 0]])
docstring_summary: Create a two-dimensional array with the flattened input as a diagonal.
docstring_tokens: Create a two - dimensional array with the flattened input as a diagonal .
function: def diagflat(v, k=0):
      """
      Create a two-dimensional array with the flattened input as a diagonal.
  
      Parameters
      ----------
      v : array_like
          Input data, which is flattened and set as the `k`-th
          diagonal of the output.
      k : int, optional
          Diagonal to set; 0, the default, corresponds to the "main" diagonal,
          a positive (negative) `k` giving the number of the diagonal above
          (below) the main.
  
      Returns
      -------
      out : ndarray
          The 2-D output array.
  
      See Also
      --------
      diag : MATLAB work-alike for 1-D and 2-D arrays.
      diagonal : Return specified diagonals.
      trace : Sum along diagonals.
  
      Examples
      --------
      >>> np.diagflat([[1,2], [3,4]])
      array([[1, 0, 0, 0],
             [0, 2, 0, 0],
             [0, 0, 3, 0],
             [0, 0, 0, 4]])
      >>> np.diagflat([1,2], 1)
      array([[0, 1, 0],
             [0, 0, 2],
             [0, 0, 0]])
      """
      return _api_internal.diagflat(v, k)
function_tokens: def diagflat ( v , k = 0 ) : return _api_internal . diagflat ( v , k )