bluemira.radiation_transport.neutronics.radial_wall
===================================================

.. py:module:: bluemira.radiation_transport.neutronics.radial_wall

.. autoapi-nested-parse::

   Defining (and changing) the radial (side) walls of PreCell in PreCellArrays.



Classes
-------

.. autoapisummary::

   bluemira.radiation_transport.neutronics.radial_wall.Vert
   bluemira.radiation_transport.neutronics.radial_wall.CellWalls


Module Contents
---------------

.. py:class:: Vert

   Bases: :py:obj:`enum.IntEnum`

   .. autoapi-inheritance-diagram:: bluemira.radiation_transport.neutronics.radial_wall.Vert
      :parts: 1
      :private-bases:


   Vertices index for cells


   .. py:attribute:: exterior_end
      :value: 0



   .. py:attribute:: interior_start
      :value: 1



   .. py:attribute:: interior_end
      :value: 2



   .. py:attribute:: exterior_start
      :value: 3



.. py:class:: CellWalls(cell_walls: numpy.typing.ArrayLike)

   A list of start- and end-location vectors of all of the walls dividing neighbouring
   pre-cells.


   .. py:attribute:: cell_walls


   .. py:attribute:: _starts


   .. py:attribute:: _init_ends


   .. py:attribute:: original_lengths


   .. py:attribute:: directions


   .. py:attribute:: num_cells
      :type:  int
      :value: 0



   .. py:method:: __len__() -> int

      Number of cell wall panels



   .. py:method:: __getitem__(index_or_slice) -> numpy.typing.NDArray | float

      Get cell wall panel



   .. py:method:: __setitem__(index_or_slice, new_coordinates: numpy.typing.NDArray | float)

      self[:, :, :] = ... can completely reset some coordinates.
      However, a full-reset should be avoided because we don't want to mess with the
      start rz coordinates.



   .. py:method:: __repr__() -> str

      String representation



   .. py:method:: copy() -> CellWalls

      Copy cell wall



   .. py:method:: from_pre_cell_array(pre_cell_array: bluemira.radiation_transport.neutronics.make_pre_cell.PreCellArray) -> CellWalls
      :classmethod:


      Use the corner vertices in an array of pre-cells to make a CellWalls.

      :returns: A list of cell walls from from a pre-cell array, specifically made from the
                walls dividing adjacent pre-cells from each other.



   .. py:method:: from_pre_cell_array_vv(pre_cell_array: bluemira.radiation_transport.neutronics.make_pre_cell.PreCellArray) -> CellWalls
      :classmethod:


      Use the corner vertices and the vacuum vessel vertices of the pre-cell array to
      make a CellWall.

      :returns: A list of cell walls extracted from a divertor pre-cell array, specifically
                made from the walls dividing adjacent divertor pre-cells from each other.



   .. py:property:: starts
      :type: numpy.typing.NDArray


      The start points of each cell wall. shape = (N+1, 2)


   .. py:property:: ends
      :type: numpy.typing.NDArray


      The end point changes value depending on the user-set length.


   .. py:method:: calculate_new_end_points(lengths: float | numpy.typing.NDArray[numpy.float64]) -> numpy.typing.NDArray

      Get the end points of each cell wall if they were changed to have the specified
      lengths. This is different to set_length in that the new end points are returned,
      and the object itself is not modified by the test length(s).

      :param lengths: np.ndarray of shape = (N+1,) where N+1 == number of cell walls.
                      It can also be a scalar, which would then be broadcasted into (N+1,).

      :returns: an array of the same shape as self.starts
      :rtype: new end points



   .. py:method:: get_length(i: int) -> float

      Get the length of the i-th cell-wall

      :returns: **length**
      :rtype: float



   .. py:method:: set_length(i, new_length)

      Set the length of the i-th cell-wall



   .. py:property:: lengths

      Current lengths of the cell walls.


   .. py:method:: get_volume(i)

      Get the volume of the i-ith cell

      :returns: **volume**
      :rtype: float



   .. py:property:: volumes

      Current volumes of the (simplified) cells created by joining straight lines
      between neighbouring cell walls.


   .. py:method:: check_volumes_and_lengths()

      Ensure all cells have positive volumes, to minimise the risk of self-intersecting
      lines and negative lengths

      :raises GeometryError: Cell has non positive volume



   .. py:method:: volume_of_cells_neighbouring(i, test_length)

      Get the volume of cell[i-1] and cell[i] when cell_wall[i] is set to the
      test_length.

      :returns: **volume**
      :rtype: float



   .. py:method:: volume_derivative_of_cells_neighbouring(i, test_length)

      Measure the derivative on the volume of cell[i-1] and cell[i] w.r.t. to
      length of cell_wall[i], at cell_wall[i] length = test_length.

      :returns: **dV/dl**
      :rtype: float



   .. py:method:: optimise_to_match_individual_volumes(volume_list: collections.abc.Iterable[float], *, maxiter=1000)

      Allow the lengths of each wall to increase, so that the overall volumes are
      preserved as much as possible. Assuming the entire exterior curve is convex,
      then our linear approximation is only going to under-approximate. Therefore
      to achieve better approximation, we only need to increase the lengths.