pyfebiopt.visualization.plotter
===============================

.. py:module:: pyfebiopt.visualization.plotter

.. autoapi-nested-parse::

   Helpers for translating FEBio meshes to PyVista geometries and fields.



Classes
-------

.. autoapisummary::

   pyfebiopt.visualization.plotter.PVBridge


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

.. py:class:: PVBridge

   Build per-domain grids and attach pre-sliced results to PyVista.


   .. py:attribute:: mesh
      :type:  pyfebiopt.mesh.mesh.Mesh


   .. py:method:: domain_grid(domain: str) -> Any

      Build the unstructured grid for the requested domain.

      :param domain: Domain/part name from the mesh.

      :returns: PyVista ``UnstructuredGrid`` for the domain.
      :rtype: Any

      .. rubric:: Example

      ``grid = PVBridge(mesh).domain_grid("artery")``



   .. py:method:: surface_mesh(surface: str) -> Any

      Build the surface mesh for the requested surface.

      :param surface: Surface name from the mesh.

      :returns: PyVista ``PolyData`` for the surface.
      :rtype: Any



   .. py:method:: add_node_result_array(ds: pyvista.DataSet, *, view: pyfebiopt.xplt.views.NodeResultView, data: numpy.ndarray, name: str | None = None, set_active: bool = True) -> str

      Attach nodal results to the dataset with appropriate structure.

      :param ds: Target PyVista dataset.
      :param view: Source view that describes the nodal result.
      :param data: Nodal array (N or N x C).
      :param name: Optional field name override.
      :param set_active: Whether to set scalars/vectors/tensors active.

      :returns: Name of the attached field.
      :rtype: str

      .. rubric:: Example

      ``bridge.add_node_result_array(grid, view=U_view, data=U, name="U")``



   .. py:method:: add_elem_item_array(ds: pyvista.UnstructuredGrid, *, view: pyfebiopt.xplt.views.ItemResultView, domain: str, data: numpy.ndarray, name: str | None = None, set_active: bool = True) -> str

      Attach the provided element array to the cell data.

      :param ds: Target unstructured grid.
      :param view: Item view describing the result.
      :param domain: Domain label (unused; kept for symmetry with callers).
      :param data: Element result array.
      :param name: Optional field name override.
      :param set_active: Whether to set the field active.

      :returns: Name of the attached field.
      :rtype: str



   .. py:method:: add_face_item_array(ds: pyvista.PolyData | pyvista.UnstructuredGrid, *, view: pyfebiopt.xplt.views.ItemResultView, surface: str, data: numpy.ndarray, name: str | None = None, set_active: bool = True) -> str

      Attach the provided face array to the surface or cell data.

      :param ds: Target polydata or unstructured grid.
      :param view: Item view describing the result.
      :param surface: Surface name (unused; for API symmetry).
      :param data: Face result array.
      :param name: Optional field name override.
      :param set_active: Whether to set the field active.

      :returns: Name of the attached field.
      :rtype: str



   .. py:method:: add_elem_mult_reduced_array(ds: pyvista.UnstructuredGrid, *, view: pyfebiopt.xplt.views.MultResultView, domain: str, data: numpy.ndarray, reducer: str = 'mean', name: str | None = None, set_active: bool = True) -> str

      Reduce node-wise element arrays to one value per cell then attach.

      :param ds: Target unstructured grid.
      :param view: Mult result view.
      :param domain: Domain label (unused; for API symmetry).
      :param data: Block array shaped (R, Kmax[, C]).
      :param reducer: Reduction method (mean, max, min, first).
      :param name: Optional field name override.
      :param set_active: Whether to set the field active.

      :returns: Name of the attached field.
      :rtype: str



   .. py:method:: region_series_array(*, data: numpy.ndarray) -> numpy.ndarray

      Normalize region time series data to float32 arrays.

      :param data: Array shaped (T, C...) to be flattened on the last axes.

      :returns: Array shaped (T, -1) in float32.
      :rtype: np.ndarray

      Usage:
          ``flattened = bridge.region_series_array(data=series_block)``