spateo.tdr.models.models_individual.mesh_utils
==============================================

.. py:module:: spateo.tdr.models.models_individual.mesh_utils

.. autoapi-nested-parse::

   This code contains methods to optimize the final reconstructed mesh model.
       1. uniform mesh
       2. fix mesh



Functions
---------

.. autoapisummary::

   spateo.tdr.models.models_individual.mesh_utils.uniform_larger_pc
   spateo.tdr.models.models_individual.mesh_utils.uniform_mesh
   spateo.tdr.models.models_individual.mesh_utils.smooth_mesh
   spateo.tdr.models.models_individual.mesh_utils.fix_mesh
   spateo.tdr.models.models_individual.mesh_utils.clean_mesh


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

.. py:function:: uniform_larger_pc(pc: pyvista.PolyData, alpha: Union[float, int] = 0, nsub: Optional[int] = 5, nclus: int = 20000) -> pyvista.PolyData

   Generates a uniform point cloud with a larger number of points.
   If the number of points in the original point cloud is too small or the distribution of the original point cloud is
   not uniform, making it difficult to construct the surface, this method can be used for preprocessing.

   :param pc: A point cloud model.
   :param alpha: Specify alpha (or distance) value to control output of this filter.
                 For a non-zero alpha value, only edges or triangles contained within a sphere centered at mesh vertices
                 will be output. Otherwise, only triangles will be output.
   :param nsub: Number of subdivisions. Each subdivision creates 4 new triangles, so the number of resulting triangles is
                nface*4**nsub where nface is the current number of faces.
   :param nclus: Number of voronoi clustering.

   :returns: A uniform point cloud with a larger number of points.
   :rtype: new_pc


.. py:function:: uniform_mesh(mesh: pyvista.PolyData, nsub: Optional[int] = 3, nclus: int = 20000) -> pyvista.PolyData

   Generate a uniformly meshed surface using voronoi clustering.

   :param mesh: A mesh model.
   :param nsub: Number of subdivisions. Each subdivision creates 4 new triangles, so the number of resulting triangles is
                nface*4**nsub where nface is the current number of faces.
   :param nclus: Number of voronoi clustering.

   :returns: A uniform mesh model.
   :rtype: new_mesh


.. py:function:: smooth_mesh(mesh: pyvista.PolyData, n_iter: int = 100, **kwargs) -> pyvista.PolyData

   Adjust point coordinates using Laplacian smoothing.
   https://docs.pyvista.org/api/core/_autosummary/pyvista.PolyData.smooth.html#pyvista.PolyData.smooth

   :param mesh: A mesh model.
   :param n_iter: Number of iterations for Laplacian smoothing.
   :param \*\*kwargs: The rest of the parameters in pyvista.PolyData.smooth.

   :returns: A smoothed mesh model.
   :rtype: smoothed_mesh


.. py:function:: fix_mesh(mesh: pyvista.PolyData) -> pyvista.PolyData

   Repair the mesh where it was extracted and subtle holes along complex parts of the mesh.


.. py:function:: clean_mesh(mesh: pyvista.PolyData) -> pyvista.PolyData

   Removes unused points and degenerate cells.