code: def convex_decomposition(self, maxhulls=20, **kwargs):
          
          result = decomposition.convex_decomposition(self,
                                                      maxhulls=maxhulls,
                                                      **kwargs)
          return result
docs: Compute an approximate convex decomposition of a mesh.
  
          testVHACD Parameters which can be passed as kwargs:
  
          Name                                        Default
          -----------------------------------------------------
          resolution                                  100000
          max. concavity                              0.001
          plane down-sampling                         4
          convex-hull down-sampling                   4
          alpha                                       0.05
          beta                                        0.05
          maxhulls                                    10
          pca                                         0
          mode                                        0
          max. vertices per convex-hull               64
          min. volume to add vertices to convex-hulls 0.0001
          convex-hull approximation                   1
          OpenCL acceleration                         1
          OpenCL platform ID                          0
          OpenCL device ID                            0
          output                                      output.wrl
          log                                         log.txt
  
  
          Parameters
          ----------
          maxhulls :  int
            Maximum number of convex hulls to return
          **kwargs :  testVHACD keyword arguments
  
          Returns
          -------
          meshes : list of trimesh.Trimesh
            List of convex meshes that approximate the original