Python module for 3D scientific visualization with VTK

 A Python module for scientific visualization, analysis and animation
 of 3D objects and point clouds based on VTK and numpy.
 .
 Intuitive and straightforward API which can be combined with VTK
 seamlessly in a program, whilst maintaining access to the full range
 of VTK native classes.
 .
 It includes a large set of working examples for the all following
 functionalities:
 .
   * Import meshes from VTK format, STL, Wavefront OBJ, 3DS, XML,
       Neutral, GMSH, OFF, PCD (PointCloud), volumetric TIFF stacks, SLC,
       MHD, 2D images PNG, JPEG.
   * Export meshes as ASCII or binary to VTK, STL, OBJ, PLY formats.
   * Mesh analysis through the built-in methods of VTK package.
       Additional analysis tools like Moving Least Squares, mesh
       morphing.
   * Tools to visualize and edit meshes (cutting a mesh with another
       mesh, slicing, normalizing, moving vertex positions, etc..).
       Interactive cutter widget.
   * Split mesh based on surface connectivity. Extract the largest
       connected area.
   * Calculate mass properties, like area, volume, center of mass,
       average size etc.
   * Calculate vertex and face normals, curvatures, feature edges.
       Fill mesh holes.
   * Subdivide faces of a mesh, increasing the number of vertex
       points. Mesh simplification.
   * Coloring and thresholding of meshes based on associated scalar
       or vectorial data.
   * Point-surface operations: find nearest points, determine if a
       point lies inside or outside a mesh.
   * Create primitive objects like: spheres, arrows, cubes, torus,
       ellipsoids...
   * Generate glyphs (associating a mesh to each vertex of a source
       mesh).
   * Create animations easily by just defining the position of the
       displayed objects in the 3D scene. Add trailing lines to moving
       objects automatically.
   * Straightforward support for multiple sync-ed or independent
       renderers in the same window.
   * Registration (alignment) of meshes with different techniques.
   * Mesh smoothing with Laplacian and WindowedSinc algorithms.
   * Delaunay triangulation in 2D and 3D.
   * Generate meshes by joining nearby lines in space.
   * Find the closest path from one point to another, travelling
       along the edges of a mesh.
   * Find the intersection of a mesh with a line (or with another
       mesh).
   * Analysis of Point Clouds:
       - Moving Least Squares smoothing of 2D, 3D and 4D clouds
       - Fit lines, planes and spheres in space
       - Perform PCA (Principal Component Analysis) on point
          coordinates
       - Identify outliers in a distribution of points
       - Decimate a cloud to a uniform distribution.
   * Basic histogramming and function plotting in 1D and 2D.
   * Interpolate scalar and vectorial fields with Radial Basis
       Functions and Thin Plate Splines.
   * Analysis of volumetric datasets:
       - Isosurfacing of volumes
       - Direct maximum projection rendering
       - Generate volumetric signed-distance data from an input
          surface mesh
       - Probe a volume with lines and planes.
   * Add sliders and buttons to interact with the scene and the
       individual objects.
   * Examples using SHTools package for spherical harmonics
       expansion of a mesh shape.
   * Integration with the Qt5 framework.
   * Support for FEniCS/dolfin package.
 .
 vedo is published in M. Musy et al. "vedo, a Python
 module for scientific visualization and analysis of 3D objects and
 point clouds based on VTK (Visualization Toolkit)", Zenodo, 10
 February 2019, doi:10.5281/zenodo.2561401.
 Formerly known as vtkplotter.
 .
 This package installs the library for Python 3.
 It also include vedo and vtkconvert executables.