A pure python module for scientific visualization, analysis and animation of 3D objects and point clouds based on VTK and numpy.

Use pip to install:

pip install vtkplotter

Automatically generated documentation can be found here.

Intuitive and straightforward API which can be combined with VTK seamlessly in a program, whilst mantaining 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, DICOM, 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
  • Generate stream-lines and stream-tubes from vectorial fields
• Add sliders and buttons to interact with the scene and the individual objects.
• Draw latex-formatted formulas on the rending window.
• Examples using SHTools package for spherical harmonics expansion of a mesh shape.
• Integration with the Qt5 framework.
• Support for FEniCS/Dolfin platform for visualization of finite-element calculations.
• Export a 3D scene and embed it into a web page.

vtkplotter mesh.obj 
# valid formats: [vtk,vtu,vts,vtp,vtm,ply,obj,stl,3ds,xml,neutral,
#                 gmsh,pcd,xyz,txt,byu,tif,off,slc,vti,mhd,dcm,png,jpg]

to visualize multiple files or files time-sequences try -n or -s options. Use -h for help.
Voxel-data (mhd, vti, slc, tiff) files can also be visualized with options -g, --slicer, or --lego e.g.:

vtkplotter            examples/data/head.vti    #1 use a slider to control isosurfacing
vtkplotter -g -c blue examples/data/embryo.slc  #2 (3D scan of a mouse embryo)
vtkplotter --slicer   examples/data/embryo.slc  #3 can be used to read DICOM datasets
vtkplotter --lego     examples/data/embryo.tif  #4 visualize colorized voxels

A get-started tutorial script is available for download:

git clone https://github.com/marcomusy/vtkplotter.git
cd vtkplotter/examples
python tutorial.py

More than 160 working examples can be found in directories (scroll down to see the screenshots):
examples/basic
examples/advanced
examples/volumetric
examples/simulations
examples/other
examples/other/dolfin.

	Apply a Moving Least Squares algorithm to obtain a smooth surface from a to a large cloud of scattered points in space (script) python advanced/moving_least_squares2D.py
	Simulation of a gyroscope hanging from a spring (script) python simulations/gyroscope1.py
	Quantum-tunnelling effect integrating the Schroedinger equation with 4th order Runge-Kutta method. The animation shows the evolution of a particle in a box hitting a sinusoidal potential barrier. (script) python simulations/tunnelling2.py
	Visualizing a Turing system of reaction-diffusion between two molecules1 (script) python simulations/turing.py
	Support for the FEniCS/dolfin platform for visualization of finite element solutions (see here).

Scientific publications using vtkplotter so far:

1. X. Diego et al.: "Key features of Turing systems are determined purely by network topology", Physical Review X, 20 June 2018.
2. M. Musy, K. Flaherty et al.: "A Quantitative Method for Staging Mouse Limb Embryos based on Limb Morphometry", Development, 5 April 2018, doi: 10.1242/dev.154856.
3. G. Dalmasso et al., "Evolution in space and time of 3D volumetric images", in preparation.

Have you found this software useful for your research? Please cite it as:
M. Musy et al. "vtkplotter, 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.2561402.