A 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, PCD (PointCloud), volumetric TIFF stacks, SLC, MHD, 2D images PNG, JPEG.
• Export meshes as ASCII or binary to VTK, STL, PLY formats with command vtkconvert.
• 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 with SHTools package for spherical harmonics expansion of a mesh shape.
• Integration with the Qt5 framework.

In your python script, load a simple 3DS file and display it:

from vtkplotter import show

show('data/shapes/flamingo.3ds') 

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

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

vtkplotter -g -c blue examples/data/embryo.slc  # (3D scan of a mouse embryo)
vtkplotter --slicer   examples/data/embryo.slc    

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 100 examples can be found in directories (scroll down to see the screenshots):
examples/basic
examples/advanced
examples/volumetric
examples/simulations
examples/other.

	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
	Simulation of Rutherford scattering of charged particles on a fixed target (script) python simulations/particle_simulator.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

Scientific publications using vtkplotter so far:

1. Diego, X. et al: "Key features of Turing systems are determined purely by network topology", Physical Review X, 20 June 2018.
2. M. Musy, K. Flaherty, J. Raspopovic, A. Robert-Moreno, J. T. Richtsmeier, J. Sharpe: "A Quantitative Method for Staging Mouse Limb Embryos based on Limb Morphometry", Development 2018, doi: 10.1242/dev.154856, 5 April 2018.
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, G. Dalmasso, & B. Sullivan, "vtkplotter, a python module for scientific visualization, analysis and animation of 3D objects and point clouds based on VTK", (version v8.9.0), Zenodo 2019, doi: 10.5281/zenodo.2561402, 10 February 2019.