VTK is an excellent visualization toolkit, and with Python bindings it should be able to combine the speed of C++ with the rapid prototyping of Python. However, despite this VTK code programmed in Python generally looks the same as its C++ counterpart. This module seeks to simplify mesh creation and plotting without losing functionality.
Compare two approaches for loading and plotting a surface mesh from a file:
Plotting a Mesh using Python's VTK
Using this example,
loading and plotting an STL file requires a lot of code when using only the
import vtk # create reader reader = vtk.vtkSTLReader() reader.SetFileName("myfile.stl") mapper = vtk.vtkPolyDataMapper() if vtk.VTK_MAJOR_VERSION <= 5: mapper.SetInput(reader.GetOutput()) else: mapper.SetInputConnection(reader.GetOutputPort()) # create actor actor = vtk.vtkActor() actor.SetMapper(mapper) # Create a rendering window and renderer ren = vtk.vtkRenderer() renWin = vtk.vtkRenderWindow() renWin.AddRenderer(ren) # Create a renderwindowinteractor iren = vtk.vtkRenderWindowInteractor() iren.SetRenderWindow(renWin) # Assign actor to the renderer ren.AddActor(actor) # Enable user interface interactor iren.Initialize() renWin.Render() iren.Start() # clean up objects del iren del renWin
Plot a Mesh using PyVista
The same stl can be loaded and plotted using pyvista with:
import pyvista mesh = pyvista.PolyData('myfile.stl') mesh.plot()
The mesh object is more pythonic and the code is much more straightforward. Garbage collection is taken care of automatically and the renderer is cleaned up after the user closes the VTK plotting window.
Advanced Plotting with Numpy
When combined with numpy, you can make some truly spectacular plots:
.. testcode:: python import pyvista import numpy as np # Make a grid x, y, z = np.meshgrid(np.linspace(-5, 5, 20), np.linspace(-5, 5, 20), np.linspace(-5, 5, 5)) points = np.empty((x.size, 3)) points[:, 0] = x.ravel('F') points[:, 1] = y.ravel('F') points[:, 2] = z.ravel('F') # Compute a direction for the vector field direction = np.sin(points)**3 # plot using the plotting class plobj = pyvista.Plotter() plobj.add_arrows(points, direction, 0.5) plobj.show(screenshot='vectorfield.png')
While not everything can be simplified without losing functionality, many of the objects can. For example, triangular surface meshes in VTK can be subdivided but every other object in VTK cannot. It then makes sense that a subdivided method be added to the existing triangular surface mesh. That way, subdivision can be performed with:
from pyvista import examples mesh = examples.load_ant() submesh = mesh.subdivide(3, 'linear')
Additionally, the docstrings for all methods in PyVista are intended to be used within interactive coding sessions. This allows users to use sophisticated processing routines on the fly with immediate access to a description of how to use those methods: