pyvista-3d

name	pyvista-3d
description	AI interface skill for PyVista 3D visualization --- VTK wrapper for mesh rendering, STL/OBJ/VTK I/O, scalar coloring, offscreen rendering, and engineering analysis post-processing.
type	reference
version	1.0.0
updated	"2026-03-31T00:00:00.000Z"
category	engineering
triggers	["PyVista","pyvista","3D mesh visualization","VTK visualization Python","offscreen 3D rendering","mesh quality visualization","point cloud rendering","STL visualization"]
capabilities	["input_generation","execution","output_parsing","failure_diagnosis","validation"]
requires	[]
see_also	["blender-interface","paraview-interface","gmsh-meshing"]
tags	["pyvista","vtk","3d","mesh","visualization"]
scripts_exempt	true

PyVista 3D Visualization

Overview

PyVista (MIT, 3.6k stars) is a Pythonic wrapper around VTK for 3D spatial data visualization. It provides a streamlined API for rendering meshes, point clouds, STL/OBJ geometry, and scalar fields without low-level VTK boilerplate.

Key Capabilities

Feature	Details
Mesh rendering	Surface, wireframe, point cloud, volume rendering
Scalar coloring	Map data arrays to colormaps (coolwarm, viridis, plasma, etc.)
File I/O	STL, OBJ, PLY, VTK, VTP --- plus all meshio-supported formats
Offscreen rendering	off_screen=True for headless/CI environments
GPU acceleration	Uses OpenGL via VTK; works with NVIDIA GPUs
Jupyter integration	Interactive 3D in notebooks via trame
Mesh quality	Built-in quality metrics (scaled Jacobian, aspect ratio, etc.)
Engineering use	Pipe geometry, FEA results, terrain, bathymetry, point clouds

Quick Start

import pyvista as pv

# Load and render a mesh
mesh = pv.read("geometry.stl")
mesh.plot(scalars="pressure", cmap="coolwarm")

# Offscreen rendering
plotter = pv.Plotter(off_screen=True, window_size=(1280, 720))
plotter.add_mesh(mesh, scalars="depth", cmap="viridis")
plotter.screenshot("output.png")
plotter.close()

# Pipe geometry from spline
import numpy as np
t = np.linspace(0, 10, 50)
points = np.column_stack((t, np.zeros_like(t), np.cosh((t-5)/5)))
spline = pv.Spline(points, n_points=200)
pipe = spline.tube(radius=, n_sides=)
pipe.plot()