pyvista

name	pyvista
description	3D visualization and mesh analysis for geoscience data using PyVista/VTK. Use when Claude needs to: (1) Create 3D visualizations of geological models, (2) Render seismic volumes or voxel data, (3) Visualize point clouds or well paths, (4) Plot surfaces and meshes in 3D, (5) Read/write VTK, STL, OBJ files, (6) Create cross-sections through 3D models, (7) Export publication-quality figures or interactive HTML.
version	1.0.0
author	Geoscience Skills
license	MIT
tags	["3D Visualization","VTK","Mesh","Geological Models","Point Clouds"]
dependencies	["pyvista>=0.42.0","numpy","vtk"]
complements	["gempy","simpeg","verde","segyio","xarray"]
workflow_role	visualization

PyVista - 3D Visualization

Quick Reference

import pyvista as pv

mesh = pv.read('model.vtk')
plotter = pv.Plotter()
plotter.add_mesh(mesh, scalars='property', cmap='viridis')
plotter.show()

Key Classes

Class	Purpose
pv.Plotter	Main visualization window
pv.PolyData	Surface meshes, point clouds
pv.StructuredGrid	Regular 3D grids
pv.UnstructuredGrid	Irregular meshes
pv.ImageData	3D voxel data (seismic)

Essential Operations

Load and Display Mesh

mesh = pv.read('model.vtk')
plotter = pv.Plotter()
plotter.add_mesh(mesh, scalars='lithology', cmap='Set1')
plotter.show()

Create Structured Grid (Surface)

x, y = np.meshgrid(np.arange(-10, 10, 0.5), np.arange(-10, 10, 0.5))
z = np.sin(np.sqrt(x**2 + y**2))
grid = pv.StructuredGrid(x, y, z)
pv.Plotter().add_mesh(grid, scalars=z.ravel(), cmap='terrain').show()

Visualize Point Cloud

cloud = pv.PolyData(np.random.rand(1000, 3) * 100)
cloud['depth'] = cloud.points[:, 2]
pv.Plotter().add_mesh(cloud, scalars='depth', point_size=5,
                      render_points_as_spheres=True).show()