pyvista

Installation
SKILL.md

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()

Volume Rendering (Seismic)

grid = pv.ImageData(dimensions=(nx+1, ny+1, nz+1), spacing=(25, 25, 10))
grid.cell_data['amplitude'] = data.ravel(order='F')
pv.Plotter().add_volume(grid, cmap='seismic', opacity='sigmoid').show()

Slice Through Volume

volume = pv.read('seismic.vti')
slice_x = volume.slice(normal='x', origin=volume.center)
pv.Plotter().add_mesh(slice_x, cmap='seismic').show()

Well Path Visualization

points = np.column_stack([x, y, z])  # Well trajectory
tube = pv.Spline(points, 500).tube(radius=5)
pv.Plotter().add_mesh(tube, color='brown', label='Well').add_legend().show()

Combine Multiple Surfaces

plotter = pv.Plotter()
plotter.add_mesh(horizon1, color='gold', opacity=0.7, label='Top')
plotter.add_mesh(horizon2, color='blue', opacity=0.7, label='Base')
plotter.add_mesh(fault, color='red', opacity=0.5, label='Fault')
plotter.add_legend().show()

Export for Publication

plotter = pv.Plotter(off_screen=True)
plotter.add_mesh(mesh, cmap='terrain')
plotter.screenshot('figure.png', scale=3)   # High-res image
plotter.export_html('model.html')           # Interactive HTML

Color Maps

Map Use Case
terrain Topography, elevation
seismic Seismic amplitudes (diverging)
viridis General scientific
Set1, Set2 Categorical (lithology)

Supported Formats

.vtk, .vtu, .vti, .vtp, .stl, .obj, .ply (read/write)

When to Use vs Alternatives

Tool Best For Limitations
pyvista Pythonic 3D viz, VTK wrapper, mesh operations, scripting Requires display or off-screen backend
Mayavi Scientific 3D visualization, volume rendering Heavier dependency, less active development
ParaView Interactive GUI exploration of large 3D datasets GUI-focused, scripting is secondary
matplotlib 3D Simple 3D scatter/surface plots Limited interactivity, not true 3D engine

Use pyvista when you need programmatic 3D visualization of geological models, meshes, or point clouds with VTK power but a Pythonic API.

Consider alternatives when you need a full GUI for exploring large models (use ParaView), legacy scientific visualization (use Mayavi), or only need simple 3D scatter plots (use matplotlib 3D).

Common Workflows

Visualize 3D geological model with multiple surfaces

  • Load mesh files with pv.read() for each surface/horizon
  • Create plotter with pv.Plotter() (use off_screen=True for scripts)
  • Add each surface with plotter.add_mesh() and distinct colors/opacity
  • Add well paths as tubes with pv.Spline().tube()
  • Add axes and legend with plotter.add_axes() and plotter.add_legend()
  • Set camera position for desired view angle
  • Export screenshot with plotter.screenshot() or HTML with plotter.export_html()

Tips

  • Use off_screen=True for batch processing
  • Add axes with plotter.add_axes() for publication
  • Export to HTML for interactive sharing
  • Use opacity to show internal structure

References

Scripts

Related skills
Installs
18
GitHub Stars
23
First Seen
Mar 8, 2026