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

Mesh Types - PyVista mesh classes and when to use each
Plotting Options - Plotter settings and rendering options

Scripts

scripts/visualize_surface.py - Visualize geological surfaces from file

pyvista

PyVista - 3D Visualization

Quick Reference

Key Classes