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)...
import pyvista as pv
mesh = pv.read('model.vtk')
plotter = pv.Plotter()
plotter.add_mesh(mesh, scalars='property', cmap='viridis')
plotter.show()
| 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) |
mesh = pv.read('model.vtk')
plotter = pv.Plotter()
plotter.add_mesh(mesh, scalars='lithology', cmap='Set1')
plotter.show()
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()
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()
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()
volume = pv.read('seismic.vti')
slice_x = volume.slice(normal='x', origin=volume.center)
pv.Plotter().add_mesh(slice_x, cmap='seismic').show()
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()
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()
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
| Map | Use Case |
|---|---|
terrain |
Topography, elevation |
seismic |
Seismic amplitudes (diverging) |
viridis |
General scientific |
Set1, Set2 |
Categorical (lithology) |
.vtk, .vtu, .vti, .vtp, .stl, .obj, .ply (read/write)
| 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).
pv.read() for each surface/horizonpv.Plotter() (use off_screen=True for scripts)plotter.add_mesh() and distinct colors/opacitypv.Spline().tube()plotter.add_axes() and plotter.add_legend()plotter.screenshot() or HTML with plotter.export_html()off_screen=True for batch processingplotter.add_axes() for publication