%matplotlib inline from pyvista import set_plot_theme set_plot_theme('document')
#Terrain Following Mesh
Use a topographic surface to create a 3D terrain-following mesh.
Terrain following meshes are common in the environmental sciences, for instance
in hydrological modelling (see
Maxwell 2013 <https://www.sciencedirect.com/science/article/abs/pii/S0309170812002564>_
In this example, we demonstrate a simple way to make a 3D grid/mesh that follows a given topographic surface. In this example, it is important to note that the given digital elevation model (DEM) is structured (gridded and not triangulated): this is common for DEMs.
# sphinx_gallery_thumbnail_number = 3 import pyvista as pv import numpy as np from pyvista import examples
Download a gridded topography surface (DEM)
dem = examples.download_crater_topo() dem
Now let's subsample and extract an area of interest to make this example
simple (also the DEM we just load is pretty big).
Since the DEM we loaded is a :class:
pyvista.UniformGrid mesh, we can use
subset = dem.extract_subset((500, 900, 400, 800, 0, 0), (5, 5, 1)) subset.plot(cpos="xy")
Now that we have a region of interest for our terrain following mesh, lets make a 3D surface of that DEM:
terrain = subset.warp_by_scalar() terrain
And now we have a 3D structured surface of the terrain! We can now extend
that structured surface into a 3D mesh to form a terrain following grid.
To do this, we first our cell spacings in the z-direction (these start
from the terrain surface). Then we repeat the XYZ structured coordinates
of the terrain mesh and decrease each Z level by our Z cell spacing.
Once we have those structured coordinates, we can create a
z_cells = np.array( * 5 +  * 3 +  * 2 + [75, 100]) xx = np.repeat(terrain.x, len(z_cells), axis=-1) yy = np.repeat(terrain.y, len(z_cells), axis=-1) zz = np.repeat(terrain.z, len(z_cells), axis=-1) - np.cumsum(z_cells).reshape( (1, 1, -1) ) mesh = pv.StructuredGrid(xx, yy, zz) mesh["Elevation"] = zz.ravel(order="F") mesh
cpos = [ (1826736.796308761, 5655837.275274233, 4676.8405505181745), (1821066.1790519988, 5649248.765538796, 943.0995128226014), (-0.2797856225380979, -0.27966946337594883, 0.9184252809434081), ] mesh.plot(show_edges=True, lighting=False, cpos=cpos)