Weighted Random Surface Sampling

Sampling can be weighted on the mesh. Compare to Random Surface Sampling.

import pyvista as pv
from pyvista import examples

import pyransame

antarctica = examples.download_antarctica_velocity()

The units of this mesh are in meters, which causes plotting issues over an entire continent. So the units are first converted to kilometers.

antarctica.points /= 1000.0  # convert to kilometers

The random sampling occurs over the area of the mesh, i.e. inside the cells. So cell data is needed for weighting. Here, pyvista.cell_centers is used to get position of the cells relative to the top of the mesh. pyvista.DataSetFilters.point_data_to_cell_data filter can be used to convert point data to the needed cell data if required.

ymax = antarctica.bounds[3]
weights = (ymax - antarctica.cell_centers().points[:, 1]) ** 2

Do weighted sampling.

points = pyransame.random_surface_dataset(antarctica, 500, weights=weights)

Now plot result.

pl = pv.Plotter()
pl.add_mesh(antarctica, color="tan")
spheres = pv.wrap(points).glyph(geom=pv.Sphere(radius=50), scale=False, orient=False)
pl.add_mesh(spheres, scalars="ssavelocity", clim=[0, 750])
pl.view_xy()
pl.show()

Static Scene

Interactive Scene

The same thing can be done with cell data on the mesh.

antarctica.cell_data["weights"] = weights
points = pyransame.random_surface_dataset(antarctica, 500, weights="weights")

Now plot result. The result will be slightly different due to random nature of the sampling.

pl = pv.Plotter()
pl.add_mesh(antarctica, color="tan")
spheres = pv.wrap(points).glyph(geom=pv.Sphere(radius=50), scale=False, orient=False)
pl.add_mesh(spheres, scalars="ssavelocity", clim=[0, 750])
pl.view_xy()
pl.show()

Static Scene

Interactive Scene