| 123456789101112131415161718192021222324252627 |
- # A StructuredGrid is a dataset where edges of the hexahedrons are
- # not necessarily parallel to the coordinate axes.
- # It can be thought of as a tessellation of a block of 3D space,
- # similar to a `RectilinearGrid`
- # except that the cells are not necessarily cubes, they can have different
- # orientations but are connected in the same way as a `RectilinearGrid`.
- from vedo import *
- # a noisy geometry
- cx = np.sqrt(np.linspace(100, 400, 10))
- cy = np.linspace(30, 40, 20)
- cz = np.linspace(40, 50, 30)
- x, y, z = np.meshgrid(cx, cy, cz) + np.random.normal(0, 0.01, (20, 10, 30))
- # sgrid1 = StructuredGrid(dataurl + "structgrid.vts")
- sgrid1 = StructuredGrid([x, y, z])
- sgrid1.cmap("viridis", sgrid1.vertices[:, 0]+np.sin(sgrid1.vertices[:, 1]))
- print(sgrid1)
- sgrid2 = sgrid1.clone().cut_with_plane(normal=(-1,1,1), origin=[14,34,44])
- msh2 = sgrid2.tomesh(shrink=0.9).linewidth(1).cmap("viridis")
- show(
- [["StructuredGrid", sgrid1], ["Shrinked Mesh", msh2]],
- N=2, axes=1, viewup="z",
- )
|
