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I'm pretty sure you'd have to maintain some sort of "dual mesh" in parallel, e.g. a pointset with 6 * nx * ny * nz points. |
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What about using multi-component scalars? E.g. use cell data, but instead of a single value stored for each cell, store 6 values, one for each face. You can adopt a convention like The visualization isn't great, since you still have cubic cells showing even though the values are tied to faces, but this way you can filter values per-face, e.g. using import pyvista as pv
import numpy as np
Nx, Ny, Nz = 2,2, 2
x = np.linspace(0,1, Nx 1)
z = np.linspace(0,1, Ny 1)
y = np.linspace(0,1, Nz 1)
x, y, z = np.meshgrid(x, y, z)
grid = pv.StructuredGrid(x, y, z)
# Add a length-6 vector of cell data for each cell
grid.cell_data['data'] = np.reshape(range(grid.n_cells*6), (grid.n_cells,6))
# Extract cells which have a value between 0-25 for the negative x face
component = 0 # negative x component
x_neg = grid.extract_values(ranges=[0,25], component_mode=component)
x_neg.plot(opacity=0.5, show_edges=True, component=component) |
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Sample Code What is the problem, question, or error?
Write a short description telling me what you are doing, what you expect to happen, and what is currently happening.
If I have a structured grid of a unit cube, how can I "tag" each boundary face with a separate value so that I can use it for finite element analysis?
Description
I know you can add point data based on the point coordinates, but this becomes ambiguous for points that lie on the intersection of 2 faces of the unit cube. If I use cell data, it will apply to the entire 3D cell instead of the 2D face. This also has the problem of ambiguity when a cell is on the intersection of 2 faces of the unit cube.
System Information
-------------------------------------------------------------------------------- Date: Thu Nov 14 16:10:00 2024 Central Standard Time OS : Windows CPU(s) : 12 Machine : AMD64 Architecture : 64bit RAM : 31.7 GiB Environment : IPython GPU Vendor : Intel GPU Renderer : Intel(R) UHD Graphics 630 GPU Version : 4.5.0 - Build 31.0.101.2121 MathText Support : False Python 3.11.2 (tags/v3.11.2:878ead1, Feb 7 2023, 16:38:35) [MSC v.1934 64 bit (AMD64)] pyvista : 0.44.1 vtk : 9.2.6 numpy : 2.1.3 matplotlib : 3.9.2 scooby : 0.7.1 pooch : v1.6.0 pillow : 9.5.0 imageio : 2.35.1 IPython : 8.10.0 ipywidgets : 8.0.4 scipy : 1.14.1 tqdm : 4.66.5 meshio : 5.3.5 jupyterlab : 3.6.1 jupyter_server_proxy : 3.2.2 nest_asyncio : 1.5.6 --------------------------------------------------------------------------------Screenshots
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