Generating a Complex Mesh
Let’s make an example of an altered mesh structure. By making use of the PyVista library, we’ll craft a surface mesh for a 3D equation. Assemble mesh of torus knot with specified magnitude and a number of circles.
Python3
import pyvista as pv import numpy as np # Define the torus knot parameters radius = 2n1 = 3n2 = 7 # Define the 3D function for the torus knot def torus_knot(u, v): x = (radius + np.cos(n1 * u) * 0.5) * np.cos(n2 * v) y = (radius + np.cos(n1 * u) * 0.5) * np.sin(n2 * v) z = np.sin(n1 * u) * 0.5 return x, y, z # Create a mesh from the 3D function using PyVista u = np.linspace(0, 2 * np.pi, 100) v = np.linspace(0, 2 * np.pi, 100) x, y, z = torus_knot(*np.meshgrid(u, v, indexing='ij')) points = np.column_stack((x.ravel(), y.ravel(), z.ravel())) mesh = pv.PolyData(points) mesh.triangulate() mesh = mesh.extract_surface() # Visualize the torus knot mesh pv.plot(mesh, color='w', smooth_shading=True) |
Output :
Complex Mesh output
Generating meshes in Python
In computer graphics and scientific computing, the mesh is an arrangement of points, lines, and surfaces that outline the shape and structure of a 3D object or surface. Making meshes is a critical process in several industries, such as 3D modelling, simulation, visualization, and gaming. In this article, we’ll explore various libraries and techniques for crafting meshes in Python.
Prerequisites:
To comprehend this tutorial, you ought to have a fundamental comprehension of Python programming, linear algebra, and 3D geometry. You also need to have the following Python libraries installed.
- NumPy: for numerical computations and linear algebra
- Matplotlib: for visualization of 3D objects and surfaces
- Pyvista: to fabricate, alter, and render 3D objects and surfaces.