Spatial data refers to data represented in a geometric space, such as points on a coordinate system. We encounter spatial data problems in various tasks, such as determining whether a point lies inside a boundary. SciPy offers the scipy.spatial module, which includes functions for working with spatial data.
A triangulation of a polygon involves dividing the polygon into multiple triangles, allowing us to compute the polygon’s area. Triangulation with points refers to creating a surface of triangles where each given point is a vertex of at least one triangle. One method for generating such triangulations using points is the Delaunay() Triangulation.
Generate a triangulation from the following points:
| import numpy as np from scipy.spatial import Delaunay import matplotlib.pyplot as plt points = np.array([ [2, 4], [3, 4], [3, 0], [2, 2], [4, 1] ]) simplices = Delaunay(points).simplices plt.triplot(points[:, 0], points[:, 1], simplices) plt.scatter(points[:, 0], points[:, 1], color=‘r’) plt.show() |
Note: The simplices property generalizes the concept of a triangle notation. |
