query_pairs(self, r, p=2.0, eps=0)¶
Find all pairs of points in self whose distance is at most r.
- rpositive float
The maximum distance.
- pfloat, optional
Which Minkowski norm to use. p has to meet the condition
1 <= p <= infinity.
- epsfloat, optional
Approximate search. Branches of the tree are not explored if their nearest points are further than
r/(1+eps), and branches are added in bulk if their furthest points are nearer than
r * (1+eps). eps has to be non-negative.
Set of pairs
i < j, for which the corresponding positions are close.
You can search all pairs of points in a kd-tree within a distance:
>>> import matplotlib.pyplot as plt >>> import numpy as np >>> from scipy.spatial import KDTree >>> np.random.seed(21701) >>> points = np.random.random((20, 2)) >>> plt.figure(figsize=(6, 6)) >>> plt.plot(points[:, 0], points[:, 1], "xk", markersize=14) >>> kd_tree = KDTree(points) >>> pairs = kd_tree.query_pairs(r=0.2) >>> for (i, j) in pairs: ... plt.plot([points[i, 0], points[j, 0]], ... [points[i, 1], points[j, 1]], "-r") >>> plt.show()