scipy.spatial.KDTree.query_ball_tree¶

KDTree.query_ball_tree(other, r, p=2.0, eps=0)[source]¶

Find all pairs of points whose distance is at most r

Parameters:

Parameters:	other : KDTree instance The tree containing points to search against. r : float The maximum distance, has to be positive. p : float, optional Which Minkowski norm to use. p has to meet the condition `1 <= p <= infinity`. eps : float, 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.
Returns:	results : list of lists For each element `self.data[i]` of this tree, `results[i]` is a list of the indices of its neighbors in `other.data`.

other : KDTree instance

The tree containing points to search against.

r : float

The maximum distance, has to be positive.

p : float, optional

Which Minkowski norm to use. p has to meet the condition 1 <= p <= infinity.

eps : float, 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.

Returns:

results : list of lists

For each element self.data[i] of this tree, results[i] is a list of the indices of its neighbors in other.data.