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scipy.spatial.KDTree.query_ball_point

KDTree.query_ball_point(x, r, p=2.0, eps=0)

Find all points within r of x

Parameters :

x : array_like, shape tuple + (self.m,)

The point or points to search for neighbors of

r : positive float

The radius of points to return

p : float 1<=p<=infinity

Which Minkowski p-norm to use

eps : nonnegative float

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).

Returns :

results : list or array of lists

If x is a single point, returns a list of the indices of the neighbors of x. If x is an array of points, returns an object array of shape tuple containing lists of neighbors.

Note: if you have many points whose neighbors you want to find, you may save :

substantial amounts of time by putting them in a KDTree and using query_ball_tree. :