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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. :

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