Finding index of nearest point in numpy arrays of x and y coordinates

Question

I have two 2d numpy arrays: x_array contains positional information in the x-direction, y_array contains positions in the y-direction.

I then have a long list of x,y

Answer 1

scipy.spatial also has a k-d tree implementation: scipy.spatial.KDTree.

The approach is generally to first use the point data to build up a k-d tree. The computational complexity of that is on the order of N log N, where N is the number of data points. Range queries and nearest neighbour searches can then be done with log N complexity. This is much more efficient than simply cycling through all points (complexity N).

Thus, if you have repeated range or nearest neighbor queries, a k-d tree is highly recommended.