rtree

from rtree import index # Create an in-memory R-tree index idx = index.Index() # Insert some bounding boxes (id, (minx, miny, maxx, maxy)) # Note: IDs are not enforced to be unique by Rtree itself idx.insert(0, (0, 0, 1, 1)) # Item with ID 0, bounds (0,0) to (1,1) idx.insert(1, (0.5, 0.5, 1.5, 1.5)) idx.insert(2, (2, 2, 3, 3)) idx.insert(3, (0.8, 0.8, 1.2, 1.2), obj={'name': 'Intersection Point'}) # Query for intersections with a given bounding box search_bounds = (0.7, 0.7, 1.1, 1.1) hits = list(idx.intersection(search_bounds)) print(f"IDs intersecting {search_bounds}: {hits}") # Query for intersections and retrieve objects (if stored) hits_with_objects = list(idx.intersection(search_bounds, objects=True)) print("Items intersecting (with objects):") for item in hits_with_objects: print(f" ID: {item.id}, Bounds: {item.bbox}, Object: {item.object}") # Query for nearest neighbors nearest_point = (0.1, 0.1) nearest_items = list(idx.nearest(nearest_point, num_results=1)) print(f"Nearest item to {nearest_point}: {nearest_items}")