def test_search(nr_points, dim, bucket_size, radius): """Test search all points within radius of center. Search all point pairs that are within radius. Arguments: - nr_points: number of points used in test - dim: dimension of coords - bucket_size: nr of points per tree node - radius: radius of search Returns true if the test passes. """ kdt = KDTree(dim, bucket_size) coords = random.random((nr_points, dim)) kdt.set_coords(coords) kdt.search(coords[0], radius * 100) radii = kdt.get_radii() l1 = 0 for i in range(0, nr_points): p = coords[i] if _dist(p, coords[0]) <= radius * 100: l1 = l1 + 1 if l1 == len(radii): return True else: return False