from collections import defaultdict, deque


def distance_risk(items, thr=80):
    centers = [((it["x1"]+it["x2"])/2, (it["y1"]+it["y2"])/2) for it in items]
    n = len(centers)
    if n < 2:
        return 0.0

    close_pairs = 0
    for i in range(n):
        cx1, cy1 = centers[i]
        for j in range(i+1, n):
            cx2, cy2 = centers[j]
            dist = ((cx1-cx2)**2 + (cy1-cy2)**2)**0.5
            if dist < thr:
                close_pairs += 1

    return min(close_pairs / 30.0, 1.0)


prev_centers = {}
trajectories = defaultdict(lambda: deque(maxlen=10))
last_seen = {}
KEEP_FRAMES = 15
frame_counter = 0


def motion_risk_and_path(items):
    global prev_centers, trajectories, last_seen, frame_counter

    frame_counter += 1
    fid = frame_counter

    curr = {}
    speeds = []

    for it in items:

        if it["tid"] == 65535:
            continue

        tid = it["tid"]

        cx = (it["x1"] + it["x2"]) / 2
        cy = (it["y1"] + it["y2"]) / 2

        curr[tid] = (cx, cy)
        trajectories[tid].append((cx, cy))

        last_seen[tid] = fid

        if tid in prev_centers:
            px, py = prev_centers[tid]
            spd = ((cx - px)**2 + (cy - py)**2)**0.5
            speeds.append(spd)

    prev_centers = curr

    for tid in list(trajectories.keys()):
        if tid not in curr:
            if fid - last_seen.get(tid, fid) > KEEP_FRAMES:
                del trajectories[tid]
                del last_seen[tid]

    if not speeds:
        risk = 0.0
    else:
        risk = min((sum(speeds) / len(speeds)) / 20.0, 1.0)

    return risk, trajectories