import numpy as np
import time
from inire.geometry.collision import CollisionEngine
from inire.geometry.primitives import Port
from inire.router.astar import AStarContext, AStarMetrics
from inire.router.cost import CostEvaluator
from inire.router.danger_map import DangerMap
from inire.router.pathfinder import PathFinder
from inire.utils.visualization import plot_routing_results, plot_danger_map, plot_expanded_nodes, plot_expansion_density
from shapely.geometry import box

def main() -> None:
    print("Running Example 07: Fan-Out (10 Nets, 50um Radius)...")

    # 1. Setup Environment
    bounds = (0, 0, 1000, 1000)
    engine = CollisionEngine(clearance=6.0)

    # Bottleneck at x=500, 200um gap
    obstacles = [
        box(450, 0, 550, 400),
        box(450, 600, 550, 1000),
    ]
    for obs in obstacles:
        engine.add_static_obstacle(obs)

    danger_map = DangerMap(bounds=bounds)
    danger_map.precompute(obstacles)

    evaluator = CostEvaluator(engine, danger_map, greedy_h_weight=1.5, unit_length_cost=0.1, bend_penalty=100.0, sbend_penalty=400.0, congestion_penalty=100.0)

    context = AStarContext(evaluator, node_limit=2000000, bend_radii=[50.0], sbend_radii=[50.0])
    metrics = AStarMetrics()
    pf = PathFinder(context, metrics, max_iterations=15, base_congestion_penalty=100.0, congestion_multiplier=1.4)

    # 2. Define Netlist
    netlist = {}
    num_nets = 10
    start_x = 50
    start_y_base = 500 - (num_nets * 10.0) / 2.0

    end_x = 950
    end_y_base = 100
    end_y_pitch = 800.0 / (num_nets - 1)

    for i in range(num_nets):
        sy = int(round(start_y_base + i * 10.0))
        ey = int(round(end_y_base + i * end_y_pitch))
        netlist[f"net_{i:02d}"] = (Port(start_x, sy, 0), Port(end_x, ey, 0))

    net_widths = {nid: 2.0 for nid in netlist}

    # 3. Route
    print(f"Routing {len(netlist)} nets through 200um bottleneck...")

    iteration_stats = []

    def iteration_callback(idx, current_results):
        successes = sum(1 for r in current_results.values() if r.is_valid)
        total_collisions = sum(r.collisions for r in current_results.values())
        total_nodes = metrics.nodes_expanded

        print(f"  Iteration {idx} finished. Successes: {successes}/{len(netlist)}, Collisions: {total_collisions}")
        
        # Adaptive Greediness: Decay from 1.5 to 1.1 over 10 iterations
        new_greedy = max(1.1, 1.5 - ((idx + 1) / 10.0) * 0.4)
        evaluator.greedy_h_weight = new_greedy
        print(f"  Adaptive Greedy Weight for Next Iteration: {new_greedy:.3f}")

        iteration_stats.append({
            'Iteration': idx,
            'Success': successes,
            'Congestion': total_collisions,
            'Nodes': total_nodes
        })
        metrics.reset_per_route()

    t0 = time.perf_counter()
    results = pf.route_all(netlist, net_widths, store_expanded=True, iteration_callback=iteration_callback, shuffle_nets=True, seed=42)
    t1 = time.perf_counter()

    print(f"Routing took {t1-t0:.4f}s")

    # 4. Check Results
    print("\n--- Iteration Summary ---")
    print(f"{'Iter':<5} | {'Success':<8} | {'Congest':<8} | {'Nodes':<10}")
    print("-" * 40)
    for s in iteration_stats:
        print(f"{s['Iteration']:<5} | {s['Success']:<8} | {s['Congestion']:<8} | {s['Nodes']:<10}")

    success_count = sum(1 for res in results.values() if res.is_valid)
    print(f"\nFinal: Routed {success_count}/{len(netlist)} nets successfully.")

    for nid, res in results.items():
        if not res.is_valid:
            print(f"  FAILED: {nid}, collisions={res.collisions}")
        else:
            print(f"  {nid}: SUCCESS")

    # 5. Visualize
    fig, ax = plot_routing_results(results, obstacles, bounds, netlist=netlist)
    plot_danger_map(danger_map, ax=ax)

    fig.savefig("examples/07_large_scale_routing.png")
    print("Saved plot to examples/07_large_scale_routing.png")

if __name__ == "__main__":
    main()