108 lines
3.8 KiB
Python
108 lines
3.8 KiB
Python
import numpy as np
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import time
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from inire.geometry.collision import CollisionEngine
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from inire.geometry.primitives import Port
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from inire.router.astar import AStarContext, AStarMetrics
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from inire.router.cost import CostEvaluator
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from inire.router.danger_map import DangerMap
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from inire.router.pathfinder import PathFinder
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from inire.utils.visualization import plot_routing_results, plot_danger_map, plot_expanded_nodes, plot_expansion_density
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from shapely.geometry import box
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def main() -> None:
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print("Running Example 07: Fan-Out (10 Nets, 50um Radius)...")
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# 1. Setup Environment
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bounds = (0, 0, 1000, 1000)
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engine = CollisionEngine(clearance=6.0)
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# Bottleneck at x=500, 200um gap
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obstacles = [
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box(450, 0, 550, 400),
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box(450, 600, 550, 1000),
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]
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for obs in obstacles:
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engine.add_static_obstacle(obs)
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danger_map = DangerMap(bounds=bounds)
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danger_map.precompute(obstacles)
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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)
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context = AStarContext(evaluator, node_limit=2000000, bend_radii=[50.0], sbend_radii=[50.0])
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metrics = AStarMetrics()
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pf = PathFinder(context, metrics, max_iterations=15, base_congestion_penalty=100.0, congestion_multiplier=1.4)
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# 2. Define Netlist
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netlist = {}
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num_nets = 10
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start_x = 50
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start_y_base = 500 - (num_nets * 10.0) / 2.0
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end_x = 950
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end_y_base = 100
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end_y_pitch = 800.0 / (num_nets - 1)
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for i in range(num_nets):
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sy = int(round(start_y_base + i * 10.0))
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ey = int(round(end_y_base + i * end_y_pitch))
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netlist[f"net_{i:02d}"] = (Port(start_x, sy, 0), Port(end_x, ey, 0))
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net_widths = {nid: 2.0 for nid in netlist}
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# 3. Route
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print(f"Routing {len(netlist)} nets through 200um bottleneck...")
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iteration_stats = []
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def iteration_callback(idx, current_results):
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successes = sum(1 for r in current_results.values() if r.is_valid)
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total_collisions = sum(r.collisions for r in current_results.values())
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total_nodes = metrics.nodes_expanded
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print(f" Iteration {idx} finished. Successes: {successes}/{len(netlist)}, Collisions: {total_collisions}")
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# Adaptive Greediness: Decay from 1.5 to 1.1 over 10 iterations
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new_greedy = max(1.1, 1.5 - ((idx + 1) / 10.0) * 0.4)
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evaluator.greedy_h_weight = new_greedy
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print(f" Adaptive Greedy Weight for Next Iteration: {new_greedy:.3f}")
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iteration_stats.append({
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'Iteration': idx,
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'Success': successes,
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'Congestion': total_collisions,
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'Nodes': total_nodes
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})
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metrics.reset_per_route()
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t0 = time.perf_counter()
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results = pf.route_all(netlist, net_widths, store_expanded=True, iteration_callback=iteration_callback, shuffle_nets=True, seed=42)
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t1 = time.perf_counter()
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print(f"Routing took {t1-t0:.4f}s")
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# 4. Check Results
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print("\n--- Iteration Summary ---")
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print(f"{'Iter':<5} | {'Success':<8} | {'Congest':<8} | {'Nodes':<10}")
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print("-" * 40)
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for s in iteration_stats:
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print(f"{s['Iteration']:<5} | {s['Success']:<8} | {s['Congestion']:<8} | {s['Nodes']:<10}")
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success_count = sum(1 for res in results.values() if res.is_valid)
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print(f"\nFinal: Routed {success_count}/{len(netlist)} nets successfully.")
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for nid, res in results.items():
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if not res.is_valid:
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print(f" FAILED: {nid}, collisions={res.collisions}")
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else:
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print(f" {nid}: SUCCESS")
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# 5. Visualize
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fig, ax = plot_routing_results(results, obstacles, bounds, netlist=netlist)
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plot_danger_map(danger_map, ax=ax)
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fig.savefig("examples/07_large_scale_routing.png")
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print("Saved plot to examples/07_large_scale_routing.png")
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if __name__ == "__main__":
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main()
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