improve exmples

examples/02_congestion_resolution.py

@@ -1,4 +1,3 @@
-
 from inire.geometry.collision import CollisionEngine
 from inire.geometry.primitives import Port
 from inire.router.astar import AStarRouter
@@ -9,7 +8,7 @@ from inire.utils.visualization import plot_routing_results
 
 
 def main() -> None:
-    print("Running Example 02: Congestion Resolution (Crossing)...")
+    print("Running Example 02: Congestion Resolution (Triple Crossing)...")
 
     # 1. Setup Environment (Open space)
     bounds = (0, 0, 100, 100)
@@ -22,23 +21,24 @@ def main() -> None:
     pf = PathFinder(router, evaluator)
 
     # 2. Define Netlist
-    # Two nets that MUST cross.
-    # Since crossings are illegal in single-layer routing, one net must detour around the other.
+    # Three nets that all converge on the same central area.
+    # Negotiated Congestion must find non-overlapping paths for all of them.
     netlist = {
         "horizontal": (Port(10, 50, 0), Port(90, 50, 0)),
-        "vertical": (Port(50, 10, 90), Port(50, 90, 90)),
+        "vertical_up": (Port(45, 10, 90), Port(45, 90, 90)),
+        "vertical_down": (Port(55, 90, 270), Port(55, 10, 270)),
     }
-    net_widths = {"horizontal": 2.0, "vertical": 2.0}
+    net_widths = {nid: 2.0 for nid in netlist}
 
     # 3. Route with Negotiated Congestion
     # We increase the base penalty to encourage faster divergence
-    pf.base_congestion_penalty = 500.0
+    pf.base_congestion_penalty = 1000.0
     results = pf.route_all(netlist, net_widths)
 
     # 4. Check Results
     all_valid = all(r.is_valid for r in results.values())
     if all_valid:
-        print("Success! Congestion resolved (one net detoured).")
+        print("Success! Congestion resolved for all nets.")
     else:
         print("Some nets failed or have collisions.")
         for nid, res in results.items():

examples/03_locked_paths.py

@@ -1,4 +1,3 @@
-
 from inire.geometry.collision import CollisionEngine
 from inire.geometry.primitives import Port
 from inire.router.astar import AStarRouter
@@ -9,68 +8,64 @@ from inire.utils.visualization import plot_routing_results
 
 
 def main() -> None:
-    print("Running Example 03: Locked Paths (Incremental Routing)...")
+    print("Running Example 03: Locked Paths (Incremental Routing - Bus Scenario)...")
 
     # 1. Setup Environment
-    bounds = (0, 0, 100, 100)
+    bounds = (0, 0, 120, 120)
     engine = CollisionEngine(clearance=2.0)
     danger_map = DangerMap(bounds=bounds)
-    danger_map.precompute([]) # No initial obstacles
+    danger_map.precompute([]) # Start with empty space
 
-    evaluator = CostEvaluator(engine, danger_map)
-    router = AStarRouter(evaluator)
+    evaluator = CostEvaluator(engine, danger_map, greedy_h_weight=1.2)
+    router = AStarRouter(evaluator, node_limit=200000)
     pf = PathFinder(router, evaluator)
 
-    # 2. Phase 1: Route a "Critical" Net
-    # This net gets priority and takes the best path.
-    netlist_phase1 = {
-        "critical_net": (Port(10, 50, 0), Port(90, 50, 0)),
+    # 2. Phase 1: Route a "Bus" of 3 parallel nets
+    # We give them a small jog to make the locked geometry more interesting
+    netlist_p1 = {
+        "bus_0": (Port(10, 40, 0), Port(110, 45, 0)),
+        "bus_1": (Port(10, 50, 0), Port(110, 55, 0)),
+        "bus_2": (Port(10, 60, 0), Port(110, 65, 0)),
     }
-    print("Phase 1: Routing critical_net...")
-    results1 = pf.route_all(netlist_phase1, {"critical_net": 3.0}) # Wider trace
+    print("Phase 1: Routing bus (3 nets)...")
+    results_p1 = pf.route_all(netlist_p1, {nid: 2.0 for nid in netlist_p1})
 
-    if not results1["critical_net"].is_valid:
-        print("Error: Phase 1 failed.")
-        return
+    # Lock all Phase 1 nets
+    path_polys = []
+    for nid, res in results_p1.items():
+        if res.is_valid:
+            print(f"  Locking {nid}...")
+            engine.lock_net(nid)
+            path_polys.extend([p for comp in res.path for p in comp.geometry])
+        else:
+            print(f"  Warning: {nid} failed to route correctly.")
 
-    # 3. Lock the Critical Net
-    # This converts the dynamic path into a static obstacle in the collision engine.
-    print("Locking critical_net...")
-    engine.lock_net("critical_net")
-
-    # Update danger map to reflect the new obstacle (optional but recommended for heuristics)
-    # Extract polygons from result
-    path_polys = [p for comp in results1["critical_net"].path for p in comp.geometry]
+    # Update danger map with the newly locked geometry
+    print("Updating DangerMap with locked paths...")
     danger_map.precompute(path_polys)
 
-    # 4. Phase 2: Route a Secondary Net
-    # This net must route *around* the locked critical_net.
-    # Start and end points force a crossing path if it were straight.
-    netlist_phase2 = {
-        "secondary_net": (Port(50, 10, 90), Port(50, 90, 90)),
+    # 3. Phase 2: Route secondary nets that must navigate around the locked bus
+    # These nets cross the bus vertically.
+    netlist_p2 = {
+        "cross_left": (Port(30, 10, 90), Port(30, 110, 90)),
+        "cross_right": (Port(80, 110, 270), Port(80, 10, 270)), # Top to bottom
     }
     
-    print("Phase 2: Routing secondary_net around locked path...")
-    results2 = pf.route_all(netlist_phase2, {"secondary_net": 2.0})
+    print("Phase 2: Routing crossing nets around locked bus...")
+    # We use a slightly different width for variety
+    results_p2 = pf.route_all(netlist_p2, {nid: 1.5 for nid in netlist_p2})
 
-    if results2["secondary_net"].is_valid:
-        print("Success! Secondary net routed around locked path.")
-    else:
-        print("Failed to route secondary net.")
+    # 4. Check Results
+    for nid, res in results_p2.items():
+        status = "Success" if res.is_valid else "Failed"
+        print(f"  {nid:12}: {status}, collisions={res.collisions}")
 
     # 5. Visualize
-    # Combine results and netlists for plotting
-    all_results = {**results1, **results2}
-    all_netlists = {**netlist_phase1, **netlist_phase2}
-
-    # Note: 'critical_net' is now in engine.static_obstacles internally, 
-    # but for visualization we plot it from the result object to see it clearly.
-    # We pass an empty list for 'static_obstacles' to plot_routing_results 
-    # because we want to see the path colored, not grayed out as an obstacle.
+    all_results = {**results_p1, **results_p2}
+    all_netlists = {**netlist_p1, **netlist_p2}
 
     fig, ax = plot_routing_results(all_results, [], bounds, netlist=all_netlists)
     fig.savefig("examples/locked.png")
-
     print("Saved plot to examples/locked.png")