Convert TSP start/end idx to nodes

sgptools/utils/tsp.py

@@ -24,21 +24,23 @@ def run_tsp(nodes,
             max_dist=25, 
             depth=1, 
             resample=None, 
-            start_idx=None,
-            end_idx=None,
+            start_nodes=None,
+            end_nodes=None,
             time_limit=10):
     """Method to run TSP/VRP with arbitrary start and end nodes, 
     and without any distance constraint
     
     Args:
-        nodes (ndarray): (# nodes, n_dim); Nodes to visit 
+        nodes (ndarray): (# nodes, ndim); Nodes to visit 
         num_vehicles (int): Number of robots/vehicles
         max_dist (float): Maximum distance allowed for each path when handling mutli-robot case
         depth (int): Internal parameter used to track re-try recursion depth
         resample (int): Each solution path will be resampled to have
                         `resample` number of points
-        start_idx (list): Optionl list of start node indices from which to start the solution path 
-        end_idx (list): Optionl list of end node indices from which to start the solution path 
+        start_nodes (ndarray): (# num_vehicles, ndim); Optionl array of start nodes from which 
+                                to start each vehicle's solution path
+        end_nodes (ndarray): (# num_vehicles, ndim); Optionl array of end nodes at which 
+                                to end each vehicle's solution path
         time_limit (int): TSP runtime time limit in seconds
 
     Returns:
@@ -48,28 +50,42 @@ def run_tsp(nodes,
     if depth > 5:
         print('Warning: Max depth reached')
         return None, None
-
+
+    # Add the start and end nodes to the node list
+    if end_nodes is not None:
+        assert end_nodes.shape == (num_vehicles, nodes.shape[-1]), \
+            "Incorrect end_nodes shape, should be (num_vehicles, ndim)!"
+        nodes = np.concatenate([end_nodes, nodes])
+    if start_nodes is not None:
+        assert start_nodes.shape == (num_vehicles, nodes.shape[-1]), \
+            "Incorrect start_nodes shape, should be (num_vehicles, ndim)!"
+        nodes = np.concatenate([start_nodes, nodes])
+
     # Add dummy 0 location to get arbitrary start and end node sols
-    if start_idx is None or end_idx is None:
+    if start_nodes is None or end_nodes is None:
         distance_mat = np.zeros((len(nodes)+1, len(nodes)+1))
         distance_mat[1:, 1:] = pairwise_distances(nodes, nodes)*1e4
-        trim_paths = True
+        trim_paths = True #shift to account for dummy node
     else:
         distance_mat = pairwise_distances(nodes, nodes)*1e4
         trim_paths = False
     distance_mat = distance_mat.astype(int)
     max_dist = int(max_dist*1e4)
 
-    if start_idx is None:
+    # Get start and end node indices for ortools
+    if start_nodes is None:
         start_idx = [0]*num_vehicles
-    elif trim_paths:
-        start_idx = [i+1 for i in start_idx]
+        num_start_nodes = 0
+    else:
+        start_idx = np.arange(num_vehicles)+int(trim_paths)
+        num_start_nodes = len(start_nodes)
 
-    if end_idx is None:
+    if end_nodes is None:
         end_idx = [0]*num_vehicles
-    elif trim_paths:
-        end_idx = [i+1 for i in end_idx]
+    else:
+        end_idx = np.arange(num_vehicles)+num_start_nodes+int(trim_paths)
 
+    # used by ortools
     def distance_callback(from_index, to_index):
         from_node = manager.IndexToNode(from_index)
         to_node = manager.IndexToNode(to_index)
@@ -78,8 +94,8 @@ def distance_callback(from_index, to_index):
     # num_locations, num vehicles, start, end
     manager = pywrapcp.RoutingIndexManager(len(distance_mat), 
                                            num_vehicles, 
-                                           start_idx,
-                                           end_idx)
+                                           start_idx.tolist(),
+                                           end_idx.tolist())
     routing = pywrapcp.RoutingModel(manager)
     transit_callback_index = routing.RegisterTransitCallback(distance_callback)
     routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)
@@ -165,11 +181,11 @@ def resample_path(waypoints, num_inducing=10):
     inducing points path with fixed number of waypoints
 
     Args:
-        waypoints (ndarray): (num_waypoints, n_dim); waypoints of path from vrp solver
+        waypoints (ndarray): (num_waypoints, ndim); waypoints of path from vrp solver
         num_inducing (int): Number of inducing points (waypoints) in the returned path
         
     Returns:
-        points (ndarray): (num_inducing, n_dim); Resampled path
+        points (ndarray): (num_inducing, ndim); Resampled path
     """
     ndim = np.shape(waypoints)[-1]
     if not (ndim==2 or ndim==3):