Removing travis warnings

PythonClient/carla/benchmarks/agent.py

@@ -16,7 +16,7 @@ from carla.planner.planner import Planner
 
 class Agent(object):
     def __init__(self, city_name):
-        __metaclass__ = abc.ABCMeta  # Try to remove
+        self.__metaclass__ = abc.ABCMeta
         self._planner = Planner(city_name)
 
     def get_distance(self, start_point, end_point):

PythonClient/carla/benchmarks/benchmark.py

@@ -40,7 +40,7 @@ class Benchmark(object):
             continue_experiment=False,
             save_images=False):
 
-        __metaclass__ = abc.ABCMeta
+        self.__metaclass__ = abc.ABCMeta
 
         self._city_name = city_name
 

PythonClient/carla/planner/astar.py

@@ -128,7 +128,7 @@ class AStar(object):
         heapq.heappush(self.opened, (self.start.f, self.start))
         while len(self.opened):
             # pop cell from heap queue
-            f, cell = heapq.heappop(self.opened)
+            _, cell = heapq.heappop(self.opened)
             # add cell to closed list so we don't process it twice
             self.closed.add(cell)
             # if ending cell, return found path

PythonClient/carla/planner/city_track.py

@@ -84,7 +84,7 @@ class CityTrack(object):
         route = a_star.solve()
 
         # JuSt a Corner Case
-        # TODO: Clean this to avoid having to use this function
+        # Clean this to avoid having to use this function
         if route is None:
             a_star = AStar()
             a_star.init_grid(self._map.get_graph_resolution()[0],

PythonClient/carla/planner/graph.py

@@ -35,9 +35,9 @@ class Graph(object):
         self._node_density = node_density
 
         if graph_file is not None:
-            with open(graph_file, 'r') as file:
+            with open(graph_file, 'r') as f:
                 # Skipe the first four lines that
-                lines_after_4 = file.readlines()[4:]
+                lines_after_4 = f.readlines()[4:]
 
                 # the graph resolution.
                 linegraphres = lines_after_4[0]
@@ -72,7 +72,7 @@ class Graph(object):
             sorted(distance_dic.items()))
 
         self._angles[node] = heading
-        for k, v in distance_dic.items():
+        for _, v in distance_dic.items():
             start_to_goal = np.array([node[0] - v[0], node[1] - v[1]])
 
             print(start_to_goal)
@@ -116,7 +116,7 @@ class Graph(object):
         lines = [[(p[0], p[1]), (p[0] + line_len * self._angles[p][0],
                                  p[1] + line_len * self._angles[p][1])] for p in self._nodes]
         lc = mc.LineCollection(lines, linewidth=2, color='green')
-        fig, ax = plt.subplots()
+        _, ax = plt.subplots()
         ax.add_collection(lc)
 
         ax.autoscale()

PythonClient/carla/planner/test_planner.py

@@ -0,0 +1,41 @@
+from carla import sensor
+from carla.sensor import Camera
+from carla.settings import CarlaSettings
+from carla.tcp import TCPConnectionError
+from carla.util import print_over_same_line
+from carla.planner.planner  import Planner
+
+from carla.carla_server_pb2 import Control
+
+
+
+
+planner= Planner('Town01')
+
+
+
+
+resolution = planner._city_track._map.get_graph_resolution()
+
+for i in range(resolution[0]):
+    for j in range(resolution[1]):
+        
+        world_source = planner._city_track._map.convert_to_world((i,j))
+        source_ori = planner._city_track._map.get_lane_orientation(world_source)
+        print (' Making Route from (',i, ',',j,') o (',source_ori[0],',',source_ori[1],')')
+
+        for k in range(resolution[0]):
+            for l in range(resolution[1]):
+                world_target = planner._city_track._map.convert_to_world((k,l))
+
+                target_ori = planner._city_track._map.get_lane_orientation(world_target)
+                print  ('    To (',k, ',',l,') o (',target_ori[0],',',target_ori[1],')')
+
+                path_distance=planner.get_shortest_path_distance(
+                    world_source,source_ori,world_target,target_ori)
+
+                #print ('Distance is ',path_distance)
+                command=planner.get_next_command(
+                    world_source,source_ori,world_target,target_ori)
+                #print ('Command is ',command)
+                #print ('Latest Route ',planner._city_track._route)