fixing style #22

tests/netedit/shapeelements/jupedsim/obstacle/inspect/shape/test.py

@@ -52,7 +52,8 @@
 netedit.modifyAttribute(netedit.attrs.jpsObstacle.inspect.shape, "12.00,8.00", False)
 
 # Change parameter 1 with a valid value
-netedit.modifyAttribute(netedit.attrs.jpsObstacle.inspect.shape, "12.00,8.00 9.00,13.00 12.00,18.00 7.00,15.00 2.00,18.00 " +
+netedit.modifyAttribute(netedit.attrs.jpsObstacle.inspect.shape,
+                        "12.00,8.00 9.00,13.00 12.00,18.00 7.00,15.00 2.00,18.00 " +
                         "5.00,13.00 2.00,8.00 7.00,11.00 12.00,8.00", False)
 
 # Check undos and redos

tests/netedit/shapeelements/jupedsim/sink/inspect/shape/test.py

@@ -52,7 +52,8 @@
 netedit.modifyAttribute(netedit.attrs.jpsSink.inspect.shape, "12.00,8.00", False)
 
 # Change parameter 1 with a valid value
-netedit.modifyAttribute(netedit.attrs.jpsSink.inspect.shape, "12.00,8.00 9.00,13.00 12.00,18.00 7.00,15.00 2.00,18.00 " +
+netedit.modifyAttribute(netedit.attrs.jpsSink.inspect.shape,
+                        "12.00,8.00 9.00,13.00 12.00,18.00 7.00,15.00 2.00,18.00 " +
                         "5.00,13.00 2.00,8.00 7.00,11.00 12.00,8.00", False)
 
 # Check undos and redos

tests/netedit/shapeelements/jupedsim/source/inspect/shape/test.py

@@ -52,7 +52,8 @@
 netedit.modifyAttribute(netedit.attrs.jpsSource.inspect.shape, "12.00,8.00", False)
 
 # Change parameter 1 with a valid value
-netedit.modifyAttribute(netedit.attrs.jpsSource.inspect.shape, "12.00,8.00 9.00,13.00 12.00,18.00 7.00,15.00 2.00,18.00 " +
+netedit.modifyAttribute(netedit.attrs.jpsSource.inspect.shape,
+                        "12.00,8.00 9.00,13.00 12.00,18.00 7.00,15.00 2.00,18.00 " +
                         "5.00,13.00 2.00,8.00 7.00,11.00 12.00,8.00", False)
 
 # Check undos and redos

tests/netedit/shapeelements/jupedsim/waitingarea/inspect/shape/test.py

@@ -52,7 +52,8 @@
 netedit.modifyAttribute(netedit.attrs.jpsWaitingArea.inspect.shape, "12.00,8.00", False)
 
 # Change parameter 1 with a valid value
-netedit.modifyAttribute(netedit.attrs.jpsWaitingArea.inspect.shape, "12.00,8.00 9.00,13.00 12.00,18.00 7.00,15.00 2.00,18.00 " +
+netedit.modifyAttribute(netedit.attrs.jpsWaitingArea.inspect.shape,
+                        "12.00,8.00 9.00,13.00 12.00,18.00 7.00,15.00 2.00,18.00 " +
                         "5.00,13.00 2.00,8.00 7.00,11.00 12.00,8.00", False)
 
 # Check undos and redos

tests/netedit/shapeelements/jupedsim/walkablearea/inspect/shape/test.py

@@ -52,7 +52,8 @@
 netedit.modifyAttribute(netedit.attrs.jpsWalkableArea.inspect.shape, "12.00,8.00", False)
 
 # Change parameter 1 with a valid value
-netedit.modifyAttribute(netedit.attrs.jpsWalkableArea.inspect.shape, "12.00,8.00 9.00,13.00 12.00,18.00 7.00,15.00 2.00,18.00 " +
+netedit.modifyAttribute(netedit.attrs.jpsWalkableArea.inspect.shape,
+                        "12.00,8.00 9.00,13.00 12.00,18.00 7.00,15.00 2.00,18.00 " +
                         "5.00,13.00 2.00,8.00 7.00,11.00 12.00,8.00", False)
 
 # Check undos and redos

tools/drt/drtOrtools.py

@@ -50,11 +50,13 @@ class CostType(Enum):
     TIME = 2
 
 
-def dispatch(reservations, fleet, time_limit, cost_type, drf, waiting_time, end, fix_allocation, solution_requests, verbose):
+def dispatch(reservations, fleet, time_limit, cost_type, drf, waiting_time, end,
+             fix_allocation, solution_requests, verbose):
     """Dispatch using ortools."""
     if verbose:
         print('Start creating the model.')
-    data = create_data_model(reservations, fleet, cost_type, drf, waiting_time, end, fix_allocation, solution_requests, verbose)
+    data = create_data_model(reservations, fleet, cost_type, drf, waiting_time, end,
+                             fix_allocation, solution_requests, verbose)
     if verbose:
         print('Start solving the problem.')
     solution_ortools = ortools_pdp.main(data, time_limit, verbose)
@@ -64,7 +66,8 @@ def dispatch(reservations, fleet, time_limit, cost_type, drf, waiting_time, end,
     return solution_requests
 
 
-def create_data_model(reservations, fleet, cost_type, drf, waiting_time, end, fix_allocation, solution_requests, verbose):
+def create_data_model(reservations, fleet, cost_type, drf, waiting_time, end,
+                      fix_allocation, solution_requests, verbose):
     """Creates the data for the problem."""
     n_vehicles = len(fleet)
     # use only reservations that haven't been picked up yet; reservation.state!=8 (not picked up)
@@ -127,7 +130,7 @@ def create_data_model(reservations, fleet, cost_type, drf, waiting_time, end, fi
     cost_matrix, time_matrix = get_cost_matrix(edges, type_vehicle, cost_type, pickup_indices, dropoff_indices)
 
     # safe cost and time matrix
-    #if verbose:
+    # if verbose:
     #    import csv
     #    with open("cost_matrix.csv", 'a') as cost_file:
     #        wr = csv.writer(cost_file)
@@ -350,7 +353,8 @@ def solution_by_requests(solution_ortools, reservations, data, verbose=False):
     return solution_requests
 
 
-def run(end=None, interval=30, time_limit=10, cost_type='distance', drf=1.5, waiting_time=900, fix_allocation=False, verbose=False):
+def run(end=None, interval=30, time_limit=10, cost_type='distance', drf=1.5, waiting_time=900,
+        fix_allocation=False, verbose=False):
     """
     Execute the TraCI control loop and run the scenario.
 
@@ -425,9 +429,10 @@ def run(end=None, interval=30, time_limit=10, cost_type='distance', drf=1.5, wai
 
         fleet = traci.vehicle.getTaxiFleet(-1)
         reservations_not_assigned = traci.person.getTaxiReservations(3)
-        
+
         # find and remove unassigned reservations that cannot be picked up by time
-        reservations_removed = [res for res in reservations_not_assigned if res.reservationTime + waiting_time < timestep]
+        reservations_removed = [
+            res for res in reservations_not_assigned if res.reservationTime + waiting_time < timestep]
         for res in reservations_removed:
             for person in res.persons:
                 traci.person.removeStages(person)
@@ -454,8 +459,8 @@ def run(end=None, interval=30, time_limit=10, cost_type='distance', drf=1.5, wai
         if reservations_not_assigned:
             if verbose:
                 print("Solve CPDP")
-            solution_requests = dispatch(reservations_all, fleet, time_limit,
-                                         cost_type, drf, waiting_time, int(end), fix_allocation, solution_requests, verbose)
+            solution_requests = dispatch(reservations_all, fleet, time_limit, cost_type, drf, waiting_time, int(end),
+                                         fix_allocation, solution_requests, verbose)
             if solution_requests is not None:
                 for index_vehicle in solution_requests:  # for each vehicle
                     id_vehicle = fleet[index_vehicle]
@@ -503,8 +508,8 @@ def get_arguments():
     ap.add_argument("-a", "--fix-allocation", action="store_true", default=False,
                     help="if true: after first solution the allocation of reservations to vehicles" +
                     "does not change anymore")
-    ap.add_argument("-w", "--waiting-time", type = ap.time, default = 900,
-                    help = "maximum waiting time to serve a request in s")
+    ap.add_argument("-w", "--waiting-time", type=ap.time, default=900,
+                    help="maximum waiting time to serve a request in s")
     return ap.parse_args()
 
 
@@ -523,10 +528,12 @@ def check_set_arguments(arguments):
         raise ValueError(f"Wrong cost type '{arguments.cost_type}'. Only 'distance' and 'time' are allowed.")
 
     if arguments.drf < 1 and arguments.drf != -1:
-        raise ValueError(f"Wrong value for drf '{arguments.drf}'. Value must be equal or greater than 1. -1 means no drf is used.")
-
+        raise ValueError(
+            f"Wrong value for drf '{arguments.drf}'. Value must be equal or greater than 1. -1 means no drf is used.")
+
     if arguments.waiting_time < 0:
-        raise ValueError(f"Wrong value for waiting time '{arguments.waiting_time}'. Value must be equal or greater than 0.")
+        raise ValueError(
+            f"Wrong value for waiting time '{arguments.waiting_time}'. Value must be equal or greater than 0.")
 
 
 if __name__ == "__main__":
@@ -539,5 +546,5 @@ def check_set_arguments(arguments):
     # this is the normal way of using traci. sumo is started as a
     # subprocess and then the python script connects and runs
     traci.start([arguments.sumoBinary, "-c", arguments.sumo_config])
-    run(arguments.end, arguments.interval,
-        arguments.time_limit, arguments.cost_type, arguments.drf, arguments.waiting_time, arguments.fix_allocation, arguments.verbose)
+    run(arguments.end, arguments.interval, arguments.time_limit, arguments.cost_type, arguments.drf,
+        arguments.waiting_time, arguments.fix_allocation, arguments.verbose)

tools/drt/ortools_pdp.py

@@ -254,14 +254,17 @@ def time_callback(from_index, to_index):
     time_dimension = routing.GetDimensionOrDie(dimension_name)
     return time_dimension
 
+
 def add_time_windows_constraint(data, time_dimension, manager, verbose):
     if verbose:
         print(' Add time windows constraints...')
 
     depot = data['depot']
-    new_requests_nodes = [node for req in data['pickups_deliveries'] for node in (req.from_node, req.to_node) if req.is_new]
+    new_requests_nodes = [node for req in data['pickups_deliveries']
+                          for node in (req.from_node, req.to_node) if req.is_new]
     old_requests_nodes = ([req.to_node for req in data['dropoffs']] +
-            [node for req in data['pickups_deliveries'] for node in (req.from_node, req.to_node) if not req.is_new])
+                          [node for req in data['pickups_deliveries']
+                           for node in (req.from_node, req.to_node) if not req.is_new])
     # Add time window constraints for each location except depot.
     for location_idx, time_window in enumerate(data['time_windows']):
         # no time window for depot:
@@ -272,17 +275,16 @@ def add_time_windows_constraint(data, time_dimension, manager, verbose):
         if location_idx in data['starts'] + new_requests_nodes:
             if verbose:
                 print(f'hard time window for node {location_idx}: [{time_window[0]}, {time_window[1]}]')
-            time_dimension.CumulVar(index).SetRange(time_window[0], time_window[1])  # TODO: check if set, else ignore it
+            time_dimension.CumulVar(index).SetRange(
+                time_window[0], time_window[1])  # TODO: check if set, else ignore it
         # soft time window for old requests:
         if location_idx in old_requests_nodes:
             if verbose:
                 print(f'soft time window for node {location_idx}: [{time_window[0]}, {time_window[1]}]')
             time_dimension.SetCumulVarSoftLowerBound(index, time_window[0], 100)
             time_dimension.SetCumulVarSoftUpperBound(index, time_window[1], 100)
-            #time_dimension.CumulVar(index).SetRange(time_window[0], time_window[1])
+            # time_dimension.CumulVar(index).SetRange(time_window[0], time_window[1])
 
-
-
     # TODO: check if the followwing is needed
     # # Add time window constraints for each vehicle start node.
     # depot_idx = data['depot']
@@ -323,14 +325,13 @@ def add_waiting_time_constraints(data, routing, manager, solver, time_dimension,
         # add soft constraint for old reservations
         else:
             time_dimension.SetCumulVarSoftUpperBound(
-                    pickup_index,
-                    maximum_pickup_time,
-                    100)  # cost = coefficient * (cumulVar - maximum_pickup_time)
+                pickup_index,
+                maximum_pickup_time,
+                100)  # cost = coefficient * (cumulVar - maximum_pickup_time)
             if verbose:
                 print(f"reservation {request.id} has a maximum (soft) pickup time at {maximum_pickup_time}")
 
 
-
 def solve_from_initial_solution(routing, manager, search_parameters, data, verbose):
     solution_requests = data['initial_routes']
     # get inital solution
@@ -390,20 +391,20 @@ def set_first_solution_heuristic(time_limit_seconds, verbose):
     # search_parameters.first_solution_strategy = routing_enums_pb2.FirstSolutionStrategy.PATH_MOST_CONSTRAINED_ARC
     # search_parameters.first_solution_strategy = routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC
     search_parameters.first_solution_strategy = routing_enums_pb2.FirstSolutionStrategy.AUTOMATIC
-
-    # search_parameters.local_search_metaheuristic = routing_enums_pb2.LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH  # langsam
+
+    # GUIDED_LOCAL_SEARCH seems slow
+    # search_parameters.local_search_metaheuristic = routing_enums_pb2.LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH
     # search_parameters.local_search_metaheuristic = routing_enums_pb2.LocalSearchMetaheuristic.GREEDY_DESCENT
     search_parameters.local_search_metaheuristic = routing_enums_pb2.LocalSearchMetaheuristic.AUTOMATIC
 
     search_parameters.time_limit.FromSeconds(time_limit_seconds)
-    
+
     search_parameters.sat_parameters.num_search_workers = 8
     # search_parameters.lns_time_limit.seconds = 7
     # search_parameters.solution_limit = 100
-
-    # Switch logging on for the search
-    #search_parameters.log_search = True 
 
+    # Switch logging on for the search
+    # search_parameters.log_search = True
 
     return search_parameters
 
@@ -417,8 +418,8 @@ def main(data: dict, time_limit_seconds=10, verbose=False):
 
     # Create Routing Model.
     routing_parameters = pywrapcp.DefaultRoutingModelParameters()
-    #routing_parameters.solver_parameters.trace_propagation = True
-    #routing_parameters.solver_parameters.trace_search = True
+    # routing_parameters.solver_parameters.trace_propagation = True
+    # routing_parameters.solver_parameters.trace_search = True
     routing = pywrapcp.RoutingModel(manager, routing_parameters)
 
     # get solver
@@ -451,7 +452,7 @@ def main(data: dict, time_limit_seconds=10, verbose=False):
 
     # Add waiting time constraints.
     add_waiting_time_constraints(data, routing, manager, solver, time_dimension, verbose)
-    
+
     print('## Done')
     # Setting first solution heuristic.
     search_parameters = set_first_solution_heuristic(time_limit_seconds, verbose)

tools/randomTrips.py

@@ -922,7 +922,7 @@ def generate_one(idx, departureTime, arrivalTime, period, origin, destination, i
     try:
         if not main(get_options()):
             print("Error: Trips couldn't be generated as requested. "
-                "Try the --verbose option to output more details on the failure.")
+                  "Try the --verbose option to output more details on the failure.")
             sys.exit(1)
     except ValueError as e:
         print("Error:", e, file=sys.stderr)