* Merged master on to "issue-41". #41

jinete/algorithms/heuristics/local_search.py

@@ -55,4 +55,6 @@ def _optimize(self) -> Planning:
             best = self.objective.best(best, current)
             again = best == current
 
+        assert best is not None
+
         return best.planning

jinete/algorithms/metaheuristics/grasp.py

@@ -47,20 +47,18 @@ def build_first_solution_algorithm(self, *args, **kwargs) -> Algorithm:
         args = (*self.args, *args)
         kwargs.update(self.kwargs)
 
-        return IterativeAlgorithm(
-            episodes=self.first_solution_episodes,
-            seed=self.random.randint(0, MAX_INT),
-            *args, **kwargs,
-        )
+        kwargs['episodes'] = self.first_solution_episodes,
+        kwargs['seed'] = self.random.randint(0, MAX_INT),
+
+        return IterativeAlgorithm(*args, **kwargs)
 
     def build_local_search_algorithm(self, *args, **kwargs) -> Algorithm:
         args = (*self.args, *args)
         kwargs.update(self.kwargs)
 
-        return LocalSearchAlgorithm(
-            seed=self.random.randint(0, MAX_INT),
-            *args, **kwargs,
-        )
+        kwargs['seed'] = self.random.randint(0, MAX_INT),
+
+        return LocalSearchAlgorithm(*args, **kwargs)
 
     def again(self, episode_count: int, *args, **kwargs):
         return episode_count < self.first_solution_episodes

jinete/algorithms/metaheuristics/iterative.py

@@ -18,6 +18,10 @@
 if TYPE_CHECKING:
     from typing import (
         Type,
+        Optional,
+    )
+    from ...models import (
+        Result,
     )
 
 logger = logging.getLogger(__name__)
@@ -37,12 +41,17 @@ def __init__(self, episodes: int = 100, algorithm_cls: Type[Algorithm] = None, s
         self.kwargs = kwargs
 
     def build_algorithm(self, *args, **kwargs) -> Algorithm:
-        return self.algorithm_cls(*self.args, *args, **self.kwargs, **kwargs)
+        args = (*self.args, *args)
+        kwargs.update(self.kwargs)
+
+        return self.algorithm_cls(*args, **kwargs)
 
     def _optimize(self) -> Planning:
-        best = None
+        best: Optional[Result] = None
         for i in range(self.episodes):
             seed = self.random.randint(0, MAX_INT)
             current = self.build_algorithm(seed=seed).optimize()
             best = self.objective.best(best, current)
+
+        assert best is not None
         return best.planning

jinete/models/criterions.py

@@ -32,7 +32,7 @@ def __init__(self, name: str, direction: OptimizationDirection):
     def scoring(self, planned_trip: PlannedTrip) -> float:
         pass
 
-    def best(self, *args: Optional[PlannedTrip]) -> Optional[PlannedTrip]:
+    def best(self, *args: Optional[PlannedTrip]) -> PlannedTrip:
         return self.direction(
             (arg for arg in args if arg is not None),
             key=self.scoring,

jinete/models/objectives.py

@@ -39,7 +39,7 @@ def __init__(self, name: str, direction: OptimizationDirection):
         self.name = name
         self.direction = direction
 
-    def best(self, *args: Optional[Optimizable]) -> Optional[Optimizable]:
+    def best(self, *args: Optional[Optimizable]) -> Optimizable:
         return self.direction(
             (arg for arg in args if arg is not None),
             key=self.optimization_function,

jinete/models/plannings.py

@@ -33,6 +33,8 @@ class Planning(Model):
     def __init__(self, routes: Set[Route] = None, uuid: UUID = None):
         if uuid is None:
             uuid = uuid4()
+        if routes is None:
+            routes = set()
 
         self.routes = routes
         self.uuid = uuid

jinete/models/stops.py

@@ -64,7 +64,7 @@ class Stop(Model):
     _previous_departure_time: Optional[float]
 
     def __init__(self, route: Route, position: Position, previous: Optional[Stop], following: Optional[Stop] = None,
-                 pickups: Tuple[PlannedTrip] = tuple(), deliveries: Tuple[PlannedTrip] = tuple()):
+                 pickups: Tuple[PlannedTrip, ...] = tuple(), deliveries: Tuple[PlannedTrip, ...] = tuple()):
 
         self.route = route
         self.position = position

tests/test_algorithms/test_metaheuristics/test_grasp.py

@@ -14,11 +14,9 @@ def test_creation(self):
         job = jit.Job(generate_trips(10), objective_cls=jit.DialARideObjective)
         fleet = jit.Fleet(generate_vehicles(10))
         algorithm = jit.GraspAlgorithm(
-            algorithm_cls=jit.InsertionAlgorithm,
             job=job,
             fleet=fleet,
         )
-        self.assertEqual(algorithm.algorithm_cls, jit.InsertionAlgorithm)
         self.assertEqual(algorithm.job, job)
         self.assertEqual(algorithm.fleet, fleet)
 

tests/utils.py

@@ -1,8 +1,17 @@
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
 from random import uniform, randint
-from typing import Set
 
 import jinete as jit
 
+if TYPE_CHECKING:
+    from typing import (
+        Set,
+        Type,
+        Optional,
+    )
+
 
 def generate_one_surface(*args, **kwargs) -> jit.Surface:
     kwargs['metric'] = jit.DistanceMetric.MANHATTAN
@@ -63,7 +72,7 @@ def generate_trips(n: int, *args, **kwargs) -> Set[jit.Trip]:
 
 
 def generate_one_job(trips_count: int = None, trips_count_min: int = 1, trips_count_max: int = 100,
-                     objective_cls: jit.Objective = None, *args, **kwargs) -> jit.Job:
+                     objective_cls: Optional[Type[jit.Objective]] = None, *args, **kwargs) -> jit.Job:
     if trips_count is None:
         trips_count = randint(trips_count_min, trips_count_max)
     if objective_cls is None: