gis: Replace schedulers with AgentSet functionality

gis/agents_and_networks/src/model/model.py

@@ -22,19 +22,21 @@ def get_time(model) -> pd.Timedelta:
 
 def get_num_commuters_by_status(model, status: str) -> int:
     commuters = [
-        commuter for commuter in model.schedule.agents if commuter.status == status
+        commuter
+        for commuter in model.agents_by_type[Commuter]
+        if commuter.status == status
     ]
     return len(commuters)
 
 
 def get_total_friendships_by_type(model, friendship_type: str) -> int:
     if friendship_type == "home":
         num_friendships = [
-            commuter.num_home_friends for commuter in model.schedule.agents
+            commuter.num_home_friends for commuter in model.agents_by_type[Commuter]
         ]
     elif friendship_type == "work":
         num_friendships = [
-            commuter.num_work_friends for commuter in model.schedule.agents
+            commuter.num_work_friends for commuter in model.agents_by_type[Commuter]
         ]
     else:
         raise ValueError(
@@ -45,7 +47,6 @@ def get_total_friendships_by_type(model, friendship_type: str) -> int:
 
 class AgentsAndNetworks(mesa.Model):
     running: bool
-    schedule: mesa.time.RandomActivation
     show_walkway: bool
     show_lakes_and_rivers: bool
     current_id: int
@@ -82,7 +83,6 @@ def __init__(
         show_driveway=False,
     ) -> None:
         super().__init__()
-        self.schedule = mesa.time.RandomActivation(self)
         self.show_walkway = show_walkway
         self.show_lakes_and_rivers = show_lakes_and_rivers
         self.data_crs = data_crs
@@ -144,7 +144,6 @@ def _create_commuters(self) -> None:
             commuter.set_work(random_work)
             commuter.status = "home"
             self.space.add_commuter(commuter)
-            self.schedule.add(commuter)
 
     def _load_buildings_from_file(
         self, buildings_file: str, crs: str, campus: str
@@ -215,7 +214,7 @@ def _set_building_entrance(self) -> None:
 
     def step(self) -> None:
         self.__update_clock()
-        self.schedule.step()
+        self.agents.shuffle_do("step")
         self.datacollector.collect(self)
 
     def __update_clock(self) -> None:

gis/geo_schelling/model.py

@@ -55,12 +55,11 @@ def step(self):
         if similar < different:
             # Select an empty region
             empties = [a for a in self.model.space.agents if a.atype is None]
-            # Switch atypes and add/remove from scheduler
+            # Switch atypes
             new_region = random.choice(empties)
             new_region.atype = self.atype
-            self.model.schedule.add(new_region)
             self.atype = None
-            self.model.schedule.remove(self)
+            self.remove()
         else:
             self.model.happy += 1
 
@@ -77,7 +76,6 @@ def __init__(self, density=0.6, minority_pc=0.2, export_data=False):
         self.minority_pc = minority_pc
         self.export_data = export_data
 
-        self.schedule = mesa.time.RandomActivation(self)
         self.space = mg.GeoSpace(warn_crs_conversion=False)
 
         self.happy = 0
@@ -100,7 +98,6 @@ def __init__(self, density=0.6, minority_pc=0.2, export_data=False):
                     agent.atype = 1
                 else:
                     agent.atype = 0
-                self.schedule.add(agent)
 
     def export_agents_to_file(self) -> None:
         self.space.get_agents_as_GeoDataFrame(agent_cls=SchellingAgent).to_crs(
@@ -113,10 +110,10 @@ def step(self):
         If All agents are happy, halt the model.
         """
         self.happy = 0  # Reset counter of happy agents
-        self.schedule.step()
+        self.agents.shuffle_do("step")
         self.datacollector.collect(self)
 
-        if self.happy == self.schedule.get_agent_count():
+        if self.happy == len(self.agents):
             self.running = False
 
         if not self.running and self.export_data:

gis/geo_schelling_points/geo_schelling_points/model.py

@@ -17,7 +17,6 @@ def __init__(self, red_percentage=0.5, similarity_threshold=0.5):
         self.red_percentage = red_percentage
         PersonAgent.SIMILARITY_THRESHOLD = similarity_threshold
 
-        self.schedule = mesa.time.RandomActivation(self)
         self.space = Nuts2Eu()
 
         self.datacollector = mesa.DataCollector(
@@ -40,7 +39,6 @@ def __init__(self, red_percentage=0.5, similarity_threshold=0.5):
                     region_id=region.unique_id,
                 )
                 self.space.add_person_to_region(person, region_id=region.unique_id)
-                self.schedule.add(person)
 
         self.datacollector.collect(self)
 
@@ -57,7 +55,7 @@ def happy(self):
         return self.space.num_people - self.unhappy
 
     def step(self):
-        self.schedule.step()
+        self.agents.shuffle_do("step")
         self.datacollector.collect(self)
 
         if not self.unhappy:

gis/population/population/model.py

@@ -70,7 +70,6 @@ def __init__(
         Person.MOBILITY_RANGE_X = pixel_size_x / 2.0
         Person.MOBILITY_RANGE_Y = pixel_size_y / 2.0
 
-        self.schedule = mesa.time.RandomActivation(self)
         self._create_agents()
 
     def _create_agents(self):
@@ -90,7 +89,6 @@ def _create_agents(self):
                         )
                         person.set_random_world_coord()
                         self.space.add_agents(person)
-                        self.schedule.add(person)
 
     def step(self):
-        self.schedule.step()
+        self.agents.shuffle_do("step")

gis/rainfall/rainfall/model.py

@@ -44,7 +44,7 @@ def pos(self, pos):
 
     def step(self):
         if self.is_at_boundary:
-            self.model.schedule.remove(self)
+            self.remove()
         else:
             lowest_pos = min(
                 self.model.space.raster_layer.get_neighboring_cells(
@@ -65,7 +65,6 @@ def __init__(self, rain_rate=500, water_height=5, export_data=False, num_steps=2
         self.num_steps = num_steps
 
         self.space = CraterLake(crs="epsg:4326", water_height=water_height, model=self)
-        self.schedule = mesa.time.RandomActivation(self)
         self.datacollector = mesa.DataCollector(
             {
                 "Total Amount of Water": "water_amount",
@@ -101,10 +100,9 @@ def step(self):
                 pos=(random_x, random_y),
             )
             self.space.add_raindrop(raindrop)
-            self.schedule.add(raindrop)
             self.water_amount += 1
 
-        self.schedule.step()
+        self.agents.shuffle_do("step")
         self.datacollector.collect(self)
 
         current_water_level = self.space.raster_layer.get_raster("water_level")
@@ -113,8 +111,7 @@ def step(self):
             "water_level_normalized",
         )
 
-        self.num_steps -= 1
-        if self.num_steps == 0:
+        if self.steps >= self.num_steps:
             self.running = False
         if not self.running and self.export_data:
             self.export_water_level_to_file()

gis/urban_growth/urban_growth/model.py

@@ -33,7 +33,6 @@ def __init__(
         self.slope_coefficient = slope_coefficient
         self.critical_slope = critical_slope
         self.road_influence = road_influence
-        self.schedule = mesa.time.RandomActivation(self)
 
         self.dispersion_value = (dispersion_coefficient * 0.005) * (
             world_width**2 + world_height**2
@@ -52,7 +51,6 @@ def __init__(
             cell.road_found = False
             cell.road_pixel = None
             cell.model = self
-            self.schedule.add(cell)
 
         self.initialize_data_collector(
             model_reporters={"Percentage Urbanized": "pct_urbanized"}
@@ -110,7 +108,7 @@ def _check_suitability(self) -> None:
 
     def step(self):
         self._spontaneous_growth()
-        self.schedule.step()
+        self.agents.shuffle_do("step")
         if self.road_influence:
             self._road_influenced_growth()
         self.datacollector.collect(self)