added pre-commit suggestions

Author: Sahil-Chhoker

examples/city_walking_behaviour/app.py

@@ -1,16 +1,16 @@
 from city_walking_behaviour.agents import (
-    Human,
     GroceryStore,
-    SocialPlace,
+    Human,
     NonFoodShop,
     Other,
+    SocialPlace,
 )
 from city_walking_behaviour.model import WalkingModel
 from mesa.experimental.devs import ABMSimulator
 from mesa.visualization import (
     SolaraViz,
-    make_space_component,
     make_plot_component,
+    make_space_component,
 )
 
 # Define the scenarios
@@ -347,4 +347,4 @@ def post_process_buildings_legend(ax):
     name="Walking Model",
     simulator=simulator,
 )
-page
+page  # noqa

examples/city_walking_behaviour/city_walking_behaviour/agents.py

@@ -1,11 +1,11 @@
-from typing import Optional
-from mesa import Model
 import math
-from mesa.agent import AgentSet
-from mesa.experimental.cell_space import CellAgent, FixedAgent
-from mesa.experimental.cell_space import Cell
 from enum import Enum
+from typing import Optional
+
 import numpy as np
+from mesa import Model
+from mesa.agent import AgentSet
+from mesa.experimental.cell_space import Cell, CellAgent, FixedAgent
 
 # Constants for probability values
 FEMALE_PROBABILITY = 0.5
@@ -209,10 +209,12 @@ def simulate_daily_walks(self, human):
                 self.model.agents_by_type[SocialPlace]
             )
             distance = self.calculate_distance(human.cell, social_place.cell)
-            if distance <= self.get_max_walking_distance(human, ActivityType.SOCIAL):
-                if self.model.random.random() <= human.walking_attitude:
-                    self.add_distance(distance)
-                    walks.append((ActivityType.SOCIAL, social_place))
+            if (
+                distance <= self.get_max_walking_distance(human, ActivityType.SOCIAL)
+                and self.model.random.random() <= human.walking_attitude
+            ):
+                self.add_distance(distance)
+                walks.append((ActivityType.SOCIAL, social_place))
 
         # Leisure walk
         leisure_destination = self.decide_leisure_walk(human)
@@ -354,10 +356,7 @@ def get_feedback(self, activity: ActivityType):
         density_feedback = 0
         if self.previous_walking_density == 0:
             # If previous density was zero, treat any current density as a positive change
-            if self.current_walking_density > 0:
-                density_feedback = 1
-            else:
-                density_feedback = 0
+            density_feedback = 1 if self.current_walking_density > 0 else 0
         else:
             density_ratio = self.current_walking_density / self.previous_walking_density
             density_feedback = density_ratio - 1  # Centers the feedback around 0

examples/city_walking_behaviour/city_walking_behaviour/model.py

@@ -1,23 +1,22 @@
 import math
-from mesa import Model
+
 from city_walking_behaviour.agents import (
-    Human,
+    DOG_OWNER_PROBABILITY,
+    FEMALE_PROBABILITY,
+    MAX_AGE,
+    MIN_AGE,
+    SINGLE_HOUSEHOLD_PROBABILITY,
     GroceryStore,
-    SocialPlace,
+    Human,
     NonFoodShop,
     Other,
+    SocialPlace,
 )
+from mesa import Model
+from mesa.datacollection import DataCollector
 from mesa.experimental.cell_space import OrthogonalVonNeumannGrid
 from mesa.experimental.cell_space.property_layer import PropertyLayer
 from mesa.experimental.devs import ABMSimulator
-from mesa.datacollection import DataCollector
-from .agents import (
-    FEMALE_PROBABILITY,
-    DOG_OWNER_PROBABILITY,
-    SINGLE_HOUSEHOLD_PROBABILITY,
-    MIN_AGE,
-    MAX_AGE,
-)
 
 SCENARIOS = {
     "random_random": "Random Land Use, Random Safety",
@@ -592,14 +591,13 @@ def add_initial_humans(self):
         # Place couples
         for _ in range(self.no_of_couples):
             ses = self.generate_ses()
-            if cells_with_proximity[ses]:
-                if len(cells_with_proximity[ses]) >= 2:
-                    cell = self.random.choice(cells_with_proximity[ses])
-                    cells_with_proximity[ses].remove(cell)
-                    # Create the couple
-                    for _ in range(2):
-                        Human(self, self.unique_id, cell, SES=ses)
-                        self.unique_id += 1
+            if cells_with_proximity[ses] and len(cells_with_proximity[ses]) >= 2:
+                cell = self.random.choice(cells_with_proximity[ses])
+                cells_with_proximity[ses].remove(cell)
+                # Create the couple
+                for _ in range(2):
+                    Human(self, self.unique_id, cell, SES=ses)
+                    self.unique_id += 1
 
         # Place singles
         for _ in range(self.no_of_singles):