From 322023b66f9f9e08f5e3109f780cb4572e6230a7 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 7 Oct 2024 14:12:50 +0000
Subject: [PATCH] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 examples/hotelling_law/hotelling_law/agents.py | 8 ++++++--
 examples/hotelling_law/hotelling_law/model.py  | 4 ++--
 2 files changed, 8 insertions(+), 4 deletions(-)

diff --git a/examples/hotelling_law/hotelling_law/agents.py b/examples/hotelling_law/hotelling_law/agents.py
index 9b689e31..48ebcd6a 100644
--- a/examples/hotelling_law/hotelling_law/agents.py
+++ b/examples/hotelling_law/hotelling_law/agents.py
@@ -175,11 +175,15 @@ def determine_preferred_store(self):
         for store in stores:
             # Calculate score based on consumer preference
             if consumer_preference == "proximity":
-                score = self.euclidean_distance(self.cell.coordinate, store.cell.coordinate)
+                score = self.euclidean_distance(
+                    self.cell.coordinate, store.cell.coordinate
+                )
             elif consumer_preference == "price":
                 score = store.price
             else:  # Default case includes both proximity and price
-                score = store.price + self.euclidean_distance(self.cell.coordinate, store.cell.coordinate)
+                score = store.price + self.euclidean_distance(
+                    self.cell.coordinate, store.cell.coordinate
+                )
 
             # Update the list of best stores if a new minimum score is found
             if score < min_score:
diff --git a/examples/hotelling_law/hotelling_law/model.py b/examples/hotelling_law/hotelling_law/model.py
index 4fda9c52..cf8af7b2 100644
--- a/examples/hotelling_law/hotelling_law/model.py
+++ b/examples/hotelling_law/hotelling_law/model.py
@@ -189,7 +189,7 @@ def _initialize_agents(self):
             # Randomly place agents on the grid for a grid environment.
             x = self.random.randrange(self.grid.dimensions[0])
             y = self.random.randrange(self.grid.dimensions[1])
-            agent.cell = self.grid[(x,y)]
+            agent.cell = self.grid[(x, y)]
 
         # Place consumer agents
         for _ in range(self.num_consumers):
@@ -199,7 +199,7 @@ def _initialize_agents(self):
             # Place consumer randomly on the grid
             x = self.random.randrange(self.grid.dimensions[0])
             y = self.random.randrange(self.grid.dimensions[1])
-            consumer.cell = self.grid[(x,y)]
+            consumer.cell = self.grid[(x, y)]
 
     # Method to advance the simulation by one step.
     def step(self):