[pre-commit.ci] auto fixes from pre-commit.com hooks

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Author: pre-commit-ci[bot]

cellular_automata/von_neumann.py

@@ -26,7 +26,7 @@ def create_random_grid(
 
     Args:
         rows: Number of grid rows
-        columns: Number of grid columns  
+        columns: Number of grid columns
         alive_probability: Probability (0.0-1.0) of each cell being initially alive
         seed: Random seed for reproducibility
 
@@ -115,23 +115,25 @@ def count_von_neumann_neighbors(
         down_neighbors = np.roll(alive_mask, 1, axis=0)
         left_neighbors = np.roll(alive_mask, -1, axis=1)
         right_neighbors = np.roll(alive_mask, 1, axis=1)
-        neighbor_counts = up_neighbors + down_neighbors + left_neighbors + right_neighbors
+        neighbor_counts = (
+            up_neighbors + down_neighbors + left_neighbors + right_neighbors
+        )
     else:
         # Manually count neighbors without wraparound
         for r in range(rows):
             for c in range(cols):
                 count = 0
                 # Check up
-                if r > 0 and alive_mask[r-1, c]:
+                if r > 0 and alive_mask[r - 1, c]:
                     count += 1
                 # Check down
-                if r < rows-1 and alive_mask[r+1, c]:
+                if r < rows - 1 and alive_mask[r + 1, c]:
                     count += 1
                 # Check left
-                if c > 0 and alive_mask[r, c-1]:
+                if c > 0 and alive_mask[r, c - 1]:
                     count += 1
                 # Check right
-                if c < cols-1 and alive_mask[r, c+1]:
+                if c < cols - 1 and alive_mask[r, c + 1]:
                     count += 1
                 neighbor_counts[r, c] = count
 
@@ -168,7 +170,7 @@ def apply_cellular_automaton_rules(
     Examples:
         >>> ages = np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]], dtype=np.uint8)
         >>> new_ages = apply_cellular_automaton_rules(
-        ...     ages, birth_neighbor_counts={2}, 
+        ...     ages, birth_neighbor_counts={2},
         ...     survival_neighbor_counts={2, 3}, use_wraparound=False
         ... )
         >>> bool(new_ages[0, 0] > 0)  # corner should be born (2 neighbors: right and down)
@@ -177,7 +179,7 @@ def apply_cellular_automaton_rules(
         >>> # Test aging of dead cells
         >>> dead_aging = np.array([[2, 0, 0]], dtype=np.uint8)  # age 2, no survival
         >>> result = apply_cellular_automaton_rules(
-        ...     dead_aging, birth_neighbor_counts=set(), 
+        ...     dead_aging, birth_neighbor_counts=set(),
         ...     survival_neighbor_counts=set(), maximum_age=3
         ... )
         >>> bool(result[0, 0] == 3)  # should age from 2 to 3
@@ -198,8 +200,12 @@ def apply_cellular_automaton_rules(
     )
 
     # Determine which cells are born or survive
-    birth_mask = (~alive_cells_mask) & np.isin(neighbor_counts, list(birth_neighbor_counts))
-    survival_mask = alive_cells_mask & np.isin(neighbor_counts, list(survival_neighbor_counts))
+    birth_mask = (~alive_cells_mask) & np.isin(
+        neighbor_counts, list(birth_neighbor_counts)
+    )
+    survival_mask = alive_cells_mask & np.isin(
+        neighbor_counts, list(survival_neighbor_counts)
+    )
 
     new_ages = current_ages.copy()
 
@@ -299,4 +305,5 @@ def simulate_von_neumann_cellular_automaton(
 
 if __name__ == "__main__":
     import doctest
+
     doctest.testmod(verbose=True)