Fixes black

SneaksAndData · Jun 12, 2024 · 84be586 · 84be586
1 parent 2776bef
commit 84be586
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Showing 2 changed files with 17 additions and 11 deletions.
diff --git a/anti_clustering/tabu_search_heuristic.py b/anti_clustering/tabu_search_heuristic.py
@@ -60,7 +60,11 @@ def _solve(self, distance_matrix: npt.NDArray[float], num_groups: int) -> npt.ND
                 i = self.rnd.randint(0, len(distance_matrix) - 1)
 
                 # Get possible swaps
-                possible_exchanges = [j for j in self._get_exchanges(cluster_assignment, i) if (i,j) not in tabu_swaps and (j,i) not in tabu_swaps]
+                possible_exchanges = [
+                    j
+                    for j in self._get_exchanges(cluster_assignment, i)
+                    if (i, j) not in tabu_swaps and (j, i) not in tabu_swaps
+                ]
 
                 if len(possible_exchanges) == 0:
                     continue
@@ -76,7 +80,7 @@ def _solve(self, distance_matrix: npt.NDArray[float], num_groups: int) -> npt.ND
                 if new_objective > objective:
                     cluster_assignment = new_cluster_assignment
                     objective = new_objective
-                    tabu_swaps.append((i,j))
+                    tabu_swaps.append((i, j))
                     # Delete oldest tabu swap if tabu list is full
                     if len(tabu_swaps) > self.tabu_tenure:
                         tabu_swaps.pop(0)

diff --git a/examples/evaluation.py b/examples/evaluation.py
@@ -67,14 +67,16 @@
         # Mean of differences
         mean_df = difference_df.reset_index(level=[1]).groupby(["level_1"]).mean()
 
-        summary.append(pd.DataFrame(
-            {
-                "Method": [method.__class__.__name__],
-                "Clusters": [k],
-                "∆M": [round(mean_df.loc['mean'][0], 4)],
-                "∆SD": [round(mean_df.loc['std'][0], 4)],
-                "Time (s)": [time_taken],
-            }
-        ))
+        summary.append(
+            pd.DataFrame(
+                {
+                    "Method": [method.__class__.__name__],
+                    "Clusters": [k],
+                    "∆M": [round(mean_df.loc["mean"][0], 4)],
+                    "∆SD": [round(mean_df.loc["std"][0], 4)],
+                    "Time (s)": [time_taken],
+                }
+            )
+        )
     print("Summary (lower ∆M and ∆SD is better):")
     print(pd.concat(summary).to_string())