style: apply black formatting to samples_statistics.py and verify_aggregated_params.py

Author: Dayuxiaoshui

graph_net/samples_statistics.py

@@ -264,8 +264,10 @@ def calculate_all_aggregated_parameters(
     # Convert dictionary-based pi and thresholds to indexed format for calculate_gamma
     # Create ordered list of error types for consistent indexing
     error_types = sorted(error_type_counts.keys())
-    errno_tolerances = [error_tolerance_thresholds.get(error_type, 3) for error_type in error_types]
-    
+    errno_tolerances = [
+        error_tolerance_thresholds.get(error_type, 3) for error_type in error_types
+    ]
+
     # Create get_pi function that maps error type index to pi value
     def get_pi(error_type_index: int) -> float:
         if error_type_index < len(error_types):
@@ -279,7 +281,9 @@ def get_pi(error_type_index: int) -> float:
     eta = calculate_eta(correct_speedups)
     gamma = calculate_gamma(t_key, get_pi, errno_tolerances, fpdb)
 
-    s_t = calculate_s_t_from_aggregated(alpha, beta, lambda_, eta, negative_speedup_penalty, fpdb)
+    s_t = calculate_s_t_from_aggregated(
+        alpha, beta, lambda_, eta, negative_speedup_penalty, fpdb
+    )
     es_t = calculate_es_t_from_aggregated(
         alpha, beta, lambda_, eta, gamma, negative_speedup_penalty
     )
@@ -294,4 +298,3 @@ def get_pi(error_type_index: int) -> float:
         "s_t": s_t,
         "es_t": es_t,
     }
-

graph_net/verify_aggregated_params.py

@@ -62,9 +62,15 @@ def calculate_aggregated_parameters(
         ]
 
         # Filter correct samples and extract speedups
-        correct_samples = [(idx, speedup) for idx, _, speedup, is_correct, _ in sample_data if is_correct]
+        correct_samples = [
+            (idx, speedup)
+            for idx, _, speedup, is_correct, _ in sample_data
+            if is_correct
+        ]
         correct_count = len(correct_samples)
-        correct_speedups = [speedup for _, speedup in correct_samples if speedup is not None]
+        correct_speedups = [
+            speedup for _, speedup in correct_samples if speedup is not None
+        ]
         slowdown_speedups = [speedup for speedup in correct_speedups if speedup < 1]
         correct_negative_speedup_count = len(slowdown_speedups)
 
@@ -80,7 +86,12 @@ def calculate_aggregated_parameters(
         # Store state at t=1 using list comprehension
         if t_key == 1:
             t1_data = [
-                (idx, speedup, is_correct, fail_type if fail_type is not None else "CORRECT")
+                (
+                    idx,
+                    speedup,
+                    is_correct,
+                    fail_type if fail_type is not None else "CORRECT",
+                )
                 for idx, _, speedup, is_correct, fail_type in sample_data
             ]
             is_correct_at_t1 = [is_correct for _, _, is_correct, _ in t1_data]
@@ -250,4 +261,3 @@ def main():
 
 if __name__ == "__main__":
     main()
-