refactor: ruff

Author: iraedeus

examples/noreset_shewhart.py

@@ -24,6 +24,7 @@
 # 1. Dataset generation
 # ---------------------------------------------------------------------------
 
+
 def generate_dataset(
     n: int,
     series_length: int = 200,
@@ -47,11 +48,13 @@ def generate_dataset(
 
         df = pd.DataFrame({"value": data, "segment": segments})
 
-        seg_info = pd.DataFrame({
-            "segment": [0, 1],
-            "start": [0, change_point],
-            "end": [change_point - 1, series_length - 1],
-        })
+        seg_info = pd.DataFrame(
+            {
+                "segment": [0, 1],
+                "start": [0, change_point],
+                "end": [change_point - 1, series_length - 1],
+            }
+        )
 
         provider = PandasLabeledDataProvider(
             dataset=df,
@@ -79,11 +82,13 @@ def generate_arl_dataset(
         data = rng.normal(mu, sigma, size=series_length)
 
         df = pd.DataFrame({"value": data, "segment": 0})
-        seg_info = pd.DataFrame({
-            "segment": [0],
-            "start": [0],
-            "end": [series_length - 1],
-        })
+        seg_info = pd.DataFrame(
+            {
+                "segment": [0],
+                "start": [0],
+                "end": [series_length - 1],
+            }
+        )
 
         provider = PandasLabeledDataProvider(
             dataset=df,
@@ -100,6 +105,7 @@ def generate_arl_dataset(
 # 2. Main benchmark
 # ---------------------------------------------------------------------------
 
+
 def main() -> None:
     # --- Parameters ---
     N_SERIES = 25
@@ -118,16 +124,26 @@ def main() -> None:
 
     # --- Generate datasets ---
     providers = generate_dataset(
-        n=N_SERIES, series_length=SERIES_LENGTH, change_point=CHANGE_POINT,
-        mu_before=MU_BEFORE, mu_after=MU_AFTER, sigma=SIGMA, seed=42,
+        n=N_SERIES,
+        series_length=SERIES_LENGTH,
+        change_point=CHANGE_POINT,
+        mu_before=MU_BEFORE,
+        mu_after=MU_AFTER,
+        sigma=SIGMA,
+        seed=42,
     )
     arl_providers = generate_arl_dataset(
-        n=N_SERIES, series_length=SERIES_LENGTH,
-        mu=MU_BEFORE, sigma=SIGMA, seed=42,
+        n=N_SERIES,
+        series_length=SERIES_LENGTH,
+        mu=MU_BEFORE,
+        sigma=SIGMA,
+        seed=42,
     )
 
     print(f"Algorithm: ShewhartControlChart(learning_period={LEARNING_PERIOD}, window={WINDOW_SIZE})")
-    print(f"Dataset (NoReset): {N_SERIES} series, length={SERIES_LENGTH}, cp={CHANGE_POINT}, shift={MU_AFTER - MU_BEFORE:.1f}σ")
+    print(
+        f"Dataset (NoReset): {N_SERIES} series, length={SERIES_LENGTH}, cp={CHANGE_POINT}, shift={MU_AFTER - MU_BEFORE:.1f}σ"
+    )
     print(f"Dataset (ARL):     {N_SERIES} series, length={SERIES_LENGTH}, no change points")
     print(f"Error margin: {ERROR_MARGIN}")
     print("-" * 115)
@@ -139,9 +155,7 @@ def main() -> None:
     solver = OnlineCpdSolver()
 
     entry = OnlineBenchmarkEntry(
-        algorithm=algorithm,
-        thresholds=LinspaceThresholds(start=0, stop=7, num=30),
-        entry_name="Shewhart"
+        algorithm=algorithm, thresholds=LinspaceThresholds(start=0, stop=7, num=30), entry_name="Shewhart"
     )
 
     # ==========================================
@@ -172,7 +186,7 @@ def main() -> None:
     # ==========================================
     runner_arl = NoResetBenchmark(
         solver=solver,
-        policy=PointBasedPolicy(strict=True), # Быстрая поточечная экстракция
+        policy=PointBasedPolicy(strict=True),  # Быстрая поточечная экстракция
         metrics={"arl": ARLMetric()},
         dump_dir="benchmark_cache/arl",
         verbose=True,

pysatl_cpd/benchmark/noreset/noreset_benchmark_runner.py

@@ -1,4 +1,3 @@
-
 """
 NoReset benchmark runner implementation.
 
@@ -19,28 +18,27 @@
 import pandas as pd
 from tqdm.auto import tqdm
 
-from pysatl_cpd.analysis.labeled_data import LabeledData
 from pysatl_cpd.benchmark.core.benchmark_executor import BenchmarkExecutor
 from pysatl_cpd.benchmark.metrics.multiple_run_metric import MultipleRunMetric
 from pysatl_cpd.benchmark.noreset.noreset_detection_trace import NoResetDetectionTrace
 from pysatl_cpd.benchmark.noreset.threshold_policy import ThresholdPolicy
 from pysatl_cpd.core.algorithm_entry import AlgorithmEntry
-from pysatl_cpd.core.online.ionline_algorithm import OnlineAlgorithm
-from pysatl_cpd.core.online.online_cpd_solver import OnlineCpdSolver
-from pysatl_cpd.core.online.online_detection_trace import OnlineDetectionTrace
-
 from pysatl_cpd.core.data_providers.dataset import (
     AnnotationFilter,
     Dataset,
     PandasLabeledDataProvider,
     SegmentFilter,
 )
+from pysatl_cpd.core.online.ionline_algorithm import OnlineAlgorithm
+from pysatl_cpd.core.online.online_cpd_solver import OnlineCpdSolver
+from pysatl_cpd.core.online.online_detection_trace import OnlineDetectionTrace
 
 
 class ThresholdRange(Protocol):
     """Protocol for generating a sequence of thresholds."""
-    def get_thresholds(self) -> list[float]:
-        ...
+
+    def get_thresholds(self) -> list[float]: ...
+
 
 @dataclasses.dataclass
 class ManualThresholds(ThresholdRange):
@@ -49,6 +47,7 @@ class ManualThresholds(ThresholdRange):
     def get_thresholds(self) -> list[float]:
         return self.thresholds
 
+
 @dataclasses.dataclass
 class LinspaceThresholds(ThresholdRange):
     start: float
@@ -58,17 +57,19 @@ class LinspaceThresholds(ThresholdRange):
     def get_thresholds(self) -> list[float]:
         return np.linspace(self.start, self.stop, self.num).tolist()
 
+
 class DataTransformer(Protocol):
     """Protocol for transforming data providers before running the algorithm."""
-    def transform(self, provider: PandasLabeledDataProvider) -> PandasLabeledDataProvider:
-        ...
+
+    def transform(self, provider: PandasLabeledDataProvider) -> PandasLabeledDataProvider: ...
 
 
 @dataclasses.dataclass
 class OnlineBenchmarkEntry:
     """
     Configuration entry for running an online algorithm in the benchmark.
     """
+
     algorithm: OnlineAlgorithm
     thresholds: ThresholdRange
     data_transformer: DataTransformer | None = None
@@ -127,7 +128,7 @@ def run(
             Mapping of entry_name to a DataFrame containing thresholds and metrics.
         """
         if not providers:
-            return {entry.entry_name : pd.DataFrame() for entry in entries}
+            return {entry.entry_name: pd.DataFrame() for entry in entries}
 
         inf_entries: list[AlgorithmEntry[Any, Any, Any]] = []
         for entry in entries: