chore: enforce ruff config and fix lint findings

ashvale/estimation.py

@@ -30,7 +30,6 @@ Two jobs here, both familiar from soft-sensor work:
 
 from __future__ import annotations
 
-import math
 from dataclasses import dataclass, field
 from typing import Dict, Optional
 

ashvale/features.py

@@ -32,8 +32,14 @@ from typing import Dict, List, Tuple
 
 import numpy as np
 
-from .physics import (absolute_humidity, clear_sky_irradiance, dew_point,
-                      solar_position, vapour_pressure_deficit, wet_bulb)
+from .physics import (
+    absolute_humidity,
+    clear_sky_irradiance,
+    dew_point,
+    solar_position,
+    vapour_pressure_deficit,
+    wet_bulb,
+)
 
 FEATURE_NAMES: List[str] = [
     "bias",

ashvale/led.py

@@ -34,8 +34,7 @@ matters.
 from __future__ import annotations
 
 import asyncio
-import time
-from typing import Dict, List, Sequence, Tuple
+from typing import List, Sequence, Tuple
 
 OFF = (0, 0, 0)
 

ashvale/models/__init__.py

@@ -12,11 +12,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from .rls import RecursiveLeastSquares, AdaptiveConformal
-from .nowcast import NowcastEnsemble
-from .climatology import HarmonicClimatology
-from .precip import PrecipitationModel, zambretti
 from .anomaly import AnomalyMonitor
+from .climatology import HarmonicClimatology
+from .nowcast import NowcastEnsemble
+from .precip import PrecipitationModel, zambretti
+from .rls import AdaptiveConformal, RecursiveLeastSquares
 
 __all__ = [
     "RecursiveLeastSquares", "AdaptiveConformal", "NowcastEnsemble",

ashvale/models/climatology.py

@@ -141,9 +141,9 @@ class HarmonicClimatology:
         sigma0 = self.resid_std.get(target, 1.0)
         sigma = sigma0 * np.sqrt(1.0 + lead_h / 24.0)
         return [
-            {"ts": float(t), "lead_h": float(l), "mu": float(m),
+            {"ts": float(t), "lead_h": float(lh), "mu": float(m),
              "lo": float(m - 1.645 * s), "hi": float(m + 1.645 * s)}
-            for t, l, m, s in zip(grid, lead_h, mu, sigma)
+            for t, lh, m, s in zip(grid, lead_h, mu, sigma)
         ]
 
     def anomaly_now(self, target: str, ts: float, observed: float) -> float:

ashvale/models/precip.py

@@ -39,7 +39,7 @@ from __future__ import annotations
 
 import math
 import time
-from typing import Dict, List, Optional, Tuple
+from typing import Dict, List, Optional
 
 import numpy as np
 

ashvale/sensors.py

@@ -25,7 +25,6 @@ same code to the Pi unchanged.
 from __future__ import annotations
 
 import math
-import random
 import time
 from typing import Any, Dict, Optional
 

ashvale/station.py

@@ -34,7 +34,6 @@ from __future__ import annotations
 
 import asyncio
 import json
-import math
 import time
 from pathlib import Path
 from typing import Any, Dict, List, Optional
@@ -44,7 +43,7 @@ import numpy as np
 from . import physics
 from .config import Config
 from .estimation import SignalTracker
-from .features import N_FEATURES, build_features
+from .features import build_features
 from .models.anomaly import AnomalyMonitor
 from .models.climatology import HarmonicClimatology
 from .models.nowcast import NowcastEnsemble