Run ruff

Author: znicholls

src/openscm_calibration/cost/scmdata.py

@@ -22,7 +22,7 @@ class AlignmentError(ValueError):
     Raised when our data's metadata does not align as expected
     """
 
-    def __init__(  # noqa: PLR0913
+    def __init__(
         self,
         name_left: str,
         val_left: pd.DataFrame | pd.Series[Any],

src/openscm_calibration/emcee_plotting.py

@@ -674,7 +674,7 @@ def plot_emcee_progress(  # noqa: PLR0913
     def enough_autocorr_values_to_plot(autocorr: nptype.NDArray[np.float64]) -> bool:
         """Check whether there is any auto-correlation information to plot"""
         values_to_plot_present = np.logical_and(
-            autocorr > 0.0,  # noqa: PLR2004
+            autocorr > 0.0,
             np.logical_not(np.isnan(autocorr)),
         )
 

src/openscm_calibration/emcee_utils.py

@@ -296,7 +296,7 @@ class AutoCorrelationInfo:
     [`get_autocorrelation_info`][openscm_calibration.emcee_utils.get_autocorrelation_info].
     """
 
-    converged: nptype.NDArray[np.bool]  # noqa: NPY001 # have to use np type for type hinting
+    converged: nptype.NDArray[np.bool]
     """
     Whether, based on `convergence_ratio`, the chains for each parameter have converged
 

src/openscm_calibration/parameter_handling.py

@@ -66,12 +66,10 @@ class ParameterDefinition(Generic[BoundsValue]):
     """The bounds for the parameter"""
 
     @overload
-    def bounds_m(self, unit: None = None) -> tuple[BoundsValue, BoundsValue]:
-        ...
+    def bounds_m(self, unit: None = None) -> tuple[BoundsValue, BoundsValue]: ...
 
     @overload
-    def bounds_m(self, unit: str) -> tuple[float, float]:
-        ...
+    def bounds_m(self, unit: str) -> tuple[float, float]: ...
 
     def bounds_m(
         self, unit: str | None = None