maint: fix pyproject.toml configuration and isort settings, and reformat the code

.gitignore

@@ -136,3 +136,4 @@ dmypy.json
 test.ipynb
 dummy.py
 .DS_Store
+.cursor/

pyproject.toml

@@ -75,4 +75,4 @@ line-length = 110
 atomic = true
 profile = "black"
 skip_gitignore = true
-known_first_party = ["black", "blib2to3", "blackd", "_black_version"]
+known_first_party = ["wnb"]

wnb/_utils.py

@@ -54,7 +54,6 @@ def _check_feature_names(estimator, X, *, reset):
 except ImportError:
 
     def _fit_context(*, prefer_skip_nested_validation: bool):
-
         def decorator(fit_method):
             @functools.wraps(fit_method)
             def wrapper(estimator, *args: Any, **kwargs: Any):

wnb/gnb.py

@@ -114,7 +114,7 @@ class GeneralNB(_BaseNB):
     >>> X = np.array([[-1, 1], [-2, 1], [-3, 2], [1, 1], [2, 1], [3, 2]])
     >>> Y = np.array([1, 1, 1, 2, 2, 2])
     >>> from wnb import GeneralNB, Distribution as D
-    >>> clf = GeneralNB(distributions=[D.NORMAL, D.POISSON])
+    >>> clf = GeneralNB([D.NORMAL, D.POISSON])
     >>> clf.fit(X, Y)
     GeneralNB(distributions=[<Distribution.NORMAL: 'Normal'>,
                              <Distribution.POISSON: 'Poisson'>])
@@ -200,7 +200,9 @@ def _check_X_y(self, X, y) -> tuple[np.ndarray, np.ndarray]:
 
     @staticmethod
     def _find_dist(
-        feature_idx: int, feature_name: str | None, dist_mapping: dict[DistributionLike, ColumnKey]
+        feature_idx: int,
+        feature_name: str | None,
+        dist_mapping: dict[DistributionLike, ColumnKey],
     ) -> DistributionLike:
         for dist, cols in dist_mapping.items():
             cols_ = (

wnb/gwnb.py

@@ -250,8 +250,7 @@ def _init_parameters(self) -> None:
             # Ensure the size of error weights matrix matches number of classes
             if error_weights.shape != (self.n_classes_, self.n_classes_):
                 raise ValueError(
-                    "The shape of error weights matrix does not match the number of classes, "
-                    "must be (n_classes, n_classes)."
+                    "The shape of error weights matrix does not match the number of classes, must be (n_classes, n_classes)."
                 )
 
             self.error_weights_ = error_weights