fix(base): third round of inheritance fixes

chemfusekit/knn.py

@@ -9,7 +9,7 @@
 
 from chemfusekit.lldf import LLDFDataModel
 from chemfusekit.__utils import run_split_test, print_confusion_matrix, print_table, GraphMode
-from .__base import BaseClassifierSettings, BaseClassifier
+from .__base import BaseClassifierSettings, BaseClassifier, BaseDataModel
 
 
 class KNNSettings(BaseClassifierSettings):
@@ -39,7 +39,7 @@ def __init__(self, n_neighbors: int = 15, metric: str | Callable = 'euclidean',
 
 class KNN(BaseClassifier):
     '''Class to store the data, methods and artifacts for k-Nearest Neighbors Analysis'''
-    def __init__(self, settings: KNNSettings, fused_data: LLDFDataModel):
+    def __init__(self, settings: KNNSettings, fused_data: BaseDataModel):
         super().__init__(settings, fused_data)
 
     def knn(self):

chemfusekit/pca.py

@@ -14,7 +14,7 @@
 import scipy.stats
 
 from chemfusekit.__utils import print_table, GraphMode
-from .__base import BaseDataModel, BaseReducer
+from .__base import BaseDataModel, BaseReducer, BaseSettings
 
 
 class PCADataModel(BaseDataModel):
@@ -26,11 +26,12 @@ def __init__(self, x_data: pd.DataFrame, x_train: pd.DataFrame, y: np.ndarray, a
         self.components = components
 
 
-class PCASettings:
+class PCASettings(BaseSettings):
     '''Holds the settings for the PCA object.'''
     def __init__(self, target_variance: float = 0.95,
                  confidence_level: float = 0.05,
                  initial_components: int = 10, output: GraphMode = GraphMode.NONE):
+        super().__init__(output)
         if target_variance < 0:
             raise ValueError("Target variance should be positive or null.")
         if confidence_level < 0 or confidence_level > 1:
@@ -40,7 +41,6 @@ def __init__(self, target_variance: float = 0.95,
         self.target_variance = target_variance
         self.confidence_level = confidence_level
         self.initial_components = initial_components
-        self.output = output
 
 
 class PCA(BaseReducer):