Minor updates

Author: cbbcbail

src/flexibleSubsetSelection/dataset.py

@@ -418,7 +418,7 @@ def __len__(self) -> int:
 
     def __getattr__(self, attr: str) -> np.ndarray:
         """
-        Returns the specified transformed version of the dataset if specified.
+        Returns the specified transformed version of the dataset.
 
         Args:
             attr: Specify the name of a transform function

src/flexibleSubsetSelection/objective.py

@@ -18,7 +18,10 @@
 
 
 def preserveMetric(
-    subset: np.ndarray, metric: Callable, datasetMetric: ArrayLike, p: int | str = 1
+    subset: np.ndarray, 
+    metric: Callable, 
+    datasetMetric: ArrayLike, 
+    p: int | str = 1
 ) -> float:
     """
     An objective function for preserving a metric between a dataset and a subset
@@ -70,11 +73,6 @@ def outlierness(subset: np.ndarray, neighbors: int = 20) -> float:
     lof.fit(subset)
     return lof.negative_outlier_factor_
 
-
-def discreteDistribution(array: np.ndarray) -> float:
-    return 0
-
-
 def discreteCoverage(array: np.ndarray) -> float:
     """
     Computes the discrete coverage of the one hot encoded array

src/flexibleSubsetSelection/transform.py

@@ -86,8 +86,12 @@ def discretize(
             strategy: sklearn KBinsDiscretizer strategy to use.
         """
         selected = data[:, indices]
-        discretizer = KBinsDiscretizer(n_bins=bins, encode="ordinal", strategy=strategy)
-        return discretizer.fit_transform(selected)
+        discretizer = KBinsDiscretizer(
+            n_bins = bins, 
+            encode = "ordinal", 
+            strategy = strategy
+        )
+        return discretizer.fit_transform(selected).astype(int)
 
     @staticmethod
     def encode(