add option to pass in args to mahal dist class

src/signature_mahalanobis_knn/mahal_distance.py

@@ -5,24 +5,31 @@
 
 
 class Mahalanobis:
-    """
-    After fit is called, becomes callable and intended to be used
-    as a distance function in sklearn nearest neighbour.
-    """
-
-    def __init__(self):
-        self.Vt: np.ndarray = np.empty(
-            0
-        )  # Truncated right singular matrix transposed of the corpus
-        self.mu: np.ndarray = np.empty(0)  # Mean of the corpus
-        self.S: np.ndarray = np.empty(0)  # Truncated singular values of the corpus
-        self.subspace_thres: float = (
-            1e-3  # Threshold to decide whether a point is in the data subspace
-        )
-        self.svd_thres: float = (
-            1e-12  # Threshold to decide numerical rank of the data matrix
-        )
-        self.numerical_rank: int = -1  # Numerical rank
+    def __init__(self, subspace_thres: float = 1e-3, svd_thres: float = 1e-12):
+        """
+        After fit is called, becomes callable and intended to be used
+        as a distance function in sklearn nearest neighbour.
+
+        Parameters
+        ----------
+        subspace_thres : float, optional
+            Threshold to decide whether a point is in the data subspace,
+            by default 1e-3.
+        svd_thres : float, optional
+            Threshold to decide numerical rank of the data matrix,
+            by default 1e-12.
+        """
+        self.subspace_thres: subspace_thres
+        self.svd_thres: svd_thres
+
+        # truncated right singular matrix transposed of the corpus
+        self.Vt: np.ndarray | None = None
+        # nean of the corpus
+        self.mu: np.ndarray | None = None
+        # truncated singular values of the corpus
+        self.S: np.ndarray | None = None
+        # numerical rank of the corpus, -1 means not fitted
+        self.numerical_rank: int | None = None
 
     def fit(self, X: np.ndarray, **kwargs) -> None:
         """
@@ -83,5 +90,8 @@ def distance(self, x1: np.ndarray, x2: np.ndarray) -> float:
 
         :return: a value representing distance between x, y
         """
+        if self.numerical_rank is None:
+            msg = "Mahalanobis distance is not fitted yet."
+            raise ValueError(msg)
 
         return self.calc_distance(x1, x2, self.Vt, self.S, self.subspace_thres)