Remove old tests, revert unnecessary modifications, add a new exception

.vscode/settings.json

@@ -1,7 +0,0 @@
-{
-    "python.testing.pytestArgs": [
-        "tests"
-    ],
-    "python.testing.unittestEnabled": false,
-    "python.testing.pytestEnabled": true
-}

eis_toolkit/exceptions.py

@@ -2,6 +2,10 @@ class CoordinatesOutOfBoundsException(Exception):
     """Exception error class for out of bound coordinates."""
 
 
+class ClassificationFailedException(Exception):
+    """Exception error class for classification failures."""
+
+
 class EmptyDataFrameException(Exception):
     """Exception error class raised if the dataframe is empty."""
 
@@ -46,16 +50,12 @@ class InvalidWktFormatException(Exception):
     """Exception error for invalid WKT format."""
 
 
-class InvalidColumnIndexException(Exception):
-    """Exception error for index out of range."""
-
-
-class UnFavorableClassDoesntExistException(Exception):
-    """Exception error class for failure to generalize classes using the given studentised contrast threshold value. Class 1 (unfavorable class)  doesn't exist"""
+class MatchingCrsException(Exception):
+    """Exception error class for CRS matches."""
 
 
-class FavorableClassDoesntExistException(Exception):
-    """Exception error class for failure to generalize classes using the given studentised contrast threshold value. Class 2 (favorable class)  doesn't exist"""
+class MatchingRasterGridException(Exception):
+    """Exception error class for raster grid matches."""
 
 
 class NotApplicableGeometryTypeException(Exception):

eis_toolkit/prediction/weights_of_evidence.py

@@ -7,6 +7,7 @@
 from beartype import beartype
 from beartype.typing import List, Literal, Optional, Sequence, Tuple, Union
 
+from eis_toolkit import exceptions
 from eis_toolkit.vector_processing.rasterize_vector import rasterize_vector
 
 
@@ -89,8 +90,12 @@ def _reclassify_by_studentized_contrast(df: pd.DataFrame, studentized_contrast_t
     """Create generalized classes based on the studentized contrast threhsold value."""
     index = df.idxmax()["Contrast"]
 
-    if df.loc[index, "Studentized contrast"] < studentized_contrast_threshold:
-        raise Exception("Failed, studentized contrast is {}".format(df.loc[index, "Studentized contrast"]))
+    if df.loc[index, "Studentized contrast"] < studentized_contrast_threshold or index == len(df.index) - 1:
+        raise exceptions.ClassificationFailedException(
+            "Failed to create generalized classes with given studentized contrast treshold ({})".format(
+                df.loc[index, "Studentized contrast"]
+            )
+        )
 
     df["Generalized class"] = 1
     for i in range(0, index + 1):