Resolve "normalisation should raise exception when bad arguments given"

Closes #22 (closed)

skais/ais/ais_points.py

@@ -44,6 +44,9 @@ class AISPoints:
     def normalize(self, min_max_features=(), standardization_features=(), third_quartile_features=(),
                   divide_by_value=(), divide_by_max=(), normalization_dict=None):
         if normalization_dict is None:
+            if len(min_max_features) == len(standardization_features) == len(third_quartile_features) == len(
+                    divide_by_value) == len(divide_by_max) == 0:
+                raise ValueError("All arguments are empty")
             normalization_dict = {}
             for f in min_max_features:
                 if f in self.df.columns:
@@ -94,7 +97,7 @@ class AISPoints:
                     normalization_dict[f] = {'type': 'divide by max',
                                              'maximum': maximum}
                     self.df[f] = self.df[f] / maximum
-        else:
+        elif type(normalization_dict) == dict:
             for f in normalization_dict:
                 if f in self.df.columns:
                     if normalization_dict[f]['type'] == 'min-max':
@@ -125,6 +128,8 @@ class AISPoints:
                         raise ValueError(
                             f"{normalization_dict[f]['type']} not a valid normalization method. Must be on of [min-max,"
                             f" standardization, 3rd quartile, divide by value]")
+        else:
+            raise ValueError("normalization_dict not a dictionary")
         return normalization_dict
 
     # New features