Fix logo in documentation

streamsight/matrix/interaction_matrix.py

@@ -457,7 +457,7 @@ def __sub__(self, im: "InteractionMatrix") -> "InteractionMatrix":
             True
         )
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         return repr(self._df)
 
     def __eq__(self, value: object) -> bool:
@@ -466,6 +466,19 @@ def __eq__(self, value: object) -> bool:
             return False
         return self._df.equals(value._df)
 
+    def __len__(self) -> int:
+        """Return the number of interactions in the matrix.
+
+        This is distinct from the shape of the matrix, which is the number of
+        users and items that has been released to the model. The length of the
+        matrix is the number of interactions present in the matrix resulting
+        from filter operations.
+
+        :return: Number of interactions in the matrix.
+        :rtype: int
+        """
+        return len(self._df)
+
     @overload
     def items_in(self, I: Set[int], inplace=False) -> "InteractionMatrix": ...
     @overload

streamsight/settings/base.py

@@ -132,6 +132,7 @@ def split(self, data: InteractionMatrix) -> None:
         self._check_split()
 
         self._split_complete = True
+        logger.info(f"{self.name} data split complete.")
 
     def _check_split_complete(self):
         """Check if the setting is ready to be used for evaluation.

streamsight/settings/sliding_window_setting.py

@@ -115,6 +115,13 @@ def _split(self, data: InteractionMatrix):
             past_interaction, future_interaction = self._window_splitter.split(
                 data
             )
+
+            # if past_interaction, future_interaction is empty, log an info message
+            if len(past_interaction) == 0:
+                logger.info(f"Split at time {sub_time} resulted in empty unlabelled testing samples.")
+            if len(future_interaction) == 0:
+                logger.info(f"Split at time {sub_time} resulted in empty incremental data.")
+
             unlabeled_set, ground_truth = self.prediction_data_processor.process(past_interaction,
                                                                                  future_interaction,
                                                                                  self.top_K)