feat: add _nonoverlap_mean()

Take the mean of non-overlapping windows of scores

    Input:  list of tuples in the format (time, score)
    Output: list of tuples in the format (time, mean_score)
            (reduced set)

pipeline/feature_extractors.py

@@ -282,6 +282,28 @@ class VideoActivityFeatureExtractor(FeatureExtractor):
                                 )
         return scores
 
+    def _nonoverlap_mean(self, scores, window_size=0.500) -> list:
+        """Take the mean of non-overlapping windows of scores
+
+        Input: list of tuples in the format (time, score)
+        Output: list of tuples in the format (time, mean_score) (reduced set)
+        """
+        means = []
+        current_window = []
+        current_window_start = 0.0
+
+        for time, score in scores:
+            if time - current_window_start > window_size:
+                # calculate mean of current window
+                mean_score = sum([s for _, s in current_window]) / len(current_window)
+                means.append((current_window_start, round(mean_score, 3)))
+                # reset window
+                current_window = []
+                current_window_start = time
+            current_window.append((time, score))
+
+        return means
+
     def _drop_lowest(self, scores, percent=33):
         """Drop the lowest n% scores from the list"""
         scores = sorted(scores, key=lambda x: x[1], reverse=True)