improve avg dist metrics

1 files changed, 26 insertions, 13 deletions

diff --git a/bjoern/videoanalyse/utils.py b/bjoern/videoanalyse/utils.py
index b1eaa4f..df00482 100644
--- a/bjoern/videoanalyse/utils.py
+++ b/bjoern/videoanalyse/utils.py
@@ -130,22 +130,35 @@ def write_grouped_metrics(df, url_groups, data_path):
 
 def evaluate_results(vp_results):
     vp_code = [df["vp_code"].values[0] for df in vp_results]
-    mean_lev = [
-        sum(df["levenshtein-distance"].values) / len(df["levenshtein-distance"])
-        for df in vp_results
-    ]
-    mean_long = [
-        sum(df["longest-distance"].values) / len(df["longest-distance"])
-        for df in vp_results
-    ]
-    mean_freq = [
-        sum(df["most_frequent-distance"].values) / len(df["most_frequent-distance"])
-        for df in vp_results
-    ]
+    # mean_lev = [
+    #     sum(df["levenshtein-distance"].values) / len(df["levenshtein-distance"])
+    #     for df in vp_results
+    # ]
+    mean_long = []
+    mean_freq = []
+    for df in vp_results:
+        groups = set(df["group"].values)
+        group_long = 0
+        group_freq = 0
+        for group in groups:
+            group_df = df.loc[df['group'] == group]
+            group_long += group_df["longest-distance"].values[0]
+            group_freq += group_df["most_frequent-distance"].values[0]
+        mean_long.append(group_long / len(groups))
+        mean_freq.append(group_freq / len(groups))
+
+    # mean_long = [
+    #     sum(df["longest-distance"].values) / len(df["longest-distance"])
+    #     for df in vp_results
+    # ]
+    # mean_freq = [
+    #     sum(df["most_frequent-distance"].values) / len(df["most_frequent-distance"])
+    #     for df in vp_results
+    # ]
 
     metrics = {
         "vp_code": vp_code,
-        "mean_lev": mean_lev,
+        # "mean_lev": mean_lev,
         "mean_long": mean_long,
         "mean_freq": mean_freq,
     }