Update app.py

app.py

@@ -42,43 +42,50 @@ def visualize(df_pairwise: pd.DataFrame) -> Figure:
 
 
 def counting(xs: "pd.Series[str]", ys: "pd.Series[str]",
-             ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", "pd.Index[str]"]:  # type: ignore[type-var]
+             ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", dict[str, int]]:  # type: ignore[type-var]
+    result = evalica.counting(xs, ys, ws)
+    return result.scores, result.index
+
+
+def average_win_rate(xs: "pd.Series[str]", ys: "pd.Series[str]",
+                     ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", dict[str, int]]:  # type: ignore[type-var]
     result = evalica.counting(xs, ys, ws)
     return result.scores, result.index
 
 
 def bradley_terry(xs: "pd.Series[str]", ys: "pd.Series[str]",
-                  ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", "pd.Index[str]"]:  # type: ignore[type-var]
+                  ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", dict[str, int]]:  # type: ignore[type-var]
     result = evalica.bradley_terry(xs, ys, ws, tolerance=TOLERANCE, limit=LIMIT)
     return result.scores, result.index
 
 
 def elo(xs: "pd.Series[str]", ys: "pd.Series[str]",
-        ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", "pd.Index[str]"]:  # type: ignore[type-var]
+        ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", dict[str, int]]:  # type: ignore[type-var]
     result = evalica.elo(xs, ys, ws)
     return result.scores, result.index
 
 
 def eigen(xs: "pd.Series[str]", ys: "pd.Series[str]",
-          ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", "pd.Index[str]"]:  # type: ignore[type-var]
+          ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", dict[str, int]]:  # type: ignore[type-var]
     result = evalica.eigen(xs, ys, ws, tolerance=TOLERANCE, limit=LIMIT)
     return result.scores, result.index
 
 
 def pagerank(xs: "pd.Series[str]", ys: "pd.Series[str]",
-             ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", "pd.Index[str]"]:  # type: ignore[type-var]
+             ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", dict[str, int]]:  # type: ignore[type-var]
     result = evalica.pagerank(xs, ys, ws, tolerance=TOLERANCE, limit=LIMIT)
     return result.scores, result.index
 
 
 def newman(xs: "pd.Series[str]", ys: "pd.Series[str]",
-           ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", "pd.Index[str]"]:  # type: ignore[type-var]
+           ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", dict[str, int]]:  # type: ignore[type-var]
     result = evalica.newman(xs, ys, ws, tolerance=TOLERANCE, limit=LIMIT)
     return result.scores, result.index
 
 
 ALGORITHMS = {
     "Counting": counting,
+    "Average Win Rate": average_win_rate,
     "Bradley-Terry (1952)": bradley_terry,
     "Elo (1960)": elo,
     "Eigenvector (1987)": eigen,
@@ -132,9 +139,9 @@ def handler(
     ws = df_pairs["winner"].map({"left": Winner.X, "right": Winner.Y, "tie": Winner.Draw})
 
     scores, index = ALGORITHMS[algorithm](xs, ys, ws)
-    index.name = "item"
 
     df_result = pd.DataFrame(data={"score": scores}, index=index)
+    df_result.index.name = "item"
 
     df_result["pairs"] = pd.Series(0, dtype=int, index=index).add(
         df_pairs.groupby("left")["left"].count(), fill_value=0,
@@ -204,6 +211,7 @@ def main() -> None:
             ["food.csv", "Eigenvector (1987)", False, False],
             ["food.csv", "PageRank (1998)", False, False],
             ["food.csv", "Newman (2023)", False, False],
+            ["llmfao.csv", "Average Win Rate", False, True],
             ["llmfao.csv", "Bradley-Terry (1952)", False, True],
             ["llmfao.csv", "Elo (1960)", False, True],
         ],