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4097ba4 2b552ac 4097ba4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 | import pandas as pd
from typing import List, Optional
from .data_loader import DataLoader
class Leaderboard:
def __init__(self, data_loader: DataLoader):
self.data_loader = data_loader
def update_leaderboard(self, metric: str = "Average", top_k: int = 25,
model_filter: str = "", open_source_filter: str = "All",
year_filter: str = "All", category_filter: str = "All",
sort_mode: str = "Auto",
selected_metrics: Optional[List[str]] = None) -> pd.DataFrame:
df = self.data_loader.filter_data(model_filter, open_source_filter,
year_filter, category_filter)
if df.empty:
return pd.DataFrame()
if sort_mode == "Auto":
ascending = False
elif sort_mode == "Ascending (low → high)":
ascending = True
else:
ascending = False
if metric in df.columns:
df = df.sort_values(by=metric, ascending=ascending)
df = df.head(top_k).reset_index(drop=True)
df.insert(0, "Rank", range(1, len(df) + 1))
base_cols = ["Rank", "Model", "Category"]
if selected_metrics is None:
selected_metrics = ["Average"]
display_cols = base_cols.copy()
for m in selected_metrics:
if m in df.columns and m not in display_cols:
display_cols.append(m)
# Add optional link columns if they exist
link_cols = []
if "Paper" in df.columns:
link_cols.append("Paper")
if "Code" in df.columns:
link_cols.append("Code")
display_cols.extend(link_cols)
result_df = df[display_cols].copy()
# Format numeric values
for col in result_df.columns:
if col not in ["Rank", "Model", "Category", "Paper", "Code", "Open Source", "Year"]:
result_df[col] = result_df[col].apply(
lambda x: f"{x:.4f}" if pd.notna(x) and isinstance(x, (int, float)) else "-"
)
# Do NOT generate HTML links; keep as plain text
# (If you want links, you can add them here, but for sorting they are fine as text)
return result_df |