updating extreme cases

tabs/tokens_dist.py

@@ -4,7 +4,7 @@ import matplotlib.pyplot as plt
 import seaborn as sns
 from seaborn import FacetGrid
 import plotly.express as px
-import logging
+from datetime import datetime, UTC
 from typing import Tuple
 
 
@@ -63,7 +63,11 @@ def get_based_votes_distribution(market_id: str, all_markets: pd.DataFrame):
 def get_extreme_cases(live_fpmms: pd.DataFrame) -> Tuple:
     """Function to return the id of the best and worst case according to the dist gap metric"""
     # select markets with some trades
-    selected_markets = live_fpmms.loc[live_fpmms["total_trades"] > 0]
+    today = datetime.now(UTC).date()
+    live_fpmms["sample_date"] = pd.to_datetime(live_fpmms["sample_timestamp"]).dt.date
+    selected_markets = live_fpmms.loc[
+        (live_fpmms["total_trades"] > 0) and (live_fpmms["sample_date"] == today)
+    ]
     selected_markets.sort_values(by="dist_gap_perc", ascending=False, inplace=True)
     return (
         selected_markets.iloc[-1].id,