winning graph by trader types

app.py

@@ -131,6 +131,13 @@ weekly_non_agent_metrics_by_market_creator = compute_weekly_metrics_by_market_cr
 weekly_winning_metrics = compute_winning_metrics_by_trader(
     trader_agents_data=trader_agents_data
 )
+weekly_agent_winning_metrics = compute_winning_metrics_by_trader(
+    trader_agents_data=trader_agents_data, trader_filter="agent"
+)
+weekly_non_agent_winning_metrics = compute_winning_metrics_by_trader(
+    trader_agents_data=trader_agents_data, trader_filter="non_agent"
+)
+
 with demo:
     gr.HTML("<h1>Trader agents monitoring dashboard </h1>")
     gr.Markdown(
@@ -229,38 +236,38 @@ with demo:
                 inputs=trader_na_details_selector,
                 outputs=na_trader_markets_plot,
             )
-        with gr.TabItem("🔥 Daily metrics"):
-            with gr.Row():
-                gr.Markdown("# Daily metrics of last week of all traders")
-            with gr.Row():
-                trader_daily_details_selector = gr.Dropdown(
-                    label="Select a daily trader metric",
-                    choices=trader_metric_choices,
-                    value=default_trader_metric,
-                )
-
-            with gr.Row():
-                with gr.Column(scale=3):
-                    trader_daily_markets_plot = (
-                        plot_trader_daily_metrics_by_market_creator(
-                            metric_name=default_trader_metric,
-                            traders_df=daily_metrics_by_market_creator,
-                        )
-                    )
-                with gr.Column(scale=1):
-                    trade_details_text = get_metrics_text()
-
-            def update_trader_daily_details(trader_detail):
-                return plot_trader_daily_metrics_by_market_creator(
-                    metric_name=trader_detail,
-                    traders_df=daily_metrics_by_market_creator,
-                )
-
-            trader_daily_details_selector.change(
-                update_trader_daily_details,
-                inputs=trader_daily_details_selector,
-                outputs=trader_daily_markets_plot,
-            )
+        # with gr.TabItem("🔥 Daily metrics (WIP)"):
+        #     with gr.Row():
+        #         gr.Markdown("# Daily metrics of last week of all traders")
+        #     with gr.Row():
+        #         trader_daily_details_selector = gr.Dropdown(
+        #             label="Select a daily trader metric",
+        #             choices=trader_metric_choices,
+        #             value=default_trader_metric,
+        #         )
+
+        #     with gr.Row():
+        #         with gr.Column(scale=3):
+        #             trader_daily_markets_plot = (
+        #                 plot_trader_daily_metrics_by_market_creator(
+        #                     metric_name=default_trader_metric,
+        #                     traders_df=daily_metrics_by_market_creator,
+        #                 )
+        #             )
+        #         with gr.Column(scale=1):
+        #             trade_details_text = get_metrics_text()
+
+        #     def update_trader_daily_details(trader_detail):
+        #         return plot_trader_daily_metrics_by_market_creator(
+        #             metric_name=trader_detail,
+        #             traders_df=daily_metrics_by_market_creator,
+        #         )
+
+        #     trader_daily_details_selector.change(
+        #         update_trader_daily_details,
+        #         inputs=trader_daily_details_selector,
+        #         outputs=trader_daily_markets_plot,
+        #     )
 
         with gr.TabItem("📉Closed Markets Kullback–Leibler divergence"):
             with gr.Row():
@@ -281,11 +288,30 @@ with demo:
 
         with gr.TabItem("🎖️Weekly winning trades % per trader"):
             with gr.Row():
-                gr.Markdown("# Winning trades percentage from weekly trades by trader")
+                gr.Markdown("# Weekly winning trades percentage from all traders")
             with gr.Row():
                 metrics_text = get_metrics_text()
             with gr.Row():
-
                 winning_metric = plot_winning_metric_per_trader(weekly_winning_metrics)
 
+            # Agentic traders
+            with gr.Row():
+                gr.Markdown("# Weekly winning trades percentage from traders Agents")
+            with gr.Row():
+                metrics_text = get_metrics_text()
+            with gr.Row():
+                winning_metric = plot_winning_metric_per_trader(
+                    weekly_agent_winning_metrics
+                )
+
+            # Non_agentic traders
+            with gr.Row():
+                gr.Markdown("# Weekly winning trades percentage from Non-agent traders")
+            with gr.Row():
+                metrics_text = get_metrics_text()
+            with gr.Row():
+                winning_metric = plot_winning_metric_per_trader(
+                    weekly_non_agent_winning_metrics
+                )
+
 demo.queue(default_concurrency_limit=40).launch()

scripts/metrics.py

@@ -224,7 +224,7 @@ def compute_daily_metrics_by_market_creator(
 
 
 def compute_winning_metrics_by_trader(
-    trader_agents_data: pd.DataFrame,
+    trader_agents_data: pd.DataFrame, trader_filter: str = None
 ) -> pd.DataFrame:
     """Function to compute the winning metrics at the trader level per week and with different market creators"""
     market_all = trader_agents_data.copy(deep=True)
@@ -234,6 +234,11 @@ def compute_winning_metrics_by_trader(
     final_traders = pd.concat([market_all, trader_agents_data], ignore_index=True)
     final_traders = final_traders.sort_values(by="creation_timestamp", ascending=True)
 
+    if trader_filter == "agentic":
+        final_traders = final_traders.loc[final_traders["staking"] != "non_agent"]
+    else:  # non_agent traders
+        final_traders = final_traders.loc[final_traders["staking"] == "non_agent"]
+
     winning_df = win_metrics_trader_level(final_traders)
     winning_df.head()
     return winning_df