adding votes graphs

app.py

@@ -9,6 +9,7 @@ from tabs.tokens_votes_dist import (
     get_based_tokens_distribution,
     get_based_votes_distribution,
 )
+from tabs.dist_gap import get_distribution_plot
 
 
 def get_logger():
@@ -96,5 +97,30 @@ with demo:
 
             with gr.Row():
                 gr.Markdown("# Evolution of outcomes probability based on votes")
+            with gr.Row():
+                gr.Markdown("Best case: a market with a low distribution gap metric")
+            with gr.Row():
+                gr.Markdown(f"Market id = {best_market_id}")
+            with gr.Row():
+                best_market_votes_dist = get_based_votes_distribution(
+                    best_market_id, markets_data
+                )
+            with gr.Row():
+                gr.Markdown("Worst case: a market with a high distribution gap metric")
+            with gr.Row():
+                gr.Markdown(f"Market id = {worst_market_id}")
+
+            with gr.Row():
+                worst_market_tokens_dist = get_based_votes_distribution(
+                    worst_market_id, markets_data
+                )
 
+        with gr.TabItem("📏 Distribution gap metric"):
+            with gr.Row():
+                gr.Markdown(
+                    "This metric measures the difference between the probability distribution based on the tokens distribution and the one based on the votes distribution"
+                )
+
+            with gr.Row():
+                dist_plot = get_distribution_plot(markets_data)
     demo.queue(default_concurrency_limit=40).launch()

tabs/dist_gap.py

@@ -13,3 +13,12 @@ def plot_top_best_behaviour_markets(markets_data: pd.DataFrame):
         5
     )
     return gr.DataFrame(top_best_markets)
+
+
+def get_distribution_plot(markets_data: pd.DataFrame):
+    """Function to paint the density plot of the metric distribution gap percentage"""
+    plt.figure(figsize=(25, 10))
+    plot = sns.kdeplot(markets_data, x="dist_gap_perc", fill=True)
+    # TODO Add title and labels
+    # Display the plot using gr.Plot
+    return gr.Plot(value=plot.get_figure())

tabs/tokens_votes_dist.py

@@ -29,7 +29,6 @@ def get_based_tokens_distribution(market_id: str, all_markets: pd.DataFrame):
     first_outcome = selected_market.iloc[0].first_outcome
     second_outcome = selected_market.iloc[0].second_outcome
     ax.legend(
-        bbox_to_anchor=(1, 1.02),
         loc="upper left",
         labels=[first_outcome, second_outcome],
     )
@@ -48,6 +47,7 @@ def get_based_votes_distribution(market_id: str, all_markets: pd.DataFrame):
         rot=0,
         stacked=True,
     )
+    plt.figure(figsize=(25, 10))
     # add overall title
     plt.title("Outcomes probability over time based on votes distributions", fontsize=8)
 
@@ -57,7 +57,6 @@ def get_based_votes_distribution(market_id: str, all_markets: pd.DataFrame):
     first_outcome = selected_market.iloc[0].first_outcome
     second_outcome = selected_market.iloc[0].second_outcome
     ax.legend(
-        bbox_to_anchor=(1, 1.02),
         loc="upper left",
         labels=[first_outcome, second_outcome],
     )