Update app.py

app.py

@@ -11,7 +11,7 @@ try:
 except:
     pass
 
-# === PART 1: PRESETS + SIMULATION ENGINE ===
+# === STRATEGY PRESETS ===
 def get_strategy_presets():
     return {
         "Aggressive Prop Trader": {
@@ -53,6 +53,7 @@ def get_strategy_presets():
 
 strategy_presets = get_strategy_presets()
 
+# === CORE SIMULATION ENGINE ===
 def simulate_tp_strategy_full(starting_balance, trades_min, trades_max, weeks,
                               tp1_prob, tp2_prob, tp1_r, tp2_r, base_risk_pct,
                               profit_target=None, fatigue=0.0, trump_vol=0.0):
@@ -133,12 +134,93 @@ def simulate_tp_strategy_full(starting_balance, trades_min, trades_max, weeks,
     }
     
     return df, summary
+
+# === HISTOGRAM SIMULATION (NEW) ===
+def simulate_multiple_runs(config, metric="EdgeCast Score", runs=100):
+    metric_values = []
+    for _ in range(runs):
+        _, summary = simulate_tp_strategy_full(
+            config["starting_balance"],
+            config["trades_min"],
+            config["trades_max"],
+            config["weeks"],
+            config["tp1_prob"],
+            config["tp2_prob"],
+            config["tp1_r"],
+            config["tp2_r"],
+            config["base_risk_pct"],
+            config["profit_target"],
+            config["fatigue"],
+            config["trump_vol"]
+        )
+        metric_values.append(summary[metric])
+    return pd.DataFrame({metric: metric_values})
+
+def plot_histogram(df, metric):
+    fig = px.histogram(df, x=metric, nbins=30, title=f"{metric} Distribution")
+    fig.update_layout(
+        xaxis_title=metric,
+        yaxis_title="Frequency",
+        bargap=0.1,
+        height=400
+    )
+    return fig
+# === PART 2: PLOTTING ===
+
+def equity_curve_plot(df, label="Equity Curve"):
+    fig = go.Figure()
+    fig.add_trace(go.Scatter(
+        x=df["Week"],
+        y=df["End Balance"],
+        mode="lines+markers",
+        name=label
+    ))
+    fig.update_layout(
+        title=f"📈 {label}",
+        xaxis_title="Week",
+        yaxis_title="Balance ($)",
+        height=400
+    )
+    return fig
+
+
+def generate_histogram(metric="Final Balance"):
+    results = []
+    for name, config in strategy_presets.items():
+        _, summary = simulate_tp_strategy_full(**{k: v for k, v in config.items() if k != "description"})
+        summary["Strategy"] = name
+        results.append(summary)
+
+    df = pd.DataFrame(results)
+
+    if metric not in df.columns:
+        return go.Figure()
+
+    fig = px.histogram(
+        df,
+        x=metric,
+        color="Strategy",
+        barmode="overlay",
+        nbins=25,
+        title=f"📊 Histogram: {metric}",
+        labels={metric: metric}
+    )
+
+    fig.update_layout(
+        xaxis_title=metric,
+        yaxis_title="Frequency",
+        bargap=0.2
+    )
+
+    return fig
+# === PART 3: ANALYSIS TABS ===
+
 def show_descriptions():
     return pd.DataFrame([
         {"Strategy": name, "Description": config["description"]}
         for name, config in strategy_presets.items()
     ])
-    
+
 def analytics_dashboard(rank_by="EdgeCast Score"):
     results = []
     for name, config in strategy_presets.items():
@@ -164,6 +246,7 @@ def analytics_dashboard(rank_by="EdgeCast Score"):
 
     return df[["🏅 Rank", "Strategy", "Final Balance", "Sharpe Ratio", "EdgeCast Score", "Max Drawdown %"]]
 
+
 def generate_risk_matrix():
     names = list(strategy_presets.keys())
     scores = {
@@ -188,97 +271,11 @@ def generate_risk_matrix():
         hovertemplate="<b>%{y}</b> vs <b>%{x}</b><br>Δ Score: %{z:.2f}<extra></extra>"
     )
     return fig
-    
-def run_preset_strategy(style, fatigue=0.0, trump_vol=0.0):
-    if style not in strategy_presets:
-        return pd.DataFrame(), {}, go.Figure(), "Please select a strategy to begin."
-
-    config = strategy_presets[style]
-    df, summary = simulate_tp_strategy_full(
-        config["starting_balance"],
-        config["trades_min"],
-        config["trades_max"],
-        config["weeks"],
-        config["tp1_prob"],
-        config["tp2_prob"],
-        config["tp1_r"],
-        config["tp2_r"],
-        config["base_risk_pct"],
-        config["profit_target"],
-        fatigue=fatigue,
-        trump_vol=trump_vol
-    )
 
-    fig = go.Figure()
-    fig.add_trace(go.Scatter(
-        x=df["Week"], y=df["End Balance"],
-        mode="lines+markers", name=style
-    ))
-    fig.update_layout(
-        title=f"{style} – Equity Curve",
-        xaxis_title="Week",
-        yaxis_title="Balance ($)"
-    )
-
-    return df, summary, fig, config["description"]
-def run_manual_sim(starting_balance, trades_min, trades_max, weeks,
-                   tp1_prob, tp2_prob, tp1_r, tp2_r, base_risk_pct, profit_target,
-                   fatigue, trump_vol):
-    df, summary = simulate_tp_strategy_full(
-        starting_balance, trades_min, trades_max, weeks,
-        tp1_prob, tp2_prob, tp1_r, tp2_r, base_risk_pct,
-        profit_target, fatigue, trump_vol
-    )
-
-    fig = go.Figure()
-    fig.add_trace(go.Scatter(
-        x=df["Week"], y=df["End Balance"],
-        mode="lines+markers", name="Manual Config"
-    ))
-    fig.update_layout(
-        title="Manual Config – Equity Curve",
-        xaxis_title="Week",
-        yaxis_title="Balance ($)"
-    )
-
-    return df, summary, fig
-
-def get_manual_battle_interface():
-    return gr.Interface(
-        fn=dual_manual_battle,
-        inputs=[
-            gr.Markdown("#### ⚙️ Manual Config A"),
-            gr.Slider(100, 20000, 2500, label="A: Start Balance"),
-            gr.Slider(1, 10, 3, label="A: Trades Min"),
-            gr.Slider(1, 15, 7, label="A: Trades Max"),
-            gr.Slider(1, 52, 12, label="A: Weeks"),
-            gr.Slider(0, 1, 0.3, step=0.05, label="A: TP1 %"),
-            gr.Slider(0, 1, 0.3, step=0.05, label="A: TP2 %"),
-            gr.Slider(0.1, 5.0, 1.0, step=0.1, label="A: TP1 R"),
-            gr.Slider(0.1, 20.0, 2.0, step=0.1, label="A: TP2 R"),
-            gr.Slider(0.001, 0.05, 0.01, step=0.001, label="A: Risk %"),
-            gr.Slider(0, 100000, 0, step=500, label="A: Profit Target 💰"),
-            gr.Slider(0, 1, 0.0, step=0.1, label="A: Fatigue Level"),
-            gr.Slider(0, 1, 0.0, step=0.1, label="A: Trump Volatility"),
-
-            gr.Markdown("#### ⚙️ Manual Config B"),
-            gr.Slider(100, 20000, 2500, label="B: Start Balance"),
-            gr.Slider(1, 10, 3, label="B: Trades Min"),
-            gr.Slider(1, 15, 7, label="B: Trades Max"),
-            gr.Slider(1, 52, 12, label="B: Weeks"),
-            gr.Slider(0, 1, 0.3, step=0.05, label="B: TP1 %"),
-            gr.Slider(0, 1, 0.3, step=0.05, label="B: TP2 %"),
-            gr.Slider(0.1, 5.0, 1.0, step=0.1, label="B: TP1 R"),
-            gr.Slider(0.1, 20.0, 2.0, step=0.1, label="B: TP2 R"),
-            gr.Slider(0.001, 0.05, 0.01, step=0.001, label="B: Risk %"),
-            gr.Slider(0, 100000, 0, step=500, label="B: Profit Target 💰"),
-            gr.Slider(0, 1, 0.0, step=0.1, label="B: Fatigue Level"),
-            gr.Slider(0, 1, 0.0, step=0.1, label="B: Trump Volatility")
-        ],
-        outputs=["dataframe", gr.Plot()],
-        title="🧪 Manual Battle Mode"
-    )
 
+def histogram_viewer_ui(metric):
+    return generate_histogram(metric)
+# === PART 4: GRADIO INTERFACE ===
 
 app = gr.TabbedInterface(
     interface_list=[
@@ -295,7 +292,7 @@ app = gr.TabbedInterface(
             title="🎯 Preset Strategy Mode"
         ),
 
-        # 🛠️ Manual Config Tab (Single Simulation)
+        # 🛠️ Manual Config Tab
         gr.Interface(
             fn=run_manual_sim,
             inputs=[
@@ -316,68 +313,21 @@ app = gr.TabbedInterface(
             title="🛠️ Manual Config Mode"
         ),
 
-
-def dual_manual_battle(
-    sb1, tmin1, tmax1, w1, tp1a, tp2a, r1a, r2a, risk1, pt1, fat1, trump1,
-    sb2, tmin2, tmax2, w2, tp1b, tp2b, r1b, r2b, risk2, pt2, fat2, trump2
-):
-    df1, s1 = simulate_tp_strategy_full(sb1, tmin1, tmax1, w1, tp1a, tp2a, r1a, r2a, risk1, pt1, fat1, trump1)
-    df2, s2 = simulate_tp_strategy_full(sb2, tmin2, tmax2, w2, tp1b, tp2b, r1b, r2b, risk2, pt2, fat2, trump2)
-
-    s1["Strategy"] = "Manual A"
-    s2["Strategy"] = "Manual B"
-
-    comparison_df = pd.DataFrame([s1, s2])
-    comparison_df = comparison_df[["Strategy", "Final Balance", "Sharpe Ratio", "EdgeCast Score", "Max Drawdown %"]]
-
-    for col in ["Final Balance", "Sharpe Ratio", "EdgeCast Score"]:
-        best_val = comparison_df[col].astype(float).max()
-        comparison_df[col] = [
-            f"{val} 🏆" if float(val) == best_val else val for val in comparison_df[col]
-        ]
-
-    fig = go.Figure()
-    fig.add_trace(go.Scatter(x=df1["Week"], y=df1["End Balance"], name="Manual A"))
-    fig.add_trace(go.Scatter(x=df2["Week"], y=df2["End Balance"], name="Manual B"))
-    fig.update_layout(
-        title="⚔️ Manual Strategy Battle",
-        xaxis_title="Week",
-        yaxis_title="Balance ($)"
-    )
-
-    return comparison_df, fig
-        
-def dual_manual_battle(
-    sb1, tmin1, tmax1, w1, tp1a, tp2a, r1a, r2a, risk1, pt1, fat1, trump1,
-    sb2, tmin2, tmax2, w2, tp1b, tp2b, r1b, r2b, risk2, pt2, fat2, trump2
-):
-    df1, s1 = simulate_tp_strategy_full(sb1, tmin1, tmax1, w1, tp1a, tp2a, r1a, r2a, risk1, pt1, fat1, trump1)
-    df2, s2 = simulate_tp_strategy_full(sb2, tmin2, tmax2, w2, tp1b, tp2b, r1b, r2b, risk2, pt2, fat2, trump2)
-
-    s1["Strategy"] = "Manual A"
-    s2["Strategy"] = "Manual B"
-
-    comparison_df = pd.DataFrame([s1, s2])
-    comparison_df = comparison_df[["Strategy", "Final Balance", "Sharpe Ratio", "EdgeCast Score", "Max Drawdown %"]]
-
-    for col in ["Final Balance", "Sharpe Ratio", "EdgeCast Score"]:
-        best_val = comparison_df[col].astype(float).max()
-        comparison_df[col] = [
-            f"{val} 🏆" if float(val) == best_val else val for val in comparison_df[col]
-        ]
-
-    fig = go.Figure()
-    fig.add_trace(go.Scatter(x=df1["Week"], y=df1["End Balance"], name="Manual A"))
-    fig.add_trace(go.Scatter(x=df2["Week"], y=df2["End Balance"], name="Manual B"))
-    fig.update_layout(title="⚔️ Manual Strategy Battle", xaxis_title="Week", yaxis_title="Balance")
-
-    return comparison_df, fig
-
-        
-        # 🧪 Manual Battle Mode (Dual Sliders + Histogram)
+        # 🧪 Manual Battle Tab
         get_manual_battle_interface(),
 
-        # 📊 Leaderboard
+        # 📊 Histogram Viewer
+        gr.Interface(
+            fn=histogram_viewer_ui,
+            inputs=gr.Dropdown(
+                choices=["Final Balance", "Sharpe Ratio", "EdgeCast Score", "Max Drawdown %"],
+                label="Select Metric"
+            ),
+            outputs=gr.Plot(),
+            title="📊 Histogram Viewer"
+        ),
+
+        # 🏅 Leaderboard
         gr.Interface(
             fn=analytics_dashboard,
             inputs=gr.Dropdown(
@@ -386,10 +336,10 @@ def dual_manual_battle(
                 label="Sort leaderboard by:"
             ),
             outputs="dataframe",
-            title="📊 Strategy Leaderboard"
+            title="🏅 Strategy Leaderboard"
         ),
 
-        # 📘 Strategy Descriptions
+        # 📘 Descriptions
         gr.Interface(
             fn=show_descriptions,
             inputs=[], outputs="dataframe",
@@ -400,11 +350,50 @@ def dual_manual_battle(
         gr.Interface(
             fn=generate_risk_matrix,
             inputs=[], outputs=gr.Plot(),
-            title="🔬 Risk Matrix Heatmap"
+            title="🔬 Risk Matrix"
         )
     ],
-    tab_names=["Preset", "Manual", "Battle", "Leaderboard", "Descriptions", "Risk Matrix"],
+    tab_names=["Preset", "Manual", "Battle", "Histogram", "Leaderboard", "Descriptions", "Risk Matrix"],
     title="EdgeCast – Strategy Simulation Suite"
 )
 
 app.launch()
+# === PART 5: HISTOGRAM VIEWER ENGINE ===
+
+def generate_histogram(metric="EdgeCast Score"):
+    results = []
+    for name, config in strategy_presets.items():
+        _, summary = simulate_tp_strategy_full(
+            config["starting_balance"], config["trades_min"], config["trades_max"], config["weeks"],
+            config["tp1_prob"], config["tp2_prob"], config["tp1_r"], config["tp2_r"],
+            config["base_risk_pct"], config["profit_target"], config["fatigue"], config["trump_vol"]
+        )
+        summary["Strategy"] = name
+        results.append(summary)
+
+    df = pd.DataFrame(results)
+
+    if metric not in df.columns:
+        return go.Figure()
+
+    fig = px.histogram(
+        df,
+        x=metric,
+        color="Strategy",
+        marginal="box",
+        opacity=0.7,
+        barmode="overlay",
+        title=f"📊 Distribution of {metric} Across Strategies"
+    )
+
+    fig.update_layout(
+        xaxis_title=metric,
+        yaxis_title="Count",
+        bargap=0.1,
+        height=500
+    )
+
+    return fig
+
+def histogram_viewer_ui(metric):
+    return generate_histogram(metric)