Update app.py

app.py

@@ -12,8 +12,13 @@ PORT = 7860
 HISTORY_LENGTH = 300 
 BROADCAST_RATE = 0.1
 
+# --- Tuning Parameters ---
+# Short: Scalping/Spread focus
 DECAY_LAMBDA_SHORT = 100.0 
+# Long: Swing/Structure focus
 DECAY_LAMBDA_LONG = 500.0  
+# Macro: Deep Orderbook/Whale focus
+DECAY_LAMBDA_MACRO = 2000.0 
 
 IMPACT_SENSITIVITY = 0.5 
 
@@ -25,6 +30,7 @@ market_state = {
     "history": [], 
     "pred_history_short": [], 
     "pred_history_long": [],
+    "pred_history_macro": [],
     "current_mid": 0.0,
     "prev_mid": 0.0,
     "ready": False
@@ -36,8 +42,9 @@ def analyze_structure(diff_x, diff_y, current_mid):
     if not diff_y or len(diff_y) < 5:
         return None
 
-    w_imbalance_short = 0.0
-    w_imbalance_long = 0.0
+    w_short = 0.0
+    w_long = 0.0
+    w_macro = 0.0
     prev_vol = 0.0
     
     for i in range(len(diff_x)):
@@ -47,26 +54,26 @@ def analyze_structure(diff_x, diff_y, current_mid):
         marginal_vol = cum_vol - prev_vol
         prev_vol = cum_vol
         
-        weight_short = math.exp(-dist / DECAY_LAMBDA_SHORT)
-        w_imbalance_short += marginal_vol * weight_short
+        # 1. Short Term Decay
+        w_short += marginal_vol * math.exp(-dist / DECAY_LAMBDA_SHORT)
         
-        weight_long = math.exp(-dist / DECAY_LAMBDA_LONG)
-        w_imbalance_long += marginal_vol * weight_long
-
-    if w_imbalance_short != 0:
-        impact_s = math.sqrt(abs(w_imbalance_short)) * IMPACT_SENSITIVITY
-        if w_imbalance_short < 0: impact_s = -impact_s
-    else: impact_s = 0.0
+        # 2. Long Term Decay
+        w_long += marginal_vol * math.exp(-dist / DECAY_LAMBDA_LONG)
+        
+        # 3. Macro Term Decay
+        w_macro += marginal_vol * math.exp(-dist / DECAY_LAMBDA_MACRO)
 
-    if w_imbalance_long != 0:
-        impact_l = math.sqrt(abs(w_imbalance_long)) * IMPACT_SENSITIVITY
-        if w_imbalance_long < 0: impact_l = -impact_l
-    else: impact_l = 0.0
+    # Helper for impact calc
+    def get_impact(w_imb):
+        if w_imb == 0: return 0.0
+        imp = math.sqrt(abs(w_imb)) * IMPACT_SENSITIVITY
+        return -imp if w_imb < 0 else imp
 
     return {
-        "proj_short": current_mid + impact_s,
-        "proj_long": current_mid + impact_l,
-        "net_score": w_imbalance_short
+        "proj_short": current_mid + get_impact(w_short),
+        "proj_long": current_mid + get_impact(w_long),
+        "proj_macro": current_mid + get_impact(w_macro),
+        "net_score": w_short # We drive the gauge with the short-term pressure
     }
 
 def process_market_data():
@@ -75,8 +82,9 @@ def process_market_data():
 
     mid = market_state['current_mid']
     
-    raw_bids = sorted(market_state['bids'].items(), key=lambda x: -x[0])[:300]
-    raw_asks = sorted(market_state['asks'].items(), key=lambda x: x[0])[:300]
+    # We need a deeper snapshot for Macro analysis
+    raw_bids = sorted(market_state['bids'].items(), key=lambda x: -x[0])[:600]
+    raw_asks = sorted(market_state['asks'].items(), key=lambda x: x[0])[:600]
 
     d_b_x, d_b_y, cum = [], [], 0
     for p, q in raw_bids:
@@ -117,19 +125,27 @@ def process_market_data():
     now = time.time()
     if analysis:
         if not market_state['pred_history_short'] or (now - market_state['pred_history_short'][-1]['t'] > 0.5):
+            # Short
             market_state['pred_history_short'].append({'t': now, 'p': analysis['proj_short']})
             if len(market_state['pred_history_short']) > HISTORY_LENGTH:
                 market_state['pred_history_short'].pop(0)
-                
+            
+            # Long
             market_state['pred_history_long'].append({'t': now, 'p': analysis['proj_long']})
             if len(market_state['pred_history_long']) > HISTORY_LENGTH:
                 market_state['pred_history_long'].pop(0)
+                
+            # Macro
+            market_state['pred_history_macro'].append({'t': now, 'p': analysis['proj_macro']})
+            if len(market_state['pred_history_macro']) > HISTORY_LENGTH:
+                market_state['pred_history_macro'].pop(0)
 
     return {
         "mid": mid,
         "history": market_state['history'],
         "pred_history_short": market_state['pred_history_short'],
         "pred_history_long": market_state['pred_history_long'],
+        "pred_history_macro": market_state['pred_history_macro'],
         "depth_x": diff_x,
         "depth_net": diff_y,
         "depth_bids": chart_bids,
@@ -152,6 +168,7 @@ HTML_PAGE = f"""
             --accent-green: #66fcf1;
             --accent-red: #ff3b3b;
             --accent-purple: #ce93d8;
+            --accent-cyan: #4dd0e1;
             --border: #2d3842;
         }}
         body {{ margin: 0; padding: 0; background-color: var(--bg-color); color: var(--text-main); font-family: monospace; overflow: hidden; height: 100vh; width: 100vw; }}
@@ -185,6 +202,7 @@ HTML_PAGE = f"""
         .green {{ color: var(--accent-green); }}
         .red {{ color: var(--accent-red); }}
         .purple {{ color: var(--accent-purple); }}
+        .cyan {{ color: var(--accent-cyan); }}
         
         #loader {{ position: absolute; top:0; left:0; width:100%; height:100%; background: rgba(0,0,0,0.95); z-index: 999; display: flex; flex-direction: column; justify-content: center; align-items: center; color: var(--accent-green); }}
     </style>
@@ -217,7 +235,7 @@ HTML_PAGE = f"""
             <div class="panel-header">HFT ANALYTICS ENGINE</div>
             <div class="stats-content">
                 <div class="stat-box">
-                    <span class="stat-label">WEIGHTED IMBALANCE (SHORT)</span>
+                    <span class="stat-label">WEIGHTED IMBALANCE (SCALP)</span>
                     <span id="score-val" class="stat-value">0</span>
                 </div>
                 <div class="stat-box" style="border: 1px solid #444;">
@@ -225,9 +243,13 @@ HTML_PAGE = f"""
                     <span id="proj-short" class="stat-value">---</span>
                 </div>
                 <div class="stat-box" style="border: 1px solid #7b1fa2;">
-                    <span class="stat-label" style="color:var(--accent-purple);">LONG TERM TARGET (CENTER OF MASS)</span>
+                    <span class="stat-label" style="color:var(--accent-purple);">LONG TERM (SWING)</span>
                     <span id="proj-long" class="stat-value purple">---</span>
                 </div>
+                <div class="stat-box" style="border: 1px solid #00acc1;">
+                    <span class="stat-label" style="color:var(--accent-cyan);">MACRO (WHALE)</span>
+                    <span id="proj-macro" class="stat-value cyan">---</span>
+                </div>
             </div>
         </div>
     </div>
@@ -240,7 +262,8 @@ HTML_PAGE = f"""
                 price: document.getElementById('live-price'),
                 scoreVal: document.getElementById('score-val'),
                 projShort: document.getElementById('proj-short'),
-                projLong: document.getElementById('proj-long')
+                projLong: document.getElementById('proj-long'),
+                projMacro: document.getElementById('proj-macro')
             }};
 
             const chartCommon = {{
@@ -255,11 +278,15 @@ HTML_PAGE = f"""
             
             const priceSeries = priceChart.addLineSeries({{ color: '#2962FF', lineWidth: 2, title: 'Price' }});
             
-            const pastShortSeries = priceChart.addLineSeries({{ color: '#555555', lineWidth: 1, title: 'Short Term (Past)' }});
-            const futureShortSeries = priceChart.addLineSeries({{ color: '#ff9800', lineWidth: 2, lineStyle: 2, title: 'Short Term (Fut)' }});
+            // Short Term: Show Past + Future Dotted
+            const pastShortSeries = priceChart.addLineSeries({{ color: '#555555', lineWidth: 1, title: 'Short (Past)' }});
+            const futureShortSeries = priceChart.addLineSeries({{ color: '#ff9800', lineWidth: 2, lineStyle: 2, title: 'Short (Fut)' }});
 
-            const pastLongSeries = priceChart.addLineSeries({{ color: '#7b1fa2', lineWidth: 1, title: 'Long Term (Past)' }});
-            const futureLongSeries = priceChart.addLineSeries({{ color: '#ce93d8', lineWidth: 2, lineStyle: 2, title: 'Long Term (Fut)' }});
+            // Long Term: Past Only
+            const pastLongSeries = priceChart.addLineSeries({{ color: '#7b1fa2', lineWidth: 1, title: 'Long (Past)' }});
+            
+            // Macro Term: Past Only
+            const pastMacroSeries = priceChart.addLineSeries({{ color: '#4dd0e1', lineWidth: 1, title: 'Macro (Past)' }});
 
             const rawChart = LightweightCharts.createChart(document.getElementById('tv-raw'), {{
                 ...chartCommon,
@@ -329,22 +356,33 @@ HTML_PAGE = f"""
                         }});
                     }}
 
+                    const predMacro = [];
+                    const seenM = new Set();
+                    if(data.pred_history_macro) {{
+                        data.pred_history_macro.forEach(d => {{
+                            const t = Math.floor(d.t);
+                            if(!seenM.has(t)) {{ seenM.add(t); predMacro.push({{ time: t, value: d.p }}); }}
+                        }});
+                    }}
+
                     if (cleanHistory.length) {{
                         priceSeries.setData(cleanHistory);
                         pastShortSeries.setData(predShort);
                         pastLongSeries.setData(predLong);
+                        pastMacroSeries.setData(predMacro);
 
                         const last = cleanHistory[cleanHistory.length-1];
                         dom.price.innerText = last.value.toLocaleString(undefined, {{minimumFractionDigits: 2}});
                         
                         if (data.analysis) {{
-                            const {{ proj_short, proj_long, net_score }} = data.analysis;
+                            const {{ proj_short, proj_long, proj_macro, net_score }} = data.analysis;
                             
+                            // Only plot short term future line
                             futureShortSeries.setData([last, {{ time: last.time + 60, value: proj_short }}]);
-                            futureLongSeries.setData([last, {{ time: last.time + 300, value: proj_long }}]);
                             
                             dom.projShort.innerText = proj_short.toLocaleString(undefined, {{minimumFractionDigits: 0, maximumFractionDigits: 0}});
                             dom.projLong.innerText = proj_long.toLocaleString(undefined, {{minimumFractionDigits: 0, maximumFractionDigits: 0}});
+                            dom.projMacro.innerText = proj_macro.toLocaleString(undefined, {{minimumFractionDigits: 0, maximumFractionDigits: 0}});
 
                             dom.scoreVal.innerText = net_score.toFixed(2);
                             dom.scoreVal.className = net_score > 0 ? "stat-value green" : "stat-value red";