refactor: clean up

backend/api/routes.py

@@ -614,7 +614,6 @@ def get_optimize(req: OptimizeRequest):
     ranking_key = req.rank_objective
 
     def _rank_results(items):
-        # Lower drawdown is better; all other objectives are maximize.
         if ranking_key == "max_drawdown_pct":
             return sorted(items, key=lambda x: x.get(ranking_key, 0))
         return sorted(items, key=lambda x: x.get(ranking_key, 0), reverse=True)
@@ -666,10 +665,8 @@ def get_optimize(req: OptimizeRequest):
     total_generated_combinations = base_count_without_sweep * sweep_factor
 
     if sample_mode == "first":
-        # Stop iteration as soon as we hit the cap (no ghost work on remaining permutations).
         combos = list(islice(_candidate_iter(), req.max_combinations))
     else:
-        # Reservoir sampling keeps an unbiased random sample without storing all combos.
         for generated_idx, candidate in enumerate(_candidate_iter(), start=1):
             if len(combos) < req.max_combinations:
                 if len(combos) < req.max_combinations:
@@ -686,7 +683,6 @@ def get_optimize(req: OptimizeRequest):
         started = time.perf_counter()
         results = []
 
-        # Emit immediately so the UI can move off 0% as soon as the stream opens.
         yield f"data: {json.dumps({'type': 'progress', 'progress': 0, 'processed': 0, 'total_combinations': executed_combinations, 'generated_combinations': total_generated_combinations, 'executed_combinations': executed_combinations, 'max_combinations': req.max_combinations, 'capped_by_max_combinations': capped_by_max_combinations, 'combo_sampling_mode': sample_mode, 'combo_sampling_seed': req.combo_sampling_seed, 'valid_results': 0, 'top_results': []})}\n\n"
 
         for i, params in enumerate(combos):
@@ -924,12 +920,12 @@ def stream_backtest(
     use_fvg: bool = True,
     use_ob: bool = True,
     proximity_pct: float = 0.5,
-    # FVG Quality
+
     min_gap_size: float = 0.0,
     impulse_multiplier: float = 0.0,
     require_unmitigated_fvg: bool = True,
     require_bos_confluence: bool = False,
-    # Order Block
+
     min_ob_size: float = 0.0,
     require_fvg_ob_confluence: bool = False,
     # Liquidity

backend/engine/backtester.py

@@ -30,54 +30,6 @@ def _apply_break_even_if_triggered(position, candle, strategy):
         position["break_even_armed"] = True
 
 
-def _apply_partial_tp_if_triggered(position, candle, strategy):
-    if not position:
-        return
-
-    if not getattr(strategy, "use_partial_tp", False):
-        return
-
-    if position.get("partial_taken"):
-        return
-
-    trigger_rr = float(getattr(strategy, "partial_tp_rr", 1.0) or 0.0)
-    if trigger_rr <= 0:
-        return
-
-    partial_pct = float(getattr(strategy, "partial_tp_percent", 0.0) or 0.0)
-    if partial_pct <= 0:
-        return
-
-    close_fraction = min(max(partial_pct / 100.0, 0.0), 1.0)
-    remaining_fraction = max(position.get("remaining_fraction", 1.0), 0.0)
-    if remaining_fraction <= 0:
-        position["partial_taken"] = True
-        return
-
-    close_fraction = min(close_fraction, remaining_fraction)
-    if close_fraction <= 0:
-        return
-
-    is_long = position["direction"] == "long"
-    entry = position["entry_price"]
-    risk_distance = max(position.get("risk_distance", 0.0), 0.0)
-    if risk_distance <= 0:
-        return
-
-    trigger_price = entry + (risk_distance * trigger_rr) if is_long else entry - (risk_distance * trigger_rr)
-    reached_trigger = candle.high >= trigger_price if is_long else candle.low <= trigger_price
-    if not reached_trigger:
-        return
-
-    lot_size = max(position.get("lot_size", 0.0), 0.0)
-    price_move = (trigger_price - entry) if is_long else (entry - trigger_price)
-    realized_piece = price_move * lot_size * close_fraction
-
-    position["realized_pnl"] = position.get("realized_pnl", 0.0) + realized_piece
-    position["remaining_fraction"] = max(0.0, remaining_fraction - close_fraction)
-    position["partial_taken"] = True
-
-
 def run_backtest(candles, strategy, starting_balance, risk_reward=1.0,
                  max_daily_loss=0.0, max_consecutive_losses=0, risk_pct=1.0):
     trades = []
@@ -89,7 +41,6 @@ def run_backtest(candles, strategy, starting_balance, risk_reward=1.0,
 
     for i, candle in enumerate(candles):
         if position:
-            _apply_partial_tp_if_triggered(position, candle, strategy)
             _apply_break_even_if_triggered(position, candle, strategy)
 
             is_long = position["direction"] == "long"
@@ -102,11 +53,9 @@ def run_backtest(candles, strategy, starting_balance, risk_reward=1.0,
                 exit_price = sl if hit_sl else tp
                 price_move = (exit_price - position["entry_price"]) if is_long else (position["entry_price"] - exit_price)
                 lot_size = max(position.get("lot_size", 0.0), 0.0)
-                remaining_fraction = max(position.get("remaining_fraction", 1.0), 0.0)
+                pnl = price_move * lot_size
-                remaining_pnl = price_move * lot_size * remaining_fraction
+                risk_distance = max(position.get("risk_distance", 0.0), 1e-12)
-                pnl = position.get("realized_pnl", 0.0) + remaining_pnl
+                r_multiple = price_move / risk_distance
-                initial_risk = max(position.get("initial_risk_amount", 0.0), 1e-12)
-                r_multiple = pnl / initial_risk
 
                 trades.append(Trade(
                     enter_time=position["enter_time"],
@@ -116,8 +65,6 @@ def run_backtest(candles, strategy, starting_balance, risk_reward=1.0,
                     exit_price=exit_price,
                     pnl=pnl,
                     r_multiple=r_multiple,
-                    partial_tp_taken=bool(position.get("partial_taken", False)),
-                    partial_tp_realized_pnl=float(position.get("realized_pnl", 0.0) or 0.0),
                 ))
                 position = None
 
@@ -171,10 +118,6 @@ def run_backtest(candles, strategy, starting_balance, risk_reward=1.0,
                     "risk_distance": sl_distance,
                     "lot_size": lot_size,
                     "break_even_armed": False,
-                    "partial_taken": False,
-                    "remaining_fraction": 1.0,
-                    "realized_pnl": 0.0,
-                    "initial_risk_amount": risk_amount,
                 }
 
     return trades
@@ -199,7 +142,6 @@ def run_backtest_stream(candles, strategy, starting_balance, risk_reward=1.0,
             yield {"type": "progress", "processed_candles": i, "total_candles": total}
 
         if position:
-            _apply_partial_tp_if_triggered(position, candle, strategy)
             _apply_break_even_if_triggered(position, candle, strategy)
 
             is_long = position["direction"] == "long"
@@ -212,11 +154,9 @@ def run_backtest_stream(candles, strategy, starting_balance, risk_reward=1.0,
                 exit_price = sl if hit_sl else tp
                 price_move = (exit_price - position["entry_price"]) if is_long else (position["entry_price"] - exit_price)
                 lot_size = max(position.get("lot_size", 0.0), 0.0)
-                remaining_fraction = max(position.get("remaining_fraction", 1.0), 0.0)
+                pnl = price_move * lot_size
-                remaining_pnl = price_move * lot_size * remaining_fraction
+                risk_distance = max(position.get("risk_distance", 0.0), 1e-12)
-                pnl = position.get("realized_pnl", 0.0) + remaining_pnl
+                r_multiple = price_move / risk_distance
-                initial_risk = max(position.get("initial_risk_amount", 0.0), 1e-12)
-                r_multiple = pnl / initial_risk
 
                 trade = Trade(
                     enter_time=position["enter_time"],
@@ -226,8 +166,6 @@ def run_backtest_stream(candles, strategy, starting_balance, risk_reward=1.0,
                     exit_price=exit_price,
                     pnl=pnl,
                     r_multiple=r_multiple,
-                    partial_tp_taken=bool(position.get("partial_taken", False)),
-                    partial_tp_realized_pnl=float(position.get("realized_pnl", 0.0) or 0.0),
                 )
                 position = None
 
@@ -283,10 +221,6 @@ def run_backtest_stream(candles, strategy, starting_balance, risk_reward=1.0,
                     "risk_distance": sl_distance,
                     "lot_size": lot_size,
                     "break_even_armed": False,
-                    "partial_taken": False,
-                    "remaining_fraction": 1.0,
-                    "realized_pnl": 0.0,
-                    "initial_risk_amount": risk_amount,
                 }
 
     yield {"type": "done", "total_candles": total}

backend/indicators/fvg.py

@@ -1,12 +1,4 @@
 def find_fvgs(candles, min_gap_size=0.0, impulse_multiplier=0.0):
-    """
-    Find Fair Value Gaps in candle data.
-
-    Args:
-        candles: list of Candle objects
-        min_gap_size: minimum gap size in price units to filter noise (0 = no filter)
-        impulse_multiplier: minimum body-to-avg ratio for the middle candle (0 = no filter)
-    """
     fvgs = []
 
     avg_body = 0
@@ -50,7 +42,6 @@ def find_fvgs(candles, min_gap_size=0.0, impulse_multiplier=0.0):
                     "bottom": c3.high,
                     "mitigated": False,
                 })
-
         # Mark mitigated FVGs
         for fvg in fvgs:
             if fvg["mitigated"]:

frontend/src/App.jsx

@@ -14,6 +14,7 @@ import { EquityCurve } from './components/EquityCurve';
 import { MetricCard } from './components/MetricCard';
 import { PerformanceBreakdown } from './components/PerformanceBreakdown';
 import { TradeDistribution } from './components/TradeDistribution';
+import appLogo from './assets/favicon.png';
 
 const TIMEFRAMES = [
   { label: '1m', value: 1 },
@@ -143,6 +144,17 @@ export default function App() {
 
   useEffect(() => { setMounted(true); }, []);
 
+  useEffect(() => {
+    let link = document.querySelector("link[rel='icon']");
+    if (!link) {
+      link = document.createElement('link');
+      link.rel = 'icon';
+      document.head.appendChild(link);
+    }
+    link.type = 'image/png';
+    link.href = appLogo;
+  }, []);
+
   useEffect(() => {
     let isMounted = true;
     const loadDatasets = async () => {
@@ -461,12 +473,13 @@ export default function App() {
           animate={mounted ? 'visible' : 'hidden'}
         >
           <div className="flex items-center gap-4">
-            <div className="w-10 h-10 bg-[#fafafa] text-black font-mono font-bold text-[13px] flex items-center justify-center tracking-tight">
+            <img
-              nQ
+              src={appLogo}
-            </div>
+              alt="noteQuant logo"
+              className="w-10 h-10 object-contain border border-[#262626] bg-black p-1"
+            />
             <div>
               <div className="text-[17px] font-semibold tracking-tight">noteQuant</div>
-              <div className="text-[11px] text-[#737373] font-mono uppercase tracking-widest">ICT / SMC Backtester</div>
             </div>
           </div>
           <div className="flex items-center gap-3 flex-wrap">

frontend/src/components/BacktestingTab.jsx

@@ -81,7 +81,8 @@ function savePresets(presets) {
 function loadRecentResults() {
   try {
     const parsed = JSON.parse(localStorage.getItem(RESULT_HISTORY_KEY) || '[]');
-    return Array.isArray(parsed) ? parsed.slice(0, 5) : [];
+    return Array.isArray(parsed) ? parsed.slice(0,
+        5) : [];
   } catch {
     return [];
   }