Update app.py

app.py

@@ -53,18 +53,77 @@ def average_downtrend(data, method, window=4):
     return avg_diff if avg_diff < 0 else 0.0
 
 
+def score_candle(candle, prev_candle, trend_strength):
+    """Score a single candle based on its characteristics and previous candle."""
+    open_price = candle['Open']
+    close_price = candle['Close']
+    low_price = candle['Low']
+    high_price = candle['High']
+    prev_close = prev_candle['Close']
+
+    # Bottom and top wick lengths
+    bottom_wick_length = min(open_price, close_price) - low_price
+    top_wick_length = high_price - max(open_price, close_price)
+
+    # Initial score based on trend strength
+    score = trend_strength * 2
+
+    # Doji: Open and Close are almost the same (small body)
+    if abs(open_price - close_price) <= 0.1 * (high_price - low_price):  # Adjust tolerance if needed
+        score += 5  # Bonus points for doji candles
+
+    # Hammer: Small body at the top, long bottom wick (typical reversal candle)
+    if close_price < open_price and bottom_wick_length > 2 * (open_price - close_price):
+        score += 7  # Extra points for hammer-like candles
+
+    # Bottom Tailing Wick: Long bottom wick compared to the overall range
+    if bottom_wick_length > 0.5 * (high_price - low_price):
+        score += 6  # Extra points for bottom tailing wick
+
+    # Additional logic: Boost red candles with long bottom wicks following a downtrend
+    if close_price < open_price and bottom_wick_length > 0.5 * (open_price - close_price):
+        score += 3  # Boost for red candle with long bottom wick
+
+    # Penalize if the current close is higher than the previous close
+    if close_price > prev_close:
+        score -= ((close_price - prev_close) / prev_close) * 100
+
+
+    return score
+
 def score_today_candle(data, window=4):
+    """Score today's candle based on the downtrend from the past 'window' days."""
     if len(data) < window + 1:
-        return 0
+        return 0  # Not enough data
+
+    today_candle = data.iloc[-1]
+    prev_candle = data.iloc[-2]
+    
+    close_price = today_candle['Close']
+
+
+    previous_data = data.iloc[-(window+1):-1]
+    down_High = average_downtrend(previous_data, method="High",window=window) + average_downtrend(previous_data, method="High",window=7) / 2
+    down_Close = average_downtrend(previous_data, method="Close",window=window) + average_downtrend(previous_data, method="Close",window=7) / 2
 
-    trend_score = score_downward_trend(data.iloc[-window:], window=window)
-    candle_score = score_candle(data.iloc[-1], data, len(data) - 1)
-    risk_reward = calculate_risk_reward(data, len(data) - 1)
 
-    # Combine scores (you can adjust the weights as needed)
-    total_score = trend_score + candle_score + (risk_reward * 10)
+    avg_downtrend = (down_High + down_Close) / 2
+  
+    if avg_downtrend == 0.0:
+        return -1
 
-    return total_score
+    # Calculate SMAs for the last row
+    sma_50 = calculate_sma(data, window=50).iloc[-1]
+    sma_200 = calculate_sma(data, window=200).iloc[-1]
+    sma_20 = calculate_sma(data, window=20).iloc[-1]
+    
+    ema_10 = calculate_ema(data, window=10).iloc[-1]
+    
+    if (close_price < ema_10) or (close_price < sma_20) or  (close_price < sma_50) or (close_price < sma_200):
+        return -1
+
+    
+    return score_candle(today_candle, prev_candle, abs(avg_downtrend))
 
 def scan_sp500(top_n=25, progress=gr.Progress()):
     tickers = load_sp500_tickers()
@@ -119,4 +178,4 @@ iface = gr.Interface(
 )
 
 if __name__ == "__main__":
-    iface.launch(server_name="0.0.0.0", server_port=7860)
+    iface.launch(server_name="0.0.0.0", server_port=7860)