init

2022-05-20 15:52:09 +09:00
parent 7e55d4d696
commit 35a9ad4dbc
2 changed files with 27 additions and 41 deletions
--- a/hts/BuySellChecker.py
+++ b/hts/BuySellChecker.py
@@ -369,13 +369,6 @@ class BuySellChecker:


    def analyze(self, result):
-        df = pd.DataFrame(result["close"])
-
-        max20 = df.rolling(window=10).mean()
-        stddev20 = df.rolling(window=10).std()
-        upper_df = max20 + (stddev20 * 2)                  # 상단 볼린저 밴드
-        lower_df = max20 - (stddev20 * 2)                  # 하단 볼린저 밴드
-
        window = 5
        open = result["open"]
        close = result["close"]
@@ -383,31 +376,27 @@ class BuySellChecker:
        low = result["low"]
        vol = result["vol"]

-        close_df = pd.DataFrame(close)
-        avg1_list = close_df.rolling(window=1).mean().fillna(close[0]).values.tolist()
-        avg1 = [item[0] for item in avg1_list]
-        avg2_list = close_df.rolling(window=2).mean().fillna(close[0]).values.tolist()
-        avg2 = [item[0] for item in avg2_list]
-        avg3_list = close_df.rolling(window=3).mean().fillna(close[0]).values.tolist()
-        avg3 = [item[0] for item in avg3_list]
-        avg5_list = close_df.rolling(window=5).mean().fillna(close[0]).values.tolist()
+        open_list = open[:-window+1]
+        close_list = close[window-1:]
+        high_list = [max(high[i + window - 1:i + 2 * window - 1]) for i in range(len(high) - window + 1)]
+        low_list = [min(low[i + window - 1:i + 2 * window - 1]) for i in range(len(low) - window + 1)]
+        vol_list = [sum(vol[i + window - 1:i + 2 * window - 1]) for i in range(len(vol) - window + 1)]
+
+        close_df = pd.DataFrame(close_list)
+        avg5_list = close_df.rolling(window=5).mean().fillna(close_list[0]).values.tolist()
        avg5 = [item[0] for item in avg5_list]
-        avg10_list = close_df.rolling(window=10).mean().fillna(close[0]).values.tolist()
+        avg10_list = close_df.rolling(window=10).mean().fillna(close_list[0]).values.tolist()
        avg10 = [item[0] for item in avg10_list]
-        avg20_list = close_df.rolling(window=20).mean().fillna(close[0]).values.tolist()
-        avg20 = [item[0] for item in avg20_list]
-        avg30_list = close_df.rolling(window=30).mean().fillna(close[0]).values.tolist()
+        avg30_list = close_df.rolling(window=30).mean().fillna(close_list[0]).values.tolist()
        avg30 = [item[0] for item in avg30_list]
-        avg40_list = close_df.rolling(window=40).mean().fillna(close[0]).values.tolist()
-        avg40 = [item[0] for item in avg40_list]
-        avg50_list = close_df.rolling(window=50).mean().fillna(close[0]).values.tolist()
-        avg50 = [item[0] for item in avg50_list]
-        avg60_list = close_df.rolling(window=60).mean().fillna(close[0]).values.tolist()
+        avg60_list = close_df.rolling(window=60).mean().fillna(close_list[0]).values.tolist()
        avg60 = [item[0] for item in avg60_list]
-        avg120_list = close_df.rolling(window=120).mean().fillna(close[0]).values.tolist()
-        avg120 = [item[0] for item in avg120_list]
-        avg240_list = close_df.rolling(window=240).mean().fillna(close[0]).values.tolist()
-        avg240 = [item[0] for item in avg240_list]
+
+        df = pd.DataFrame(close_list)
+        max20 = df.rolling(window=10).mean()
+        stddev20 = df.rolling(window=10).std()
+        upper_df = max20 + (stddev20 * 2) # 상단 볼린저 밴드
+        lower_df = max20 - (stddev20 * 2) # 하단 볼린저 밴드

        upper, lower = [], []
        for i in range(len(upper_df)):
@@ -421,10 +410,9 @@ class BuySellChecker:
        point_temp = result["time"]

        STOCK = []
-        for i in range(len(result["open"])):
-            STOCK.append({'volume': vol[i], 'close': close[i], 'open': open[i], 'high': high[i], 'low': low[i],
-                          'avg1': avg1[i],'avg2': avg2[i],'avg3': avg3[i],'avg5': avg5[i],'avg10': avg10[i],
-                          'avg20': avg20[i], 'avg60': avg60[i], 'avg120': avg120[i],'avg240': avg240[i]})
+        for i in range(len(open_list)):
+            STOCK.append({'volume': vol_list[i], 'close': close_list[i], 'open': open_list[i], 'high': high_list[i], 'low': low_list[i],
+                          'avg5': avg5[i],'avg10': avg10[i],'avg30': avg30[i],'avg60': avg60[i]})

        # stochastic 계산
        stochastic_df = self.stochastic.apply(STOCK, n=12, m=5, t=5)
@@ -439,12 +427,12 @@ class BuySellChecker:
        rsi = rsi_df['rsi'].values.tolist()
        rsis = rsi_df['rsis'].values.tolist()

-        temp = {"date": point_temp,
-                "open": open, "high": high, "low": low, "close": close, "volume": vol, "upper": upper, "lower": lower,
-                "avg1": avg1, "avg2": avg2, "avg3": avg3, "avg5": avg5, "avg10": avg10, "avg20": avg20, "avg30": avg30, "avg40": avg40, "avg50": avg50, "avg60": avg60, "avg120": avg120, "avg240": avg240,
+        temp = {"date": point_temp[:-window+1],
+                "open": open_list, "high": high_list, "low": low_list, "close": close_list, "volume": vol_list, "upper": upper, "lower": lower,
+                "avg5": avg5, "avg10": avg10, "avg30": avg30, "avg60": avg60,
                "fast_k": fast_k, "slow_k": slow_k, "slow_d": slow_d, "rsi": rsi, "rsis": rsis}
        data = pd.DataFrame(temp)
-        df_final_time = pd.DatetimeIndex(point_temp)
+        df_final_time = pd.DatetimeIndex(point_temp[:-window+1])
        data.index = df_final_time

        return data
--- a/hts/Simulation.py
+++ b/hts/Simulation.py
@@ -101,12 +101,10 @@ class Simulation:
        sell_check = go.Scatter(x=data['date'], y=sell_line, mode='markers', name="sell", marker=dict(size=14, color=sell_colors, line_width=0))
        bolinger_upper = go.Scatter(x=data['date'], y=data["upper"], name="upper", line_color='#8B4513')
        bolinger_lower = go.Scatter(x=data['date'], y=data["lower"], name="lower", line_color='#8B4513')
-        avg2 = go.Scatter(x=data['date'], y=data["avg2"], name="avg2", line_color='#000000')
-        avg3 = go.Scatter(x=data['date'], y=data["avg3"], name="avg3", line_color='#c0c0c0')
        avg5 = go.Scatter(x=data['date'], y=data["avg5"], name="avg5", line_color='#800080')
        avg10 = go.Scatter(x=data['date'], y=data["avg10"], name="avg10", line_color='#ff00ff')
-        avg20 = go.Scatter(x=data['date'], y=data["avg20"], name="avg20", line_color='#00ffff')
-        avg30 = go.Scatter(x=data['date'], y=data["avg30"], name="avg30", line_color='#008000')
+        avg30 = go.Scatter(x=data['date'], y=data["avg30"], name="avg30", line_color='#00ffff')
+        avg60 = go.Scatter(x=data['date'], y=data["avg60"], name="avg60", line_color='#008000')

        candle_stick = go.Candlestick(x=data['date'], open=data['open'], high=data['high'], low=data['low'], close=data['close'], increasing_line_color='red', decreasing_line_color='blue')
        volume_line = go.Scatter(x=data['date'], y=data["volume"], mode='lines', name='volume')
@@ -117,7 +115,7 @@ class Simulation:
        rsis_line = go.Scatter(x=data['date'], y=data["rsis"], mode='lines', name='rsis')

        #candle_data = [candle_stick, bolinger_upper, bolinger_lower, buy_check, sell_check, avg1, avg2, avg5, avg10, avg20, avg30, avg40, avg50, avg60]
-        candle_data = [candle_stick, bolinger_upper, bolinger_lower, avg2, avg3, avg5, avg10, buy_check, sell_check]
+        candle_data = [candle_stick, bolinger_upper, bolinger_lower, avg5, avg10, avg30, avg60, buy_check, sell_check]
        volume_data = [volume_line]
        stochastic_data = [slow_k_line, slow_d_line]
        rsi_data = [rsi_line, rsis_line]