init

hts/Simulation.py

@@ -1,16 +1,16 @@
 import os
-from datetime import datetime, timedelta
+from datetime import datetime
 import pandas as pd
 import plotly.graph_objects as go
 from plotly import subplots
 
-from BS import BS
+from BuySellChecker import BuySellChecker
 
 class Simulation:
 
-    bs = None
+    buySellChecker = None
     def __init__(self):
-        self.bs = BS()
+        self.buySellChecker = BuySellChecker()
         #self.connect()
         return
 
@@ -50,7 +50,7 @@ class Simulation:
         bsLine['sell'] = [-1 for i in range(size)]
 
         for i in range(6, size-5):
-            buy, weight, sell = self.bs.getPriceAndWeight1(data, i)
+            buy, weight, sell = self.buySellChecker.getPriceAndWeight1(data, i)
             bsLine['buy'][i] = buy
             bsLine['weight'][i] = weight
             bsLine['sell'][i] = sell
@@ -97,6 +97,7 @@ class Simulation:
         avg5 = go.Scatter(x=data['Date'], y=data["avg5"], name="avg5", line_color='#000000')
 
         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')
         fast_k_line = go.Scatter(x=data['Date'], y=data["fast_k"], mode='lines', name='fast_k')
         slow_k_line = go.Scatter(x=data['Date'], y=data["slow_k"], mode='lines', name='slow_k')
         slow_d_line = go.Scatter(x=data['Date'], y=data["slow_d"], mode='lines', name='slow_d')
@@ -105,6 +106,7 @@ class Simulation:
 
         #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, avg5, buy_check, sell_check]
+        volume_data = [volume_line]
         stochastic_data = [slow_k_line, slow_d_line]
         rsi_data = [rsi_line, rsis_line]
 
@@ -115,13 +117,15 @@ class Simulation:
         fig.show()
         """
 
-        fig = subplots.make_subplots(rows=3, cols=1, subplot_titles=('캔들', "스토캐스틱", "RSI"))
+        fig = subplots.make_subplots(rows=4, cols=1, subplot_titles=('캔들', "거래량", "스토캐스틱", "RSI"))
         for trace in candle_data:
             fig.append_trace(trace, 1, 1)
-        for trace in stochastic_data:
+        for trace in volume_data:
             fig.append_trace(trace, 2, 1)
-        for trace in rsi_data:
+        for trace in stochastic_data:
             fig.append_trace(trace, 3, 1)
+        for trace in rsi_data:
+            fig.append_trace(trace, 4, 1)
         #fig.update_xaxes(nticks=5)
         #fig.update_layout(height=1800, title=stock_code + "_" + given_day, xaxis_rangeslider_visible=False)
         fig.update_layout(height=1800, title=stock_code + "_" + given_day)
@@ -142,7 +146,7 @@ class Simulation:
         self.getCSV("./data/"+stock_code+"_"+given_day+".csv", given_day, result)
 
         # 분석을 통해서 볼린저밴드 상/하단을 계산한다.
-        data = self.bs.analyze(result)
+        data = self.buySellChecker.analyze(result)
 
         # 사야 할 시점과 팔아야 할 시점을 체크한다.
         bsLine = self.checkTransaction(data)