init

stockpredictor/analysis/IchimokuCloud.py

@@ -1,9 +1,4 @@
 import pandas as pd
-import datetime
-from plotly import tools, subplots
-import plotly.offline as offline
-import plotly.graph_objs as go
-import plotly.io as po
 
 from stockpredictor.analysis.Common import Common
 
@@ -18,28 +13,6 @@ class IchimokuCloud:
         self.common = Common()
         return
 
-    def draw(self, stock):
-        item_name = stock["NAME"]
-        item_code = stock["CODE"]
-
-        df = pd.DataFrame(stock["PRICE"])
-        leadingSpan1 = go.Scatter(x=df.DATE, y=df['leadingSpan1'], name="선행스팬1", line_color='#8B4513')
-        leadingSpan2 = go.Scatter(x=df.DATE, y=df['leadingSpan2'], name="선행스팬2", line_color='#4169E1')
-        candle = go.Candlestick(x=df.DATE, open=df.open, high=df.high, low=df.low, close=df.close, increasing_line_color= 'red', decreasing_line_color= 'blue')
-        data = [leadingSpan1, leadingSpan2, candle]
-
-        layout = go.Layout(title='{} MACD 그래프'.format(item_name))
-        fig = subplots.make_subplots(rows=1, cols=1, shared_xaxes=True)
-
-        for trace in data:
-            fig.append_trace(trace, 1,1)
-
-        fig = go.Figure(data=data, layout=layout)
-
-        path = "/Users/dsyoon/workspace/StockPredictor/resources/analysis/html"
-        po.write_html(fig, file=path + "/ichimokuCloud_" + item_code+'.html', auto_open=False)
-        return fig
-
     # c=9, b=26, l=52
     def apply(self, df, c=9, b=26, l=52):
         # 입력받은 값이 dataframe이라는 것을 정의해줌