import pandas as pd
from stockpredictor.analysis.Common import Common
import plotly.graph_objs as go
from plotly import tools, subplots
import plotly.io as po

class BolingerBand:

    common = None

    def __init__(self):
        self.common = Common()
        return

    def apply(self, df, n=10, m=6, t=6):
        # 입력받은 값이 dataframe이라는 것을 정의해줌
        df = pd.DataFrame(df)

        max20 = df["close"].rolling(window=20).mean()
        stddev = df["close"].rolling(window=20).std()
        upper = max20 + (stddev * 2) # 상단 볼리저 밴드
        lower = max20 - (stddev * 2) # 하단 볼리저 밴드
        middle = (upper + lower ) / 2

        # dataframe에 컬럼 추가
        #df = df.assign(fast_k=fast_k, slow_k=slow_k, slow_d=slow_d).dropna()
        df = df.assign(upper=upper, middle=middle, lower=lower)

        return df

    def analyze(self, stock):
        df = pd.DataFrame()
        df = df.from_dict(stock['PRICE'])
        df = self.apply(df)

        for i in range(len(df.upper)):
            stock['PRICE'][i]['upper'] = df.upper.values[i]
            stock['PRICE'][i]['middle'] = df.middle.values[i]
            stock['PRICE'][i]['lower'] = df.lower.values[i]

            # 0: 중립, 1: 매수, -1: 매도
            stock['PRICE'][i]['bolingerband_buy'] = 0

            if i > 0:
                stock['PRICE'][i]['bolingerband_buy'] = self.common.getBolingerBandScore(stock['PRICE'], i)

        results = []
        for day in stock['PRICE']:
            results.append({'DATE': day['DATE'],
                            'upper': day['upper'],
                            'middle': day['middle'],
                            'lower': day['lower'],
                            'bolingerband_buy': day['bolingerband_buy']})
        return results