def boll_df(cls, date, ifcode, period_short, period_long, pre_point):
data = BacktestData.get_data_by_ifcode(date, ifcode)
if not data:
return pd.DataFrame()
_df = pd.DataFrame(data, columns=['time_index', 'price', 'volume'])
df = point_prosess(_df, pre_point)
price_list = list(df['price'])
df['boll_mb'] = Indicator.ma_metric(period_short, price_list)
mb_list = list(df['boll_mb'])
df['boll_md'] = Indicator.boll_md_metric(period_long, mb_list)
df['boll_up'] = df['boll_mb'] + 2.0 * df['boll_md']
df['boll_dn'] = df['boll_mb'] - 2.0 * df['boll_md']
return df
def boll_chart(cls,
date,
ifcode,
period_short=50,
period_long=80,
offset=10):
df_list = realtime_data(date, ifcode)
df = pd.DataFrame(df_list, columns=['time_index', 'price', 'volume'])
boll_df = point_prosess(df, offset)
price_list = list(boll_df['price'])
boll_df['boll_mb'] = Indicator.ma_metric(period_short, price_list)
mb_list = list(boll_df['boll_mb'])
boll_df['boll_md'] = Indicator.boll_md_metric(period_long, mb_list)
boll_df['boll_up'] = boll_df['boll_mb'] + 2.0 * boll_df['boll_md']
boll_df['boll_dn'] = boll_df['boll_mb'] - 2.0 * boll_df['boll_md']
price = boll_df[['time_index', 'price']].values.tolist()
boll_up = boll_df[['time_index', 'boll_up']].values.tolist()
boll_dn = boll_df[['time_index', 'boll_dn']].values.tolist()
boll_mb = boll_df[['time_index', 'boll_mb']].values.tolist()
return price, boll_up, boll_dn, boll_mb