def save_df(df_list, ifcode, today, period_short, period_long):
df = pd.DataFrame(df_list, columns=['time_index', 'price', 'volume'])
price = list(df['price'])
df['ema_short'] = Indicator.ema_metric(period_short, price)
df['ema_long'] = Indicator.ema_metric(period_long, price)
#macd
macd_df = point_prosess_v3(df, 8)
macd_df['ma_short'] = Indicator.ewma_metric(12, macd_df[['price']], 'price', False)
macd_df['ma_long'] = Indicator.ewma_metric(26, macd_df[['price']], 'price', False)
macd_df['macd_dif'] = macd_df['ma_short'] - macd_df['ma_long']
macd_dif = list(macd_df['macd_dif'])
macd_df['macd_dem'] = Indicator.ewma_metric(9, macd_df[['macd_dif']], 'macd_dif')
_macd_file = '%s/%s_%s_macd' % (validate_df_dir, ifcode, today)
macd_df.to_csv(_macd_file, index=False)
sig_infos = PushSellSignal.compare_sig(macd_df, 'macd_dif', 'macd_dem', 16)
profit_infos = PushSellSignal.profit_infos(sig_infos)
print '*******macd******'
print profit_infos
print len(profit_infos)
_file = '%s/%s_%s' % (validate_df_dir, ifcode, today)
df.to_csv(_file, index=False)
sig_infos = PushSellSignal.compare_sig(df, 'ema_short', 'ema_long')
profit_infos = PushSellSignal.profit_infos(sig_infos)
print '*******ema*******'
print profit_infos
print len(profit_infos)
def push_signal(df_list, code, ifcode, today, period_short, period_long):
df = pd.DataFrame(df_list, columns=['time_index', 'price', 'volume'])
price = list(df['price'])
df['ema_short'] = Indicator.ema_metric(period_short, price)
df['ema_long'] = Indicator.ema_metric(period_long, price)
sig_infos = PushSellSignal.compare_ema(df)
profit_infos = PushSellSignal.profit_infos(sig_infos)
if is_push(profit_infos, ifcode, today):
if len(profit_infos) == 1:
print '*' * 20
print 'init message~!'
time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
info_dict = profit_infos[0]
theevent = info_dict.get('event', '')
is_success = 'failed'
#添加交易接口
if theevent == '卖出信号':
trans_session = yinhe_trans()
r = trans_short_start(trans_session, code, ifcode)
if 'error_info' not in r:
is_success = '交易成功'
elif theevent == '买入信号':
trans_session = yinhe_trans()
r = trans_long_start(trans_session, code, ifcode)
if 'error_info' not in r:
is_success = '交易成功'
tip = 'ema 策略: \n%s, 交易价格: %s; 时间: %s; %s' % (
theevent, info_dict.get('price', 0), time_str, is_success)
push_sig(tip)
elif len(profit_infos) >= 2:
print '*' * 20
print 'push message~!'
time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
info_dict_1 = profit_infos[-2]
info_dict_2 = profit_infos[-1]
_p = info_dict_2.get('price', 0)
trading_fee = cal_fee(_p)
_g = info_dict_1.get('gain', 0)
gain = _g - trading_fee
theevent = info_dict_2.get('event', '')
is_success = 'failed'
#添加交易接口
if theevent == '卖出信号':
trans_session = yinhe_trans()
r1 = trans_short_close(trans_session, code, ifcode)
r2 = trans_short_start(trans_session, code, ifcode)
if 'error_info' not in r1 and 'error_info' not in r2:
is_success = '交易成功'
elif theevent == '买入信号':
trans_session = yinhe_trans()
r1 = trans_long_close(trans_session, code, ifcode)
r2 = trans_long_start(trans_session, code, ifcode)
if 'error_info' not in r1 and 'error_info' not in r2:
is_success = '交易成功'
tip = 'ema 策略: \n%s, 盈利: %s, 实际盈利: %s, 交易费用: %s; \n%s, 交易价格: %s; 时间: %s; %s' % (
info_dict_1.get('event', ''), _g, gain, trading_fee,
info_dict_2.get('event', ''), _p, time_str, is_success)
push_sig(tip)
def ema_df(cls, date, ifcode, period_short, period_long):
data = BacktestData.get_data_by_ifcode(date, ifcode)
if not data:
return pd.DataFrame()
df = pd.DataFrame(data, columns=['time_index', 'price', 'volume'])
price = list(df['price'])
df['ema_short'] = Indicator.ema_metric(period_short, price)
df['ema_long'] = Indicator.ema_metric(period_long, price)
return df
def ema_chart(cls, date, ifcode, period_short, period_long):
_file = '%s/%s_%s_%s_%s' % (ema_file_dir, date, ifcode, period_short,
period_long)
if os.path.isfile(_file):
df = read_df(_file)
else:
data = BacktestData.get_data_by_ifcode(date, ifcode)
df = pd.DataFrame(data, columns=['time_index', 'price', 'volume'])
price = list(df['price'])
df['ema_short'] = Indicator.ema_metric(period_short, price)
df['ema_long'] = Indicator.ema_metric(period_long, price)
price = df[['time_index', 'price']].values.tolist()
ema_short = df[['time_index', 'ema_short']].values.tolist()
ema_long = df[['time_index', 'ema_long']].values.tolist()
volume = df[['time_index', 'volume']].values.tolist()
return [price, ema_short, ema_long, volume]