def next(self):
if len(self.data.Volume) > LOOK_BACK:
prices = self.data.Close
# if np.datetime64(self.data.Date[-1]) == np.datetime64('2018-01-29T00:00:00.000000000'):
# t4 = jModel.isBearishEngulfing(self.data.Open, self.data.Close, self.data.High, self.data.Low, self.data.Body, self.data.Height, self.data.UpShadow, self.data.LowerShadow)
# print('today - isBearishEngulfing - ' + str(t4))
# exit()
the1stDayIsBlack = jModel.isBlackCandlestick(
self.data.Open[-3], self.data.Close[-3])
isDownTrend = jModel.isDownTrendV1(self.data.Open, self.data.Close,
self.data.High, self.data.Low,
self.data.Body,
self.data.Height,
self.data.UpShadow,
self.data.LowerShadow)
the2ndDayIsDoji = jModel.isDoji(self.data.Body[-2],
self.data.Height[-2])
todayIsShavenHead = jModel.isShavenHead(self.data.Height[-1],
self.data.UpShadow[-1])
todayIsWhite = jModel.isWhiteCandlestick(self.data.Open[-1],
self.data.Close[-1])
if isDownTrend is True and the2ndDayIsDoji is True and todayIsShavenHead is True and todayIsWhite is True:
hasBuySignal = True
else:
hasBuySignal = False
if hasBuySignal is not False:
self.buy(sl=0.9 * prices[-1], tp=1.2 * prices[-1])
# print(ticker_data)
# print(len(ticker_data.index))
# print(ticker_data[0:5])
# print(ticker_data.size)
# exit()
d2 = jModel.convertToJapanCandle(ticker_data)
for index, row in d2.iterrows():
# print(row['Open'])
# isHammer = jModel.isHammer(row['Open'], row['Close'], row['Body'], row['Height'], row['UpShadow'], row['LowerShadow'])
# if isHammer is True:
# print(index)
if np.datetime64(row['Date']) == np.datetime64('2019-01-04T00:00:00.000000000'):
isHammer = jModel.isDoji(row['Body'], row['Height'])
print(isHammer)
# last = 0
# np_ticker_data = ticker_data.to_numpy()
# data_len = len(ticker_data.index)
# for i in range(data_len):
# if i > 2:
# ii = i + 1
# data = ticker_data.head(ii)
# k = data.copy().tail(4)
# _4daysData = jModel.convertToJapanCandle(k)
# isHangingMan = jModel.isHangingMan(_4daysData)
# if isHangingMan is True:
# print(np_ticker_data[i])