def get_md_data(self, md_array):
# tranfer the string to float
# md_array[LASTPRICE] = float(md_array[LASTPRICE])
# md_array[VOLUME] = float(md_array[VOLUME])
# md_array[OPENINTEREST] = float(md_array[OPENINTEREST])
# md_array[TURNONER] = float(md_array[TURNONER])
# md_array[BIDPRICE1] = float(md_array[BIDPRICE1])
# md_array[ASKPRICE1] = float(md_array[ASKPRICE1])
self._pre_md_price = self._now_md_price
self._now_md_price = md_array
lastprice = self._now_md_price[LASTPRICE]
# self._lastprice_array.append(lastprice)
# print lastprice
if len(self._pre_md_price) == 0:
# "the is the first line data"
return
if self._pre_ema_val_60 == 0:
self._pre_ema_val_60 = lastprice
self._pre_ema_val_5 = lastprice
self._pre_ema_val_1 = lastprice
self._now_middle_60 = bf.get_ema_data(lastprice, self._pre_ema_val_60,
self._ema_period)
self._now_middle_5 = bf.get_ema_data(lastprice, self._pre_ema_val_5,
self._ema_period)
self._now_middle_1 = bf.get_ema_data(lastprice, self._pre_ema_val_1,
self._ema_period)
self._sd_val = bf.get_sd_data(lastprice, self._lastprice_array,
self._ema_period)
self._rsi_val = bf.get_rsi_data(lastprice, self._lastprice_array,
self._rsi_period)
# print len(self._lastprice_array)
hour = int(self._now_md_price[TIME].split(':')[0])
if hour != self._current_hour and hour != 13 and hour != 21:
# print "the hour is not equal "
self._current_hour = hour
self._pre_ema_val_60 = self._now_middle_60
self._lastprice_array.append(lastprice)
if self._now_ema_tick_1 >= self._limit_ema_tick_1:
self._now_ema_tick_1 = 0
self._pre_ema_val_1 = self._now_middle_1
else:
self._now_ema_tick_1 += 1
if self._now_ema_tick_5 >= self._limit_ema_tick_5:
self._now_ema_tick_5 = 0
self._pre_ema_val_5 = self._now_middle_5
else:
self._now_ema_tick_5 += 1
diff_volume = self._now_md_price[VOLUME] - self._pre_md_price[VOLUME]
diff_interest = self._now_md_price[OPENINTEREST] - self._pre_md_price[
OPENINTEREST]
diff_turnover = self._now_md_price[TURNONER] - self._pre_md_price[
TURNONER]
if diff_volume != 0 and (self._pre_md_price[ASKPRICE1] -
self._pre_md_price[BIDPRICE1]) != 0:
avg_price = float(diff_turnover) / diff_volume / self._multiple
spread = 100 * (avg_price - self._pre_md_price[BIDPRICE1]) / (
self._pre_md_price[ASKPRICE1] - self._pre_md_price[BIDPRICE1])
else:
spread = 50
tmp_to_csv = [
self._now_md_price[TIME], self._now_md_price[LASTPRICE],
round(self._now_middle_60, 2),
round(self._now_middle_5, 2),
round(self._now_middle_1, 2),
round(self._sd_val, 2),
round(self._rsi_val, 2),
round(diff_volume, 2),
round(spread, 2)
]
# print tmp_to_csv
self._write_to_csv_data.append(tmp_to_csv)
return True
def get_md_data(self,md_array): # tranfer the string to float md_array[LASTPRICE] = float(md_array[LASTPRICE]) md_array[VOLUME] = float(md_array[VOLUME]) md_array[OPENINTEREST] = float(md_array[OPENINTEREST]) md_array[TURNONER] = float(md_array[TURNONER]) md_array[BIDPRICE1] = float(md_array[BIDPRICE1]) md_array[ASKPRICE1] = float(md_array[ASKPRICE1]) self._pre_md_price = self._now_md_price self._now_md_price = md_array lastprice = self._now_md_price[LASTPRICE] # print lastprice if len(self._pre_md_price) ==0: return # self._rsi_array.append(0) else: # self._rsi_array.append(lastprice - self._pre_md_price[LASTPRICE]) if self._now_bar_rsi_tick >= self._rsi_bar_period: # 表示已经到了一个bar的周期。 tmpdiff = lastprice - self._pre_rsi_lastprice self._pre_rsi_lastprice = lastprice self._now_bar_rsi_tick = 1 self._ris_data =bf.get_rsi_data(tmpdiff,self._rsi_array,self._rsi_period) self._rsi_array.append(tmpdiff) else: self._now_bar_rsi_tick +=1 tmpdiff = lastprice - self._pre_rsi_lastprice self._ris_data =bf.get_rsi_data(tmpdiff,self._rsi_array,self._rsi_period) # self._ris_data = 0 if len(self._lastprice_array) < self._param_period: self._lastprice_array.append(lastprice) # this is we dont start the period. ema_period = len(self._lastprice_array) pre_ema_val = bf.get_ema_data(lastprice,self._pre_ema_val,ema_period) self._pre_ema_val = pre_ema_val # save the pre_ema_val and return if lastprice not in self._lastprice_map: self._lastprice_map[lastprice] =1 else: self._lastprice_map[lastprice] +=1 return True else: self._lastprice_array.append(lastprice) front_lastprice = self._lastprice_array[0] self._lastprice_array.pop(0) if front_lastprice != lastprice: if lastprice not in self._lastprice_map : self._lastprice_map[lastprice] = 1 else: self._lastprice_map[lastprice] +=1 self._lastprice_map[front_lastprice] -=1 # start the judge if self._moving_theo =="EMA": self._now_middle_value = bf.get_ema_data(lastprice,self._pre_ema_val,self._param_period) self._pre_ema_val = self._now_middle_value else: self._now_middle_value = bf.get_ma_data(self._lastprice_array,self._param_period) self._now_sd_val =bf.get_sd_data_by_map(self._lastprice_map,self._param_period) # self.f.write(str(self._now_md_price[TIME])+","+str(lastprice)+","+str(self._now_middle_value)+","+str(self._now_sd_val)+","+str(self._ris_data)+"\n") if self._now_md_price[LASTPRICE] > self._pre_md_price[LASTPRICE]: if self._series_lastprice >=0: self._series_lastprice +=1 else: self._series_lastprice = 0 elif self._now_md_price[LASTPRICE] < self._pre_md_price[LASTPRICE]: if self._series_lastprice <=0: self._series_lastprice -=1 else: self._series_lastprice =0 else: if self._series_lastprice >0: self._series_lastprice +=1 elif self._series_lastprice <0: self._series_lastprice -=1 else: self._series_lastprice =0 # if self._direction ==LONG: # if self._now_md_price[LASTPRICE] >= self._pre_md_price[LASTPRICE]: # self._series_lastprice = self._series_lastprice +1 # else: # self._series_lastprice = 0 # elif self._direction ==SHORT: # if self._now_md_price[LASTPRICE] <= self._pre_md_price[LASTPRICE]: # self._series_lastprice = self._series_lastprice +1 # else: # self._series_lastprice = 0 # else: # return diff_volume = self._now_md_price[VOLUME] - self._pre_md_price[VOLUME] self._tmp_sum_diff_volume += diff_volume self._now_bar_volume_tick +=1 if self._now_bar_volume_tick >= self._limit_bar_volume_tick: self._diff_volume_array.append(self._tmp_sum_diff_volume) self._tmp_sum_diff_volume = 0 self._now_bar_volume_tick = 0 open_time = self.is_trend_open_time() close_time = self.is_trend_close_time() # close_time = False if open_time and self._now_interest < self._limit_interest: # if open_time: self._now_interest +=1 # print "we start to open" self._open_lastprice = self._now_md_price[LASTPRICE] self._max_profit = 0 mesg= "the time of open: "+self._now_md_price[TIME] + ",the price: " + str(self._now_md_price[LASTPRICE]) # mesg1 = "the diff volume: "+str(ema_diff_volume)+", the interest: " + str(ema_diff_openinerest) + ", the spread: "+ str(ema_spread) self._file.write(mesg+"\n") # self._file.write(mesg1+"\n") # print "the diff volume is:" + str(self._now_md_price[VOLUME] - self._pre_md_price[VOLUME]) # elif close_time: elif close_time and self._now_interest >0: self._now_interest -=1 # print "we need to close" if self._direction ==LONG: self._profit +=(self._now_md_price[LASTPRICE] - self._open_lastprice) elif self._direction ==SHORT: self._profit +=(self._open_lastprice - self._now_md_price[LASTPRICE]) self._open_lastprice = 0 self._max_profit = 0 mesg= "the time of close:"+self._now_md_price[TIME] + ",the price: " + str(self._now_md_price[LASTPRICE]) self._file.write(mesg+"\n") return True
def get_md_data(self,md_array): # tranfer the string to float md_array[LASTPRICE] = float(md_array[LASTPRICE]) md_array[VOLUME] = float(md_array[VOLUME]) md_array[OPENINTEREST] = float(md_array[OPENINTEREST]) md_array[TURNONER] = float(md_array[TURNONER]) md_array[BIDPRICE1] = float(md_array[BIDPRICE1]) md_array[ASKPRICE1] = float(md_array[ASKPRICE1]) self._pre_md_price = self._now_md_price self._now_md_price = md_array lastprice = self._now_md_price[LASTPRICE] # self._lastprice_array.append(lastprice) # print lastprice if len(self._pre_md_price) ==0: # "the is the first line data" return # self._rsi_array.append(lastprice - self._pre_md_price[LASTPRICE]) if self._now_bar_rsi_tick >= self._rsi_bar_period: # 表示已经到了一个bar的周期。 tmpdiff = lastprice - self._pre_rsi_lastprice self._pre_rsi_lastprice = lastprice self._now_bar_rsi_tick = 1 self._ris_data =bf.get_rsi_data(tmpdiff,self._rsi_array,self._rsi_period) self._rsi_array.append(tmpdiff) else: self._now_bar_rsi_tick +=1 tmpdiff = lastprice - self._pre_rsi_lastprice self._ris_data =bf.get_rsi_data(tmpdiff,self._rsi_array,self._rsi_period) # self._ris_data = 0 self._lastprice_array.append(lastprice) if len(self._lastprice_array) <= self._param_period: # this is we dont start the period. # print "the lastprice length is small: " +str(len(self._lastprice_array)) ema_period = len(self._lastprice_array) pre_ema_val = bf.get_ema_data(lastprice,self._pre_ema_val,ema_period) self._pre_ema_val = pre_ema_val # save the pre_ema_val and return if lastprice not in self._lastprice_map: self._lastprice_map[lastprice] =1 else: self._lastprice_map[lastprice] +=1 return True front_lastprice = self._lastprice_array[0] self._lastprice_array.pop(0) if front_lastprice != lastprice: if lastprice not in self._lastprice_map : self._lastprice_map[lastprice] = 1 else: self._lastprice_map[lastprice] +=1 self._lastprice_map[front_lastprice] -=1 # start the judge if self._moving_theo =="EMA": self._now_middle_value = bf.get_ema_data(lastprice,self._pre_ema_val,self._param_period) self._pre_ema_val = self._now_middle_value else: self._now_middle_value = bf.get_ma_data(self._lastprice_array,self._param_period) self._now_sd_val =bf.get_sd_data_by_map(self._lastprice_map,self._param_period) diff_volume = self._now_md_price[VOLUME] - self._pre_md_price[VOLUME] diff_interest = self._now_md_price[OPENINTEREST] - self._pre_md_price[OPENINTEREST] diff_turnover = self._now_md_price[TURNONER] - self._pre_md_price[TURNONER] if diff_volume != 0 and (self._pre_md_price[ASKPRICE1] - self._pre_md_price[BIDPRICE1]) !=0: avg_price = float(diff_turnover)/diff_volume/self._multiple spread = 100*(avg_price - self._pre_md_price[BIDPRICE1])/(self._pre_md_price[ASKPRICE1] - self._pre_md_price[BIDPRICE1]) else: spread = 50 tmp_to_csv = [self._now_md_price[TIME],self._now_md_price[LASTPRICE], round(self._now_middle_value,2),round(self._now_sd_val,2), round(self._ris_data,2), round(diff_volume,2),round(diff_interest,2),round(spread,2)] # print tmp_to_csv self._write_to_csv_data.append(tmp_to_csv) return True
