"""
Broker 经济人，负责处理处理撮合交易订单等功能.
微信：bitquant51
火币交易所推荐码：asd43
币安推荐码: 22795115
币安推荐链接：https://www.binance.co/?ref=22795115
Gateio交易所荐码：1100714
Bitmex交易所推荐码：SzZBil 或者 https://www.bitmex.com/register/SzZBil
代码地址： https://github.com/ramoslin02/51bitqunt
视频更新：首先在Youtube上更新，搜索51bitquant 关注我
B站视频：
"""
import numpy as np
import talib
from .data import BarData
class ArrayManager(object):
"""
For:
1. time series container of bar data
2. calculating technical indicator value
"""
def __init__(self, size=500):
"""Constructor"""
self.count = 0
self.size = size
self.inited = False
self.open_array = np.zeros(size)
self.high_array = np.zeros(size)
self.low_array = np.zeros(size)
self.close_array = np.zeros(size)
self.volume_array = np.zeros(size)
def update_bar(self, bar: BarData):
"""
Update new bar data into array manager.
"""
self.count += 1
if not self.inited and self.count >= self.size:
self.inited = True
# [1,2,3,4,5,6,7,8,9,10]
# [1,2,3,4,5,6,7,8,9] = [2,3,4,5,6,7,8,9,10]
# [2,3,4,5,6,7,8,9,10, 10]
self.open_array[:-1] = self.open_array[1:]
self.high_array[:-1] = self.high_array[1:]
self.low_array[:-1] = self.low_array[1:]
self.close_array[:-1] = self.close_array[1:]
self.volume_array[:-1] = self.volume_array[1:]
# [2,3,4,5,6,7,8,9,10, 10] 然后最后一个数字被替换了.
self.open_array[-1] = bar.open_price
self.high_array[-1] = bar.high_price
self.low_array[-1] = bar.low_price
self.close_array[-1] = bar.close_price
self.volume_array[-1] = bar.volume
@property
def open(self):
"""
Get open price time series.
"""
return self.open_array
@property
def high(self):
"""
Get high price time series.
"""
return self.high_array
@property
def low(self):
"""
Get low price time series.
"""
return self.low_array
@property
def close(self):
"""
Get close price time series.
"""
return self.close_array
@property
def volume(self):
"""
Get trading volume time series.
"""
return self.volume_array
def sma(self, n, array=False):
"""
Simple moving average.
"""
result = talib.SMA(self.close, n)
if array:
return result
return result[-1]
def std(self, n, array=False):
"""
Standard deviation
"""
result = talib.STDDEV(self.close, n)
if array:
return result
return result[-1]
def cci(self, n, array=False):
"""
Commodity Channel Index (CCI).
"""
result = talib.CCI(self.high, self.low, self.close, n)
if array:
return result
return result[-1]
def atr(self, n, array=False):
"""
Average True Range (ATR).
"""
result = talib.ATR(self.high, self.low, self.close, n)
if array:
return result
return result[-1]
def rsi(self, n, array=False):
"""
Relative Strenght Index (RSI).
"""
result = talib.RSI(self.close, n)
if array:
return result
return result[-1]
def macd(self, fast_period, slow_period, signal_period, array=False):
"""
MACD.
"""
macd, signal, hist = talib.MACD(
self.close, fast_period, slow_period, signal_period
)
if array:
return macd, signal, hist
return macd[-1], signal[-1], hist[-1]
def adx(self, n, array=False):
"""
ADX.
"""
result = talib.ADX(self.high, self.low, self.close, n)
if array:
return result
return result[-1]
def boll(self, n, dev, array=False):
"""
Bollinger Channel.
"""
mid = self.sma(n, array)
std = self.std(n, array)
up = mid + std * dev
down = mid - std * dev
return up, down
def keltner(self, n, dev, array=False):
"""
Keltner Channel.
"""
mid = self.sma(n, array)
atr = self.atr(n, array)
up = mid + atr * dev
down = mid - atr * dev
return up, down
def donchian(self, n, array=False):
"""
Donchian Channel.
"""
up = talib.MAX(self.high, n)
down = talib.MIN(self.low, n)
if array:
return up, down
return up[-1], down[-1]
