optstrategy

[adairhmj]

When I change the add policy to traversal parameter and add def stop, the error comes
I'm a novice. Please help me!

import backtrader as bt
import os
import sys
import datetime
import pandas as pd
import optunity.metrics
'''Data Feeds（数据加载）、Indicators（技术指标）和Strategies（策略）都会生成 Lines。'''
class DT_Line(bt.Indicator): # bt.SignalStrategy bt.indicators

lines = ('U', 'D')  # u-up最高价 D-down最低价
params = (('period', 2), ('k_u', 0.7), ('k_d', 0.7))  # params简写 .p


def __init__(self):

    self.addminperiod(self.p.period + 1)


def next(self):

    HH = max(self.data.high.get(-1, size=self.p.period))
    LC = min(self.data.close.get(-1, size=self.p.period))
    HC = max(self.data.close.get(-1, size=self.p.period))
    LL = min(self.data.low.get(-1, size=self.p.period))
    R = max(HH-LC, HC-LL)

    self.lines.U[0] = self.data.open[0] + self.p.k_u * R
    self.lines.D[0] = self.data.open[0] - self.p.k_u * R

class DualThrust(bt.SignalStrategy):

def __init__(self):
    self.dataclose = self.data0.close
    self.D_Line = DT_Line(self.data1)


    self.D_Line = self.D_Line()
    self.D_Line.plotinfo.plot = True
    self.D_Line.plotinfo.plotmaster = self.data0 #  把图移到主图

    self.buy_signal = bt.indicators.CrossOver(self.dataclose, self.D_Line.U)
    self.sell_signal = bt.indicators.CrossDown(self.dataclose, self.D_Line.D)

def start(self):
    print('这是start')

def prenext(self):
    print('这是prenext')


def next(self): # 核心就是这个next方法,本质是数据流

    if not self.position and self.buy_signal[0] == 1: # 如果没有持仓和上穿
        self.order = self.buy()

    if not self.position and self.sell_signal[0] == -1: # 下穿
        self.order = self.sell()


    if self.getposition().size < 0 and self.buy_signal[0] == 1:  # self.getposition().size < 0 有空头
        self.order = self.close()
        self.order = self.buy()


    if self.getposition().size > 0 and self.buy_signal[0] == -1:  # self.getposition().size > 0 有多头
        self.order = self.close()
        self.order = self.sell()


def stop(self):  # 打印最优参数    self.broker.getvalue()是策略的净值
   self.log('period:%s,k_u:%s,k_d:%s,final_value:%.2f' %
        (self.p.period, self.p.k_u, self.p.k_d, self.broker.getvalue()), doprint=True)

if name == 'main':

# 初始化模型
cerebro = bt.Cerebro()


# 2.====== add data feed  添加数据 feed
# 2.1 creat a data feed 创建数据

data = bt.feeds.GenericCSVData(
    dataname=r'D:\xbxsp\xbx-coin-2020_part3\adaira\EOS-USDT_15m.csv',
    # dataname=dataframe,  D:\adaira\EOS-USDT_15m.h5
    fromdate=datetime.datetime(2020, 12, 1, 0, 0, 0),
    todate=datetime.datetime(2021, 1, 4, 0, 0, 0),
    timeframe=bt.TimeFrame.Minutes, # 告诉框架我们用的是分钟线
    dtformat='%Y-%m-%d %H:%M:%S',
    datetime=1,
    open=2,
    high=3,
    low=4,
    close=5,
    volume=6
)

# 2.2 add the data feed to cerebro 将数据提要添加到脑
cerebro.adddata(data)
cerebro.resampledata(data, timeframe=bt.TimeFrame.Days)


# 3. add strategy  添加策略
# cerebro.addstrategy(DualThrust,)   # optstrategy

cerebro.optstrategy(
                    DualThrust,   # 遍历最优参数 下面的的可视化模块需要注释
                    period=range(1, 7),
                    k_u=[n/10.0 for n in range(2, 10)],
                    k_d=[n/10.0 for n in range(2, 10)]
                    )




# 设定初始资金和佣金
cerebro.broker.setcash(1000000.0)
cerebro.broker.setcommission(0.005)

# 策略执行前的资金
print('启动资金: %.2f' % cerebro.broker.getvalue())

# 4. run 策略执行
cerebro.run()


# 5.plot result  绘图结果
# cerebro.plot(style='candle')# 可视化