def test_local_data(self):
from quantdigger.datasource.data import LocalData
from quantdigger.util import pcontract
""" 测试本地数据接口 """
db = LocalData()
target = db.load_data(pcontract('BB.SHFE', '1.Minute'))
fname = os.path.join(os.getcwd(), 'data', 'CC.SHFE-1.Minute.csv')
source = pd.read_csv(fname, parse_dates='datetime', index_col='datetime')
self.assertFalse(source.equals(target), '本地数据接口负测试失败！')
fname = os.path.join(os.getcwd(), 'data', 'BB.SHFE-1.Minute.csv')
source = pd.read_csv(fname, parse_dates='datetime', index_col='datetime')
self.assertTrue(source.equals(target), '本地数据接口正测试失败！')
logger.info('----------------- 本地数据接口测试成功 -------------------')
def on_bar(self):
""" 策略函数，对每根Bar运行一次。"""
#self.ma2.update(average(self.open, 10))
if self.ma10[1] < self.ma20[1] and self.ma10 > self.ma20:
self.buy('long', self.open, 1, contract = 'IF000.SHFE')
elif self.position() > 0 and self.ma10[1] > self.ma20[1] and self.ma10 < self.ma20:
self.sell('long', self.open, 1)
# 夸品种数据引用
print self.open_(1)[1], self.open
#print self.position(), self.cash()
#print self.datetime, self.b_upper, self.b_middler, self.b_lower
if __name__ == '__main__':
try:
pcon = pcontract('IF000.SHFE', '10.Minute')
begin_dt, end_dt = None, None
#begin_dt, end_dt = '2015-05-25', '2015-06-01'
#pcon = stock('600848','10.Minute') # 通过tushare下载股票数据
simulator = ExecuteUnit([pcon, pcon], begin_dt, end_dt)
algo = DemoStrategy(simulator)
#algo1 = DemoStrategy(simulator)
#algo2 = DemoStrategy(simulator)
simulator.run()
#for deal in algo.blotter.deal_positions:
## code...
#print("----------------")
#print("开仓时间: %s；成交价格: %f；买卖方向: %s；成交量: %d；") % \
#(deal.open_datetime, deal.open_price, Direction.type_to_str(deal.direction), deal.quantity)
#print("平仓时间: %s；成交价格: %f；买卖方向: %s；成交量: %d；盈亏: %f；") % \
def on_bar(self):
""" 策略函数，对每根Bar运行一次。"""
#self.ma2.update(average(self.open, 10))
if self.ma10[1] < self.ma20[1] and self.ma10 > self.ma20:
self.buy('long', self.open, 1, contract = 'IF000.SHFE')
elif self.position() > 0 and self.ma10[1] > self.ma20[1] and self.ma10 < self.ma20:
self.sell('long', self.open, 1)
# 夸品种数据引用
#print self.position(), self.cash()
#print self.datetime, self.b_upper, self.b_middler, self.b_lower
#print self.datetime[0]
if __name__ == '__main__':
try:
pcon = pcontract('BB.SHFE', '1.Minute')
#begin_dt, end_dt = '2015-05-25', '2015-06-01'
#pcon = stock('600848','10.Minute') # 通过tushare下载股票数据
simulator = ExecuteUnit([pcon, pcon], '2013-12-12', '2013-12-25')
algo = DemoStrategy(simulator)
#algo1 = DemoStrategy(simulator)
#algo2 = DemoStrategy(simulator)
simulator.run()
#for deal in algo.blotter.deal_positions:
## code...
#print("----------------")
#print("开仓时间: %s；成交价格: %f；买卖方向: %s；成交量: %d；") % \
#(deal.open_datetime, deal.open_price, Direction.type_to_str(deal.direction), deal.quantity)
#print("平仓时间: %s；成交价格: %f；买卖方向: %s；成交量: %d；盈亏: %f；") % \
#(deal.close_datetime, deal.close_price, Direction.type_to_str(deal.direction), deal.quantity, deal.profit())
def on_bar(self):
""" 策略函数，对每根Bar运行一次。"""
#self.ma2.update(average(self.open, 10))
if self.ma10[1] < self.ma20[1] and self.ma10 > self.ma20:
self.buy('long', self.open, 1, contract = 'IF000.SHFE')
elif self.position() > 0 and self.ma10[1] > self.ma20[1] and self.ma10 < self.ma20:
self.sell('long', self.open, 1)
# 夸品种数据引用
#print self.position(), self.cash()
#print self.datetime, self.b_upper, self.b_middler, self.b_lower
#print self.datetime[0]
if __name__ == '__main__':
try:
pcon = pcontract('BB.SHFE', '1.Minute')
#begin_dt, end_dt = '2015-05-25', '2015-06-01'
#pcon = stock('600848','10.Minute') # 通过tushare下载股票数据
simulator = ExecuteUnit([pcon, pcon])
algo = DemoStrategy(simulator)
#algo1 = DemoStrategy(simulator)
#algo2 = DemoStrategy(simulator)
simulator.run()
# 显示回测结果
from quantdigger.datastruct import TradeSide
ping = 0
kai = 0
for t in algo.blotter.transactions:
if t.side == TradeSide.PING:
if self.ma10[1] < self.ma20[1] and self.ma10 > self.ma20:
self.buy('long', self.open, 1, contract='IF000.SHFE')
elif self.position(
) > 0 and self.ma10[1] > self.ma20[1] and self.ma10 < self.ma20:
self.sell('long', self.open, 1)
# 夸品种数据引用
print self.open_(1)[1], self.open
#print self.position(), self.cash()
#print self.datetime, self.b_upper, self.b_middler, self.b_lower
if __name__ == '__main__':
try:
begin_dt, end_dt = None, None
pcon = pcontract('IF000.SHFE', '10.Minute')
pcon = stock('600848') # 通过tushare下载股票数据
simulator = ExecuteUnit([pcon, pcon], begin_dt, end_dt)
algo = DemoStrategy(simulator)
algo1 = DemoStrategy(simulator)
algo2 = DemoStrategy(simulator)
simulator.run()
for deal in algo.blotter.deal_positions:
# code...
print("----------------")
print("开仓时间: %s；成交价格: %f；买卖方向: %s；成交量: %d；") % \
(deal.open_datetime, deal.open_price, Direction.type_to_str(deal.direction), deal.quantity)
print("平仓时间: %s；成交价格: %f；买卖方向: %s；成交量: %d；盈亏: %f；") % \
(deal.close_datetime, deal.close_price, Direction.type_to_str(deal.direction), deal.quantity, deal.profit())
if self.ma10[1] < self.ma20[1] and self.ma10 > self.ma20:
self.buy('long', self.open, 1, contract = 'IF000.SHFE')
elif self.position() > 0 and self.ma10[1] > self.ma20[1] and self.ma10 < self.ma20:
self.sell('long', self.open, 1)
# 输出pcon1的当前K线开盘价格。
print(self.open)
# 夸品种数据引用
# pcon2的前一根K线开盘价格。
print(self.open_(1)[1])
if __name__ == '__main__':
try:
# 策略的运行对象周期合约
pcon1 = pcontract('IF000.SHFE', '10.Minute')
pcon2 = pcontract('IF000.SHFE', '10.Minute')
# 创建模拟器，这里假设策略要用到两个不同的数据，比如套利。
simulator = ExecuteUnit([pcon1, pcon2]);
# 创建策略。
algo = DemoStrategy(simulator)
# 运行模拟器，这里会开始事件循环。
simulator.run()
# 显示回测结果
plotting.plot_result(simulator.data[pcon], algo._indicators,
algo.blotter.deal_positions, algo.blotter)
except Exception, e:
print(e)
# self.ma2.update(average(self.open, 10))
if self.ma10[1] < self.ma20[1] and self.ma10 > self.ma20:
self.buy("long", self.open, 1, contract="IF000.SHFE")
elif self.position() > 0 and self.ma10[1] > self.ma20[1] and self.ma10 < self.ma20:
self.sell("long", self.open, 1)
# 夸品种数据引用
print self.open_(1)[1], self.open
# print self.position(), self.cash()
# print self.datetime, self.b_upper, self.b_middler, self.b_lower
if __name__ == "__main__":
try:
begin_dt, end_dt = None, None
pcon = pcontract("IF000.SHFE", "10.Minute")
# pcon = stock('600848') # 通过tushare下载股票数据
simulator = ExecuteUnit([pcon, pcon], begin_dt, end_dt)
algo = DemoStrategy(simulator)
# algo1 = DemoStrategy(simulator)
# algo2 = DemoStrategy(simulator)
simulator.run()
# for deal in algo.blotter.deal_positions:
## code...
# print("----------------")
# print("开仓时间: %s；成交价格: %f；买卖方向: %s；成交量: %d；") % \
# (deal.open_datetime, deal.open_price, Direction.type_to_str(deal.direction), deal.quantity)
# print("平仓时间: %s；成交价格: %f；买卖方向: %s；成交量: %d；盈亏: %f；") % \
# (deal.close_datetime, deal.close_price, Direction.type_to_str(deal.direction), deal.quantity, deal.profit())
if self.ma10[1] < self.ma20[1] and self.ma10 > self.ma20:
self.buy("long", self.open, 1, contract="IF000.SHFE")
elif self.position() > 0 and self.ma10[1] > self.ma20[1] and self.ma10 < self.ma20:
self.sell("long", self.open, 1)
# 输出pcon1的当前K线开盘价格。
print(self.open)
# 夸品种数据引用
# pcon2的前一根K线开盘价格。
print(self.open_(1)[1])
if __name__ == "__main__":
try:
# 策略的运行对象周期合约
pcon1 = pcontract("IF000.SHFE", "10.Minute")
pcon2 = pcontract("IF000.SHFE", "10.Minute")
# 创建模拟器，这里假设策略要用到两个不同的数据，比如套利。
simulator = ExecuteUnit([pcon1, pcon2])
# 创建策略。
algo = DemoStrategy(simulator)
# 运行模拟器，这里会开始事件循环。
simulator.run()
# 显示回测结果
plotting.plot_result(simulator.data[pcon], algo._indicators, algo.blotter.deal_positions, algo.blotter)
except Exception, e:
print(e)
