def test_ordered_optimize(cerebro: bt.Cerebro):
cerebro.optstrategy(bt.strategies.MA_CrossOver,
slow=[20],
fast=[5, 10, 20])
res = cerebro.run(optreturn=True)
def df(optresults):
a = [x.analyzers.tradeanalyzer.get_analysis() for x in optresults]
return sum([x.pnl.gross.total if 'pnl' in x else 0 for x in a])
usercolumns = {
'Profit & Loss': df,
}
b = Bokeh(style='bar', output_mode=_output_mode)
browser = OptBrowser(b,
res,
usercolumns=usercolumns,
sortcolumn='Profit & Loss')
model = browser.build_optresult_model()
# browser.start()
def count_children(obj):
numo = 1
if hasattr(obj, "children"):
numo = count_children(obj.children)
if hasattr(obj, '__len__'):
numo += len(obj)
return numo
num = count_children(model)
assert num == 3
def test_optimize_no_optreturn(cerebro_no_optreturn: bt.Cerebro):
cerebro_no_optreturn.optstrategy(bt.strategies.MA_CrossOver,
slow=[5, 10, 20],
fast=[5, 10, 20])
res = cerebro_no_optreturn.run()
s = backtrader_plotting.schemes.Blackly()
b = Bokeh(style='bar', output_mode=_output_mode, scheme=s)
browser = OptBrowser(b, res)
model = browser.build_optresult_model()
#browser.start()
def count_children(obj):
numo = 1
if hasattr(obj, "children"):
numo = count_children(obj.children)
if hasattr(obj, '__len__'):
numo += len(obj)
return numo
num = count_children(model)
assert num == 3
def test_optimize_2strat(cerebro: bt.Cerebro):
cerebro.optstrategy(bt.strategies.MA_CrossOver,
slow=[5, 10, 20],
fast=[5, 10, 20])
cerebro.optstrategy(ToggleStrategy, modbuy=[12, 15], modsell=[17, 19])
res = cerebro.run()
b = Bokeh(style='bar', output_mode=_output_mode)
browser = OptBrowser(b, res)
with pytest.raises(RuntimeError):
browser.build_optresult_model()
def test_optimize(cerebro: bt.Cerebro):
cerebro.optstrategy(bt.strategies.MA_CrossOver,
slow=[5, 10, 20],
fast=[5, 10, 20])
res = cerebro.run(optreturn=True)
b = Bokeh(style='bar', output_mode=_output_mode)
browser = OptBrowser(b, res)
model = browser.build_optresult_model()
# browser.start()
def count_children(obj):
numo = 1
if hasattr(obj, "children"):
numo = count_children(obj.children)
if hasattr(obj, '__len__'):
numo += len(obj)
return numo
num = count_children(model)
assert num == 3
if __name__ == '__main__':
cerebro = bt.Cerebro(maxcpus=1)
data = bt.feeds.YahooFinanceCSVData(
dataname="datas/orcl-1995-2014.txt",
fromdate=datetime.datetime(2000, 1, 1),
todate=datetime.datetime(2001, 2, 28),
reverse=False,
swapcloses=True,
)
cerebro.adddata(data)
cerebro.addanalyzer(bt.analyzers.TradeAnalyzer)
cerebro.optstrategy(MyStrategy, buydate=range(40, 180, 30))
result = cerebro.run(optreturn=False)
def get_pnl_gross(strats):
a = strats[0].analyzers.tradeanalyzer.get_analysis()
return a.pnl.gross.total if 'pnl' in a else 0
b = Bokeh(style='bar', scheme=Tradimo())
browser = OptBrowser(b,
result,
usercolumns=dict(pnl=get_pnl_gross),
sortcolumn='pnl',
sortasc=False)
browser.start()
def next(self):
pos = len(self.data)
if pos == self.p.buydate:
self.buy(self.datas[0], size=None)
if pos == self.p.buydate + self.p.holdtime:
self.sell(self.datas[0], size=None)
if __name__ == '__main__':
cerebro = bt.Cerebro(maxcpus=1)
data = bt.feeds.YahooFinanceCSVData(
dataname="datas/orcl-1995-2014.txt",
fromdate=datetime.datetime(2000, 1, 1),
todate=datetime.datetime(2001, 2, 28),
reverse=False,
swapcloses=True,
)
cerebro.adddata(data)
cerebro.addanalyzer(bt.analyzers.TradeAnalyzer)
cerebro.optstrategy(MyStrategy, buydate=range(40, 180, 30))
result = cerebro.run(optreturn=True)
b = Bokeh(style='bar', scheme=Tradimo())
browser = OptBrowser(b, result)
browser.start()
self.sell(self.datas[0], size=None)
if __name__ == '__main__':
cerebro = bt.Cerebro(maxcpus=1)
data = bt.feeds.YahooFinanceCSVData(
dataname="datas/orcl-1995-2014.txt",
fromdate=datetime.datetime(2000, 1, 1),
todate=datetime.datetime(2001, 2, 28),
reverse=False,
swapcloses=True,
)
cerebro.adddata(data)
cerebro.addanalyzer(bt.analyzers.TradeAnalyzer)
cerebro.optstrategy(MyStrategy, buydate=range(40, 180, 30))
optres = cerebro.run(optreturn=False)
def df(optresults):
a = [x.analyzers.tradeanalyzer.get_analysis() for x in optresults]
return sum([x.pnl.gross.total if 'pnl' in x else 0 for x in a])
usercolumns = {'Profit & Loss': df}
b = Bokeh(style='bar', scheme=Tradimo())
browser = OptBrowser(b, optres, usercolumns=usercolumns, sortcolumn='Profit & Loss', sortasc=False)
browser.start()