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 run_bt_multiple():
cerebro = Cerebro()
df = get_pickle('tiingo', 'SPY')
data = PandasData(dataname=df)
cerebro.adddata(data)
cerebro.addanalyzer(Returns)
cerebro.optstrategy(StrategyFetcher, idx=[0, 1])
results = cerebro.run()
strats = [x[0] for x in results]
for i, strat in enumerate(strats):
rets = strat.analyzers.returns.get_analysis()
print('Strategy {} Name {}:\n - analyzer: {}\n'.format(
i, strat.__class__.__name__, rets))
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
"golden_cross": GoldenCross,
"buy_hold": BuyHold,
"macd": MacdStrat,
"macd_opt": MacdStrat,
"moving_avg": MovingAverage,
"sar": Sar,
"adx_macd": AdxMacd
}
#check against - golden_cross, buy_hold, macd, moving_avg, sar
strategy = "sar"
if strategy == "golden_cross_opt":
cerebro.optstrategy(
GoldenCross,
fast=range(40, 60, 10),
slow=range(160, 220, 20),
#fast=range(10, 30, 10), slow=range(50, 90, 20),
)
cerebro.run(maxcpus=1)
GoldenCross.show_max()
elif strategy == "macd_opt":
strats = cerebro.optstrategy(
MacdStrat,
fast=range(8, 16, 1),
slow=range(16, 32, 2),
)
cerebro.run(maxcpus=1)
best_fast, best_slow, best_roi = MacdStrat.show_max()
print('Best params: fast={}, slow={}, roi={}'.format(
best_fast, best_slow, best_roi))
"""
