Closed
Description
Expected Behavior
charts plotted
Actual Behavior
Follow traceback
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TypeError Traceback (most recent call last)
[d:\machine_learning_examples\tf2.0\backtest.ipynb](file:///D:/machine_learning_examples/tf2.0/backtest.ipynb) Cell 1 in 3
[28](vscode-notebook-cell:/d%3A/machine_learning_examples/tf2.0/backtest.ipynb#W0sZmlsZQ%3D%3D?line=27) output = bt.run()
[29](vscode-notebook-cell:/d%3A/machine_learning_examples/tf2.0/backtest.ipynb#W0sZmlsZQ%3D%3D?line=28) print(output)
---> [30](vscode-notebook-cell:/d%3A/machine_learning_examples/tf2.0/backtest.ipynb#W0sZmlsZQ%3D%3D?line=29) bt.plot()
File [c:\Users\nguye\anaconda3\envs\env_dlearning\lib\site-packages\backtesting\backtesting.py:1592](file:///C:/Users/nguye/anaconda3/envs/env_dlearning/lib/site-packages/backtesting/backtesting.py:1592), in Backtest.plot(self, results, filename, plot_width, plot_equity, plot_return, plot_pl, plot_volume, plot_drawdown, smooth_equity, relative_equity, superimpose, resample, reverse_indicators, show_legend, open_browser)
1589 raise RuntimeError('First issue `backtest.run()` to obtain results.')
1590 results = self._results
-> 1592 return plot(
1593 results=results,
1594 df=self._data,
1595 indicators=results._strategy._indicators,
1596 filename=filename,
1597 plot_width=plot_width,
1598 plot_equity=plot_equity,
1599 plot_return=plot_return,
1600 plot_pl=plot_pl,
1601 plot_volume=plot_volume,
1602 plot_drawdown=plot_drawdown,
1603 smooth_equity=smooth_equity,
1604 relative_equity=relative_equity,
1605 superimpose=superimpose,
1606 resample=resample,
...
348 sizing_mode=sizing_mode,
349 )
351 return gp
TypeError: bokeh.models.tools.Toolbar() got multiple values for keyword argument 'logo'Steps to Reproduce
The code I using is the code at your homepage
from backtesting import Backtest, Strategy
from backtesting.lib import crossover
from backtesting.test import SMA, GOOG
class SmaCross(Strategy):
n1 = 10
n2 = 20
def init(self):
close = self.data.Close
self.sma1 = self.I(SMA, close, self.n1)
self.sma2 = self.I(SMA, close, self.n2)
def next(self):
if crossover(self.sma1, self.sma2):
self.buy()
elif crossover(self.sma2, self.sma1):
self.sell()
bt = Backtest(GOOG, SmaCross,
cash=10000, commission=.002,
exclusive_orders=True)
output = bt.run()
bt.plot()Additional info
- Backtesting version: 0.3.3
- bokeh: 3.2.2
- OS: Windown 64