Many thanks for the reply and the help.

Do you mean instead of changing the data of the indicator, change the data feed itself?

I tried that below and although the data feed changes, the moving average is not updated.

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)
import backtrader as bt
import pandas as pd
import datetime

# Create a Strategy
class TestStrategy(bt.Strategy):

    params = (
        ('maperiod', 2),
    )

    def log(self, txt, dt=None):
        ''' Logging function for this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        self.ind = bt.indicators.SimpleMovingAverage(self.datas[0], period=self.params.maperiod)

    def next(self):
        if self.datas[0].datetime.date(0) == datetime.datetime(2018, 1, 6).date():
            self.datas[0] = self.datas[1]
            # del self.datas[0]
        self.log("{}, {}".format(self.datas[0].lines.close[0], self.ind.lines.sma[0]))


if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()

    # Add a strategy with parameters
    cerebro.addstrategy(TestStrategy, maperiod=2)

    df1 = pd.DataFrame({'Close': list(range(1,11))}, index=pd.date_range(start='1/1/2018', periods=10))
    df2 = pd.DataFrame({'Close': list(range(2,12))}, index=pd.date_range(start='1/1/2018', periods=10))
    cerebro.adddata(bt.feeds.PandasData(dataname=df1, nocase=True))
    cerebro.adddata(bt.feeds.PandasData(dataname=df2, nocase=True))

    # Set our desired cash start
    cerebro.broker.setcash(100000.0)

    # Print out the starting conditions
    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

    # Run over everything
    cerebro.run(runonce=False, preload=False)

    # Print out the final result
    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())

Starting Portfolio Value: 100000.00
2018-01-02, 2.0, 1.5
2018-01-03, 3.0, 2.5
2018-01-04, 4.0, 3.5
2018-01-05, 5.0, 4.5
2018-01-06, 7.0, 5.5
2018-01-07, 8.0, 6.5
2018-01-08, 9.0, 7.5
2018-01-09, 10.0, 8.5
2018-01-10, 11.0, 9.5
Final Portfolio Value: 100000.00

Hi,

I am using multiple data feeds (all daily data but with different timeline) and a dummy data feed added first that has the full timeline (all possible times 'seen' in the rest). The strategy does not use any indicators, just printing the timeline.

The strategy starts later than expected. I can see using prenext() that minimum period is later than expected. If I prepend all data with a dummy bar with the first time as in the dummy data feed, the strategy starts correctly.

I wonder why the above behaviour happens. I thought minimum period is something used for indicators. Is there some option I am missing?

Thanks

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)
import backtrader as bt
import numpy as np
import pandas as pd
import random


# Create a Stratey
class TestStrategy(bt.Strategy):

    def log(self, txt, dt=None):
        ''' Logging function for this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def next(self):
        self.log("{}, {}".format(self.datas[0].lines.close[0], self.datas[1].lines.close[0]))


if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()

    # Add a strategy with parameters
    cerebro.addstrategy(TestStrategy)

    df_timeline = pd.DataFrame({'Close': random.sample(range(100), 10)}, index=pd.date_range(start='1/1/2018', periods=10))
    df1 = pd.DataFrame({'Close': random.sample(range(100), 7)}, index=pd.date_range(start='1/3/2018', periods=7))
    # Adding the below it works
    # df_first = pd.DataFrame([[np.nan]], index=[df_timeline.index[0]], columns=df1.columns)
    # df1 = df_first.append(df1)
    cerebro.adddata(bt.feeds.PandasData(dataname=df_timeline, nocase=True))
    cerebro.adddata(bt.feeds.PandasData(dataname=df1, nocase=True))

    # Set our desired cash start
    cerebro.broker.setcash(100000.0)

    # Print out the starting conditions
    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

    # Run over everything
    cerebro.run(runonce=True, preload=True)

    # Print out the final result
    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())

Hi,

I am really new to backtrader, so apologies if this is trivial.

If I create a custom dummy indicator, I can change its data feeds dynamically inside the strategy and if I run the strategy with runonce=False, it works fine (look below for the code). However, if I use an existing indicator instead e.g. bt.indicators.SimpleMovingAverage, the same approach does not work.

Many thanks for your help.

class DynamicIndicator(bt.Indicator):
    lines = ('indicator1',)

    def next(self):
        self.lines.indicator1[0] = self.datas[0][0]

class TestStrategy(bt.Strategy):
    def __init__(self):
    self.ind = DynamicIndicator(self.datas[1].lines.close)

    def next(self):
        if <condition>:
            self.ind.datas[0] = self.datas[2].lines.close