@dasch thanks a lot. much appreciated
Yes it probably could be a lot better than I have created it. I'm still quite new to backtrader so learning bit by bit.
what was then actually the problem which caused the error?

@dasch

class Trend_Indicator(bt.Indicator):
    lines = ('Trend', 'ohlc')
    params = (
            ('slowma', 21),
            ('fastma', 8),
    )

    def __init__(self):
        
        # Add Bollinger bands
        self.BB = bt.indicators.BollingerBands(self.datas[0])
      
        self.ohlc.open = self.datas[0].open[0]
        self.ohlc.high = self.datas[0].high[0]
        self.ohlc.low = self.datas[0].low[0]
        self.ohlc.close = self.datas[0].close[0]
        
        self.SlowEMA= bt.indicators.EMA(self.datas[0],period=self.params.slowma)
        self.FastEMA = bt.indicators.EMA(self.datas[0],period=self.params.fastma)
        
        self.Trend.bollinger_touch = ""
        self.Trend.Status = ""
        self.Trend.Enter = ""
        self.Trend.ExitParameters = {"20BarRule": False, "EMARule": False, "OppositeBollingerTouch": False}
        self.Trend.EMARule = {"Close1":False, "Close2":False}
        self.Trend.Position = 0 
        self.Trend.Test = 0 
        self.addminperiod(21)
        
    def next(self):          
        
        if self.Trend.bollinger_touch == "Top" and self.data.low[0] > self.BB.lines.bot[0] and self.Trend.Enter == "":
        # if the upper bollinger band was touched and the candle we have now makes the highest high and highest close, 
        # we enter in an uptrend
            if self.data.high[0] > self.ohlc.high and self.data.close[0] > self.ohlc.close:
                self.Trend.Enter = "Uptrend entered"
                self.ohlc.high = self.data.high[0]
                self.Trend.Status = "Up"
                self.Trend.ExitParameters["OppositeBollingerTouch"] = False
                self.Trend.ExitParameters["20BarRule"] = False
                self.Trend.ExitParameters["EMARule"] = False
                self.Trend.Position = len(self.ohlc)
                self.Trend.Test = len(self.data.high)
            if self.data.high[0] > self.ohlc.high:
                self.ohlc.high = self.data.high[0]
            if self.data.close[0] > self.ohlc.close:
                self.ohlc.close = self.data.close[0]                

        # we enter in a downtrend
        elif self.Trend.bollinger_touch == 'Bottom' and self.data.high[0] < self.BB.lines.top[0] and self.Trend.Enter == "":
        # if the bottom bollinger band was touched and the candle we have now makes the lowest low and lowest close, 
        # we enter in a downtrend
            if self.data.low[0] < self.ohlc.low and self.data.close[0] < self.ohlc.close:
                self.Trend.Enter = "Downtrend entered"
                self.ohlc.low = self.data.low[0]
                self.Trend.Status = "Down"
                self.Trend.ExitParameters["OppositeBollingerTouch"] = False
                self.Trend.ExitParameters["20BarRule"] = False
                self.Trend.ExitParameters["EMARule"] = False
                self.Trend.Position = len(self.ohlc)
                self.Trend.Test = len(self.data.low)
            if self.data.low[0] < self.ohlc.low:
                self.ohlc.low = self.data.low[0]
            if self.data.close[0] < self.ohlc.close:
                self.ohlc.close = self.data.close[0]                

        elif self.Trend.bollinger_touch == "":
            # look for a top bollinger touch, then store that bar's data
            if self.data.high[0] >= self.BB.lines.top[0] and self.data.low[0] > self.BB.lines.bot[0]:
                self.ohlc.open = self.data.open[0]
                self.ohlc.high = self.data.high[0]
                self.ohlc.low = self.data.low[0]
                self.ohlc.close = self.data.close[0]
                self.Trend.bollinger_touch = "Top"
                
            elif self.data.low[0] <= self.BB.lines.bot[0] and self.data.high[0] < self.BB.lines.top[0]:
                self.ohlc.open = self.data.open[0]
                self.ohlc.high = self.data.high[0]
                self.ohlc.low = self.data.low[0]
                self.ohlc.close = self.data.close[0]
                self.Trend.bollinger_touch = "Bottom"
        
        # if the upper bollinger band was touched but now the lower bollinger band got touched, the upper bollinger touch resets
        if self.Trend.bollinger_touch == "Top" and self.data.low[0] <= self.BB.lines.bot[0]:
                self.Trend.bollinger_touch = "Bottom"
                self.ohlc.open = self.data.open[0]
                self.ohlc.high = self.data.high[0]
                self.ohlc.low = self.data.low[0]
                self.ohlc.close = self.data.close[0]
                
        # if the bottom bollinger band was touched but now the top bollinger band got touched, the bottom bollinger touch resets
        elif self.Trend.bollinger_touch == "Bottom" and self.data.high[0] >= self.BB.lines.top[0]:
                self.Trend.bollinger_touch = "Top"
                self.ohlc.open = self.data.open[0]
                self.ohlc.high = self.data.high[0]
                self.ohlc.low = self.data.low[0]
                self.ohlc.close = self.data.close[0]

        # we are in an uptrend
        if self.Trend.Status == "Up":
            # if the opposite bollinger band was touched, we exit the uptrend
            if self.data.low[0] <= self.BB.lines.bot[0]:
                self.Trend.Status = ""
                self.Trend.Enter = ""
                self.Trend.ExitParameters["OppositeBollingerTouch"] = True
                self.Trend.bollinger_touch = "Bottom"
                self.Trend.EMARule['Close1'] = False
                self.Trend.EMARule['Close2'] = False
                self.ohlc.open = self.data.open[0]
                self.ohlc.high = self.data.high[0]
                self.ohlc.low = self.data.low[0]
                self.ohlc.close = self.data.close[0]
            # if a fresh high is made, keep track of the position
            if self.data.high[0] > self.ohlc.high:
                self.ohlc.high = self.data.high[0]
                self.Trend.Position = len(self.data.high)
            # after 20 bars (excluding the first) no new high is made, we are not in a trend anymore
            elif self.data.high[0] < self.ohlc.high:
                if len(self.data.high) - self.Trend.Position >= 21:
                    self.Trend.Status = ""
                    self.Trend.Enter = ""
                    self.Trend.ExitParameters["20BarRule"] = True
                    self.Trend.bollinger_touch = "Bottom"
                    self.Trend.EMARule['Close1'] = False
                    self.Trend.EMARule['Close2'] = False
                    self.Trend.ExitParameters['20BarRule'] = True
                    
            # if the top bollinger band was touched, reset the EMA rule
            if self.data.high[0] >= self.BB.lines.top[0]:
                self.Trend.EMARule['Close1'] = False
                self.Trend.EMARule['Close2'] = False
                
            if self.data.close[0] < self.SlowEMA[0] and self.data.close[0] < self.FastEMA[0]:
                self.Trend.EMARule['Close1'] = True

            if self.Trend.EMARule['Close1'] == True and self.data.close[0] > self.SlowEMA[0] and self.data.close[0] > self.FastEMA[0]:
                self.Trend.EMARule['Close2'] = True
                
            if self.Trend.EMARule['Close1'] == True and self.Trend.EMARule['Close2'] == True and self.data.close[0] < self.SlowEMA[0] and self.data.close[0] < self.FastEMA[0]:
                self.Trend.EMARule['Close1'] = False
                self.Trend.EMARule['Close2'] = False
                self.Trend.Status = ""
                self.Trend.Enter = ""
                self.Trend.ExitParameters['EMARule'] = True
                self.Trend.bollinger_touch = ""
                  
        if self.Trend.Enter == "Uptrend entered" and True not in self.Trend.ExitParameters.values():
            self.Trend[0] = 1
            
        # we are in a downtrend
        if self.Trend.Status == "Down":
            # if the opposite bollinger band was touched, we exit the downtrend
            if self.data.high[0] >= self.BB.lines.top[0]:
                self.Trend.Status = ""
                self.Trend.Enter = ""
                self.Trend.ExitParameters["OppositeBollingerTouch"] = True
                self.Trend.bollinger_touch = "Top"
                self.Trend.EMARule['Close1'] = False
                self.Trend.EMARule['Close2'] = False
                self.ohlc.open = self.data.open[0]
                self.ohlc.high = self.data.high[0]
                self.ohlc.low = self.data.low[0]
                self.ohlc.close = self.data.close[0]

            # if a fresh low is made, keep track of the position
            if self.data.low[0] < self.ohlc.high:
                self.ohlc.low = self.data.low[0]
                self.Trend.Position = len(self.data.low)
            # after 20 bars (excluding the first) no new low is made, we are not in a trend anymore
            elif self.data.low[0] > self.ohlc.low:
                if len(self.data.low) - self.Trend.Position >= 21:
                    self.Trend.Status = ""
                    self.Trend.Enter = ""
                    self.Trend.ExitParameters["20BarRule"] = True
                    self.Trend.bollinger_touch = ""
                    self.Trend.EMARule['Close1'] = False
                    self.Trend.EMARule['Close2'] = False
                    self.Trend.ExitParameters['20BarRule'] = True
                    
            # if the bottom bollinger band was touched, reset the EMA rule
            if self.data.low[0] <= self.BB.lines.bot[0]:
                self.Trend.EMARule['Close1'] = False
                self.Trend.EMARule['Close2'] = False
                
            if self.data.close[0] > self.SlowEMA[0] and self.data.close[0] > self.FastEMA[0]:
                self.Trend.EMARule['Close1'] = True

            if self.Trend.EMARule['Close1'] == True and self.data.close[0] < self.SlowEMA[0] and self.data.close[0] < self.FastEMA[0]:
                self.Trend.EMARule['Close2'] = True
                
            if self.Trend.EMARule['Close1'] == True and self.Trend.EMARule['Close2'] == True and self.data.close[0] > self.SlowEMA[0] and self.data.close[0] > self.FastEMA[0]:
                self.Trend.EMARule['Close1'] = False
                self.Trend.EMARule['Close2'] = False
                self.Trend.Status = ""
                self.Trend.Enter = ""
                self.Trend.ExitParameters['EMARule'] = True
                self.Trend.bollinger_touch = ""
                
        if self.Trend.Enter == "Downtrend entered" and True not in self.Trend.ExitParameters.values():
            self.Trend[0] = -1

@dasch I added self.addminperiod(21) in init in the indicator but that still doesn't seem to solve the issue

@dasch

thanks,

yes I forgot to mention it uses EMA's (8 and 21) when I run it without resampling it works. but it doesn't when I resample.

I'll have a look

next problem I'm running into is when I run my customer indicator in init I'm getting an error

def __init__(self):
        self.TI = Trend_Indicator(self.datas[0]) 

error:

---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-39-1a3e58d6bea6> in <module>
     39 #     cerebro.adddata(data)
     40 
---> 41     cerebro.run()

~\Anaconda3\lib\site-packages\backtrader\cerebro.py in run(self, **kwargs)
   1125             # let's skip process "spawning"
   1126             for iterstrat in iterstrats:
-> 1127                 runstrat = self.runstrategies(iterstrat)
   1128                 self.runstrats.append(runstrat)
   1129                 if self._dooptimize:

~\Anaconda3\lib\site-packages\backtrader\cerebro.py in runstrategies(self, iterstrat, predata)
   1215             sargs = self.datas + list(sargs)
   1216             try:
-> 1217                 strat = stratcls(*sargs, **skwargs)
   1218             except bt.errors.StrategySkipError:
   1219                 continue  # do not add strategy to the mix

~\Anaconda3\lib\site-packages\backtrader\metabase.py in __call__(cls, *args, **kwargs)
     86         _obj, args, kwargs = cls.donew(*args, **kwargs)
     87         _obj, args, kwargs = cls.dopreinit(_obj, *args, **kwargs)
---> 88         _obj, args, kwargs = cls.doinit(_obj, *args, **kwargs)
     89         _obj, args, kwargs = cls.dopostinit(_obj, *args, **kwargs)
     90         return _obj

~\Anaconda3\lib\site-packages\backtrader\metabase.py in doinit(cls, _obj, *args, **kwargs)
     76 
     77     def doinit(cls, _obj, *args, **kwargs):
---> 78         _obj.__init__(*args, **kwargs)
     79         return _obj, args, kwargs
     80 

<ipython-input-39-1a3e58d6bea6> in __init__(self)
     18 
     19 #         self.DVM = Decreasing_Volatility_Mode(self.datas[0])
---> 20         self.TI = Trend_Indicator(self.datas[0])
     21 
     22     def next(self):

~\Anaconda3\lib\site-packages\backtrader\indicator.py in __call__(cls, *args, **kwargs)
     51     def __call__(cls, *args, **kwargs):
     52         if not cls._icacheuse:
---> 53             return super(MetaIndicator, cls).__call__(*args, **kwargs)
     54 
     55         # implement a cache to avoid duplicating lines actions

~\Anaconda3\lib\site-packages\backtrader\metabase.py in __call__(cls, *args, **kwargs)
     86         _obj, args, kwargs = cls.donew(*args, **kwargs)
     87         _obj, args, kwargs = cls.dopreinit(_obj, *args, **kwargs)
---> 88         _obj, args, kwargs = cls.doinit(_obj, *args, **kwargs)
     89         _obj, args, kwargs = cls.dopostinit(_obj, *args, **kwargs)
     90         return _obj

~\Anaconda3\lib\site-packages\backtrader\metabase.py in doinit(cls, _obj, *args, **kwargs)
     76 
     77     def doinit(cls, _obj, *args, **kwargs):
---> 78         _obj.__init__(*args, **kwargs)
     79         return _obj, args, kwargs
     80 

<ipython-input-5-cc6e0edefdb2> in __init__(self)
     11         self.BB = bt.indicators.BollingerBands(self.datas[0])
     12 
---> 13         self.ohlc.open = self.datas[0].open[0]
     14         self.ohlc.high = self.datas[0].high[0]
     15         self.ohlc.low = self.datas[0].low[0]

~\Anaconda3\lib\site-packages\backtrader\linebuffer.py in __getitem__(self, ago)
    161 
    162     def __getitem__(self, ago):
--> 163         return self.array[self.idx + ago]
    164 
    165     def get(self, ago=0, size=1):

IndexError: array index out of range

@dasch Yes. I realized that because the lowest dataframe is 2 minutes, there will never be a time ending on 5. I tried the following work around where I'm separately adding the one minute frame

    # Add a strategy
    cerebro.addstrategy(resampling)
    # Create a Data Feed
    data = bt.feeds.PandasData(dataname=df2020)
    one_minute = cerebro.resampledata(data, timeframe=bt.TimeFrame.Minutes, compression=1)
    two_minute = cerebro.resampledata(data, timeframe=bt.TimeFrame.Minutes, compression=2)
    five_minute = cerebro.resampledata(data, timeframe=bt.TimeFrame.Minutes, compression=5)
    ten_minute = cerebro.resampledata(data, timeframe=bt.TimeFrame.Minutes, compression=10)

when logging the 5-minute closes I can see now it works properly

2020-01-02 09:00, 1.12075
2020-01-02 09:01, 1.12075
2020-01-02 09:02, 1.12075
2020-01-02 09:03, 1.12075
2020-01-02 09:04, 1.12075
2020-01-02 09:05, 1.12087
2020-01-02 09:06, 1.12087
2020-01-02 09:07, 1.12087
2020-01-02 09:08, 1.12087
2020-01-02 09:09, 1.12087
2020-01-02 09:10, 1.12086
2020-01-02 09:11, 1.12086
2020-01-02 09:12, 1.12086
2020-01-02 09:13, 1.12086
2020-01-02 09:14, 1.12086
2020-01-02 09:15, 1.1207799999999999

thanks for the help guys

@run-out I did and I had the issue where only a couple rows were showing up. tried it again now and now I'm getting all the rows for some reason

@run-out great.

For the 5 minute:

        self.log(self.datas[1].close[0])

instead of 09:05 it's showing 09:04 twice which is a bit annoying when I would want to make a reference

2020-01-02 09:00, 1.12075
2020-01-02 09:02, 1.12075
2020-01-02 09:04, 1.12075
2020-01-02 09:04, 1.12083
2020-01-02 09:06, 1.12083
2020-01-02 09:08, 1.12083
2020-01-02 09:10, 1.12086
2020-01-02 09:12, 1.12086
2020-01-02 09:14, 1.12086
2020-01-02 09:14, 1.1207
2020-01-02 09:16, 1.1207

@run-out Perfect! you always come to the rescue :) do you then also know how to refer to the datafeeds in the init / next functions?

I have now created the three timeframes as follows which seems to work. When I log, I'm getting the closes of the 2 minute timeframe. Can't see how to refer to the other two though.

    # Add a strategy
    cerebro.addstrategy(resampling)
    # Create a Data Feed
    minute_data = bt.feeds.PandasData(dataname=df2020)
    two_minute = cerebro.resampledata(minute_data, timeframe=bt.TimeFrame.Minutes, compression=2)
    five_minute = cerebro.resampledata(minute_data, timeframe=bt.TimeFrame.Minutes, compression=5)
    ten_minute = cerebro.resampledata(minute_data, timeframe=bt.TimeFrame.Minutes, compression=10)

I actually tried this before and then I'm only getting a couple rows showing up. Below is all the output there is from the log while there should be 100's of rows

2020-01-02 23:59, 1.1171200000000001
2020-01-03 23:59, 1.1154700000000002
2020-01-05 23:59, 1.1154700000000002
2020-01-06 23:59, 1.11958
2020-01-07 23:59, 1.11513
2020-01-08 23:59, 1.1103399999999999
2020-01-09 23:59, 1.11059
2020-01-10 23:59, 1.11196