Memory Error Plotting (Ticks)

[Bayne]

Hey, any idea what i can do ? When plotting (see last line of script) I get :

MemoryError                               Traceback (most recent call last)
<ipython-input-17-2cb10347888b> in <module>
    551 
    552     #Finally plot the end results
--> 553     cerebro.plot(style='bar',volume=False)
    554 
    555     # Print out the final result

c:\users\ben\appdata\local\programs\python\python37\lib\site-packages\backtrader\cerebro.py in plot(self, plotter, numfigs, iplot, start, end, width, height, dpi, tight, use, **kwargs)
    989                 rfig = plotter.plot(strat, figid=si * 100,
    990                                     numfigs=numfigs, iplot=iplot,
--> 991                                     start=start, end=end, use=use)
    992                 # pfillers=pfillers2)
    993 

c:\users\ben\appdata\local\programs\python\python37\lib\site-packages\backtrader\plot\plot.py in plot(self, strategy, figid, numfigs, iplot, start, end, **kwargs)
    218                         downinds=self.dplotsdown[ind])
    219 
--> 220                 self.plotdata(data, self.dplotsover[data])
    221 
    222                 for ind in self.dplotsdown[data]:

c:\users\ben\appdata\local\programs\python\python37\lib\site-packages\backtrader\plot\plot.py in plotdata(self, data, indicators)
    722                     colorup=self.pinf.sch.barup,
    723                     colordown=self.pinf.sch.bardown,
--> 724                     label=datalabel)
    725 
    726         self.pinf.zorder[ax] = plotted[0].get_zorder()

c:\users\ben\appdata\local\programs\python\python37\lib\site-packages\backtrader\plot\finance.py in plot_ohlc(ax, x, opens, highs, lows, closes, colorup, colordown, width, tickwidth, alpha, label, **kwargs)
    508         alpha,
    509         label,
--> 510         **kwargs)
    511 
    512     return handler.barcol, handler.opencol, handler.closecol

c:\users\ben\appdata\local\programs\python\python37\lib\site-packages\backtrader\plot\finance.py in __init__(self, ax, x, opens, highs, lows, closes, colorup, colordown, width, tickwidth, alpha, label, **kwargs)
    386             width=width, tickwidth=tickwidth,
    387             label=label,
--> 388             **kwargs)
    389 
    390         self.barcol = bcol

c:\users\ben\appdata\local\programs\python\python37\lib\site-packages\backtrader\plot\finance.py in barcollection(self, xs, opens, highs, lows, closes, width, tickwidth, label, scaling, bot, **kwargs)
    463             antialiaseds=useaa,
    464             label=label,
--> 465             **kwargs)
    466 
    467         def tickopen(i, open):

c:\users\ben\appdata\local\programs\python\python37\lib\site-packages\matplotlib\collections.py in __init__(self, segments, linewidths, colors, antialiaseds, linestyles, offsets, transOffset, norm, cmap, pickradius, zorder, facecolors, **kwargs)
   1331             **kwargs)
   1332 
-> 1333         self.set_segments(segments)
   1334 
   1335     def set_segments(self, segments):

c:\users\ben\appdata\local\programs\python\python37\lib\site-packages\matplotlib\collections.py in set_segments(self, segments)
   1346             _segments = self._add_offsets(_segments)
   1347 
-> 1348         self._paths = [mpath.Path(_seg) for _seg in _segments]
   1349         self.stale = True
   1350 

c:\users\ben\appdata\local\programs\python\python37\lib\site-packages\matplotlib\collections.py in <listcomp>(.0)
   1346             _segments = self._add_offsets(_segments)
   1347 
-> 1348         self._paths = [mpath.Path(_seg) for _seg in _segments]
   1349         self.stale = True
   1350 

MemoryError: 

the script is using Tickdata (for accuracy purposes), but its getting signals from Minutely Bars.
Data is not more than 2 weeks, but even need more.
Is it possible to plot it in Upsampled Bars, to save memory?
Here is the script:

if using_TickData == False:
    Backtraderfilename = BarBackTraderFileName
elif using_TickData == True:
    Backtraderfilename = "Backtrader TickData/TicksSampledForTimeFrame/"+TickBackTraderFileName+"_"+TimeFrame


     
if __name__ == '__main__':
    
    cerebro = bt.Cerebro(stdstats=False,optreturn=True,optdatas=True)    # Create a cerebro entity
    if using_TickData == False:
        
        data    = btfeed.GenericCSVData(dataname=Backtraderfilename,
                                     fromdate=datetime.datetime(from_year,from_month,from_day,from_hour,from_minute),#(1999,1,13, 10),
                                     todate=datetime.datetime(to_year,to_month,to_day,to_hour,to_minute),#2019,5,1, 20),#(2019,5,1, 20),
                                     nullvalue=0.0,dtformat=('%Y.%m.%d %H:%M:%S'),
                                     timeframe = bt.TimeFrame.Minutes, compression = 60,
                                     datetime=0,high=1,low=2,open=3,close=4,volume=5,openinterest=-1)
        # Add the Data Feed to Cerebro
        cerebro.adddata(data)
        
    elif using_TickData:    
        #import argparse      
        #args = parse_args()
        Backtraderfilename = BarBackTraderFileName
        data = bt.feeds.GenericCSVData(dataname="Backtrader TickData/TicksSampledForTimeFrame/"+TickBackTraderFileName+"_"+TimeFrame,
                                  dtformat=('%Y-%m-%d %H:%M:%S'),
                                  timeframe=bt.TimeFrame.Ticks,
                                  fromdate=datetime.datetime(from_year,from_month,from_day,from_hour,from_minute),#fromdate=datetime.datetime(2019,5,25,0,2), 
                                  todate=datetime.datetime(to_year,to_month,to_day,to_hour,to_minute),#todate=datetime.datetime(2019,5,30,23),
                                  datetime=1,high=2,low=2,open=2,close=2,volume=-1,openinterest=-1)


        cerebro.adddata(data)
        
    # Add a strategy
    cerebro.addstrategy(TestStrategy)
    
    # Add the analyzers we are interested in
    #cerebro.addanalyzer(bt.analyzers.TradeAnalyzer, _name="ta")
    #cerebro.addanalyzer(bt.analyzers.SQN, _name="sqn")
    #cerebro.addanalyzer(bt.analyzers.SQN, _name="dd")
    
    # Set our desired cash start
    cerebro.broker.setcash(StartCash)
    #slippage
    cerebro.broker = bt.brokers.BackBroker(slip_perc=0)  # 0.5%

    # Add a FixedSize sizer according to the stake     #was ist ein stake? eine Unit-Y 1000 = 0.01 Lot
    cerebro.addsizer(bt.sizers.FixedSize, stake=VolumeSize)

    # Set the commission
    cerebro.broker.setcommission(commission=0)
    
    # Print out the starting conditions
    print('Starting Portfolio Value: %.3f' % cerebro.broker.getvalue())

    # Run over everything
    StrategyResult = cerebro.run()
    
    # print the analyzers
    #printTradeAnalysis(StrategyResult[0].analyzers.ta.get_analysis())
    #printSQN(StrategyResult[0].analyzers.sqn.get_analysis())
    #printDrawDown(StrategyResult[0].analyzers.dd.get_analysis())
    
    # Print out the final result
    print('Final Portfolio Value: %.3f' % cerebro.broker.getvalue())
    
    #Finally plot the end results
    cerebro.plot(style='bar',volume=False)

    # Print out the final result
    print('Final Portfolio Value: %.3f' % cerebro.broker.getvalue())

[backtrader]

@Bayne said in Memory Error Plotting (Ticks):

Data is not more than 2 weeks, but even need more.

Buy a PC with more memory and you will be able to plot more (OS may impose limits on memory allocation)

@Bayne said in Memory Error Plotting (Ticks):

Is it possible to plot it in Upsampled Bars, to save memory?

It will obviously use less room. But you won't see the ticks.

[Bayne]

@backtrader
I mean, is it possible to backtest on Ticks (like above) but resample the Data only in plot?