thanks @Robin-Dhillon, gonna check it out.

@robin-dhillon Alright, so I added the following lines:
import matplotlib
matplotlib.use('PS')
then it worked. (when i directly save the plots they still don't look nice.. but that's not so important)

Hey @Robin-Dhillon Thanks for your answer. I had everything running with anaconda, but the plots didn't look as nice as they should (i pointed it out in an earlier post here). So I deinstalled everything conda related and switched to pycharm. Now I have the problem mentioned above.
So I now installed matplotlib as described on their site: python -m pip install -U matplotlib
Is this what you mean by "reinstalling it from the source itself" ? Or should I do what is written in the "Installing from source section" ? on this site https://matplotlib.org/users/installing.html . can it be that complicated ? :O
Thanks

Hi!
Whenever I try to plot something I get the following error:

Would be amazing if anyone here has a solution to that problem.
Thanks.

same result unfortunately... also updated matplotlib, de- and reinstalled anconda, but nothing helps so far.

Hi @nikitaj and @backtrader

Actually the figsize = (30,30) command didn't do anything to the plots. I also deleted hight = 30, but nothing changed...
I'm using anaconda -> spyder.

The code now looks like this

fig = cerebro.plot(numfigs = num,barupfill = False, bardownfill = False, style = 'candle', plotdist = 0.5, 
                   volume = False, barup = 'green', valuetags = False, subtxtsize = 7,
                   start = startdate, end = enddate)

for i in range(num):
    fig[0][i].tight_layout()
    fig[0][i].savefig(output_folder + '/{}_'.format(timeframe) + stratname + '_{}'.format(strat_type) + '_plot{}.png'.format(i), dpi=500)

and unfortunately I still get one nice plot and all others are small... no idea why.
Should all plots look like the big one I posted ?

Thanks,
Alain

Hi!
When I make a plot as in the following:

num = 20
fig = cerebro.plot(numfigs = num, barupfill = False, bardownfill = False, style = 'candle', plotdist = 0.5, 
                   figsize=(30,30), volume = False, barup = 'green', valuetags = False, subtxtsize = 7,
                   start = startdate, end = enddate)

for i in range(num):
    fig[0][i].tight_layout()
    fig[0][i].savefig(output_folder + '/{}_'.format(timeframe) + stratname + '_{}'.format(strat_type) + '_plot{}.png'.format(i), dpi=300, hight = 30, width = 30, tight = True)

I get one very nice big plot as can be seen here (it's the second image printed):

and 19 small not so nice plots (where one can be seen here):

What could be the reason ? Would love to see 20 plots similar to the first one.

Thank you for your help!

@backtrader Ok, I actually did find canceled orders because of floating point errors also when "buy on close" with "bt.sizers.AllInsizer).

So I tried to fix this problem by simply subtracting a small number from the position size, so there would be enough cash to enter the position. However I found canceled orders even though I subtracted a pretty large number 0.1 :

Same code with corrected sizer by 0.1 :

def next(self):
    self.log('open %.2f and close %.2f' % (self.datas[0].open[0], self.dataclose[0])) 
    
    
def next_open(self):
    self.log('open %.2f and close %.2f' % (self.datas[0].open[0], self.dataclose[0])) 
    sizer = self.broker.get_cash() / self.datas[0].open[0] - 0.1
    print("sizer: ", sizer)
    print("cash: ", self.broker.get_cash())
    print("next_open price: ", self.datas[0].open[0])
    if self.position:
        self.order = self.close()
    
    else:
       self.order = self.buy(size = sizer)

I receive:

2017-04-01 00:00:00, open 1033.79 and close 1070.31
2017-04-02 00:00:00, open 1070.93 and close 1083.40
sizer: 9.23767846637969
cash: 10000.0
next_open price: 1070.93
2017-04-02 00:00:00, Order Canceled/Margin/Rejected
2017-04-02 00:00:00, open 1070.93 and close 1083.40
2017-04-03 00:00:00, open 1083.33 and close 1077.88
sizer: 9.130797633223487
cash: 10000.0
next_open price: 1083.33
2017-04-03 00:00:00, BUY EXECUTED, 1083.33
2017-04-03 00:00:00, BUY EXECUTED, 9.130797633223487
2017-04-03 00:00:00, open 1083.33 and close 1077.88
2017-04-04 00:00:00, open 1077.04 and close 1146.42
sizer: 0.0005840080219866872
cash: 108.33300000000054
next_open price: 1077.04
2017-04-04 00:00:00, SELL EXECUTED, 1077.04
2017-04-04 00:00:00, open 1077.04 and close 1146.42
2017-04-05 00:00:00, open 1145.62 and close 1143.00
sizer: 8.578765457033768
cash: 9942.567282887025
next_open price: 1145.62
2017-04-05 00:00:00, BUY EXECUTED, 1145.62
2017-04-05 00:00:00, BUY EXECUTED, 8.578765457033768
2017-04-05 00:00:00, open 1145.62 and close 1143.00

Which is weird to me, because 1070.93... * 9.2376... ~ 9892.18... which is clearly less than 10k.
?! What did I do wrong this time ?

yes! I thought the issue could be something like that. Thank you @backtrader.
What I find strange though is that if I buy and sell on the close by use of "cerebro.broker.set_coc(True)" and use the built in all in sizer "cerebro.addsizer(bt.sizers.AllInSizer)" I don't get any errors because of floating point precision:

backtrader sizers

def _getsizing(self, comminfo, cash, data, isbuy):

position = self.broker.getposition(data)

if not position:
    size = cash / data.close[0] * (self.params.percents / 100)
    
else:
    size = position.size
    
return size

I don't see why this won't give me any floating point errors ? I mean I'm happy if it doesn't, but I'm not sure if anything in this code differs from my implementation above.

@backtrader and @ab_trader thank you for your help. I still have the following problem: Even though I seem to calculate the right amount of BTC to go all in on the next open I sometimes get the buy orders rejected.

Here I implemented the most simple strategy which is to buy on one candle, sell on the next one and so on...

def next(self):
    self.log('open %.2f and close %.2f' % (self.datas[0].open[0], self.dataclose[0])) 
    
    
def next_open(self):
    self.log('open %.2f and close %.2f' % (self.datas[0].open[0], self.dataclose[0])) 
    sizer = self.broker.get_cash() / self.datas[0].open[0] 
    print("sizer: ", sizer)
    print("cash: ", self.broker.get_cash())
    print("next_open price: ", self.datas[0].open[0])
    if self.position:
        self.order = self.close()
    
    else:
       self.order = self.buy(size = sizer)

"It would help you (and the logs) if you logged the value you are actually using for the sizing calculations, which is the open when using cheat-on-open" . I did exactly that to check if I calculate the sizer with the right open price but I still sometimes get buy orders rejected as can be seen here:

Starting Portfolio Value: 10000.00

2017-04-01 00:00:00, open 1033.79 and close 1070.31
2017-04-02 00:00:00, open 1070.93 and close 1083.40
sizer: 9.337678466379689
cash: 10000.0
next_open price: 1070.93
2017-04-02 00:00:00, Order Canceled/Margin/Rejected
2017-04-02 00:00:00, open 1070.93 and close 1083.40
2017-04-03 00:00:00, open 1083.33 and close 1077.88
sizer: 9.230797633223487
cash: 10000.0
next_open price: 1083.33
2017-04-03 00:00:00, BUY EXECUTED, 1083.33
2017-04-03 00:00:00, open 1083.33 and close 1077.88
2017-04-04 00:00:00, open 1077.04 and close 1146.42
sizer: 0.0
cash: 0.0
next_open price: 1077.04
2017-04-04 00:00:00, SELL EXECUTED, 1077.04
2017-04-04 00:00:00, open 1077.04 and close 1146.42
2017-04-05 00:00:00, open 1145.62 and close 1143.00
sizer: 8.678216409356528
cash: 9941.938282887024
next_open price: 1145.62
2017-04-05 00:00:00, Order Canceled/Margin/Rejected
2017-04-05 00:00:00, open 1145.62 and close 1143.00

Final Portfolio Value: 9941.94

I also tried to only return the next open from the next_open() method and execute orders from next. But that didn't solve my problem of rejected orders either...

Any ideas ?

Thank you so much!