3. Buy and Sell markers plot distance
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Buy and Sell markers plot distance

  • A

    Hi!, i am newat backtrader, i have read all documentation and fin any information related but i dont know how to change thebuy and sell markers distance to the data when i plot the results with .plot() . I am using 1 minute data and this markers are to far to the data and i cant see it easily. Can anyone help me with this? Many thanks!

    1
  • B
    administrators

    The default configuration can be switched off when running cerebro.run with the parameter stdstats.

    After that you can add your own plethora of observers, including the BuySell one and decide where you want the markers

    An example

    1
  • A

    Thank you for your answer,

    The first thing I apologize, I think I did not know how to put the code well.

    The second my code is not secret, its only a test. I put only the backtest running parts because there are too many lines.

    I read the documentation before post and had no problem hiding the imported data directly. My problem is that I don't know how to hide daily resampled data in the chart. Perhaps i lose something but I really can't find anything about it. Here I show everything:

    from __future__ import (absolute_import, division, print_function, unicode_literals)

import backtrader as bt  # The backtrader platform
import backtrader.feeds as btfeeds  # For load CSV data.
from backtrader import Indicator, CmpEx # For indicators
import backtrader.indicators as btind  # For indicators

import datetime  # For datetime objects
from datetime import time
import matplotlib # For ploting

# Symbols to load
symbol_list = ['EURUSD','GBPUSD','USDJPY']

# List for storage the loaded datas
data_list = []

# Load the data feeds
for symbol in symbol_list:     
    
    # 1 minute data (Each tick for analyze the strategy)_______________________________________________________
    data0 = btfeeds.GenericCSVData(
    dataname='{}_GMT+0_2018-2019_M1.csv'.format(symbol),    

    fromdate=datetime.datetime(2018, 1, 1),
    todate=datetime.datetime(2018, 1, 31),  #(2018, 1, 31)

    nullvalue=0.0,

    dtformat=('%d.%m.%Y %H:%M:%S'),

    datetime=0,
    open=1,
    high=2,
    low=3,
    close=4,
    volume=-1,
    openinterest=-1,

    timeframe=bt.TimeFrame.Minutes,
    compression=1,
        
    plot = True
    ) 
   
    data_list.append(data0)
    
    # 30 minute data (Pullback checking and plotting)__________________________________________________________
    data1 = btfeeds.GenericCSVData(
    dataname='{}_GMT+0_2018-2019_M30.csv'.format(symbol),    

    fromdate=datetime.datetime(2018, 1, 1),
    todate=datetime.datetime(2018, 1, 31),

    nullvalue=0.0,

    dtformat=('%d.%m.%Y %H:%M:%S'),

    datetime=0,
    open=1,
    high=2,
    low=3,
    close=4,
    volume=-1,
    openinterest=-1,

    timeframe=bt.TimeFrame.Minutes,
    compression=30,
        
    plot = False
    ) 
   
    data_list.append(data1)
    
    # 1 Day data (For pivot points indicator)_______________________________________________________________
    data2 = btfeeds.GenericCSVData(
    dataname='{}_GMT+0_2018-2019_D1.csv'.format(symbol),    

    fromdate=datetime.datetime(2018, 1, 1),
    todate=datetime.datetime(2018, 1, 31),

    nullvalue=0.0,

    dtformat=('%d.%m.%Y %H:%M:%S'),

    datetime=0,
    open=1,
    high=2,
    low=3,
    close=4,
    volume=-1,
    openinterest=-1,

    timeframe=bt.TimeFrame.Days,
    compression=1,
        
    plot = False
    ) 
   
    data_list.append(data2)
       
# Assign data feed variables
data_eurusd_m1 = data_list[0]
data_eurusd_m30 = data_list[1]
data_eurusd_d1 = data_list[2]
data_gbpusd_m1 = data_list[3]
data_gbpusd_m30 = data_list[4]
data_gbpusd_d1 = data_list[5]
data_usdjpy_m1 = data_list[6]
data_usdjpy_m30 = data_list[7]
data_usdjpy_d1 = data_list[8]

class PivotPoints_V8_Indicator(Indicator):
   
    lines = ('PP', 'R1', 'S1', 'R2', 'S2', 'R3', 'S3')
    #plotinfo = dict(subplot=False)
    plotinfo = dict(subplot=False)
    
    params = (('_autoplot', True),)  # attempt to plot on real target data

    def _plotinit(self):
        
        # Try to plot to the actual timeframe master
        if self.p._autoplot:
            if hasattr(self.data, 'data'):
                self.plotinfo.plotmaster = self.data.data
                #self.plotinfo.plotmaster = self.data.datas[1] # The second Data (M30) 
                # The indicator plots on resampled data*

    def __init__(self):
        
        h = self.data.high  # current high
        l = self.data.low  # current low
        c = self.data.close  # current close

      
        self.lines.PP = PP = (h + l + c) / 3.0
        self.lines.R1 = R1 = 2.0 * PP - l
        self.lines.S1 = S1 = 2.0 * PP - h
        self.lines.R2 = R2 = (PP - S1) + R1
        self.lines.S2 = S2 = PP - (R1 - S1)
        self.lines.R3 = (PP - S2) + R2
        self.lines.S3 = PP - (R2 - S2)

        #super(PivotPoint, self).__init__()  # enable coopertive inheritance

        if self.p._autoplot:
            self.plotinfo.plot = False  # disable own plotting
            self()  # Coupler to follow real object


def time_in_range(start, end, x):
    
    """Return true if x is in the range [start, end]"""
    
    if start <= end:
        return start <= x <= end
    else:
        return start <= x or x <= end

# The Strategy

class PIVOTPOINTS_V8(bt.Strategy):
    
    
    # datas[0] = EURUSD
    #...
    # datas[3] = GBPUSD
    #...
    # datas[6] = USDJPY
    #...
    
    def log(self, txt, dt=None):
        ''' Logging function for this strategy'''
        dt = dt or self.datas[0].datetime.datetime(0)
        print('%s, %s' % (dt.strftime('%d-%m-%Y %H:%M:%S'), txt))

    def __init__(self):
    
        # Strategy symbol
        self.symbol = 'EURUSD.r' #,'GBPUSD.r','USDJPY.r'
        
        # Indicator
        self.pivotindicator = PivotPoints_V8_Indicator(self.datas[3])  # the resampled data
        #self.pivotindicator.plotinfo.plotlinelabels = True
        
        # Data references
        self.M1_datetime = self.datas[0].datetime
        self.M1_close = self.datas[0].close
        self.M30_close = self.datas[1].close
        self.D1_close = self.datas[2].close
        self.D1_high = self.datas[2].high
        self.D1_low = self.datas[2].low
        
        # Strategy variables
        self.pullback_size = 70
        self.pullback_candles = 10 #(M30 Candles!)
        self.op_counters = [0,0,0,0,0,0,0,0,0,0,0,0,0,0]
        self.send_distance = 70  #(Points)
        self.open_distance = 20  #(Points)
        self.lot = 1.5  #(1 lot = 100.000 unitary units)
        self.stoploss = 100
        self.takeprofit = 100
        
        # Keep a reference to the orders   
        #self.order = None
        
    def notify_order(self, order):
        #date = self.data.datetime.datetime().date()
        date = self.data.datetime.datetime()

        if order.status == order.Accepted:
            print('-'*32,' NOTIFY ORDER ','-'*32)
            print('Order Accepted')
            print('{}, Status {}: Ref: {}, Size: {}, Price: {}'.format(
                                                        date,
                                                        order.status,
                                                        order.ref,
                                                        order.size,
                                                        'NA' if not order.price else round(order.price,5)
                                                        ))


        if order.status == order.Completed:
            print('-'*32,' NOTIFY ORDER ','-'*32)
            print('Order Completed')
            print('{}, Status {}: Ref: {}, Size: {}, Price: {}'.format(
                                                        date,
                                                        order.status,
                                                        order.ref,
                                                        order.size,
                                                        'NA' if not order.price else round(order.price,5)
                                                        ))
            print('Created: {} Price: {} Size: {}'.format(bt.num2date(order.created.dt), order.created.price,order.created.size))
            print('-'*80)

        if order.status == order.Canceled:
            print('-'*32,' NOTIFY ORDER ','-'*32)
            print('Order Canceled')
            print('{}, Status {}: Ref: {}, Size: {}, Price: {}'.format(
                                                        date,
                                                        order.status,
                                                        order.ref,
                                                        order.size,
                                                        'NA' if not order.price else round(order.price,5)
                                                        ))

        if order.status == order.Rejected:
            print('-'*32,' NOTIFY ORDER ','-'*32)
            print('WARNING! Order Rejected')
            print('{}, Status {}: Ref: {}, Size: {}, Price: {}'.format(
                                                        date,
                                                        order.status,
                                                        order.ref,
                                                        order.size,
                                                        'NA' if not order.price else round(order.price,5)
                                                        ))
            print('-'*80)


    def notify_trade(self, trade):
        date = self.data.datetime.datetime()
        if trade.isclosed:
            print('-'*32,' NOTIFY TRADE ','-'*32)
            print('{}, Close Price: {}, Profit, Gross {}, Net {}'.format(
                                                date,
                                                trade.price,
                                                round(trade.pnl,2),
                                                round(trade.pnlcomm,2)))
            print('-'*80)

    def next(self):
        
        #//////// Trading Time //////////////////////////////////////////////////////////////
        
        start = time(4,0,0) #4,0,0
        end = time (20,50,0) #20,50,0
        now = self.M1_datetime.time()
        weekday = self.datas[0].datetime.datetime(0).weekday()
        
        if time_in_range(start, end, now) and weekday in [1,2,3,4]:  #(Monday=0, Tueasday=1...Sunday=6)

            # --- Get Data ----------------------------------------------------------------------

            # Pivot Points values

            PP = self.pivotindicator.lines.PP[0]
            R1 = self.pivotindicator.lines.R1[0]
            S1 = self.pivotindicator.lines.S1[0]
            R2 = self.pivotindicator.lines.R2[0]
            S2 = self.pivotindicator.lines.S2[0]
            R3 = self.pivotindicator.lines.R3[0]
            S3 = self.pivotindicator.lines.S3[0]

            # List of pivot point levels for send orders iteration (Buy and Sell each level)
            pp_levels = [PP,PP,R1,R1,S1,S1,R2,R2,S2,S2,R3,R3,S3,S3]

            # Price (M1 Close, Backtrader cant handle tick data for Bid and Ask prices)
            price = self.M1_close[0]

            # Point value
            if 'JPY' in self.symbol:
                point = 0.001
            else:
                point = 0.00001

            # Pullbacks 
            periods_back = self.pullback_candles  #(M30 Candles)
            back_rates = self.M1_close.get(size=periods_back, ago=0)

            highest = max(back_rates)
            lowest = min(back_rates)

            pullback_buy = (highest - price) / point > self.pullback_size 
            pullback_sell = (price - lowest) / point > self.pullback_size

            # --- Send Orders ---------------------------------------------------------------

            # Check if any entry condition has been met
            for i in range(len(self.op_counters)):

                # BUY iterations on pivot levels
                if i in [0,2,4,6,8,10,12]:

                    if price > pp_levels[i] and price < (pp_levels[i] + self.send_distance * point) and pullback_buy == True and self.op_counters[i] == 0 :  

                        price = pp_levels[i]+(self.open_distance*point) # Price of the limit order
                        sl = price - (self.stoploss*point)
                        tp =price + (self.takeprofit*point)

                        buy_order = self.buy_bracket(limitprice=tp, price=price, stopprice=sl, exectype=bt.Order.Limit, size= self.lot*100000)

                        # Update ticket

                        # Update counter
                        self.op_counters[i] +=1

                # SELL iterations on pivot levels
                elif i in [1,3,5,7,9,11,13]:

                    if price < pp_levels[i] and price > (pp_levels[i] - self.send_distance * point) and pullback_sell == True and self.op_counters[i] == 0 :  

                        price = pp_levels[i]-(self.open_distance*point) # Price of the limit order
                        sl = price + (self.stoploss*point)
                        tp =price - (self.takeprofit*point)

                        sell_order = self.sell_bracket(limitprice=tp, price=price, stopprice=sl, exectype=bt.Order.Limit, size= self.lot*100000)

                        # Update ticket

                        # Update counter
                        self.op_counters[i] +=1

            # --- Orders Managment -----------------------------------------------------------
            
            


        
        else:
            
            #//////// Out of trading Time ////////////////////////////////////////////////////
              
            # --- Reset ----------------------------------------------------------------------
            
            self.op_counters = [0,0,0,0,0,0,0,0,0,0,0,0,0,0]
            
            # --- Close all ----------------------------------------------------------------------
            
            if self.position:
                self.close()
                #self.close(data= self.datas[0])


if __name__ == '__main__':
    
    # Instantiate the Cerebro engine  
    cerebro = bt.Cerebro(stdstats=False)  # remove the standard observers
    
    # Add a strategy
    cerebro.addstrategy(PIVOTPOINTS_V8)
    
    # Add the Data Feeds to Cerebro
    cerebro.adddata(data_eurusd_m1)
    cerebro.adddata(data_eurusd_m30)
    cerebro.adddata(data_eurusd_d1)
    #cerebro.adddata(data_gbpusd_m1)
    #cerebro.adddata(data_gbpusd_m30)
    #cerebro.adddata(data_gbpusd_d1)
    #cerebro.adddata(data_usdjpy_m1)
    #cerebro.adddata(data_usdjpy_m30)
    #cerebro.adddata(data_usdjpy_d1)
    
    # Resampled data for the indicator
    cerebro.resampledata(data_eurusd_m1, timeframe=bt.TimeFrame.Days)
    
    # Set our desired cash start
    cerebro.broker.setcash(100000.0)
    
    cerebro.broker.set_checksubmit(False)
    
    # Set the commission - 25 monetary units per 1 lot (1 lot = 100.000 monetary units), per buy/sell = 0.0125%, total= 0.025% 
    cerebro.broker.setcommission(commission=0.000125)
    
    # Add Analyzers
    
    #cerebro.addanalyzer(bt.analyzers.TradeAnalyzer, _name='TradeAnalyzer')
    #cerebro.addanalyzer(bt.analyzers.Returns, _name='Returns')
    #cerebro.addanalyzer(bt.analyzers.TimeReturn, _name='TimeReturn')
    #cerebro.addanalyzer(bt.analyzers.Transactions, _name='Transactions')
    #cerebro.addanalyzer(bt.analyzers.PositionsValue, _name='PositionsValue')
    #cerebro.addanalyzer(bt.analyzers.DrawDown, _name='DrawDown')
    #cerebro.addanalyzer(bt.analyzers.AnnualReturn, _name='AnnualReturn')
    
    # Print out the starting conditions
    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue()) 
    
    # Run over everything (loop over the data)
    results = cerebro.run() 
    strat = results[0]
    
    # Print out the final result
    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue()) 


    cerebro.plot(style='candle', numfigs=1, barup ='lime', bardown ='red', valuetags=False)
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  • A

    Sorry, I have write in the wrong post!

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  • A

    Many thanks for the answer. I cant find how can i change the buysell observer params. How can i do it? I tried this but the params didnt work.

    class MyBuySell(bt.observers.BuySell):
    
    params = (('barplot', True), ('bardist', 0.0))
    
    plotlines = dict(
        buy=dict(marker='$\u21E7$', markersize=4.0),
        sell=dict(marker='$\u21E9$', markersize=4.0)
    )
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