Thanks a lot for that fix

for low and high, you can access it with:

                self.datas[0].low
                self.datas[0].high

When rightedge=False, Backtrader will output all data immediately. The issue is due to a wrong assumption of the end of the current resampling.

The end point is added only if rightedge = True but should also when rightedge = False

Line 384,385 - resamplerfilter.py

        # If rightedge (end of boundary is activated) add it unless recursing
        point += self.p.rightedge

instead it should always add 1, but the correct timestamp should be set differently?

point += 1

You can do it this way:

# -*- coding: utf-8 -*-

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

# Import the backtrader platform
import backtrader as bt
import backtrader.indicators as btind
from backtrader.observer import Observer as btobserver

import datetime
import time

'''
TD Sequential-Style indicator

// S = Sell Signal
// B = Buy Signal
// A = Sell (above bar) or Buy (below bar) Signal that is 'not ideal' - meaning the signal bar's or the previous bar's high or low is not higer or lower than one of the previous 2 bars.
// - This could indicate that waiting another bar will deliver a 'true' signal. (Useful at the beginning of the trend reversal signal, not so much at the end)
//
// Indicator and Rules based on indicator as seen on CoinSheet.org


    Ein TD Sequential Buy Setup ist erfüllt, wenn 9 aufeinanderfolgende Bars tiefer Schliessen als 4 Bars zuvor. Für den Sell ist es umgekehrt, dort müssen 9 aufeinanderfolgende Bars höher Schliessen als 4 Bars zuvor.

    Das Ziel der Zählung ist es, mögliche Wendepunkte anzuzeigen und somit Low Risk Entrys zu finden. Falls die Bedingungen nicht bis zum 9er Count erfüllt wird, ist das Setup gecancelt. Sobald ein TD Setup erfüllt ist, würde normalerweise die Countdown resp. Intersection-Phase beginnen. Beim Countdown werden danach 13 Bars die einen tiefern Close haben, als das Low des zwei Bars zurückliegenden Stabes. Die Countdown Bars müssen jedoch nicht aufeinanderfolgen, die Zählung läuft weiter bis zu Bar 13, sofern nicht das Hoch des vorangehenden TD Setups (bei einem Buy Setup...sonst natürlich das Tief bei einem Sell) überschritten wird.

    Das ist jetzt wirklich nur ein ganz grober Überblick der Standartparameter.???

    Beim angehängten Indi handelt es sich übrigens um den TD Combo und nicht den TD Sequential. Der Unterschied zwischen den beiden liegt einfach gesagt darin, dass die Countdown Zählung beim erreichen eines kompletten TD Setups, die Countdownzählung zürückrechnet und somit schon beim ersten Bar des Setups beginnen kann, anstatt erst nach der Beendigung des Setups.:P

    Grob gesagt kann beim erfüllen eines Setups mit einem kleinen Wendepunkt gerechnet werden und beim erfüllen eines Countdowns ein grosser Wendepunkt.
    
    Entry:
    There are three methods of entry:
    (a) Enter on the close of the day on which the countdown is completed;
    (b) Long Trades: Enter on the close if Close[i] > Close[i - 4];
        Short Trades: Enter on the close if Close[i] < Close[i - 4];
    (c) Long Trades: Enter on the close if Close[i] > High[i - 2];
        Short Trades: Enter on the close if Close[i] < Low[i - 2]. Index: i ~ Current Bar. In this test we apply the 2nd method.
    
    Exit:
    Pattern Exit: The current position is liquidated once the new setup is complete and price fails to exceed the furthest price recorded by the recent inactive setup.
    Stop Loss Exit: 
    Long Trades: The difference between the close at the entry bar and the low of the lowest day of the pattern is subtracted from the low of the lowest day. Short Trades: The difference between the high of the highest day of the pattern and the close at the entry bar is added to the high of the highest day.                
    Note: In order to activate a stop loss, the close must exceed the calculated levels.

'''

class strategy(bt.Strategy):
    params = dict(
      candles_past_to_compare = 4,
      stoploss_dist = 0.0,
    )

    ''' Logging function for strategy '''
    def log(self, txt, dt=None):
        dt = dt or self.dataprimary.datetime.datetime(0)
        print('%s, %s' % (dt.isoformat(), txt))
    
    
    '''Initialization '''    
    def __init__(self):
        # Keep a reference to the primary data feed
        self.dataprimary = self.datas[0]
        # Keep a reference to the "close" line in the primary dataseries
        self.dataclose = self.dataprimary.close
        # Control vars
        self.live = True
        self.order = None

        self.bearishFlip = False
        self.bullishFlip = False

        self.tdsl = 0 # TD sequence long
        self.tdss = 0 # TD sequence short
        self.buySetup = False # TD buy setup 
        self.sellSetup = False # TD sell setup
        self.buyCountdown = 0 # TD buy countdown
        self.sellCountdown = 0 # TD sell countdown
        self.buyVal = 0 # buy value at intersection
        self.sellVal = 0 # sell value at intersection
        
        self.buySig = False
        self.idealBuySig = False
        self.sellSig = False
        self.idealSellSig = False

        print('-' * 80)
        print('Strategy Created')
        print('-' * 80)


    ''' Data notification '''
    def notify_data(self, data, status, *args, **kwargs):
        print('*' * 5, 'DATA NOTIF:', data._getstatusname(status), *args)
        if status == data.LIVE:
            self.live = True
        elif status == data.DELAYED:
            self.live = False


    ''' Store notification '''
    def notify_store(self, msg, *args, **kwargs):
        print('*' * 5, 'STORE NOTIF:', msg)
        

    ''' Order notification '''
    def notify_order(self, order):
        if order.status in [order.Completed, order.Cancelled, order.Rejected]:
            self.order = None
        print('-' * 50, 'ORDER BEGIN', datetime.datetime.now())
        print(order)
        print('-' * 50, 'ORDER END')


    ''' Trade notification '''
    def notify_trade(self, trade):
        print('-' * 50, 'TRADE BEGIN', datetime.datetime.now())
        print(trade)
        print('-' * 50, 'TRADE END')
        
        if not trade.isclosed:
            return

        self.log('OPERATION PROFIT, GROSS %.2f, NET %.2f' %
            (trade.pnl, trade.pnlcomm))

    ''' Next '''        
    def next(self):
        self.buySig = False
        self.sellSig = False
        self.idealBuySig = False
        self.idealSellSig = False
        
        # Calculate td sequential values if enough bars
        if len(self.dataclose) > self.p.candles_past_to_compare:
            
            # begin of sequence, bullish or bearish flip
            if self.dataclose[0] < self.dataclose[-self.p.candles_past_to_compare] and self.dataclose[-1] > self.dataclose[-(self.p.candles_past_to_compare + 1)]:
                self.bearishFlip = True
                self.bullishFlip = False
                self.tdsl = 0
                self.tdss = 0
                self.sellSetup = False
                self.sellCountdown = 0
            elif self.dataclose[0] > self.dataclose[-self.p.candles_past_to_compare] and self.dataclose[-1] < self.dataclose[-(self.p.candles_past_to_compare + 1)]:
                self.bullishFlip = True
                self.bearishFlip = False
                self.tdss = 0
                self.tdsl = 0
                self.buySetup = False
                self.buyCountdown = 0

            # sequence start
            if self.dataclose[0] < self.dataclose[-self.p.candles_past_to_compare] and self.bearishFlip:
                self.tdsl += 1
            elif self.dataclose[0] > self.dataclose[-self.p.candles_past_to_compare] and self.bullishFlip:
                self.tdss += 1
            
            # sequence intersection
            if self.tdsl == 9:
                self.buySig = (self.dataprimary.low[0] < self.dataprimary.low[-3] and self.dataprimary.low[0] < self.dataprimary.low[-2]) or (self.dataprimary.low[-1] < self.dataprimary.low[-2] and self.dataprimary.low[-1] < self.dataprimary.low[-3])
                self.bearishFlip = False
                self.tdsl = 0
                self.buySetup = True
                self.buyCountdown = 0
            elif self.tdss == 9:
                self.sellSig = (self.dataprimary.high[0] > self.dataprimary.high[-2] and self.dataprimary.high[0] > self.dataprimary.high[-3]) or (self.dataprimary.high[-1] > self.dataprimary.high[-3] and self.dataprimary.high[-1] > self.dataprimary.high[-2])
                self.bullishFlip = False
                self.tdss = 0
                self.sellSetup = True
                self.sellCountdown = 0
                
            # sequence countdown
            if self.buySetup:
                if self.dataprimary.close[0] <= self.dataprimary.low[-2]:
                    self.buyCountdown += 1
                if self.buyCountdown == 8:
                    self.buyVal = self.dataclose[0]
                elif self.buyCountdown == 13:
                    if self.dataprimary.low[0] <= self.buyVal:
                        self.idealBuySig = True
                    self.buySetup = False
                    self.buyCountdown = 0
                    
            elif self.sellSetup:
                if self.dataprimary.close[0] >= self.dataprimary.high[-2]:
                    self.sellCountdown += 1
                if self.sellCountdown == 8:
                    self.sellVal = self.dataclose[0]
                elif self.sellCountdown == 13:
                    if self.dataprimary.high[0] >= self.sellVal:
                        self.idealSellSig = True
                    self.sellSetup = False
                    self.sellCountdown = 0
                    
        # Trade only if no pending order and live data
        if not self.order and self.live:
            if not self.position:
                if self.buySig:
                    if self.p.stoploss_dist > 0:
                        stoplossPrice = self.dataprimary.close[0] - self.p.stoploss_dist
                        self.buy_bracket(stopprice=stoplossPrice, exectype=bt.Order.Market)
                    else:
                        self.buy()
                elif self.sellSig:
                    if self.p.stoploss_dist > 0:
                        stoplossPrice = self.dataprimary.close[0] + self.p.stoploss_dist
                        self.sell_bracket(stopprice=stoplossPrice, exectype=bt.Order.Market)
                    else:
                        self.sell()
            else:
                if self.position.size > 0 and (self.sellSig or self.idealSellSig):
                    self.close()
                elif self.position.size < 0 and (self.buySig or self.idealBuySig):
                    self.close()
                    
        # Log the closing price of the series from the reference
        self.log("Close {} TD SeqShort {} TD SeqLong {} TD CDBuy {} TD CDSell {}".format(self.dataclose[0], self.tdss, self.tdsl, self.buyCountdown, self.sellCountdown))

class observer(btobserver):
    plotinfo = dict(plot=True, subplot=False, plotlegend=False, 
                    plotlinelegend=False, plotlinevalues=False, 
                    plotabove=True, plotname="TD Sequential",)
    lines = ('buy', 'buy_ideal', 'sell', 'sell_ideal', 'seq_up_1', 
            'seq_up_2', 'seq_up_3', 'seq_up_4', 'seq_up_5', 
            'seq_up_6', 'seq_up_7', 'seq_up_8', 'seq_up_9', 
            'seq_up_1_b', 'seq_up_2_b', 'seq_up_3_b', 'seq_up_4_b', 
            'seq_up_5_b', 'seq_up_6_b', 'seq_up_7_b', 'seq_up_8_b', 
            'seq_up_9_b', 'seq_up_10_b', 'seq_up_11_b', 'seq_up_12_b', 
            'seq_down_1', 'seq_down_2', 'seq_down_3', 'seq_down_4', 
            'seq_down_5', 'seq_down_6', 'seq_down_7', 'seq_down_8', 
            'seq_down_9',
            'seq_down_1_s', 'seq_down_2_s', 'seq_down_3_s', 'seq_down_4_s', 
            'seq_down_5_s', 'seq_down_6_s', 'seq_down_7_s', 'seq_down_8_s', 
            'seq_down_9_s', 'seq_down_10_s','seq_down_11_s', 'seq_down_12_s',)
            
    plotlines = dict(
        buy_ideal = dict(marker='^', markersize=10.0, color='green',),
        buy = dict(marker='2', markersize=10.0, color='green',),
        sell_ideal = dict(marker='v', markersize=10.0, color='maroon',),
        sell = dict(marker='1', markersize=10.0, color='maroon',),
        seq_up_1 = dict(marker='$1$', markersize=6.0, color='black', ls='',),
        seq_up_2 = dict(marker='$2$', markersize=6.0, color='black', ls='',),
        seq_up_3 = dict(marker='$3$', markersize=6.0, color='black', ls='',),
        seq_up_4 = dict(marker='$4$', markersize=6.0, color='black', ls='',),
        seq_up_5 = dict(marker='$5$', markersize=6.0, color='black', ls='',),
        seq_up_6 = dict(marker='$6$', markersize=6.0, color='black', ls='',),
        seq_up_7 = dict(marker='$7$', markersize=6.0, color='black', ls='',),
        seq_up_8 = dict(marker='$8$', markersize=6.0, color='black', ls='',),
        seq_up_9 = dict(marker='$9$', markersize=6.0, color='black', ls='',),
        seq_up_1_b = dict(marker='$1$', markersize=6.0, color='blue', ls='',),
        seq_up_2_b = dict(marker='$2$', markersize=6.0, color='blue', ls='',),
        seq_up_3_b = dict(marker='$3$', markersize=6.0, color='blue', ls='',),
        seq_up_4_b = dict(marker='$4$', markersize=6.0, color='blue', ls='',),
        seq_up_5_b = dict(marker='$5$', markersize=6.0, color='blue', ls='',),
        seq_up_6_b = dict(marker='$6$', markersize=6.0, color='blue', ls='',),
        seq_up_7_b = dict(marker='$7$', markersize=6.0, color='blue', ls='',),
        seq_up_8_b = dict(marker='$8$', markersize=6.0, color='blue', ls='',),
        seq_up_9_b = dict(marker='$9$', markersize=6.0, color='blue', ls='',),
        seq_up_10_b = dict(marker='$10$', markersize=6.0, color='blue', ls='',),
        seq_up_11_b = dict(marker='$11$', markersize=6.0, color='blue', ls='',),
        seq_up_12_b = dict(marker='$12$', markersize=6.0, color='blue', ls='',),
        seq_down_1 = dict(marker='$1$', markersize=6.0, color='black', ls='',),
        seq_down_2 = dict(marker='$2$', markersize=6.0, color='black', ls='',),
        seq_down_3 = dict(marker='$3$', markersize=6.0, color='black', ls='',),
        seq_down_4 = dict(marker='$4$', markersize=6.0, color='black', ls='',),
        seq_down_5 = dict(marker='$5$', markersize=6.0, color='black', ls='',),
        seq_down_6 = dict(marker='$6$', markersize=6.0, color='black', ls='',),
        seq_down_7 = dict(marker='$7$', markersize=6.0, color='black', ls='',),
        seq_down_8 = dict(marker='$8$', markersize=6.0, color='black', ls='',),
        seq_down_9 = dict(marker='$9$', markersize=6.0, color='black', ls='',),
        seq_down_1_s = dict(marker='$1$', markersize=6.0, color='blue', ls='',),
        seq_down_2_s = dict(marker='$2$', markersize=6.0, color='blue', ls='',),
        seq_down_3_s = dict(marker='$3$', markersize=6.0, color='blue', ls='',),
        seq_down_4_s = dict(marker='$4$', markersize=6.0, color='blue', ls='',),
        seq_down_5_s = dict(marker='$5$', markersize=6.0, color='blue', ls='',),
        seq_down_6_s = dict(marker='$6$', markersize=6.0, color='blue', ls='',),
        seq_down_7_s = dict(marker='$7$', markersize=6.0, color='blue', ls='',),
        seq_down_8_s = dict(marker='$8$', markersize=6.0, color='blue', ls='',),
        seq_down_9_s = dict(marker='$9$', markersize=6.0, color='blue', ls='',),
        seq_down_10_s = dict(marker='$10$', markersize=6.0, color='blue', ls='',),
        seq_down_11_s = dict(marker='$11$', markersize=6.0, color='blue', ls='',),
        seq_down_12_s = dict(marker='$12$', markersize=6.0, color='blue', ls='',),
    )
    
    
    params = (
        ('bardist', 0.00005),  
    )
    
    def __init__(self):
        pass
        
    def next(self):
        # begin of sequence for long position
        if self._owner.tdsl > 0 and self._owner.tdsl < 10:
            name = 'seq_up_%d' % self._owner.tdsl
            attr = getattr(self.lines, name, False)
            attr[0] = self.data_low[0] - self.p.bardist
        
        # begin of sequence of short position
        elif self._owner.tdss > 0 and self._owner.tdss < 10:
            name = 'seq_down_%d' % self._owner.tdss
            attr = getattr(self.lines, name, False)
            attr[0] = self.data_high[0] + self.p.bardist
            
        if self._owner.buySetup:
            if self._owner.buyCountdown > 0 and self._owner.buyCountdown < 13:
                name = 'seq_up_%d_b' % self._owner.buyCountdown
                attr = getattr(self.lines, name, False)
                attr[0] = self.data_low[0] - (2 * self.p.bardist)
        elif self._owner.sellSetup:
            if self._owner.sellCountdown > 0 and self._owner.sellCountdown < 13 and self._owner.sellSetup:
                name = 'seq_down_%d_s' % self._owner.sellCountdown
                attr = getattr(self.lines, name, False)
                attr[0] = self.data_high[0] + (2 * self.p.bardist)
        
        if self._owner.buySig:
            self.lines.buy[0] = self.data_low[0] - (2 * self.p.bardist)
        elif self._owner.sellSig:
            self.lines.sell[0] = self.data_high[0] + (2 * self.p.bardist)
        elif self._owner.idealBuySig:
            self.lines.buy_ideal[0] = self.data_low[0] - (3 * self.p.bardist)
        elif self._owner.idealSellSig:
            self.lines.sell_ideal[0] = self.data_high[0] + (3 * self.p.bardist)
            

To plot this, you need to add the observer

I found a workaround for this issue. When creating the data feed, i used the following params which generate the correct timestamps:

rightedge=True, boundoff=1

with live data from oanda and rightedge=False the data will get delivered when arriving instead of being resampled.

It breaks when the adjusted time in live trade with rightedge = False is lower than the time of the last bar?

I got a tick

self.bar.datetime = DATE 2018-04-09T11:54:25.976293 (736793.4961339849)

the adjusted time with rightedge = False is:
dtnum = DATE 2018-04-09 11:54:00 (736793.495833333)
with rightedge = True it would be:
dtnum = DATE 2018-04-09 11:54:30 (this will be higher than self.bar.datetime)

when _adjusttime is being called with greater=True then the codition:

    if greater and dtnum <= self.bar.datetime:

is False, so no bar time is being updated.

It's not really a issue. Its how backtrader works. By default it adjusts the data to the rightedge of the current timeframe. You would need to use rightedge=False, so the data is aligned to the left edge.

It may be that there is a bug in backtrader because rightedge=False is being ignored, but i am not sure.

@backtrader it seems this code may be the culprint?

File resamplerfilter.py

    def _adjusttime(self, greater=False, forcedata=None):
        '''
        Adjusts the time of calculated bar (from underlying data source) by
        using the timeframe to the appropriate boundary, with compression taken
        into account

        Depending on param ``rightedge`` uses the starting boundary or the
        ending one
        '''
        dtnum = self._calcadjtime(greater=greater)
        if greater and dtnum <= self.bar.datetime:
            return False

        self.bar.datetime = dtnum
        return True

I did some checks:

i used the following params in resample

rightedge=False,
adjbartime=True,
bar2edge=True,

When using rightedge=False, the tick will be immediately be delivered, the time will not be adjusted.

This seems to be connected to _adjusttime in Resampler and the param greater. I replaced it with self.p.rightedge where it occured. This at least provided me correct timestamps in the resampled data. But one issue was, that the first incoming live data was not added to an existing bar. Everything else was correct after playing around with the greater param.

@backtrader so if the rightedge param is False, the time is not being adjusted to the leftedge, instead is is delivered instantly. maybe this helps to find the issue.

@nooby_mcnoob Did you find a solution for your problem? There is someone else having comparable issues. See https://github.com/ftomassetti/backtrader-oandav20/issues/13