Add more indicators
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@ -33,6 +33,20 @@ logger = logging.getLogger(__name__)
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_CONF: Dict[str, Any] = {}
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# Update the global variable TO_DISPLAY to select which indicator you want to display
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TO_DISPLAY = {
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'sma': False, # On Row 1
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'ema': True, # On Row 1
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'macd': True, # On Row 3
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'rsi': False, # On Row 3
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'fisher_rsi': False, # On Row 3
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'mfi': False, # On Row 3
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'slow': False, # On Row 3
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'fast': False # On Row 3
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}
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def plot_analyzed_dataframe(args: Namespace) -> None:
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"""
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Calls analyze() and plots the returned dataframe
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@ -88,7 +102,6 @@ def plot_analyzed_dataframe(args: Namespace) -> None:
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persistence.init(_CONF, engine)
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trades = Trade.query.filter(Trade.pair.is_(pair)).all()
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dataframes = analyze.tickerdata_to_dataframe(tickers)
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dataframe = dataframes[pair]
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dataframe = analyze.populate_buy_trend(dataframe)
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@ -97,15 +110,35 @@ def plot_analyzed_dataframe(args: Namespace) -> None:
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if len(dataframe.index) > 750:
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logger.warning('Ticker contained more than 750 candles, clipping.')
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generate_graph(
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fig = generate_graph(
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pair=pair,
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trades=trades,
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data=dataframe.tail(750)
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)
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plot(fig, filename=os.path.join('user_data', 'freqtrade-plot.html'))
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def generate_graph(pair, trades, data):
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def generate_graph(pair, trades, data) -> None:
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"""
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Generate the graph from the data generated by Backtesting or from DB
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:param pair: Pair to Display on the graph
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:param trades: All trades created
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:param data: Dataframe
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:return: None
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"""
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# Define the graph
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fig = tools.make_subplots(
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rows=3,
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cols=1,
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shared_xaxes=True,
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row_width=[1, 1, 4],
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vertical_spacing=0.0001,
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)
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fig['layout'].update(title=pair)
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# Common information
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candles = go.Candlestick(
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x=data.date,
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open=data.open,
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@ -167,6 +200,10 @@ def generate_graph(pair, trades, data):
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)
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)
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# Row 1
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fig.append_trace(candles, 1, 1)
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if 'bb_lowerband' in data and 'bb_upperband' in data:
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bb_lower = go.Scatter(
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x=data.date,
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y=data.bb_lowerband,
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@ -181,37 +218,87 @@ def generate_graph(pair, trades, data):
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fillcolor="rgba(0,176,246,0.2)",
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line={'color': "transparent"},
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)
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macd = go.Scattergl(x=data['date'], y=data['macd'], name='MACD')
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macdsignal = go.Scattergl(x=data['date'], y=data['macdsignal'], name='MACD signal')
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volume = go.Bar(x=data['date'], y=data['volume'], name='Volume')
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fig = tools.make_subplots(
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rows=3,
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cols=1,
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shared_xaxes=True,
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row_width=[1, 1, 4],
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vertical_spacing=0.0001,
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)
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# Row 1
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fig.append_trace(candles, 1, 1)
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fig.append_trace(bb_lower, 1, 1)
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fig.append_trace(bb_upper, 1, 1)
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if TO_DISPLAY['sma'] and 'sma' in data:
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sma = generate_scattergl(index='sma', name='SMA', data=data)
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fig.append_trace(sma, 1, 1)
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if TO_DISPLAY['ema'] and 'ema10' in data and 'ema50' in data:
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ema10 = generate_scattergl(index='ema10', name='EMA10', data=data)
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ema50 = generate_scattergl(index='ema50', name='EMA50', data=data)
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fig.append_trace(ema10, 1, 1)
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fig.append_trace(ema50, 1, 1)
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fig.append_trace(buys, 1, 1)
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fig.append_trace(sells, 1, 1)
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fig.append_trace(volume, 2, 1)
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fig.append_trace(macd, 3, 1)
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fig.append_trace(macdsignal, 3, 1)
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fig.append_trace(trade_buys, 1, 1)
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fig.append_trace(trade_sells, 1, 1)
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fig['layout'].update(title=pair)
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fig['layout']['yaxis1'].update(title='Price')
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# Row 2
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volume = go.Bar(
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x=data['date'],
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y=data['volume'],
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name='Volume'
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)
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fig.append_trace(volume, 2, 1)
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fig['layout']['yaxis2'].update(title='Volume')
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# Row 3 (On Row 3, we can only display one indicator)
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if TO_DISPLAY['macd'] and 'macd' in data and 'macdsignal' in data:
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macd = generate_scattergl(index='macd', name='MACD', data=data)
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macdsignal = generate_scattergl(index='macdsignal', name='MACD Signal', data=data)
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fig.append_trace(macd, 3, 1)
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fig.append_trace(macdsignal, 3, 1)
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fig['layout']['yaxis3'].update(title='MACD')
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plot(fig, filename=os.path.join('user_data', 'freqtrade-plot.html'))
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elif TO_DISPLAY['fast'] and 'fastd' in data and 'fastk' in data:
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fastd = generate_scattergl(index='fastd', name='fastd', data=data)
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fastk = generate_scattergl(index='fastk', name='fastk', data=data)
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fig.append_trace(fastd, 3, 1)
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fig.append_trace(fastk, 3, 1)
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fig['layout']['yaxis3'].update(title='Stoch Fast')
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elif TO_DISPLAY['slow'] and 'slowd' in data and 'slowk' in data:
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slowd = generate_scattergl(index='slowd', name='slowd', data=data)
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slowk = generate_scattergl(index='slowk', name='slowk', data=data)
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fig.append_trace(slowd, 3, 1)
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fig.append_trace(slowk, 3, 1)
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fig['layout']['yaxis3'].update(title='Stoch Slow')
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elif TO_DISPLAY['rsi'] and 'rsi' in data:
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rsi = generate_scattergl(index='rsi', name='RSI', data=data)
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fig.append_trace(rsi, 3, 1)
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fig['layout']['yaxis3'].update(title='RSI')
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elif TO_DISPLAY['mfi'] and 'mfi' in data:
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mfi = generate_scattergl(index='mfi', name='MFI', data=data)
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fig.append_trace(mfi, 3, 1)
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fig['layout']['yaxis3'].update(title='MFI')
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elif TO_DISPLAY['fisher_rsi'] and 'fisher_rsi' in data:
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fisher_rsi = generate_scattergl(index='fisher_rsi', name='Fisher RSI', data=data)
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fig.append_trace(fisher_rsi, 3, 1)
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fig['layout']['yaxis3'].update(title='Fisher RSI')
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return fig
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def generate_scattergl(index, name, data) -> go.Scattergl:
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"""
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Generate a Scattergl element
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:param index: code of the Indicator to generate
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:param name: Name that will be display in the graph legend
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:param data: Dataframe
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:return: Scattergl
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"""
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return go.Scattergl(
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x=data['date'],
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y=data[index],
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name=name
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)
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def plot_parse_args(args: List[str]) -> Namespace:
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