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Enhancements to BB plotting
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@ -64,14 +64,14 @@ def add_indicators(fig, row, indicators: List[str], data: pd.DataFrame) -> make_
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"""
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for indicator in indicators:
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if indicator in data:
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# TODO: Figure out why scattergl causes problems
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scattergl = go.Scatter(
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# TODO: Figure out why scattergl causes problems plotly/plotly.js#2284
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scatter = go.Scatter(
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x=data['date'],
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y=data[indicator].values,
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mode='lines',
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name=indicator
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)
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fig.add_trace(scattergl, row, 1)
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fig.add_trace(scatter, row, 1)
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else:
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logger.info(
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'Indicator "%s" ignored. Reason: This indicator is not found '
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@ -92,7 +92,7 @@ def add_profit(fig, row, data: pd.DataFrame, column: str, name: str) -> make_sub
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:param name: Name to use
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:return: fig with added profit plot
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"""
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profit = go.Scattergl(
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profit = go.Scatter(
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x=data.index,
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y=data[column],
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name=name,
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@ -222,23 +222,26 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
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logger.warning("No sell-signals found.")
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if 'bb_lowerband' in data and 'bb_upperband' in data:
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bb_lower = go.Scattergl(
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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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name='BB lower',
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showlegend=False,
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line={'color': 'rgba(255,255,255,0)'},
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)
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bb_upper = go.Scattergl(
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bb_upper = go.Scatter(
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x=data.date,
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y=data.bb_upperband,
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name='BB upper',
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name='Bollinger Band',
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fill="tonexty",
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fillcolor="rgba(0,176,246,0.2)",
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line={'color': 'rgba(255,255,255,0)'},
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)
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fig.add_trace(bb_lower, 1, 1)
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fig.add_trace(bb_upper, 1, 1)
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if 'bb_upperband' in indicators1 and 'bb_lowerband' in indicators1:
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indicators1.remove('bb_upperband')
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indicators1.remove('bb_lowerband')
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# Add indicators to main plot
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fig = add_indicators(fig=fig, row=1, indicators=indicators1, data=data)
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@ -252,7 +255,7 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
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)
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fig.add_trace(volume, 2, 1)
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# Add indicators to seperate row
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# Add indicators to separate row
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fig = add_indicators(fig=fig, row=3, indicators=indicators2, data=data)
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return fig
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@ -267,7 +270,7 @@ def generate_profit_graph(pairs: str, tickers: Dict[str, pd.DataFrame],
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df_comb = create_cum_profit(df_comb, trades, 'cum_profit')
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# Plot the pairs average close prices, and total profit growth
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avgclose = go.Scattergl(
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avgclose = go.Scatter(
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x=df_comb.index,
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y=df_comb['mean'],
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name='Avg close price',
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