adding a VolumeProfile to the plotting
new features:
- volumeProfile on the right side of the plot
- separating the Volume and volumeProfile in
seperate buy and sell trades
This commit is contained in:
Felix Meier
parent
96f99699e0
commit
edd0b8b93c
@ -211,6 +211,12 @@ Sample configuration with inline comments explaining the process:
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"RSI": {
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'rsi': {'color': 'red'}
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}
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},
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'volume': {
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'showBuySell': 'true',
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'showVolumeProfile': 'true',
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# 'VolumeProfileHistoryBars': 96, # default: all
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# 'VolumeProfilePriceRangeSplices': 100 # default: 50
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}
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}
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@ -340,6 +340,51 @@ def add_areas(fig, row: int, data: pd.DataFrame, indicators) -> make_subplots:
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return fig
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def createVolumeProfileData(df: pd.DataFrame, bar_split: int = 50,
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history_bars: int = None) -> pd.DataFrame:
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"""
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Generate the Volume Profile Date for the given dataframe
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:param df: DataFrame with candle data
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:param bar_split: in how many bars should the PriceRange be spit (default=50)
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:param history_bars: how many history bars should be considered (default=all)
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:return: DataFrame with Price/Trade Date
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"""
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df_vol = pd.DataFrame(columns=['price_lower', 'price_upper',
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'price_avg', 'volume', 'volume_buy', 'volume_sell'])
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div = df['close'].max() - df['close'].min()
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step = div/bar_split
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for i in range(0, bar_split):
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# finding the priceRange
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price_lower = df['close'].min() + step*i
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price_upper = df['close'].min() + step*(i+1)
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price_avg = (price_lower + price_upper)/2
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# the volume for the given priceRange
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if history_bars is not None:
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dt_tail = df.tail(history_bars)
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else:
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dt_tail = df
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volume_comb = dt_tail[(dt_tail['close'] >= price_lower) & (
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dt_tail['close'] < price_upper)]['volume'].sum()
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volume_buy = dt_tail[(dt_tail['close'] >= price_lower) & (
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dt_tail['close'] < price_upper)]['volume_buy'].sum()
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volume_sell = dt_tail[(dt_tail['close'] >= price_lower) & (
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dt_tail['close'] < price_upper)]['volume_sell'].sum()
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df_vol = df_vol.append({'price_lower': price_lower,
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'price_upper': price_upper,
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'price_avg': price_avg,
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'volume': volume_comb,
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'volume_buy': volume_buy,
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'volume_sell': volume_sell}, ignore_index=True)
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return df_vol
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def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFrame = None, *,
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indicators1: List[str] = [],
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indicators2: List[str] = [],
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@ -362,16 +407,21 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
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# Define the graph
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fig = make_subplots(
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rows=rows,
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cols=1,
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cols=2, # ToDo: Check if 2 columns (instead of one) cause any issues somewhere else
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# ToDo: when showVolumeProfile==false, don't show the second column
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column_widths=[8, 1], # set the width of the Volume Profile
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shared_xaxes=True,
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shared_yaxes=True,
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row_width=row_widths + [1, 4],
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vertical_spacing=0.0001,
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horizontal_spacing=0.0001,
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)
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fig['layout'].update(title=pair)
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fig['layout']['yaxis1'].update(title='Price')
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fig['layout']['yaxis2'].update(title='Volume')
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fig['layout']['yaxis3'].update(title='Volume')
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for i, name in enumerate(plot_config['subplots']):
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fig['layout'][f'yaxis{3 + i}'].update(title=name)
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fig['layout'][f'yaxis{5 + i }'].update(title=name)
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# ToDo: if more then one subplot is used, the title is not shown
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fig['layout']['xaxis']['rangeslider'].update(visible=False)
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fig.update_layout(modebar_add=["v1hovermode", "toggleSpikeLines"])
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@ -436,6 +486,65 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
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fig = add_indicators(fig=fig, row=1, indicators=plot_config['main_plot'], data=data)
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fig = add_areas(fig, 1, data, plot_config['main_plot'])
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fig = plot_trades(fig, trades)
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# VolumeProfile
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volume_config = plot_config['volume'] if 'volume' in plot_config else {}
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showBuySell = volume_config['showBuySell'] if 'showBuySell' in volume_config else 'false'
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showVolumeProfile = volume_config['showVolumeProfile'] if 'showVolumeProfile' in \
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volume_config else 'false'
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VolumeProfileHistoryBars = volume_config['VolumeProfileHistoryBars'] if \
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'VolumeProfileHistoryBars' in volume_config else -1
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VolumeProfilePriceRangeSplices = volume_config[
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'VolumeProfilePriceRangeSplices'] if 'VolumeProfilePriceRangeSplices' in \
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volume_config else 50
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if showVolumeProfile.lower() == 'true':
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volumeProfileData = createVolumeProfileData(
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data, VolumeProfilePriceRangeSplices, VolumeProfileHistoryBars)
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volume_buy = go.Bar(
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x=volumeProfileData['volume_buy'],
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y=volumeProfileData['price_avg'],
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name='VolumeProfile Buy',
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marker_color='Green',
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marker_line_color='Green',
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orientation='h',
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)
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volume_sell = go.Bar(
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x=volumeProfileData['volume_sell'],
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y=volumeProfileData['price_avg'],
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name='VolumeProfile Sell',
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marker_color='Red',
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marker_line_color='Red',
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orientation='h',
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)
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fig.add_trace(volume_sell, 1, 2)
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fig.add_trace(volume_buy, 1, 2)
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fig.update_layout(barmode='stack')
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# standard volume plot
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if showBuySell.lower() == 'true': # show volume plot split by sell & buy trades
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volume_red = go.Bar(
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x=data['date'],
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y=data['volume'] * (data['high']-data['close']) / (data['high']-data['low']),
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name='Volume Sell',
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marker_color='Red',
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marker_line_color='Red'
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)
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fig.add_trace(volume_red, 2, 1)
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volume_green = go.Bar(
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x=data['date'],
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y=data['volume'] * (data['close']-data['low']) / (data['high']-data['low']),
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name='Volume Buy',
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marker_color='Green',
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marker_line_color='Green'
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)
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fig.add_trace(volume_green, 2, 1)
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else: # show 'normal' gray volume plot
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# sub plot: Volume goes to row 2
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volume = go.Bar(
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x=data['date'],
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@ -445,6 +554,7 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
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marker_line_color='DarkSlateGrey'
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)
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fig.add_trace(volume, 2, 1)
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# add each sub plot to a separate row
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for i, label in enumerate(plot_config['subplots']):
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sub_config = plot_config['subplots'][label]
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