Add plotconfig as property documentation and sample
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docs/plotting.md
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docs/plotting.md
@ -164,16 +164,17 @@ The resulting plot will have the following elements:
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An advanced plot configuration can be specified in the strategy in the `plot_config` parameter.
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Additional features when using plot_config include:
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Additional features when using `plot_config` include:
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* Specify colors per indicator
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* Specify additional subplots
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* Specify indicator pairs to fill area in between
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* Specify indicator pairs to fill area in between
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The sample plot configuration below specifies fixed colors for the indicators. Otherwise, consecutive plots may produce different color schemes each time, making comparisons difficult.
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It also allows multiple subplots to display both MACD and RSI at the same time.
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Plot type can be configured using `type` key. Possible types are:
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* `scatter` corresponding to `plotly.graph_objects.Scatter` class (default).
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* `bar` corresponding to `plotly.graph_objects.Bar` class.
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@ -182,40 +183,89 @@ Extra parameters to `plotly.graph_objects.*` constructor can be specified in `pl
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Sample configuration with inline comments explaining the process:
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``` python
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plot_config = {
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'main_plot': {
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# Configuration for main plot indicators.
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# Specifies `ema10` to be red, and `ema50` to be a shade of gray
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'ema10': {'color': 'red'},
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'ema50': {'color': '#CCCCCC'},
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# By omitting color, a random color is selected.
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'sar': {},
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# fill area between senkou_a and senkou_b
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'senkou_a': {
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'color': 'green', #optional
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'fill_to': 'senkou_b',
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'fill_label': 'Ichimoku Cloud', #optional
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'fill_color': 'rgba(255,76,46,0.2)', #optional
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},
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# plot senkou_b, too. Not only the area to it.
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'senkou_b': {}
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@property
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def plot_config(self):
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"""
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There are a lot of solutions how to build the return dictionary.
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The only important point is the return value.
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Example:
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plot_config = {'main_plot': {}, 'subplots': {}}
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"""
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plot_config = {}
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plot_config['main_plot'] = {
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# Configuration for main plot indicators.
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# Assumes 2 parameters, emashort and emalong to be specified.
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f'ema_{self.emashort.value}': {'color': 'red'},
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f'ema_{self.emalong.value}': {'color': '#CCCCCC'},
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# By omitting color, a random color is selected.
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'sar': {},
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# fill area between senkou_a and senkou_b
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'senkou_a': {
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'color': 'green', #optional
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'fill_to': 'senkou_b',
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'fill_label': 'Ichimoku Cloud', #optional
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'fill_color': 'rgba(255,76,46,0.2)', #optional
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},
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'subplots': {
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# Create subplot MACD
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"MACD": {
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'macd': {'color': 'blue', 'fill_to': 'macdhist'},
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'macdsignal': {'color': 'orange'},
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'macdhist': {'type': 'bar', 'plotly': {'opacity': 0.9}}
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},
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# Additional subplot RSI
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"RSI": {
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'rsi': {'color': 'red'}
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}
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# plot senkou_b, too. Not only the area to it.
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'senkou_b': {}
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}
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plot_config['subplots'] = {
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# Create subplot MACD
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"MACD": {
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'macd': {'color': 'blue', 'fill_to': 'macdhist'},
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'macdsignal': {'color': 'orange'},
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'macdhist': {'type': 'bar', 'plotly': {'opacity': 0.9}}
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},
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# Additional subplot RSI
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"RSI": {
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'rsi': {'color': 'red'}
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}
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}
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return plot_config
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```
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??? Note "As attribute (former method)"
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Assigning plot_config is also possible as Attribute (this used to be the default way).
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This has the disadvantage that strategy parameters are not available, preventing certain configurations from working.
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``` python
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plot_config = {
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'main_plot': {
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# Configuration for main plot indicators.
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# Specifies `ema10` to be red, and `ema50` to be a shade of gray
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'ema10': {'color': 'red'},
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'ema50': {'color': '#CCCCCC'},
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# By omitting color, a random color is selected.
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'sar': {},
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# fill area between senkou_a and senkou_b
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'senkou_a': {
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'color': 'green', #optional
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'fill_to': 'senkou_b',
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'fill_label': 'Ichimoku Cloud', #optional
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'fill_color': 'rgba(255,76,46,0.2)', #optional
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},
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# plot senkou_b, too. Not only the area to it.
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'senkou_b': {}
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},
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'subplots': {
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# Create subplot MACD
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"MACD": {
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'macd': {'color': 'blue', 'fill_to': 'macdhist'},
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'macdsignal': {'color': 'orange'},
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'macdhist': {'type': 'bar', 'plotly': {'opacity': 0.9}}
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},
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# Additional subplot RSI
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"RSI": {
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'rsi': {'color': 'red'}
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}
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}
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}
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```
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!!! Note
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The above configuration assumes that `ema10`, `ema50`, `senkou_a`, `senkou_b`,
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`macd`, `macdsignal`, `macdhist` and `rsi` are columns in the DataFrame created by the strategy.
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@ -87,6 +87,7 @@ class {{ strategy }}(IStrategy):
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'sell': 'gtc'
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}
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{{ plot_config | indent(4) }}
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def informative_pairs(self):
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"""
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Define additional, informative pair/interval combinations to be cached from the exchange.
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@ -1,18 +1,20 @@
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plot_config = {
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# Main plot indicators (Moving averages, ...)
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'main_plot': {
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'tema': {},
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'sar': {'color': 'white'},
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},
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'subplots': {
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# Subplots - each dict defines one additional plot
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"MACD": {
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'macd': {'color': 'blue'},
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'macdsignal': {'color': 'orange'},
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@property
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def plot_config(self):
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return {
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# Main plot indicators (Moving averages, ...)
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'main_plot': {
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'tema': {},
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'sar': {'color': 'white'},
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},
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"RSI": {
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'rsi': {'color': 'red'},
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'subplots': {
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# Subplots - each dict defines one additional plot
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"MACD": {
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'macd': {'color': 'blue'},
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'macdsignal': {'color': 'orange'},
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},
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"RSI": {
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'rsi': {'color': 'red'},
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}
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}
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}
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}
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