Add plotconfig as property documentation and sample

docs/plotting.md

@@ -164,7 +164,7 @@ The resulting plot will have the following elements:
 
 An advanced plot configuration can be specified in the strategy in the `plot_config` parameter.
 
-Additional features when using plot_config include:
+Additional features when using `plot_config` include:
 
 * Specify colors per indicator
 * Specify additional subplots
@@ -174,6 +174,7 @@ The sample plot configuration below specifies fixed colors for the indicators. O
 It also allows multiple subplots to display both MACD and RSI at the same time.
 
 Plot type can be configured using `type` key. Possible types are:
+
 * `scatter` corresponding to `plotly.graph_objects.Scatter` class (default).
 * `bar` corresponding to `plotly.graph_objects.Bar` class.
 
@@ -181,6 +182,54 @@ Extra parameters to `plotly.graph_objects.*` constructor can be specified in `pl
 
 Sample configuration with inline comments explaining the process:
 
+``` python
+@property
+def plot_config(self):
+    """
+        There are a lot of solutions how to build the return dictionary.
+        The only important point is the return value.
+        Example:
+            plot_config = {'main_plot': {}, 'subplots': {}}
+
+    """
+    plot_config = {}
+    plot_config['main_plot'] = {
+        # Configuration for main plot indicators.
+        # Assumes 2 parameters, emashort and emalong to be specified.
+        f'ema_{self.emashort.value}': {'color': 'red'},
+        f'ema_{self.emalong.value}': {'color': '#CCCCCC'},
+        # By omitting color, a random color is selected.
+        'sar': {},
+        # fill area between senkou_a and senkou_b
+        'senkou_a': {
+            'color': 'green', #optional
+            'fill_to': 'senkou_b',
+            'fill_label': 'Ichimoku Cloud', #optional
+            'fill_color': 'rgba(255,76,46,0.2)', #optional
+        },
+        # plot senkou_b, too. Not only the area to it.
+        'senkou_b': {}
+    }
+    plot_config['subplots'] = {
+         # Create subplot MACD
+        "MACD": {
+            'macd': {'color': 'blue', 'fill_to': 'macdhist'},
+            'macdsignal': {'color': 'orange'},
+            'macdhist': {'type': 'bar', 'plotly': {'opacity': 0.9}}
+        },
+        # Additional subplot RSI
+        "RSI": {
+            'rsi': {'color': 'red'}
+        }
+    }
+
+    return plot_config
+```
+
+??? Note "As attribute (former method)"
+    Assigning plot_config is also possible as Attribute (this used to be the default way).
+    This has the disadvantage that strategy parameters are not available, preventing certain configurations from working.
+
     ``` python
         plot_config = {
             'main_plot': {
@@ -216,6 +265,7 @@ Sample configuration with inline comments explaining the process:
 
     ```
 
+
 !!! Note
     The above configuration assumes that `ema10`, `ema50`, `senkou_a`, `senkou_b`,
     `macd`, `macdsignal`, `macdhist` and `rsi` are columns in the DataFrame created by the strategy.

freqtrade/templates/base_strategy.py.j2

@@ -87,6 +87,7 @@ class {{ strategy }}(IStrategy):
         'sell': 'gtc'
     }
     {{ plot_config | indent(4) }}
+
     def informative_pairs(self):
         """
         Define additional, informative pair/interval combinations to be cached from the exchange.

freqtrade/templates/subtemplates/plot_config_full.j2

@@ -1,5 +1,7 @@
 
-plot_config = {
+@property
+def plot_config(self):
+    return {
         # Main plot indicators (Moving averages, ...)
         'main_plot': {
             'tema': {},