flake8 cleanup

docs/hyperopt.md

@@ -643,14 +643,23 @@ In order to use these best dynamic ROI parameters found by Hyperopt in backtesti
 If you are optimizing dynamic ROI values, Freqtrade creates the 'dynamic-roi' optimization hyperspace for you. By default, the `enabled` parameter will try both True and False values. The value the `type` vary between `linear`, `exponential`, and `connect`. 
 
 Other values have default ranges of:
+
 | Param      | Range       |
 |------------|-------------|
-| decay-time | 180..1440   |
 | decay-rate | 0.001..0.03 |
 | start      | 0.05..0.25  |
 | end        | 0..0.005    |
 
-Override the `dynamic_roi_space()` method and define the desired range in it if you want values of the dynamic ROI parameters to vary in other ranges during hyperoptimization. A sample for this method can be found in [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py).
+Just as the standard ROI table, the time decay value (in minutes) has a range which varies based on your candle size, for example:
+
+| Candle   | Range         |
+|----------|---------------|
+| 1m       | 30..144       |
+| 5m       | 150..720      |
+| 1h       | 1800..8640    |
+| 1d       | 3456..207360  |
+
+It is **highly** recommended to override the `dynamic_roi_space()` method and define the desired ranges in it if you want values of the dynamic ROI parameters to vary in other ranges during hyperoptimization. A sample for this method can be found in [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py).
 
 ## Show details of Hyperopt results
 

freqtrade/optimize/hyperopt_interface.py

@@ -263,7 +263,6 @@ class IHyperOpt(ABC):
             Real(0, 0.005, name='dynamic_roi_end')
         ]
 
-
     # This is needed for proper unpickling the class attribute ticker_interval
     # which is set to the actual value by the resolver.
     # Why do I still need such shamanic mantras in modern python?

freqtrade/strategy/interface.py

@@ -642,16 +642,16 @@ class IStrategy(ABC):
             return None, None
 
         if 'dynamic_roi_type' in dynamic_roi and dynamic_roi['dynamic_roi_type'] \
-                              in ['linear', 'exponential', 'connect']:
+           in ['linear', 'exponential', 'connect']:
             roi_type = dynamic_roi['dynamic_roi_type']
             # linear decay: f(t) = start - (rate * t)
             if roi_type == 'linear':
                 if 'dynamic_roi_start' in dynamic_roi and 'dynamic_roi_end' in dynamic_roi and \
                    'dynamic_roi_time' in dynamic_roi:
                     start = dynamic_roi['dynamic_roi_start']
-                    end   = dynamic_roi['dynamic_roi_end']
+                    end = dynamic_roi['dynamic_roi_end']
-                    time  = dynamic_roi['dynamic_roi_time']
+                    time = dynamic_roi['dynamic_roi_time']
-                    rate  = (start - end) / time
+                    rate = (start - end) / time
                     min_roi = max(end, start - (rate * trade_dur))
                     return trade_dur, min_roi
                 else:
@@ -661,8 +661,8 @@ class IStrategy(ABC):
                 if 'dynamic_roi_start' in dynamic_roi and 'dynamic_roi_end' in dynamic_roi and \
                    'dynamic_roi_rate' in dynamic_roi:
                     start = dynamic_roi['dynamic_roi_start']
-                    end   = dynamic_roi['dynamic_roi_end']
+                    end = dynamic_roi['dynamic_roi_end']
-                    rate  = dynamic_roi['dynamic_roi_rate']
+                    rate = dynamic_roi['dynamic_roi_rate']
                     min_roi = max(end, start * np.exp(-rate*trade_dur))
                     return trade_dur, min_roi
                 else:
@@ -673,7 +673,7 @@ class IStrategy(ABC):
                     return None, None
                 # figure out where we are in the defined roi table
                 past_roi = list(filter(lambda x: x <= trade_dur, minimal_roi.keys()))
-                next_roi = list(filter(lambda x: x >  trade_dur, minimal_roi.keys()))
+                next_roi = list(filter(lambda x: x > trade_dur, minimal_roi.keys()))
                 # if we are past the final point in the table, use that key/vaule pair
                 if not past_roi:
                     return None, None
@@ -716,7 +716,7 @@ class IStrategy(ABC):
         trade_dur = int((current_time.timestamp() - trade.open_date_utc.timestamp()) // 60)
 
         if self.dynamic_roi and 'dynamic_roi_enabled' in self.dynamic_roi \
-                            and self.dynamic_roi['dynamic_roi_enabled']:
+           and self.dynamic_roi['dynamic_roi_enabled']:
             _, roi = self.min_roi_reached_dynamic(trade_dur)
         else:
             _, roi = self.min_roi_reached_entry(trade_dur)

freqtrade/templates/sample_hyperopt_advanced.py

@@ -275,9 +275,9 @@ class AdvancedSampleHyperOpt(IHyperOpt):
 
         You may override it in your custom Hyperopt class.
 
-        If you are reducing the types, you may also remove the parameters that will not be used on the 
+        If you are reducing the types, you may also remove the parameters that will not be used on
-        reduced scope.  For example, if you reduce the types to only 'connect' you do not need to specify
+        the reduced scope.  For example, if you reduce the types to only 'connect' you do not
-        the ranges for decay-rate, decay-time, start, or end.
+        need to specify the ranges for decay-rate, decay-time, start, or end.
         """
         return [
             Categorical([True, False], name='dynamic_roi_enabled'),