allow user to drop ohlc from features in RL

docs/freqai-parameter-table.md

@@ -84,6 +84,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the
 | `add_state_info` | Tell FreqAI to include state information in the feature set for training and inferencing. The current state variables include trade duration, current profit, trade position. This is only available in dry/live runs, and is automatically switched to false for backtesting. <br> **Datatype:** bool. <br> Default: `False`.
 | `net_arch` | Network architecture which is well described in [`stable_baselines3` doc](https://stable-baselines3.readthedocs.io/en/master/guide/custom_policy.html#examples). In summary: `[<shared layers>, dict(vf=[<non-shared value network layers>], pi=[<non-shared policy network layers>])]`. By default this is set to `[128, 128]`, which defines 2 shared hidden layers with 128 units each.
 | `randomize_starting_position` | Randomize the starting point of each episode to avoid overfitting. <br> **Datatype:** bool. <br> Default: `False`.
+| `drop_ohlc_from_features` | Do not include the normalized ohlc data in the feature set passed to the agent during training (ohlc will still be used for driving the environment in all cases) <br> **Datatype:** Boolean. <br> **Default:** `False`
 
 ### Additional parameters
 

docs/freqai-reinforcement-learning.md

@@ -176,9 +176,11 @@ As you begin to modify the strategy and the prediction model, you will quickly r
 
                 factor = 100
 
+                pair = self.pair.replace(':', '')
+
                 # you can use feature values from dataframe
                 # Assumes the shifted RSI indicator has been generated in the strategy.
-                rsi_now = self.raw_features[f"%-rsi-period-10_shift-1_{self.pair}_"
+                rsi_now = self.raw_features[f"%-rsi-period-10_shift-1_{pair}_"
                                 f"{self.config['timeframe']}"].iloc[self._current_tick]
 
                 # reward agent for entering trades