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Flake8 compliance and documentation for hyperopt in strategy file

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Stephen Dade
2018-03-01 19:58:37 +11:00
parent 41b9165495
commit e4d29e473b
4 changed files with 44 additions and 40 deletions
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60
docs/hyperopt.md
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@@ -19,8 +19,8 @@ your strategy file located into [user_data/strategies/](https://github.com/gcarq
### 1. Configure your Guards and Triggers
There are two places you need to change in your strategy file to add a
new buy strategy for testing:
- Inside [populate_buy_trend()](https://github.com/gcarq/freqtrade/blob/develop/user_data/strategies/test_strategy.py#L278-L294).
- Inside [hyperopt_space()](https://github.com/gcarq/freqtrade/blob/develop/user_data/strategies/test_strategy.py#L244-L297) known as `SPACE`.
- Inside [populate_buy_trend()](https://github.com/gcarq/freqtrade/blob/develop/user_data/strategies/test_strategy.py#L273-L294).
- Inside [indicator_space()](https://github.com/gcarq/freqtrade/blob/develop/user_data/strategies/test_strategy.py#L251-L67).
There you have two different type of indicators: 1. `guards` and 2.
`triggers`.
@@ -55,29 +55,33 @@ Your hyperopt file must contain `guards` to find the right value for
`(dataframe['adx'] > 65)` & and `(dataframe['plus_di'] > 0.5)`. That
means you will need to enable/disable triggers.
In our case the `SPACE` and `populate_buy_trend` in your strategy file
In our case the `indicator_space` and `populate_buy_trend` in your strategy file
will look like:
```python
space = {
'rsi': hp.choice('rsi', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('rsi-value', 20, 40, 1)}
]),
'adx': hp.choice('adx', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('adx-value', 15, 50, 1)}
]),
'trigger': hp.choice('trigger', [
{'type': 'lower_bb'},
{'type': 'faststoch10'},
{'type': 'ao_cross_zero'},
{'type': 'ema5_cross_ema10'},
{'type': 'macd_cross_signal'},
{'type': 'sar_reversal'},
{'type': 'stochf_cross'},
{'type': 'ht_sine'},
]),
}
def indicator_space(self) -> Dict[str, Any]:
"""
Define your Hyperopt space for searching strategy parameters
"""
return {
'rsi': hp.choice('rsi', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('rsi-value', 20, 40, 1)}
]),
'adx': hp.choice('adx', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('adx-value', 15, 50, 1)}
]),
'trigger': hp.choice('trigger', [
{'type': 'lower_bb'},
{'type': 'faststoch10'},
{'type': 'ao_cross_zero'},
{'type': 'ema5_cross_ema10'},
{'type': 'macd_cross_signal'},
{'type': 'sar_reversal'},
{'type': 'stochf_cross'},
{'type': 'ht_sine'},
]),
}
...
@@ -100,7 +104,13 @@ def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
'stochf_cross': (crossed_above(dataframe['fastk'], dataframe['fastd'])),
'ht_sine': (crossed_above(dataframe['htleadsine'], dataframe['htsine'])),
}
...
conditions.append(triggers.get(params['trigger']['type']))
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
'buy'] = 1
return dataframe
```
@@ -116,7 +126,7 @@ The Hyperopt configuration is located in
## Advanced notions
### Understand the Guards and Triggers
When you need to add the new guards and triggers to be hyperopt
parameters, you do this by adding them into the [hyperopt_space()](https://github.com/gcarq/freqtrade/blob/develop/user_data/strategies/test_strategy.py#L244-L297).
parameters, you do this by adding them into the [indicator_space()](https://github.com/gcarq/freqtrade/blob/develop/user_data/strategies/test_strategy.py#L251-L267).
If it's a trigger, you add one line to the 'trigger' choice group and that's it.