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small corrections and typo fixes to hyperopt documentation

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Janne Sinivirta 2018-02-10 10:59:18 +02:00
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@ -51,12 +51,12 @@ def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
return dataframe return dataframe
``` ```
Your hyperopt file must contains `guards` to find the right value for Your hyperopt file must contain `guards` to find the right value for
`(dataframe['adx'] > 65)` & and `(dataframe['plus_di'] > 0.5)`. That `(dataframe['adx'] > 65)` & and `(dataframe['plus_di'] > 0.5)`. That
means you will need to enable/disable triggers. 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 `SPACE` and `populate_buy_trend` in your strategy file
will be look like: will look like:
```python ```python
space = { space = {
'rsi': hp.choice('rsi', [ 'rsi': hp.choice('rsi', [
@ -105,7 +105,7 @@ def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
### 2. Update the hyperopt config file ### 2. Update the hyperopt config file
Hyperopt is using a dedicated config file. At this moment hyperopt Hyperopt is using a dedicated config file. Currently hyperopt
cannot use your config file. It is also made on purpose to allow you cannot use your config file. It is also made on purpose to allow you
testing your strategy with different configurations. testing your strategy with different configurations.
@ -127,19 +127,21 @@ If it's a guard, you will add a line like this:
{'enabled': True, 'value': hp.quniform('rsi-value', 20, 40, 1)} {'enabled': True, 'value': hp.quniform('rsi-value', 20, 40, 1)}
]), ]),
``` ```
This says, "*one of guards is RSI, it can have two values, enabled or This says, "*one of the guards is RSI, it can have two values, enabled or
disabled. If it is enabled, try different values for it between 20 and 40*". disabled. If it is enabled, try different values for it between 20 and 40*".
So, the part of the strategy builder using the above setting looks like So, the part of the strategy builder using the above setting looks like
this: this:
``` ```
if params['rsi']['enabled']: if params['rsi']['enabled']:
conditions.append(dataframe['rsi'] < params['rsi']['value']) conditions.append(dataframe['rsi'] < params['rsi']['value'])
``` ```
It checks if Hyperopt wants the RSI guard to be enabled for this It checks if Hyperopt wants the RSI guard to be enabled for this
round `params['rsi']['enabled']` and if it is, then it will add a round `params['rsi']['enabled']` and if it is, then it will add a
condition that says RSI must be < than the value hyperopt picked condition that says RSI must be smaller than the value hyperopt picked
for this evaluation, that is given in the `params['rsi']['value']`. for this evaluation, which is given in the `params['rsi']['value']`.
That's it. Now you can add new parts of strategies to Hyperopt and it That's it. Now you can add new parts of strategies to Hyperopt and it
will try all the combinations with all different values in the search will try all the combinations with all different values in the search
@ -148,8 +150,7 @@ for best working algo.
### Add a new Indicators ### Add a new Indicators
If you want to test an indicator that isn't used by the bot currently, If you want to test an indicator that isn't used by the bot currently,
you need to add it to your strategy file (example: [user_data/strategies/test_strategy.py](https://github.com/gcarq/freqtrade/blob/develop/user_data/strategies/test_strategy.py)) you need to add it to the `populate_indicators()` method in `hyperopt.py`.
inside the `populate_indicators()` method.
## Execute Hyperopt ## Execute Hyperopt
Once you have updated your hyperopt configuration you can run it. Once you have updated your hyperopt configuration you can run it.
@ -158,17 +159,19 @@ it will take time you will have the result (more than 30 mins).
We strongly recommend to use `screen` to prevent any connection loss. We strongly recommend to use `screen` to prevent any connection loss.
```bash ```bash
python3 ./freqtrade/main.py -c config.json hyperopt python3 ./freqtrade/main.py -c config.json hyperopt -e 5000
``` ```
The `-e` flag will set how many evaluations hyperopt will do. We recommend
running at least several thousand evaluations.
### Execute hyperopt with different ticker-data source ### Execute hyperopt with different ticker-data source
If you would like to learn parameters using an alternate ticke-data that If you would like to hyperopt parameters using an alternate ticker data that
you have on-disk, use the `--datadir PATH` option. Default hyperopt will you have on-disk, use the `--datadir PATH` option. Default hyperopt will
use data from directory `user_data/data`. use data from directory `user_data/data`.
### Running hyperopt with smaller testset ### Running hyperopt with smaller testset
Use the `--timeperiod` argument to change how much of the testset
Use the --timeperiod argument to change how much of the testset
you want to use. The last N ticks/timeframes will be used. you want to use. The last N ticks/timeframes will be used.
Example: Example:
@ -267,7 +270,6 @@ customizable value.
- You should **ignore** the guard "mfi" (`"mfi"` is `"enabled": false`) - You should **ignore** the guard "mfi" (`"mfi"` is `"enabled": false`)
- and so on... - and so on...
You have to look inside your strategy file into `buy_strategy_generator()` You have to look inside your strategy file into `buy_strategy_generator()`
method, what those values match to. method, what those values match to.
@ -277,7 +279,7 @@ at `adx`-block, that translates to the following code block:
(dataframe['adx'] > 15.0) (dataframe['adx'] > 15.0)
``` ```
So translating your whole hyperopt result to as the new buy-signal Translating your whole hyperopt result to as the new buy-signal
would be the following: would be the following:
``` ```
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame: def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame: