adelorenzo/stable
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Merge commit 'e3d222912dfd775b7456a44d6d6055430711f251' into feature/objectify

Browse Source
This commit is contained in:
Gerald Lonlas 2018-03-04 00:51:22 -08:00
commit 722ed48d9d
8 changed files with 119 additions and 26 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

45
docs/hyperopt.md
View File

@ -51,12 +51,12 @@ def populate_buy_trend(dataframe: DataFrame) -> 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
means you will need to enable/disable triggers.
In our case the `SPACE` and `populate_buy_trend` in your strategy file
will be look like:
will look like:
```python
space = {
'rsi': hp.choice('rsi', [
@ -105,7 +105,7 @@ def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
### 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
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)}
]),
```
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*".
So, the part of the strategy builder using the above setting looks like
this:
```
if params['rsi']['enabled']:
conditions.append(dataframe['rsi'] < params['rsi']['value'])
```
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
condition that says RSI must be < than the value hyperopt picked
for this evaluation, that is given in the `params['rsi']['value']`.
condition that says RSI must be smaller than the value hyperopt picked
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
will try all the combinations with all different values in the search
@ -148,8 +150,7 @@ for best working algo.
### Add a new Indicators
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))
inside the `populate_indicators()` method.
you need to add it to the `populate_indicators()` method in `hyperopt.py`.
## Execute Hyperopt
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.
```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
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
use data from directory `user_data/data`.
### 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.
Example:
@ -176,6 +179,21 @@ Example:
python3 ./freqtrade/main.py hyperopt --timeperiod -200
```
### Running hyperopt with smaller search space
Use the `--spaces` argument to limit the search space used by hyperopt.
Letting Hyperopt optimize everything is a huuuuge search space. Often it
might make more sense to start by just searching for initial buy algorithm.
Or maybe you just want to optimize your stoploss or roi table for that awesome
new buy strategy you have.
Legal values are:
- `all`: optimize everything
- `buy`: just search for a new buy strategy
- `roi`: just optimize the minimal profit table for your strategy
- `stoploss`: search for the best stoploss value
- space-separated list of any of the above values for example `--spaces roi stoploss`
### Hyperopt with MongoDB
Hyperopt with MongoDB, is like Hyperopt under steroids. As you saw by
executing the previous command is the execution takes a long time.
@ -267,7 +285,6 @@ customizable value.
- You should **ignore** the guard "mfi" (`"mfi"` is `"enabled": false`)
- and so on...
You have to look inside your strategy file into `buy_strategy_generator()`
method, what those values match to.
@ -277,7 +294,7 @@ at `adx`-block, that translates to the following code block:
(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:
```
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:

9
freqtrade/arguments.py
View File

@ -180,6 +180,15 @@ class Arguments(object):
type=str,
dest='timerange',
)
parser.add_argument(
'-s', '--spaces',
help='Specify which parameters to hyperopt. Space separate list. \
Default: %(default)s',
choices=['all', 'buy', 'roi', 'stoploss'],
default='all',
nargs='+',
dest='spaces',
)
def _build_subcommands(self) -> None:
"""

5
freqtrade/configuration.py
View File

@ -156,6 +156,11 @@ class Configuration(object):
config.update({'mongodb': self.args.mongodb})
self.logger.info('Parameter --use-mongodb detected ...')
# If --spaces is used we add it to the configuration
if 'spaces' in self.args and self.args.spaces:
config.update({'spaces': self.args.spaces})
self.logger.info('Parameter -s/--spaces detected: %s', config.get('spaces'))
return config
def _validate_config(self, conf: Dict[str, Any]) -> Dict[str, Any]:

1
freqtrade/optimize/backtesting.py
View File

@ -33,7 +33,6 @@ class Backtesting(object):
# Init the logger
self.logging = Logger(name=__name__, level=config['loglevel'])
self.logger = self.logging.get_logger()
self.config = config
self.analyze = None
self.ticker_interval = None

37
freqtrade/optimize/hyperopt.py
View File

@ -335,16 +335,26 @@ class Hyperopt(Backtesting):
]),
}
@staticmethod
def hyperopt_space() -> Dict[str, Any]:
def has_space(self, space) -> bool:
"""
Tell if a space value is contained in the configuration
"""
if space in self.config['spaces'] or 'all' in self.config['spaces']:
return True
return False
def hyperopt_space(self) -> Dict[str, Any]:
"""
Return the space to use during Hyperopt
"""
return {
**Hyperopt.indicator_space(),
**Hyperopt.roi_space(),
**Hyperopt.stoploss_space()
}
spaces = {}
if self.has_space('buy'):
spaces = {**spaces, **Hyperopt.indicator_space()}
if self.has_space('roi'):
spaces = {**spaces, **Hyperopt.roi_space()}
if self.has_space('stoploss'):
spaces = {**spaces, **Hyperopt.stoploss_space()}
return spaces
@staticmethod
def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
@ -427,13 +437,19 @@ class Hyperopt(Backtesting):
if 'roi_t1' in params:
self.analyze.strategy.minimal_roi = self.generate_roi_table(params)
self.populate_buy_trend = self.buy_strategy_generator(params)
if 'trigger' in params:
self.populate_buy_trend = self.buy_strategy_generator(params)
if 'stoploss' in params:
stoploss = params['stoploss']
else:
stoploss = self.analyze.strategy.stoploss
results = self.backtest(
{
'stake_amount': self.config['stake_amount'],
'processed': self.processed,
'stoploss': params['stoploss']
'stoploss': stoploss
}
)
result_explanation = self.format_results(results)
@ -491,7 +507,8 @@ class Hyperopt(Backtesting):
timerange=timerange
)
self.analyze.populate_indicators = Hyperopt.populate_indicators
if self.has_space('buy'):
self.analyze.populate_indicators = Hyperopt.populate_indicators
self.processed = self.tickerdata_to_dataframe(data)
if self.config.get('mongodb'):

18
freqtrade/tests/optimize/test_hyperopt.py
View File

@ -126,6 +126,7 @@ def test_fmin_best_results(mocker, default_conf, caplog) -> None:
conf.update({'config': 'config.json.example'})
conf.update({'epochs': 1})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value=fmin_result)
@ -173,6 +174,7 @@ def test_fmin_throw_value_error(mocker, default_conf, caplog) -> None:
conf.update({'config': 'config.json.example'})
conf.update({'epochs': 1})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
mocker.patch('freqtrade.logger.Logger.set_format', MagicMock())
@ -200,6 +202,7 @@ def test_resuming_previous_hyperopt_results_succeeds(mocker, default_conf) -> No
conf.update({'epochs': 1})
conf.update({'mongodb': False})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
mocker.patch('freqtrade.optimize.hyperopt.os.path.exists', return_value=True)
mocker.patch('freqtrade.optimize.hyperopt.len', return_value=len(trials.results))
@ -290,6 +293,7 @@ def test_start_calls_fmin(mocker, default_conf) -> None:
conf.update({'epochs': 1})
conf.update({'mongodb': False})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
hyperopt = Hyperopt(conf)
hyperopt.trials = trials
@ -312,6 +316,7 @@ def test_start_uses_mongotrials(mocker, default_conf) -> None:
conf.update({'epochs': 1})
conf.update({'mongodb': True})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
hyperopt = Hyperopt(conf)
@ -353,3 +358,16 @@ def test_signal_handler(mocker):
hyperopt = _HYPEROPT
hyperopt.signal_handler(9, None)
assert m.call_count == 3
def test_has_space():
"""
Test Hyperopt.has_space() method
"""
_HYPEROPT.config.update({'spaces': ['buy', 'roi']})
assert _HYPEROPT.has_space('roi')
assert _HYPEROPT.has_space('buy')
assert not _HYPEROPT.has_space('stoploss')
_HYPEROPT.config.update({'spaces': ['all']})
assert _HYPEROPT.has_space('buy')

8
freqtrade/tests/test_arguments.py
View File

@ -118,10 +118,16 @@ def test_parse_args_backtesting_custom() -> None:
def test_parse_args_hyperopt_custom() -> None:
args = ['-c', 'test_conf.json', 'hyperopt', '--epochs', '20']
args = [
'-c', 'test_conf.json',
'hyperopt',
'--epochs', '20',
'--spaces', 'buy'
]
call_args = Arguments(args, '').get_parsed_arg()
assert call_args.config == 'test_conf.json'
assert call_args.epochs == 20
assert call_args.loglevel == logging.INFO
assert call_args.subparser == 'hyperopt'
assert call_args.spaces == 'buy'
assert call_args.func is not None

22
freqtrade/tests/test_configuration.py
View File

@ -261,3 +261,25 @@ def test_setup_configuration_with_arguments(mocker, default_conf, caplog) -> Non
'Parameter --export detected: {} ...'.format(config['export']),
caplog.record_tuples
)
def test_hyperopt_space_argument(mocker, default_conf, caplog) -> None:
"""
Test setup_configuration() function
"""
mocker.patch('freqtrade.configuration.open', mocker.mock_open(
read_data=json.dumps(default_conf)
))
args = [
'hyperopt',
'--spaces', 'all',
]
args = Arguments(args, '').get_parsed_arg()
configuration = Configuration(args)
config = configuration.get_config()
assert 'spaces' in config
assert config['spaces'] is 'all'
assert tt.log_has('Parameter -s/--spaces detected: all', caplog.record_tuples)