Add range property to CategoricalParameter and DecimalParameter, add their tests.

At the moment we can keep a single code path when using IntParameter, but we have to make a special hyperopt case for CategoricalParameter/DecimalParameter. Range property solves this.
This commit is contained in:
Rokas Kupstys 2021-07-03 10:08:52 +03:00
parent 9d6860337f
commit 3686efa08a
3 changed files with 51 additions and 5 deletions

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@ -403,6 +403,9 @@ While this strategy is most likely too simple to provide consistent profit, it s
!!! Note !!! Note
`self.buy_ema_short.range` will act differently between hyperopt and other modes. For hyperopt, the above example may generate 48 new columns, however for all other modes (backtesting, dry/live), it will only generate the column for the selected value. You should therefore avoid using the resulting column with explicit values (values other than `self.buy_ema_short.value`). `self.buy_ema_short.range` will act differently between hyperopt and other modes. For hyperopt, the above example may generate 48 new columns, however for all other modes (backtesting, dry/live), it will only generate the column for the selected value. You should therefore avoid using the resulting column with explicit values (values other than `self.buy_ema_short.value`).
!!! Note
`range` property may also be used with `DecimalParameter` and `CategoricalParameter`. `RealParameter` does not provide this property due to infinite search space.
??? Hint "Performance tip" ??? Hint "Performance tip"
By doing the calculation of all possible indicators in `populate_indicators()`, the calculation of the indicator happens only once for every parameter. By doing the calculation of all possible indicators in `populate_indicators()`, the calculation of the indicator happens only once for every parameter.
While this may slow down the hyperopt startup speed, the overall performance will increase as the Hyperopt execution itself may pick the same value for multiple epochs (changing other values). While this may slow down the hyperopt startup speed, the overall performance will increase as the Hyperopt execution itself may pick the same value for multiple epochs (changing other values).

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@ -205,6 +205,21 @@ class DecimalParameter(NumericParameter):
return SKDecimal(low=self.low, high=self.high, decimals=self._decimals, name=name, return SKDecimal(low=self.low, high=self.high, decimals=self._decimals, name=name,
**self._space_params) **self._space_params)
@property
def range(self):
"""
Get each value in this space as list.
Returns a List from low to high (inclusive) in Hyperopt mode.
Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
calculating 100ds of indicators.
"""
if self.in_space and self.optimize:
low = int(self.low * pow(10, self._decimals))
high = int(self.high * pow(10, self._decimals)) + 1
return [round(n * pow(0.1, self._decimals), self._decimals) for n in range(low, high)]
else:
return [self.value]
class CategoricalParameter(BaseParameter): class CategoricalParameter(BaseParameter):
default: Any default: Any
@ -239,6 +254,19 @@ class CategoricalParameter(BaseParameter):
""" """
return Categorical(self.opt_range, name=name, **self._space_params) return Categorical(self.opt_range, name=name, **self._space_params)
@property
def range(self):
"""
Get each value in this space as list.
Returns a List of categories in Hyperopt mode.
Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
calculating 100ds of indicators.
"""
if self.in_space and self.optimize:
return self.opt_range
else:
return [self.value]
class HyperStrategyMixin(object): class HyperStrategyMixin(object):
""" """

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@ -12,6 +12,7 @@ from freqtrade.data.dataprovider import DataProvider
from freqtrade.data.history import load_data from freqtrade.data.history import load_data
from freqtrade.enums import SellType from freqtrade.enums import SellType
from freqtrade.exceptions import OperationalException, StrategyError from freqtrade.exceptions import OperationalException, StrategyError
from freqtrade.optimize.space import SKDecimal
from freqtrade.persistence import PairLocks, Trade from freqtrade.persistence import PairLocks, Trade
from freqtrade.resolvers import StrategyResolver from freqtrade.resolvers import StrategyResolver
from freqtrade.strategy.hyper import (BaseParameter, CategoricalParameter, DecimalParameter, from freqtrade.strategy.hyper import (BaseParameter, CategoricalParameter, DecimalParameter,
@ -657,17 +658,31 @@ def test_hyperopt_parameters():
assert list(intpar.range) == [0, 1, 2, 3, 4, 5] assert list(intpar.range) == [0, 1, 2, 3, 4, 5]
fltpar = RealParameter(low=0.0, high=5.5, default=1.0, space='buy') fltpar = RealParameter(low=0.0, high=5.5, default=1.0, space='buy')
assert fltpar.value == 1
assert isinstance(fltpar.get_space(''), Real) assert isinstance(fltpar.get_space(''), Real)
assert fltpar.value == 1
fltpar = DecimalParameter(low=0.0, high=5.5, default=1.0004, decimals=3, space='buy') fltpar = DecimalParameter(low=0.0, high=0.5, default=0.14, decimals=1, space='buy')
assert isinstance(fltpar.get_space(''), Integer) assert fltpar.value == 0.1
assert fltpar.value == 1 assert isinstance(fltpar.get_space(''), SKDecimal)
assert isinstance(fltpar.range, list)
assert len(list(fltpar.range)) == 1
# Range contains ONLY the default / value.
assert list(fltpar.range) == [fltpar.value]
fltpar.in_space = True
assert len(list(fltpar.range)) == 6
assert list(fltpar.range) == [0.0, 0.1, 0.2, 0.3, 0.4, 0.5]
catpar = CategoricalParameter(['buy_rsi', 'buy_macd', 'buy_none'], catpar = CategoricalParameter(['buy_rsi', 'buy_macd', 'buy_none'],
default='buy_macd', space='buy') default='buy_macd', space='buy')
assert isinstance(catpar.get_space(''), Categorical)
assert catpar.value == 'buy_macd' assert catpar.value == 'buy_macd'
assert isinstance(catpar.get_space(''), Categorical)
assert isinstance(catpar.range, list)
assert len(list(catpar.range)) == 1
# Range contains ONLY the default / value.
assert list(catpar.range) == [catpar.value]
catpar.in_space = True
assert len(list(catpar.range)) == 3
assert list(catpar.range) == ['buy_rsi', 'buy_macd', 'buy_none']
def test_auto_hyperopt_interface(default_conf): def test_auto_hyperopt_interface(default_conf):