freqtrade_origin/freqtrade/optimize/space/decimalspace.py
2024-05-13 07:10:25 +02:00

48 lines
1.4 KiB
Python

import numpy as np
from skopt.space import Integer
class SKDecimal(Integer):
def __init__(
self,
low,
high,
decimals=3,
prior="uniform",
base=10,
transform=None,
name=None,
dtype=np.int64,
):
self.decimals = decimals
self.pow_dot_one = pow(0.1, self.decimals)
self.pow_ten = pow(10, self.decimals)
_low = int(low * self.pow_ten)
_high = int(high * self.pow_ten)
# trunc to precision to avoid points out of space
self.low_orig = round(_low * self.pow_dot_one, self.decimals)
self.high_orig = round(_high * self.pow_dot_one, self.decimals)
super().__init__(_low, _high, prior, base, transform, name, dtype)
def __repr__(self):
return (
f"Decimal(low={self.low_orig}, high={self.high_orig}, decimals={self.decimals}, "
f"prior='{self.prior}', transform='{self.transform_}')"
)
def __contains__(self, point):
if isinstance(point, list):
point = np.array(point)
return self.low_orig <= point <= self.high_orig
def transform(self, Xt):
return super().transform([int(v * self.pow_ten) for v in Xt])
def inverse_transform(self, Xt):
res = super().inverse_transform(Xt)
# equivalent to [round(x * pow(0.1, self.decimals), self.decimals) for x in res]
return [int(v) / self.pow_ten for v in res]