# Copyright 2020 The TensorTrade Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License
from abc import abstractmethod
from tensortrade.core.component import Component
from tensortrade.core.base import TimeIndexed
[docs]class RewardScheme(Component, TimeIndexed):
"""A component to compute the reward at each step of an episode."""
registered_name = "rewards"
[docs] @abstractmethod
def reward(self, env: 'TradingEnv') -> float:
"""Computes the reward for the current step of an episode.
Parameters
----------
env : `TradingEnv`
The trading environment
Returns
-------
float
The computed reward.
"""
raise NotImplementedError()
[docs] def reset(self) -> None:
"""Resets the reward scheme."""
pass