# 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
import numpy as np
from gym.spaces import Space
from tensortrade.core.component import Component
from tensortrade.core.base import TimeIndexed
[docs]class Observer(Component, TimeIndexed):
"""A component to generate an observation at each step of an episode.
"""
registered_name = "observer"
@property
@abstractmethod
def observation_space(self) -> Space:
"""The observation space of the `TradingEnv`. (`Space`, read-only)
"""
raise NotImplementedError()
[docs] @abstractmethod
def observe(self, env: 'TradingEnv') -> np.array:
"""Gets the observation at the current step of an episode
Parameters
----------
env: 'TradingEnv'
The trading environment.
Returns
-------
`np.array`
The current observation of the environment.
"""
raise NotImplementedError()
[docs] def reset(self):
"""Resets the observer."""
pass