#
# Copyright (c) 2017 Intel Corporation
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# 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
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# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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import numpy as np
from rl_coach.core_types import ObservationType
from rl_coach.filters.observation.observation_filter import ObservationFilter
from rl_coach.spaces import ObservationSpace
[docs]class ObservationClippingFilter(ObservationFilter):
"""
Clips the observation values to a given range of values.
For example, if the observation consists of measurements in an arbitrary range,
and we want to control the minimum and maximum values of these observations,
we can define a range and clip the values of the measurements.
"""
def __init__(self, clipping_low: float=-np.inf, clipping_high: float=np.inf):
"""
:param clipping_low: The minimum value to allow after normalizing the observation
:param clipping_high: The maximum value to allow after normalizing the observation
"""
super().__init__()
self.clip_min = clipping_low
self.clip_max = clipping_high
def filter(self, observation: ObservationType, update_internal_state: bool=True) -> ObservationType:
observation = np.clip(observation, self.clip_min, self.clip_max)
return observation
def get_filtered_observation_space(self, input_observation_space: ObservationSpace) -> ObservationSpace:
return input_observation_space