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79 lines
2.6 KiB
Python
79 lines
2.6 KiB
Python
#
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# Copyright (c) 2017 Intel Corporation
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import math
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import matplotlib.pyplot as plt
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import numpy as np
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from rl_coach.filters.observation.observation_stacking_filter import LazyStack
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def show_observation_stack(stack, channels_last=True, show=True, force_num_rows=None, row_to_update=0):
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if isinstance(stack, LazyStack):
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stack = np.array(stack)
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if isinstance(stack, list): # is list
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stack_size = len(stack)
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elif len(stack.shape) == 3:
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stack_size = stack.shape[0] # is numpy array
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elif len(stack.shape) == 4:
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stack_size = stack.shape[1] # ignore batch dimension
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stack = stack[0]
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else:
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raise ValueError("The observation stack must be a list, a numpy array or a LazyStack object")
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if channels_last:
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stack = np.transpose(stack, (2, 0, 1))
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stack_size = stack.shape[0]
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max_cols = 10
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if force_num_rows:
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rows = force_num_rows
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else:
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rows = math.ceil(stack_size / max_cols)
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cols = max_cols if stack_size > max_cols else stack_size
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for i in range(stack_size):
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plt.subplot(rows, cols, row_to_update * cols + i + 1)
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plt.imshow(stack[i], cmap='gray')
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if show:
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plt.show()
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def show_diff_between_two_observations(observation1, observation2):
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plt.imshow(observation1 - observation2, cmap='gray')
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plt.show()
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def plot_grayscale_observation(observation):
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plt.imshow(observation, cmap='gray')
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plt.show()
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def plot_episode_states(episode_transitions, state_variable: str='state', observation_index_in_stack: int=0):
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observations = []
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for transition in episode_transitions:
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observations.append(np.array(getattr(transition, state_variable)['observation'])[..., observation_index_in_stack])
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show_observation_stack(observations, False)
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def plot_list_of_observation_stacks(observation_stacks):
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for idx, stack in enumerate(observation_stacks):
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show_observation_stack(stack['observation'], True, False,
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force_num_rows=len(observation_stacks), row_to_update=idx)
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plt.show()
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