80 lines
2.6 KiB
Python
80 lines
2.6 KiB
Python
# Crown Copyright (C) Dstl 2022. DEFCON 703. Shared in confidence.
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import tempfile
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import time
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from datetime import datetime
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from pathlib import Path
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from typing import Union
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from primaite.environment.primaite_env import Primaite
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ACTION_SPACE_NODE_VALUES = 1
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ACTION_SPACE_NODE_ACTION_VALUES = 1
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def _get_temp_session_path(session_timestamp: datetime) -> Path:
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"""
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Get a temp directory session path the test session will output to.
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:param session_timestamp: This is the datetime that the session started.
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:return: The session directory path.
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"""
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date_dir = session_timestamp.strftime("%Y-%m-%d")
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session_path = session_timestamp.strftime("%Y-%m-%d_%H-%M-%S")
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session_path = Path(tempfile.gettempdir()) / "primaite" / date_dir / session_path
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session_path.mkdir(exist_ok=True, parents=True)
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return session_path
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def _get_primaite_env_from_config(
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training_config_path: Union[str, Path], lay_down_config_path: Union[str, Path]
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):
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"""Takes a config path and returns the created instance of Primaite."""
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session_timestamp: datetime = datetime.now()
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session_path = _get_temp_session_path(session_timestamp)
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timestamp_str = session_timestamp.strftime("%Y-%m-%d_%H-%M-%S")
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env = Primaite(
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training_config_path=training_config_path,
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lay_down_config_path=lay_down_config_path,
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session_path=session_path,
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timestamp_str=timestamp_str,
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)
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config_values = env.training_config
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config_values.num_steps = env.episode_steps
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# TOOD: This needs t be refactored to happen outside. Should be part of
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# a main Session class.
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if env.training_config.agent_identifier == "GENERIC":
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run_generic(env, config_values)
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return env
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def run_generic(env, config_values):
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"""Run against a generic agent."""
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# Reset the environment at the start of the episode
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# env.reset()
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for episode in range(0, config_values.num_episodes):
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for step in range(0, config_values.num_steps):
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# Send the observation space to the agent to get an action
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# TEMP - random action for now
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# action = env.blue_agent_action(obs)
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# action = env.action_space.sample()
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action = 0
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# Run the simulation step on the live environment
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obs, reward, done, info = env.step(action)
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# Break if done is True
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if done:
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break
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# Introduce a delay between steps
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time.sleep(config_values.time_delay / 1000)
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# Reset the environment at the end of the episode
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# env.reset()
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# env.close()
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