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Rename benchmark variables and add h1 to notebooks

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This commit is contained in:
Marek Wolan
2024-06-10 12:58:07 +01:00
parent 2a6a16b222
commit c538aee022
8 changed files with 18 additions and 18 deletions
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2
src/primaite/notebooks/Data-Manipulation-Customising-Red-Agent.ipynb
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@@ -458,7 +458,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.11"
"version": "3.10.12"
}
},
"nbformat": 4,

4
src/primaite/notebooks/Training-an-RLLIB-MARL-System.ipynb
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@@ -4,7 +4,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"## Train a Multi agent system using RLLIB\n",
"# Train a Multi agent system using RLLIB\n",
"\n",
"© Crown-owned copyright 2024, Defence Science and Technology Laboratory UK\n",
"\n",
@@ -108,7 +108,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.8"
"version": "3.10.12"
}
},
"nbformat": 4,

4
src/primaite/notebooks/Training-an-RLLib-Agent.ipynb
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@@ -4,7 +4,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"## Train a Single agent system using RLLib\n",
"# Train a Single agent system using RLLib\n",
"\n",
"© Crown-owned copyright 2024, Defence Science and Technology Laboratory UK\n",
"\n",
@@ -99,7 +99,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.8"
"version": "3.10.12"
}
},
"nbformat": 4,

2
src/primaite/notebooks/Using-Episode-Schedules.ipynb
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@@ -328,7 +328,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.11"
"version": "3.10.12"
}
},
"nbformat": 4,

4
src/primaite/notebooks/multi-processing.ipynb
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@@ -4,7 +4,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"## Simple multi-processing demonstration\n",
"# Simple multi-processing demonstration\n",
"\n",
"© Crown-owned copyright 2024, Defence Science and Technology Laboratory UK\n",
"\n",
@@ -143,7 +143,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.11"
"version": "3.10.12"
}
},
"nbformat": 4,

4
src/primaite/session/environment.py
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@@ -37,7 +37,7 @@ class PrimaiteGymEnv(gymnasium.Env):
"""Name of the RL agent. Since there should only be one RL agent we can just pull the first and only key."""
self.episode_counter: int = 0
"""Current episode number."""
self.average_reward_per_episode: Dict[int, float] = {}
self.total_reward_per_episode: Dict[int, float] = {}
"""Average rewards of agents per episode."""
@property
@@ -91,7 +91,7 @@ class PrimaiteGymEnv(gymnasium.Env):
f"Resetting environment, episode {self.episode_counter}, "
f"avg. reward: {self.agent.reward_function.total_reward}"
)
self.average_reward_per_episode[self.episode_counter] = self.agent.reward_function.total_reward
self.total_reward_per_episode[self.episode_counter] = self.agent.reward_function.total_reward
if self.io.settings.save_agent_actions:
all_agent_actions = {name: agent.history for name, agent in self.game.agents.items()}

6
src/primaite/utils/session_output_reader.py
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@@ -11,16 +11,16 @@ from typing import Any, Dict, Tuple, Union
import polars as pl
def av_rewards_dict(av_rewards_csv_file: Union[str, Path]) -> Dict[int, float]:
def total_rewards_dict(total_rewards_csv_file: Union[str, Path]) -> Dict[int, float]:
"""
Read an average rewards per episode csv file and return as a dict.
The dictionary keys are the episode number, and the values are the mean reward that episode.
:param av_rewards_csv_file: The average rewards per episode csv file path.
:param total_rewards_csv_file: The average rewards per episode csv file path.
:return: The average rewards per episode csv as a dict.
"""
df_dict = pl.read_csv(av_rewards_csv_file).to_dict()
df_dict = pl.read_csv(total_rewards_csv_file).to_dict()
return {int(v): df_dict["Average Reward"][i] for i, v in enumerate(df_dict["Episode"])}

10
src/primaite/utils/session_output_writer.py
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@@ -26,9 +26,9 @@ class SessionOutputWriter:
Is used to write session outputs to csv file.
"""
_AV_REWARD_PER_EPISODE_HEADER: Final[List[str]] = [
_TOTAL_REWARD_PER_EPISODE_HEADER: Final[List[str]] = [
"Episode",
"Average Reward",
"Total Reward",
]
def __init__(
@@ -43,7 +43,7 @@ class SessionOutputWriter:
:param env: PrimAITE gym environment.
:type env: Primaite
:param transaction_writer: If `true`, this will output a full account of every transaction taken by the agent.
If `false` it will output the average reward per episode, defaults to False
If `false` it will output the total reward per episode, defaults to False
:type transaction_writer: bool, optional
:param learning_session: Set to `true` to indicate that the current session is a training session. This
determines the name of the folder which contains the final output csv. Defaults to True
@@ -56,7 +56,7 @@ class SessionOutputWriter:
if self.transaction_writer:
fn = f"all_transactions_{self._env.timestamp_str}.csv"
else:
fn = f"average_reward_per_episode_{self._env.timestamp_str}.csv"
fn = f"total_reward_per_episode_{self._env.timestamp_str}.csv"
self._csv_file_path: "Path"
if self.learning_session:
@@ -94,7 +94,7 @@ class SessionOutputWriter:
if isinstance(data, Transaction):
header, data = data.as_csv_data()
else:
header = self._AV_REWARD_PER_EPISODE_HEADER
header = self._TOTAL_REWARD_PER_EPISODE_HEADER
if self._first_write:
self._init_csv_writer()