mirror of
https://github.com/GoodStartLabs/AI_Diplomacy.git
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patched for compatability with new data logging structure
This commit is contained in:
peregrinates
parent
f7c3949e57
commit
975c4f59b9
5 changed files with 407 additions and 186 deletions
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@ -53,24 +53,32 @@ Return / save
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import pandas as pd
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import numpy as np
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import os
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import copy
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import re
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import argparse
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import warnings
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from pathlib import Path
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from analysis.analysis_helpers import process_standard_game_inputs, COUNTRIES, supply_centers, coastal_scs, place_identifier, unit_identifier, unit_move, possible_commands
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from analysis.analysis_helpers import process_standard_game_inputs, get_country_to_model_mapping, COUNTRIES, ALL_SUPPLY_CENTERS, COASTAL_SCs, PLACE_IDENTIFIER, UNIT_IDENTIFIER, UNIT_MOVE, POSSIBLE_COMMANDS
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from tqdm import tqdm
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import traceback
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from typing import List, Optional, Dict, Any
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# Suppress pandas warnings
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warnings.filterwarnings('ignore', category=UserWarning, module='pandas.core.strings')
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warnings.filterwarnings('ignore', category=pd.errors.SettingWithCopyWarning)
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def make_longform_order_data(overview : pd.DataFrame, lmvs_data : pd.DataFrame, all_responses : pd.DataFrame) -> pd.DataFrame:
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try:
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country_to_model = overview.loc[1, COUNTRIES] # map countries to models
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except:
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country_to_model = {country: "not specified in overview.jsonl" for country in COUNTRIES}
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def make_longform_order_data(country_to_model : pd.Series, lmvs_data : pd.DataFrame, all_responses : pd.DataFrame) -> pd.DataFrame:
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"""
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Makes a dataframe with a row for each order given by every power, in every phase (see module docstring for more details).
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Args:
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country_to_model: A Series mapping country names to model names
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lmvs_data: A DataFrame containing the game data
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all_responses: A DataFrame containing the responses from the LLM responses csv
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Returns:
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A DataFrame with a row for each order given by every power, in every phase
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"""
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################## PART 1 ##################
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# build `turn_actions` dataframe
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@ -120,22 +128,22 @@ def make_longform_order_data(overview : pd.DataFrame, lmvs_data : pd.DataFrame,
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# categorize each order based on regex
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# note that this will overwrite if multiple regexes match, which is why we've split support into 2 commands
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for possible_command, regex in possible_commands.items():
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for possible_command, regex in POSSIBLE_COMMANDS.items():
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all_orders_ever.loc[all_orders_ever.order.str.contains(regex, regex=True), "command"] = possible_command
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all_orders_ever["unit_location"] = all_orders_ever["order"].str.extract(rf"({place_identifier})")
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all_orders_ever["location_was_sc"] = all_orders_ever["unit_location"].isin(supply_centers) | all_orders_ever["unit_location"].isin(coastal_scs)
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all_orders_ever["unit_location"] = all_orders_ever["order"].str.extract(rf"({PLACE_IDENTIFIER})")
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all_orders_ever["location_was_sc"] = all_orders_ever["unit_location"].isin(ALL_SUPPLY_CENTERS) | all_orders_ever["unit_location"].isin(COASTAL_SCs)
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# only MOVE has a destination
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all_orders_ever["destination"] = np.where(
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all_orders_ever["command"]=="Move",
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all_orders_ever["order"].str.extract(rf"{unit_identifier} . ({place_identifier})", expand=False),
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all_orders_ever["order"].str.extract(rf"{UNIT_IDENTIFIER} . ({PLACE_IDENTIFIER})", expand=False),
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np.nan
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)
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all_orders_ever["destination_was_sc"] = all_orders_ever["destination"].isin(supply_centers) | all_orders_ever["destination"].isin(coastal_scs)
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all_orders_ever["destination_was_sc"] = all_orders_ever["destination"].isin(ALL_SUPPLY_CENTERS) | all_orders_ever["destination"].isin(COASTAL_SCs)
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# Retreat also has a destination
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all_orders_ever.loc[all_orders_ever["command"]=="Retreat", "destination"] = all_orders_ever.loc[all_orders_ever["command"]=="Retreat", "order"].str.extract(rf"{unit_identifier} R ({place_identifier})", expand=False)
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all_orders_ever.loc[all_orders_ever["command"]=="Retreat", "destination"] = all_orders_ever.loc[all_orders_ever["command"]=="Retreat", "order"].str.extract(rf"{UNIT_IDENTIFIER} R ({PLACE_IDENTIFIER})", expand=False)
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all_orders_ever["immediate_result"] = all_orders_ever["order"].str.extract(r"\(([^)]+)\)")
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all_orders_ever["immediate_result"] = all_orders_ever["immediate_result"].fillna("PASS")
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@ -147,6 +155,16 @@ def make_longform_order_data(overview : pd.DataFrame, lmvs_data : pd.DataFrame,
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all_orders_ever["country_model"] = all_orders_ever["country"] + " (" + all_orders_ever["model_short_name"] + ")"
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def check_location_influence(phase_id, location):
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"""
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Helper - checks who owns a location at a given phase. Uses the `turn_actions` dataframe from overall context.
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Args:
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phase_id: The phase to check
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location: The location to check
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Returns:
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The country that owns the location, or "Unowned" if no country owns it
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"""
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# checking who owns a location at `phase_id`
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if pd.isnull(location):
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return np.nan
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@ -162,22 +180,45 @@ def make_longform_order_data(overview : pd.DataFrame, lmvs_data : pd.DataFrame,
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all_orders_ever["destination_affiliation"] = all_orders_ever.apply(lambda row: check_location_influence(row["phase"],
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row["destination"]), axis=1)
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def find_supporting_country(unit_command, command_type, phase):
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def find_supporting_country(unit_command, command_type, phase) -> Optional[str]:
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"""
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Helper - finds which orders support a given unit and records the supporting powers. Operating on the `all_orders_ever` dataframe.
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Args:
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unit_command: The unit command to find supporting orders for
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command_type: The type of command ("Move" or "Hold")
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phase: The phase to check
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Returns:
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A string containing a comma-separated list of countries that issued an order to support that unit, or None if no such orders exist
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"""
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if command_type == "Move" or command_type == "Hold": # commands that can be supported
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potential_supports = all_orders_ever[(all_orders_ever["phase"] == phase) &
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(all_orders_ever["command"].isin(["Support Move", "Support Hold"]))]
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potential_supports = potential_supports[potential_supports["order"].str.contains(unit_command, regex=False)]
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if potential_supports.empty:
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return np.nan
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return None
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else:
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return ",".join(potential_supports["country"].tolist())
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return np.nan
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return None
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all_orders_ever["supported_by"] = all_orders_ever.apply(lambda row: find_supporting_country(row["order"], row["command"], row["phase"]), axis=1)
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all_orders_ever["in_anothers_territory"] =( all_orders_ever["country"] != all_orders_ever["unit_location_affiliation"]) & (all_orders_ever["unit_location_affiliation"] != "Unowned")
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all_orders_ever["moving_into_anothers_territory"] = (all_orders_ever["country"] != all_orders_ever["destination_affiliation"]) & (all_orders_ever["destination_affiliation"].notnull()) & (all_orders_ever["destination_affiliation"] != "Unowned")
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all_orders_ever["moving_into_anothers_territory"] = ((all_orders_ever["country"] != all_orders_ever["destination_affiliation"]) &
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(all_orders_ever["destination_affiliation"].notnull()) &
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(all_orders_ever["destination_affiliation"] != "Unowned"))
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def find_owner_of_unit(unit_location, phase):
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def find_owner_of_unit(unit_location, phase) -> Optional[str]:
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"""
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Helper - finds the owner of a unit at a given phase. Operating on the `turn_actions` dataframe from overall context.
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Args:
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unit_location: The location of the unit to find the owner of
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phase: The phase to check
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Returns:
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The country that owns the unit, or None if no country owns it
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"""
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if pd.notnull(unit_location):
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unit_status = turn_actions.loc[turn_actions.index.str.contains("_units"), phase]
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unit_status.index = unit_status.index.str.replace("_units", "")
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@ -186,18 +227,30 @@ def make_longform_order_data(overview : pd.DataFrame, lmvs_data : pd.DataFrame,
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if re.match(f"[AF] {unit_location}", unit):
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return country
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# where were they going? what was their destination like?
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def find_destination_info(destination, phase):
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def find_destination_info(destination, phase) -> Optional[Dict[str, Any]]:
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"""
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Helper - finds information about the destination of a unit at a given phase.
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Operating on the `all_orders_ever` dataframe from overall context.
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Args:
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destination: The location of the unit to find the owner of
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phase: The phase to check
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Returns:
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A dictionary containing information about the destination unit, or None if no such unit exists
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"""
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if pd.notnull(destination):
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country = find_owner_of_unit(destination, phase)
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# there should only ever be one unit at a given location during a phase
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destination_unit_orders = all_orders_ever[(all_orders_ever["country"] == country) &
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(all_orders_ever["phase"] == phase) &
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(all_orders_ever["unit_location"] == destination)]
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if not destination_unit_orders.empty:
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destination_unit_orders = destination_unit_orders.iloc[0] # safe conversion to a series
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return {"destination_unit_owner": country,
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"destination_unit_order": destination_unit_orders["command"].squeeze(),
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"destination_unit_outcome":destination_unit_orders["immediate_result"].squeeze(),
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"destination_unit_supported_by": destination_unit_orders["supported_by"].squeeze()}
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"destination_unit_order": destination_unit_orders["command"],
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"destination_unit_outcome":destination_unit_orders["immediate_result"],
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"destination_unit_supported_by": destination_unit_orders["supported_by"]}
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destination_unit_info = all_orders_ever.apply(lambda row: find_destination_info(row["destination"], row["phase"]), axis=1).apply(pd.Series)
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destination_unit_info["destination_was_occupied"] = destination_unit_info["destination_unit_owner"].notnull()
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@ -205,54 +258,90 @@ def make_longform_order_data(overview : pd.DataFrame, lmvs_data : pd.DataFrame,
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all_orders_ever = pd.concat([all_orders_ever, destination_unit_info], axis=1)
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# if a Support action: who were they supporting? what was their support doing?
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def find_support_recipient_info(unit_order, command, phase):
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def find_support_recipient_info(unit_order, command, phase) -> Optional[Dict[str, Any]]:
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"""
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Helper - finds information about the recipient of a support action at a given phase.
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Operating on the `all_orders_ever` dataframe from overall context.
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Args:
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unit_order: The order of the unit to find the recipient of support for
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command: The type of command ("Support Move" or "Support Hold")
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phase: The phase to check
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Returns:
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A dictionary containing information about the recipient of support, or None if no such recipient exists
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"""
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if "Support" in command:
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recipient_location = re.match(rf"{unit_identifier} S [AF] ({place_identifier})", unit_order).group(1)
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recipient_location = re.match(rf"{UNIT_IDENTIFIER} S [AF] ({PLACE_IDENTIFIER})", unit_order).group(1)
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recipient_country = find_owner_of_unit(recipient_location, phase)
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# there should only ever be one unit at a given location during a phase
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recipient_order_info = all_orders_ever[(all_orders_ever["country"] == recipient_country) &
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(all_orders_ever["phase"] == phase) &
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(all_orders_ever["unit_location"] == recipient_location)]
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return {"recipient_unit_owner": recipient_country, "recipient_unit_outcome": recipient_order_info["immediate_result"].squeeze(),
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"recipient_unit_in_anothers_territory": recipient_order_info["in_anothers_territory"].squeeze(),
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"recipient_unit_moving_into_anothers_territory": recipient_order_info["moving_into_anothers_territory"].squeeze(),
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"recipient_unit_destination_occupied": recipient_order_info["destination_was_occupied"].squeeze()}
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(all_orders_ever["unit_location"] == recipient_location)].iloc[0]
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return {"recipient_unit_owner": recipient_country, "recipient_unit_outcome": recipient_order_info["immediate_result"],
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"recipient_unit_in_anothers_territory": recipient_order_info["in_anothers_territory"],
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"recipient_unit_moving_into_anothers_territory": recipient_order_info["moving_into_anothers_territory"],
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"recipient_unit_destination_occupied": recipient_order_info["destination_was_occupied"]}
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support_recipient_info = all_orders_ever.apply(lambda row: find_support_recipient_info(row["order"], row["command"], row["phase"]), axis=1).apply(pd.Series)
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support_recipient_info = all_orders_ever.apply(lambda row: find_support_recipient_info(row["order"],
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row["command"],
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row["phase"]), axis=1).apply(pd.Series)
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# add support recipient info to all_orders_ever as additional columns
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all_orders_ever = pd.concat([all_orders_ever, support_recipient_info], axis=1)
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# add relationships with other countries
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# if original v1
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agent_relationship_matrix_over_time = {}
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for phase in lmvs_data["phases"]:
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agent_relationship_matrix_over_time[phase["name"]] = pd.DataFrame(phase.get("agent_relationships", {}))
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longform_relationships = pd.concat(agent_relationship_matrix_over_time).reset_index(names=["phase", "agent"])
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if longform_relationships.empty:
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print("Warning: no relationship data found in phase data")
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else:
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longform_relationships.columns = longform_relationships.columns.str.lower()
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longform_relationships[['austria', 'england', 'france', 'germany', 'italy',
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'russia', 'turkey']] = longform_relationships[['austria', 'england', 'france', 'germany', 'italy',
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'russia', 'turkey']].fillna("Self")
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longform_relationships = longform_relationships.add_prefix("relationship_")
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all_orders_ever = pd.merge(all_orders_ever, longform_relationships,
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left_on=["phase", "country"], right_on=["relationship_phase", "relationship_agent"]).drop(columns=["relationship_phase", "relationship_agent"])
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alternate_relationship_view = pd.concat(agent_relationship_matrix_over_time)
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alternate_relationship_view.index.names = ["phase", "agent"]
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alternate_relationship_view = alternate_relationship_view.stack().reset_index().rename(columns={"level_2":"recipient",
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0:"status"}).set_index(["phase", "recipient",
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"agent"])["status"].unstack("agent").fillna("Self").add_suffix("s_relationship_rating").reset_index()
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all_orders_ever = pd.merge(all_orders_ever, alternate_relationship_view,
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left_on=["phase", "country"], right_on=["phase", "recipient"]).drop(columns=["recipient"])
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# Then we have v2 of the data log where relationships are stored under state_agents and need a different approach
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agent_relationship_matrix_over_time = {}
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for phase in lmvs_data["phases"]:
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agent_state = phase.get("state_agents", {})
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country_relationships = {}
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for c in COUNTRIES:
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country_relationships[c] = agent_state.get(c, {}).get("relationships", {})
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agent_relationship_matrix_over_time[phase["name"]] = pd.DataFrame(country_relationships)
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longform_relationships = pd.concat(agent_relationship_matrix_over_time).reset_index(names=["phase", "agent"])
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longform_relationships.columns = longform_relationships.columns.str.lower()
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longform_relationships[['austria', 'england', 'france', 'germany', 'italy',
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'russia', 'turkey']] = longform_relationships[['austria', 'england', 'france', 'germany', 'italy',
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'russia', 'turkey']].fillna("Self")
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longform_relationships = longform_relationships.add_prefix("relationship_")
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all_orders_ever = pd.merge(all_orders_ever, longform_relationships,
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left_on=["phase", "country"], right_on=["relationship_phase", "relationship_agent"]).drop(columns=["relationship_phase", "relationship_agent"])
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alternate_relationship_view = pd.concat(agent_relationship_matrix_over_time)
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alternate_relationship_view.index.names = ["phase", "agent"]
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alternate_relationship_view = alternate_relationship_view.stack().reset_index().rename(columns={"level_2":"recipient",
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0:"status"}).set_index(["phase", "recipient",
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"agent"])["status"].unstack("agent").fillna("Self").add_suffix("s_relationship_rating").reset_index()
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all_orders_ever = pd.merge(all_orders_ever, alternate_relationship_view,
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left_on=["phase", "country"], right_on=["phase", "recipient"]).drop(columns=["recipient"])
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# if action was supporting
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# if action was supporting, add flags
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all_orders_ever["supporting_self"] = all_orders_ever["country"]==all_orders_ever["recipient_unit_owner"]
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all_orders_ever["supporting_an_ally"] = (all_orders_ever["country"] !=all_orders_ever["recipient_unit_owner"]) & (all_orders_ever["recipient_unit_owner"].notnull())
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def countries_aside_from(a_country):
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def countries_aside_from(a_country : str) -> List[str]:
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return [country for country in all_orders_ever["country"].unique() if country != a_country]
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def check_country(supporters, country):
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def check_country(supporters : List[str], country : str) -> bool:
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"""
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Helper - checks if a given country is in a list of supporters
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Args:
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supporters: The list of supporters to check
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country: The country to check
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Returns:
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True if the country is in the list of supporters, False otherwise
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"""
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if pd.isnull(supporters):
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return False
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for other_countries in countries_aside_from(country):
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@ -267,7 +356,7 @@ def make_longform_order_data(overview : pd.DataFrame, lmvs_data : pd.DataFrame,
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all_orders_ever["destination_unit_was_supported"] = all_orders_ever["destination_unit_supported_by"].notnull()
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# add number of unit orders ever made
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# add number of unit orders ever made during this game
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unit_order_weight = 1 / all_orders_ever.groupby("country").size()
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all_orders_ever["unit_order_weight"] = all_orders_ever["country"].map(unit_order_weight)
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@ -317,30 +406,30 @@ if __name__ == "__main__":
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current_game_data_folder = Path(args.game_data_folder)
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analysis_folder = Path(args.analysis_folder) / "orders_data"
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if not os.path.exists(analysis_folder):
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if not analysis_folder.exists():
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print(f"Output folder {analysis_folder} not found, creating it.")
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os.makedirs(analysis_folder)
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analysis_folder.mkdir(parents=True, exist_ok=True)
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games_to_process = args.selected_game
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if not games_to_process:
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games_to_process = os.listdir(current_game_data_folder)
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games_to_process = [p.name for p in current_game_data_folder.iterdir() if p.is_dir()]
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for game_name in tqdm(games_to_process, desc="Processing games"):
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if game_name == ".DS_Store":
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continue
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game_path = current_game_data_folder / game_name
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if not os.path.isdir(game_path):
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if not game_path.is_dir():
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continue
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try:
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game_source_data = process_standard_game_inputs(game_path, game_name)
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data = make_longform_order_data(overview=game_source_data["overview"],
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lmvs_data=game_source_data["lmvs_data"],
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game_source_data = process_standard_game_inputs(game_path)
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overview_df = game_source_data["overview"]
|
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country_to_model = get_country_to_model_mapping(overview_df, game_source_data["all_responses"])
|
||||
data = make_longform_order_data(country_to_model=country_to_model,
|
||||
lmvs_data=game_source_data["lmvs_data"],
|
||||
all_responses=game_source_data["all_responses"])
|
||||
output_path = analysis_folder / f"{game_name}_orders_data.csv"
|
||||
data.to_csv(output_path, index=False)
|
||||
except FileNotFoundError as e:
|
||||
print(f"Could not process {game_name}. Missing file: {e.filename}")
|
||||
except Exception as e:
|
||||
print(f"An unexpected error occurred while processing {game_name}: {e}")
|
||||
print(f"An unexpected error occurred while processing {game_name}: {e}")
|
||||
traceback.print_exc()
|
||||
Loading…
Add table
Add a link
Reference in a new issue