added participant_condition_sampling attribute to GameSetup for repea…

…ted games

llm_cooperation/__init__.py

@@ -85,18 +85,18 @@ def settings_from_combinations(
 
 
 def randomized(n: int, grid: Grid) -> Iterable[Settings]:
-    keys = list(grid.keys())
+    variables = list(grid.keys())
     combinations = list(all_combinations(grid))
     num_combinations = len(combinations)
     for __i__ in range(n):
         random_index: int = int(np.random.randint(num_combinations))
-        yield settings_from_combinations(keys, combinations[random_index])
+        yield settings_from_combinations(variables, combinations[random_index])
 
 
 def exhaustive(grid: Grid) -> Iterable[Settings]:
-    keys = list(grid.keys())
+    variables = list(grid.keys())
     for values in all_combinations(grid):
-        yield settings_from_combinations(keys, values)
+        yield settings_from_combinations(variables, values)
 
 
 def amount_as_str(amount: float) -> str:

llm_cooperation/experiments/dilemma.py

@@ -8,7 +8,7 @@
 import numpy as np
 from openai_pygenerator import Completion
 
-from llm_cooperation import ModelSetup, Payoffs, Settings
+from llm_cooperation import ModelSetup, Payoffs, Settings, exhaustive
 from llm_cooperation.experiments import AI_PARTICIPANTS, run_and_record_experiment
 from llm_cooperation.gametypes import simultaneous
 from llm_cooperation.gametypes.repeated import (
@@ -196,6 +196,7 @@ def run(model_setup: ModelSetup, sample_size: int) -> RepeatedGameResults:
         extract_choice=extract_choice_pd,
         next_round=simultaneous.next_round,
         analyse_rounds=simultaneous.analyse_rounds,
+        participant_condition_sampling=exhaustive,
         model_setup=model_setup,
     )
     measurement_setup: MeasurementSetup[DilemmaChoice] = MeasurementSetup(

llm_cooperation/experiments/ultimatum.py

@@ -7,7 +7,7 @@
 import numpy as np
 from openai_pygenerator import Completion, content, user_message
 
-from llm_cooperation import ModelSetup, Payoffs, Settings, amount_as_str
+from llm_cooperation import ModelSetup, Payoffs, Settings, amount_as_str, exhaustive
 from llm_cooperation.experiments import AI_PARTICIPANTS, run_and_record_experiment
 from llm_cooperation.gametypes import alternating
 from llm_cooperation.gametypes.repeated import (
@@ -199,6 +199,7 @@ def run(model_setup: ModelSetup, sample_size: int) -> RepeatedGameResults:
         next_round=next_round_ultimatum,
         analyse_rounds=alternating.analyse_rounds,
         model_setup=model_setup,
+        participant_condition_sampling=exhaustive,
     )
     measurement_setup: MeasurementSetup[UltimatumChoice] = MeasurementSetup(
         num_samples=sample_size,

llm_cooperation/gametypes/repeated.py

@@ -19,7 +19,6 @@
     Payoffs,
     Results,
     Settings,
-    exhaustive,
 )
 from llm_cooperation.gametypes import PromptGenerator, start_game
 
@@ -53,6 +52,7 @@ class GameSetup(Generic[CT, RT]):
     payoffs: PayoffFunction[CT]
     extract_choice: ChoiceExtractor[CT]
     model_setup: ModelSetup
+    participant_condition_sampling: Callable[[Grid], Iterable[Settings]]
 
 
 @dataclass(frozen=True)
@@ -259,7 +259,9 @@ def run_experiment(
         )
         for group, participants in ai_participants.items()
         for participant in participants
-        for participant_condition in exhaustive(participant_conditions)
+        for participant_condition in game_setup.participant_condition_sampling(
+            participant_conditions
+        )
         for strategy_name, strategy_fn in partner_conditions.items()
         for score, freq, choices, history in generate_samples(
             participant=participant,

tests/test_dilemma.py

@@ -4,7 +4,7 @@
 import pytest
 from openai_pygenerator import Completion, logger
 
-from llm_cooperation import DEFAULT_MODEL_SETUP, Payoffs
+from llm_cooperation import DEFAULT_MODEL_SETUP, Payoffs, exhaustive
 from llm_cooperation.experiments.dilemma import (
     COLOR_COOPERATE,
     COLOR_DEFECT,
@@ -141,6 +141,7 @@ def test_run_repeated_game(mocker):
                 payoffs=payoffs_pd,
                 extract_choice=extract_choice_pd,
                 model_setup=DEFAULT_MODEL_SETUP,
+                participant_condition_sampling=exhaustive,
             ),
         )
     )

tests/test_repeated.py

@@ -5,7 +5,7 @@
 import pytest
 from openai_pygenerator import content, user_message
 
-from llm_cooperation import DEFAULT_MODEL_SETUP, Choice, Grid, Group
+from llm_cooperation import DEFAULT_MODEL_SETUP, Choice, Grid, Group, exhaustive
 from llm_cooperation.experiments.dilemma import (
     Cooperate,
     Defect,
@@ -63,6 +63,7 @@ def test_play_game(mocker):
             extract_choice=extract_choice_mock,
             generate_instruction_prompt=prompt_generator_mock,
             model_setup=DEFAULT_MODEL_SETUP,
+            participant_condition_sampling=exhaustive,
         ),
     )
 
@@ -87,6 +88,7 @@ def test_play_game(mocker):
                         generate_instruction_prompt=prompt_generator_mock,
                         num_rounds=n,
                         model_setup=DEFAULT_MODEL_SETUP,
+                        participant_condition_sampling=exhaustive,
                     ),
                 ),
                 "test-prompt",
@@ -168,6 +170,7 @@ def test_run_experiment(mocker):
             next_round=simultaneous.next_round,
             analyse_rounds=simultaneous.analyse_rounds,
             model_setup=DEFAULT_MODEL_SETUP,
+            participant_condition_sampling=exhaustive,
         ),
     ).to_df()
     num_participant_conditions = len(participant_conditions["chain_of_thought"])