arsam
6c5a95f3b4
Import the existing local project snapshot. This commit organizes existing files; it does not represent newly developed functionality.
60 lines
2.2 KiB
Python
60 lines
2.2 KiB
Python
import numpy as np
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import random
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from nash.game import Game
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from nash.simulation import Simulation, EvolutionarySimulation
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PRICING = Game.load_from_json("games/pricing.json")
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MATCHING_PENNIES = Game.load_from_json("games/matching_pennies.json")
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def test_pricing_simulation_converges_to_low_low_with_memory_on():
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rng = random.Random(1)
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simulation = Simulation(PRICING, num_rounds=10, memory=True, rng=rng)
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simulation.run()
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converged_round = simulation.converged_round()
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assert converged_round is not None
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assert simulation.converged_profile() == (1, 1)
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def test_matching_pennies_frequencies_trend_toward_fifty_fifty_with_memory_on():
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rng = random.Random(7)
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simulation = Simulation(MATCHING_PENNIES, num_rounds=300, memory=True, rng=rng)
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simulation.run()
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frequencies = simulation.strategy_frequencies()
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for player_idx in range(2):
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final_freqs = [frequencies[player_idx][s][-1] for s in range(2)]
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assert abs(final_freqs[0] - 0.5) < 0.15
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assert abs(final_freqs[1] - 0.5) < 0.15
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def test_evolutionary_simulation_initialization():
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# 2 players, pricing game has 2 strategies each
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sim = EvolutionarySimulation(PRICING, num_rounds=5)
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assert len(sim.populations) == 2
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assert np.allclose(sim.populations[0], [0.5, 0.5])
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assert np.allclose(sim.populations[1], [0.5, 0.5])
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assert len(sim.history) == 0
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def test_evolutionary_simulation_run_pricing():
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sim = EvolutionarySimulation(PRICING, num_rounds=5)
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history = sim.run()
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assert len(history) == 5
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assert len(sim.history) == 5
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for pop_profile in history:
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assert len(pop_profile) == 2
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# check each player's population is normalized
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assert np.allclose(np.sum(pop_profile[0]), 1.0)
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assert np.allclose(np.sum(pop_profile[1]), 1.0)
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def test_evolutionary_simulation_matching_pennies():
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# Matching pennies has no pure Nash equilibrium, populations should cycle/fluctuate
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sim = EvolutionarySimulation(MATCHING_PENNIES, num_rounds=100)
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sim.run()
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assert len(sim.history) == 100
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# Final populations should be valid probability distributions
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for pop in sim.populations:
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assert np.allclose(np.sum(pop), 1.0)
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assert np.all(pop >= 0)
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