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import matplotlib.pyplot as plt
from validation import validation
import numpy as np
# Example layout and circle settings
layout = [0, 0, 3, 0, 2, 0, 2, 0, 0, 0, 3, 0, 0, 1, 0]
circle = False
# Create an instance of validation
validation_instance = validation(layout, circle)
# Plotting function for strategy comparison
def plot_strategy_comparison(num_games=1000):
strategy_costs = validation_instance.compare_strategies(num_games=num_games)
# Bar plot for strategy comparison
plt.figure(figsize=(10, 6))
plt.bar(strategy_costs.keys(), strategy_costs.values(), color=['blue', 'green', 'orange', 'red', 'purple'])
plt.xlabel('Strategies')
plt.ylabel('Average Cost')
plt.title('Comparison of Strategies')
plt.savefig('strategy_comparison.png') # Save the plot
plt.show()
# Plotting function for state-based average turns for all strategies on the same plot
def plot_state_based_turns(save=True):
strategies = [validation_instance.optimal_strategy,
validation_instance.safe_strategy,
validation_instance.normal_strategy,
validation_instance.risky_strategy,
validation_instance.random_strategy]
strategy_names = ['Optimal', 'SafeDice', 'NormalDice', 'RiskyDice', 'Random']
plt.figure(figsize=(12, 6))
for strategy, name in zip(strategies, strategy_names):
mean_turns = validation_instance.simulate_state(strategy, layout, circle)
plt.plot(range(len(mean_turns)), mean_turns, marker='o', linestyle='-', label=name)
plt.xlabel('State')
plt.ylabel('Average Turns')
plt.title('Average Turns per State for Different Strategies')
plt.grid(True)
plt.legend()
#if save:
#plt.savefig('state_based_turns_all_strategies.png') # Save the plot
plt.show()
def plot_state_based_comparison(validation_instance, num_games=1000):
optimal_turns, empirical_turns = validation_instance.compare_state_based_turns(num_games=num_games)
# Plotting the state-based average turns comparison
plt.figure(figsize=(12, 6))
# Plot optimal strategy turns
plt.plot(range(len(optimal_turns)), optimal_turns, marker='o', linestyle='-', label='ValueIteration')
# Plot empirical strategy turns
plt.plot(range(len(empirical_turns)), empirical_turns, marker='x', linestyle='-', label='Empirical')
plt.xlabel('State')
plt.ylabel('Average Turns')
plt.title('Average Turns per State - ValueIteration vs. Empirical')
plt.grid(True)
plt.legend()
plt.show()
# Main function to generate and save plots
if __name__ == '__main__':
# Example of strategy comparison plot
plot_strategy_comparison(num_games=1000)
# Example of state-based average turns plot for all strategies on the same plot
plot_state_based_turns(save=True)
plot_state_based_comparison(validation_instance, num_games=1000)