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import numpy as np
import matplotlib.pyplot as plt

# Generate random samples for proposer's offer and responder's acceptance threshold
num_samples = 1000
proposer_offers = np.random.uniform(0, 100, num_samples)
responder_thresholds = np.random.uniform(0, 100, num_samples)

# Plot histograms of offer amounts and acceptance thresholds
plt.figure(figsize=(12, 5))

plt.subplot(1, 2, 1)
plt.hist(proposer_offers, bins=20, color='skyblue', edgecolor='black')
plt.title('Histogram of Proposer Offers')
plt.xlabel('Offer Amount')
plt.ylabel('Frequency')

plt.subplot(1, 2, 2)
plt.hist(responder_thresholds, bins=20, color='salmon', edgecolor='black')
plt.title('Histogram of Responder Acceptance Thresholds')
plt.xlabel('Acceptance Threshold')
plt.ylabel('Frequency')

plt.tight_layout()
plt.show()

# Visualize relationship between offer amounts and acceptance/rejection outcomes
plt.figure(figsize=(8, 6))
plt.scatter(proposer_offers, responder_thresholds, c=np.where(proposer_offers >= responder_thresholds, 'green', 'red'), alpha=0.5)
plt.plot([0, 100], [0, 100], linestyle='--', color='gray')  # Plot diagonal line for reference
plt.xlabel('Proposer Offer Amount')
plt.ylabel('Responder Acceptance Threshold')
plt.title('Acceptance/Rejection Outcome')
plt.xlim(0, 100)
plt.ylim(0, 100)
plt.grid(True)
plt.show()