# Prompt:
# Can you write me a script to generate a line-chart?  Here's the formula it should use:
# - Generate 10000 tabulators (one data point per tabulator)
# - The first tabulator has one recorded vote, each tabulator gets one more vote than the previous
# - For all tabulators, each vote in the first 300 has a random outcome between two candidates (A & B)
# - After the first 300 votes, each tabulator gets 60% of of votes to candidate A
# - make two trendlines, the first where all votes are random, and the second as described above

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

# Set random seed for reproducibility
np.random.seed(42)

# Generate data for 10000 tabulators
n_tabulators = 8000
votes_per_tabulator = np.arange(1, n_tabulators + 1)  # 1 to 10000 votes

# Function to simulate voting with threshold
def simulate_votes_with_threshold(n_votes, threshold=300, bias=0.6):
    if n_votes <= threshold:
        # All random votes before threshold
        return np.random.random(n_votes) < 0.5
    else:
        # Random votes up to threshold
        first_votes = np.random.random(threshold) < 0.5
        # Biased votes after threshold
        remaining_votes = np.random.random(n_votes - threshold) < bias
        return np.concatenate([first_votes, remaining_votes])

# Function to simulate completely random voting
def simulate_random_votes(n_votes):
    return np.random.random(n_votes) < 0.6

# Initialize arrays to store results
biased_results = []
random_results = []

# Calculate results for each tabulator
for votes in votes_per_tabulator:
    # Simulate votes with threshold and bias
    biased_votes = simulate_votes_with_threshold(votes)
    biased_prop = np.mean(biased_votes)
    biased_results.append(biased_prop)

    # Simulate completely random votes
    random_votes = simulate_random_votes(votes)
    random_prop = np.mean(random_votes)
    random_results.append(random_prop)

# Create the plot
plt.figure(figsize=(12, 8))
plt.plot(votes_per_tabulator, random_results, label='Random Voting', alpha=0.7)
plt.plot(votes_per_tabulator, biased_results, label='Threshold Voting', alpha=0.7)

plt.axvline(x=300, color='r', linestyle='--', alpha=0.3, label='Threshold (300 votes)')
plt.axhline(y=0.5, color='gray', linestyle='--', alpha=0.3, label='50% Line')

plt.xlabel('Number of Votes')
plt.ylabel('Proportion of Votes for Candidate A')
plt.title('Vote Distribution Analysis')
plt.legend()
plt.grid(True, alpha=0.3)

# Save the plot
plt.savefig('vote_distribution.png')
plt.close()

print("Analysis complete! The plot has been saved as 'vote_distribution.png'")