muv-apy

apy.py

import matplotlib.pyplot as plt

# Constants
total_stake = 24958  # TAO
voted_stake = 22626  # TAO (including the whale)
total_daily_return = 4.97  # TAO tokens
validator_earnings_per_day = total_daily_return * 0.09  # 9% of total daily return
whale_stake = 10018  # TAO
new_voted_stake = voted_stake - whale_stake  # Voted stake after excluding the whale

# Current Voter APY (including whale)
current_earnings_per_TAO = (total_daily_return * 0.91 / total_stake) + (validator_earnings_per_day / voted_stake)
current_APY = current_earnings_per_TAO * 100 * 365

# Voter APY excluding the big whale
new_earnings_per_TAO = (total_daily_return * 0.91 / total_stake) + (validator_earnings_per_day / new_voted_stake)
new_APY = new_earnings_per_TAO * 100 * 365

# Voter APY with 4 TAO per day injected, excluding the whale
extra_TAO_injected_per_day = 4.0  # TAO
extra_earnings_per_TAO_excluding_whale = (extra_TAO_injected_per_day / new_voted_stake)
boosted_earnings_per_TAO_excluding_whale = new_earnings_per_TAO + extra_earnings_per_TAO_excluding_whale
boosted_APY_excluding_whale = boosted_earnings_per_TAO_excluding_whale * 100 * 365

# Voter APY with 4 TAO per day injected, including the whale
extra_earnings_per_TAO_including_whale = (7 / voted_stake)
boosted_earnings_per_TAO_including_whale = current_earnings_per_TAO + extra_earnings_per_TAO_including_whale
boosted_APY_including_whale = boosted_earnings_per_TAO_including_whale * 100 * 365

# Prepare data for plotting
labels = [
    'Current Voter APY', 
    'Voter APY Excluding BET', 
    '4T/day (exclude BET in rakeback)', 
    '7T/day (include BET in rakeback)', 
]
APYs = [
    current_APY, 
    new_APY, 
    boosted_APY_excluding_whale, 
    boosted_APY_including_whale
]

# Plotting
plt.figure(figsize=(12, 8))
colors = ['blue', 'orange', 'green', 'red']
plt.bar(labels, APYs, color=colors)

# Adding titles and labels
plt.title('Comparison of Voter APY Options')
plt.ylabel('APY (%)')

# Display exact values on the bars
for i, apy in enumerate(APYs):
    plt.text(i, apy + 0.1, f'{apy:.2f}%', ha='center', va='bottom')

# Show the plot
plt.tight_layout()
plt.savefig("apy.png")