def hash_minting_process(miner_hash): """ This function categorizes a miner’s hash and mints a corresponding token based on harmonic resonance theory and sacred geometry principles. """ hash_value = calculate_hash_value(miner_hash) resonance_category = classify_hash(hash_value) minted_token = mint_token(resonance_category) return minted_token
def calculate_hash_value(miner_hash): """ Calculate hash value based on harmonic resonance principles and color frequency mapping. """ harmonic_value = analyze_harmonic_resonance(miner_hash) prime_distribution_value = analyze_prime_distribution(miner_hash) color_mapping_value = map_color_frequency(miner_hash)
# Combine these values for a final hash value calculation
final_value = harmonic_value + prime_distribution_value + color_mapping_value
return final_value
def analyze_harmonic_resonance(miner_hash): """ Analyzes the harmonic resonance of the hash. """ # Example logic: Check the number of sequences that align with a harmonic pattern. harmonic_value = 0 for i in range(len(miner_hash)): if is_harmonic(miner_hash[i]): harmonic_value += 1 return harmonic_value
def analyze_prime_distribution(miner_hash): """ Analyzes prime number distribution in the hash. """ prime_value = 0 for i in range(len(miner_hash)): if is_prime(miner_hash[i]): prime_value += 1 return prime_value
def map_color_frequency(miner_hash): """ Maps the hash to a color frequency spectrum (resonance mapping). """ color_value = 0 for char in miner_hash: color_value += get_color_frequency_value(char) return color_value
def get_color_frequency_value(char): """ Converts hash character to a color frequency value. """ color_map = {‘a’: 1, ‘b’: 2, ‘c’: 3, ’d’: 4, ’e’: 5} # Simplified map for illustration. return color_map.get(char, 0)
def is_harmonic(segment): """ Check if a given segment of the hash aligns with harmonic patterns. """ return segment in [‘a’, ‘b’, ‘c’, ’d’] # Simplified example for harmonic check
def is_prime(value): """ Checks if the number is prime. """ if value <= 1: return False for i in range(2, int(value ** 0.5) + 1): if value % i == 0: return False return True
def classify_hash(hash_value): """ Classifies the hash into a resonance category based on the final value calculated. """ if is_perfect_resonance(hash_value): return ‘Perfect Resonance’ elif is_resonant(hash_value): return ‘Resonant’ else: return ‘Standard’
def is_perfect_resonance(hash_value): """ Check if the hash belongs to the perfect resonance category. """ # Assume we have some predefined rules for perfect resonance return hash_value > 100 # Example threshold
def is_resonant(hash_value): """ Check if the hash belongs to the resonant category. """ return hash_value > 50 and hash_value <= 100
def mint_token(resonance_category): """ Mints a new token based on the hash classification. """ if resonance_category == ‘Perfect Resonance’: return create_token(value_multiplier=10) elif resonance_category == ‘Resonant’: return create_token(value_multiplier=5) else: return create_token(value_multiplier=1)
def create_token(value_multiplier): """ Create a new token with a given value multiplier. """ token_id = generate_unique_token_id() return Token(token_id, value_multiplier)
def generate_unique_token_id(): """ Generates a unique token ID, could be based on hash ID or a random value. """ return hash(random.randint(0, 1000000)) # Example, unique identifier.