faker

gistfile1.txt

for _ in range(num_customers):
    customer_name = fake.name()
    account_name = fake.iban()
    
    # Generate the initial profile for the customer
    profile_states, _ = model.sample(transactions_per_customer)
    profiles = [customer_profiles[state] for state in profile_states.ravel()]
    
    for idx, profile in enumerate(profiles):
        profile_index = customer_profiles.index(profile)
        transaction_emission_probs = emission_probabilities[profile_index]
        

        transaction_type = np.random.choice(['withdrawal', 'deposit'], p=transaction_emission_probs)
        

        transaction_time = fake.date_time_this_year()
        transaction_amount = np.random.randint(100, 1000) if transaction_type == 'deposit' else np.random.randint(20, 500)


        transaction_city = fake.city()
        transaction_category = np.random.choice(transaction_categories)
        transaction_ref_id = f"TXN-{fake.unique.random_number(digits=8)}-{idx}"
        
        transaction = {
            'customer_name': customer_name,
            'account_name': account_name,
            'profile': profile,
            'transaction_type': transaction_type,
            'Amount(United States Dollar)': transaction_amount,
            'time_transaction': transaction_time,
            'transaction_city': transaction_city,
            'transaction_category': transaction_category,
            'transaction_ref_id': transaction_ref_id
        }
        
        transactions.append(transaction)