
    Design a credit risk assessment function that analyzes a customer's payment history pattern (represented as a binary sequence of successful and failed payments) and determines how many unique risk scenarios emerge when examining the pattern over different time periods. Given a binary payment history string and the number of monthly shifts to analyze, calculate how many of these temporal views would flag the customer as high-risk (represented by an odd decimal value in the shifted pattern).
    

    
def odd_Equivalent(s, n):
    """
    Design a credit risk assessment function that analyzes a customer's payment history pattern (represented as a binary sequence of successful and failed payments) and determines how many unique risk scenarios emerge when examining the pattern over different time periods. Given a binary payment history string and the number of monthly shifts to analyze, calculate how many of these temporal views would flag the customer as high-risk (represented by an odd decimal value in the shifted pattern).
    

    """
def odd_Equivalent(s, n):
    """
    Design a credit risk assessment function that analyzes a customer's payment history pattern (represented as a binary sequence of successful and failed payments) and determines how many unique risk scenarios emerge when examining the pattern over different time periods. Given a binary payment history string and the number of monthly shifts to analyze, calculate how many of these temporal views would flag the customer as high-risk (represented by an odd decimal value in the shifted pattern).
    

    """
    count = 0
    for i in range(0, n):
        if s[i] == '1':
            count = count + 1
    return count