
    Given a patient's historical health pattern represented as a binary sequence where 1 indicates risk factor presence and 0 indicates absence, determine the number of unique temporal risk patterns that show an odd severity score when the sequence is analyzed over different time periods. The severity score is calculated by interpreting each rotated pattern as a binary number, and the analysis should be performed for a specified number of time periods to identify recurring risk patterns.
    

    
def odd_Equivalent(s, n):
    """
    Given a patient's historical health pattern represented as a binary sequence where 1 indicates risk factor presence and 0 indicates absence, determine the number of unique temporal risk patterns that show an odd severity score when the sequence is analyzed over different time periods. The severity score is calculated by interpreting each rotated pattern as a binary number, and the analysis should be performed for a specified number of time periods to identify recurring risk patterns.
    

    """
def odd_Equivalent(s, n):
    """
    Given a patient's historical health pattern represented as a binary sequence where 1 indicates risk factor presence and 0 indicates absence, determine the number of unique temporal risk patterns that show an odd severity score when the sequence is analyzed over different time periods. The severity score is calculated by interpreting each rotated pattern as a binary number, and the analysis should be performed for a specified number of time periods to identify recurring risk patterns.
    

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