
    Given a patient's historical hospital readmission pattern represented as a binary sequence where 1 indicates a hospital visit and 0 indicates no visit, determine how many unique risk periods show an elevated readmission likelihood when analyzing the pattern over n future time periods. A risk period is considered elevated when shifting the historical pattern by k positions (where k ranges from 1 to n) results in an odd numerical value of the binary sequence.
    

    
def odd_Equivalent(s, n):
    """
    Given a patient's historical hospital readmission pattern represented as a binary sequence where 1 indicates a hospital visit and 0 indicates no visit, determine how many unique risk periods show an elevated readmission likelihood when analyzing the pattern over n future time periods. A risk period is considered elevated when shifting the historical pattern by k positions (where k ranges from 1 to n) results in an odd numerical value of the binary sequence.
    

    """
def odd_Equivalent(s, n):
    """
    Given a patient's historical hospital readmission pattern represented as a binary sequence where 1 indicates a hospital visit and 0 indicates no visit, determine how many unique risk periods show an elevated readmission likelihood when analyzing the pattern over n future time periods. A risk period is considered elevated when shifting the historical pattern by k positions (where k ranges from 1 to n) results in an odd numerical value of the binary sequence.
    

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