
    Given n consecutive days of patient monitoring data and k distinct risk categories, determine the number of possible risk assessment patterns where no more than 2 consecutive days can be assigned the same risk level. This pattern analysis helps identify valid sequences of patient risk assessments for predicting hospital readmission probability, where each day must be assigned one of the k risk categories.
    

    
def count_no_of_ways(n, k):
    """
    Given n consecutive days of patient monitoring data and k distinct risk categories, determine the number of possible risk assessment patterns where no more than 2 consecutive days can be assigned the same risk level. This pattern analysis helps identify valid sequences of patient risk assessments for predicting hospital readmission probability, where each day must be assigned one of the k risk categories.
    

    """
def count_no_of_ways(n, k):
    """
    Given n consecutive days of patient monitoring data and k distinct risk categories, determine the number of possible risk assessment patterns where no more than 2 consecutive days can be assigned the same risk level. This pattern analysis helps identify valid sequences of patient risk assessments for predicting hospital readmission probability, where each day must be assigned one of the k risk categories.
    

    """
    dp = [0] * (n + 1)
    total = k
    mod = 1000000007
    dp[1] = k
    dp[2] = k * k
    for i in range(3, n + 1):
        dp[i] = (k - 1) * (dp[i - 1] + dp[i - 2]) % mod
    return dp[n]