Printing only once in a for loop

Question

Hello I'm trying to print out the items shown below.I only want them printed once but since the print statements are inside the for loop, they are being printed 100 times. and I can't take the print statements out because the values inside are dependent on the for loop. Any ideas on how to print those values only once?

def Input_Q_bounds (lower,upper):
delta_x = .1

#since there are 100 iterations
J=np.zeros(101)
for i in range(101) :
    Q_i=(i*delta_x)+(delta_x/2)
    if lower <=Q_i<= upper :
        Q =1
    else :
        Q=0
    #now fill the matrix
    J[i]=(Q+(9.5*(J[i-1])))/10.5
    J_analytical = Q*(np.exp(upper-10)+(np.exp(lower-10))

    print(J_analytical)
    print(J[100])

Answer 1

Option 1: You can use an else condition like below.

def Input_Q_bounds(lower, upper):
    delta_x = .1

    # since there are 100 iterations
    J = np.zeros(101)
    for i in range(101):
        Q_i = (i * delta_x) + (delta_x / 2)
        if lower <= Q_i <= upper:
            Q = 1
        else:
            Q = 0
        # now fill the matrix
        J[i] = (Q + (9.5 * (J[i - 1]))) / 10.5
        J_analytical = Q * (np.exp(upper - 10) + (np.exp(lower - 10))
    else:
        print(J_analytical)
        print(J[100])

if __name__ == "__main__":
    Input_Q_bounds(lower, upper)

Option 2: The below solution is by using global variables

J_analytical = -1
J = []

def Input_Q_bounds(lower, upper):
    global J
    global J_analytical
    delta_x = .1

    # since there are 100 iterations
    J = np.zeros(101)
    for i in range(101):
        Q_i = (i * delta_x) + (delta_x / 2)
        if lower <= Q_i <= upper:
            Q = 1
        else:
            Q = 0
        # now fill the matrix
        J[i] = (Q + (9.5 * (J[i - 1]))) / 10.5
        J_analytical = Q * (np.exp(upper - 10) + (np.exp(lower - 10))


if __name__ == "__main__":
    Input_Q_bounds(lower, upper)
    print(J[100])
    print(J_analytical)

Option 3: Return the values from the function.

def Input_Q_bounds(lower, upper):
    delta_x = .1

    # since there are 100 iterations
    J = np.zeros(101)
    for i in range(101):
        Q_i = (i * delta_x) + (delta_x / 2)
        if lower <= Q_i <= upper:
            Q = 1
        else:
            Q = 0
        # now fill the matrix
        J[i] = (Q + (9.5 * (J[i - 1]))) / 10.5
        J_analytical = Q * (np.exp(upper - 10) + (np.exp(lower - 10))
    return J[100], J_analytical

if __name__ == "__main__":
    Input_Q_bounds(lower, upper)

Answer 2

just put an if i == 100: in the line above the printing