hamo_evaluate

'''
    Parameter
        output_from_simulation: output from simulation (numpy array or python list)
                                shape(2,n), first row is reduced fail search
                                            second row is fail exist search
    Output
        fail_red : reduced fail percentage
        profit    : profit in Baht (can be negative)
'''
def evaluate(output_from_simulation):

    failed = np.array(output_from_simulation)
    failed_sum = np.sum(p,axis=1)

    fail_red = failed_sum[0] / (failed_sum[0] + failed_sum[1])

    #numbers from statistic
    profit = (0.8*25.4226*failed_sum[0])*0.2533 - 10/3*2

    return fail_red, profit