import numpy as np
import scipy
import time
import random

p = float(input())
ax, ay = map(float, input().split())
bx, by = map(float, input().split())
cx, cy = map(float, input().split())

dx = (ax + bx + cx) / 3
dy = (ay + by + cy) / 3

def my_pow(x):
    return np.abs(x) ** p

def f(point):
    x, y = point
    anorm = my_pow(ax - x) + my_pow(ay - y)
    bnorm = my_pow(bx - x) + my_pow(by - y)
    cnorm = my_pow(cx - x) + my_pow(cy - y)
    return max(anorm, bnorm, cnorm) - min(anorm, bnorm, cnorm)


start = time.time()

ans = []
best = 1e9

def check(X, Y):
    global ans, best
    cur = scipy.optimize.fmin(f, [X, Y], disp=False, maxiter=500, ftol=1e-7)
    if f(cur) < best:
        ans = cur
        best = f(cur)


for scale in range(0, 7):
    for X in [-(10**scale), 10**scale]:
        for Y in [-(10**scale), 10**scale]:
            check(X, Y)
            check(X + dx, Y + dy)


while time.time() - start < 1.2:
    scale = random.randint(1, 6)
    X = random.randint(-(10**scale), 10**scale) + dx
    Y = random.randint(-(10**scale), 10**scale) + dy
    check(X, Y)

print(*ans)