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 pow(max(anorm, bnorm, cnorm) - min(anorm, bnorm, cnorm), 1.0 / p)

def f2(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-12)
    if f(cur) < best:
        ans = cur
        best = f(cur)

def check2(X, Y):
    global ans, best
    cur = scipy.optimize.fmin(f2, [X, Y], disp=False, maxiter=500, ftol=1e-12)
    if f(cur) < best:
        ans = cur
        best = f(cur)

for scale in range(5, 7):
    for X in [-(10**scale), 10**scale]:
        for Y in [-(10**scale), 10**scale]:
            if time.time() - start < 1.3:
#                check(X, Y)
                check(X + dx, Y + dy)

for scale in range(5, 7):
    for X in [-(10**scale), 10**scale]:
        for Y in [-(10**scale), 10**scale]:
            if time.time() - start < 1.3:
                check2(X + dx, Y + dy)

while time.time() - start < 1.3:
    scale = random.randint(1, 6)
    X = random.randint(-(10**scale), 10**scale) 
    Y = random.randint(-(10**scale), 10**scale)
    check(X + dx, Y + dy)

print("{:.10f} {:.10f}".format(ans[0], ans[1]))