output_description: Print the distance where $p = 1, 2, 3$ and $\infty$ in a line respectively.
  The output should not contain an absolute error greater than 10-5.
input_description: In the first line, an integer $n$ is given. In the second and third line, $x =
  \\{x_1, x_2, ... x_n\\}$ and $y = \\{y_1, y_2, ... y_n\\}$ are given
  respectively. The elements in $x$ and $y$ are given in integers.
attempt: input()
  P1 = []
  P2 = []
  P3 = []
  for a, b in zip(map(int, input().split()), map(int, input().split())):
      t = abs(a - b)
      P1.append(t)
      P2.append(t**2)
      P3.append(t**3)
  print("{:f}".format(sum(P1)))
  print(sum(P2) ** (1 / 2))
  print(sum(P3) ** (1 / 3))
  print("{:f}".format(max(P1)))
  
problem_description: Distance II
  
    
  
  Your task is to calculate the distance between two $n$ dimensional vectors $x
  = \\{x_1, x_2, ..., x_n\\}$ and $y = \\{y_1, y_2, ..., y_n\\}$.
  
  The Minkowski's distance defined below is a metric which is a generalization
  of both the Manhattan distance and the Euclidean distance.  
  \\[ D_{xy} = (\sum_{i=1}^n |x_i - y_i|^p)^{\frac{1}{p}} \\]  
  It can be the Manhattan distance  
  \\[ D_{xy} = |x_1 - y_1| + |x_2 - y_2| + ... + |x_n - y_n| \\]  
  where $p = 1 $.  
    
  It can be the Euclidean distance  
  \\[ D_{xy} = \sqrt{(|x_1 - y_1|)^{2} + (|x_2 - y_2|)^{2} + ... + (|x_n -
  y_n|)^{2}} \\]  
  where $p = 2 $.  
    
  Also, it can be the Chebyshev distance  
    
  \\[ D_{xy} = max_{i=1}^n (|x_i - y_i|) \\]  
    
  where $p = \infty$
  
  Write a program which reads two $n$ dimensional vectors $x$ and $y$, and
  calculates Minkowski's distance where $p = 1, 2, 3, \infty$ respectively.
samples: [{"input": "1 2 3\n    2 0 4", "output": ".000000\n    2.449490\n    2.154435\n    2.000000"}]