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age/plot an gif to this code. This is a brownian motion python code  here it is code  import numpy as np import matplotlib.pyplot as plt def brownian_motion(L, N):    # initialize position in the center of the grid    x = L // 2    y = L // 2    # initialize the grid    grid = np.zeros((L, L), dtype=np.int32)    # loop over the number of steps    for i in range(N):        # choose a random direction

age/plot an gif to this code. This is a brownian motion python code  here it is code  import numpy as np import matplotlib.pyplot as plt def brownian_motion(L, N):    # initialize position in the center of the grid    x = L // 2    y = L // 2    # initialize the grid    grid = np.zeros((L, L), dtype=np.int32)    # loop over the number of steps    for i in range(N):        # choose a random direction

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Please add an gif image/plot an gif to this code. This is a brownian motion python code 

here it is code 

import numpy as np
import matplotlib.pyplot as plt
def brownian_motion(L, N):
   # initialize position in the center of the grid
   x = L // 2
   y = L // 2
   # initialize the grid
   grid = np.zeros((L, L), dtype=np.int32)
   # loop over the number of steps
   for i in range(N):
       # choose a random direction
       direction = np.random.choice(['up', 'down', 'left', 'right'])
       # move one step in that direction
       if direction == 'up':
          " y += 1"
       elif direction == 'down':
           "y -= 1"
       elif direction == 'left':
           "x -= 1"
       elif direction == 'right':
           "x += 1"
       # make sure the particle is still on the grid
       if x < 0 or x >= L or y < 0 or y >= L:
           "continue"
       # update the grid
       grid[y, x] = 1
   return grid
if __name__ == '__main__':
   # set the size of the grid
   L = 101
   # set the number of steps
   N = 1000000
   # generate the grid
   grid = brownian_motion(L, N)
   # plot the grid
   plt.imshow(grid, cmap='gray')
   plt.show()
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