<reponame>makp/social_grid
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
from random_walk import RandWalk

# pars
num_agents = 10
side = 100
time_steps = 400

randw = RandWalk(side, 4)

# Make initial array
arr = randw.create_init(num_agents)

# Run simulation
arrays = randw.run(arr, time_steps)

# Display arrays
fig, ax = plt.subplots()
ax.set_xticks([])
ax.set_yticks([])


def animate():
    ims = []
    for a in arrays:
        a = a.astype('float64')
        a[a == 0] = np.nan
        im = ax.imshow(a, vmin=0)
        ims.append([im])
    return ims


ani = animation.ArtistAnimation(fig, animate())
# ani.save('animation_random_walk.mp4')

plt.show()

import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
from random_walk import RandWalk

# pars
num_agents = 10
side = 100
time_steps = 400

randw = RandWalk(side, 4)

# Make initial array
arr = randw.create_init(num_agents)

# Run simulation
arrays = randw.run(arr, time_steps)

# Display arrays
fig, ax = plt.subplots()
ax.set_xticks([])
ax.set_yticks([])


def animate():
    ims = []
    for a in arrays:
        a = a.astype('float64')
        a[a == 0] = np.nan
        im = ax.imshow(a, vmin=0)
        ims.append([im])
    return ims


ani = animation.ArtistAnimation(fig, animate())
# ani.save('animation_random_walk.mp4')

plt.show()
# pars # Make initial array # Run simulation # Display arrays # ani.save('animation_random_walk.mp4')