# CS代考计算机代写 import matplotlib.pyplot as plt

import matplotlib.pyplot as plt
import matplotlib.animation as animation
import mpl_toolkits.mplot3d.axes3d as p3
import numpy as np

def animate_wave_simulation_2D(U):
“””
Creates a 2D animation of a wave simulation.

Automatically selects color-scale. In the event of instability or
a wild range of values, some components might not be easily seen.
Consider tweaking this scale if you need to.

Parameters
———-
U: list-like
A list of 2D wavefields to animate.

Returns
——-
Matplotlib animation class instance.

“””

fig = plt.figure()

cmin, cmax = U[0].min(), U[0].max()
for u in U:
cmin = min(cmin, u.min())
cmax = max(cmax, u.max())

cmin = max(-1, cmin)
cmax = min(1, cmax)

im = plt.imshow(U[0], clim=(cmin,cmax), cmap=’gray’)
def animate(i):
im.set_data(U[i])
return (im,)

ani = animation.FuncAnimation(fig, animate, interval=50, repeat_delay=1000)

return ani

def animate_wave_simulation_3D(U):
“””
Creates a 3D surface animation of a wave simulation.

Automatically selects color-scale. In the event of instability or
a wild range of values, some components might not be easily seen.
Consider tweaking this scale if you need to.

Parameters
———-
U: list-like
A list of 2D wavefields to animate.

Returns
——-
Matplotlib animation class instance.

“””

grid_y = np.linspace(0, 1, U[0].shape[0])
grid_x = np.linspace(0, 1, U[0].shape[1])
YY, XX = np.meshgrid(grid_y, grid_x)

fig = plt.figure()
ax = p3.Axes3D(fig)

cmin, cmax = U[0].min(), U[0].max()
for u in U:
cmin = min(cmin, u.min())
cmax = max(cmax, u.max())

cmin = max(-1, cmin)
cmax = min(1, cmax)

surf = [ax.plot_surface(YY, XX, U[0], cmap=”viridis”, clim=(cmin, cmax))]
ax.set_zlim(1.1*cmin, 1.1*cmax)

def animate(i, U, surf):
surf[0].remove()
surf[0] = ax.plot_surface(YY, XX, U[i], cmap=”viridis”, clim=(-1,1))

ani = animation.FuncAnimation(fig, animate, fargs=(U, surf), interval=50, repeat_delay=1000)

return ani