如何在 matplotlib 图上设置动画

Question

I have an assignment where I need to project 3D cube in to 2D Cartesian plane, I've done plotting the vertex points but will still need to animate it somehow.

I have tried using FuncAnimation(), but no clue how it works. I am still new to python so go easy on me, thank you.

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation

A = np.array([-0.5,-0.5,-0.5])
B = np.array([0.5,-0.5,-0.5])
C = np.array([0.5,0.5,-0.5])
D = np.array([-0.5,0.5,-0.5])
E = np.array([-0.5,-0.5,0.5])
F = np.array([0.5,-0.5,0.5])
G = np.array([0.5,0.5,0.5])
H = np.array([-0.5,0.5,0.5])

load = np.array([A,B,C,D,E,F,G,H])
print(load)

fig = plt.figure()
ax = plt.axes(xlim =(-1,1),ylim =(-1,1))

#   Declared to allow for x and y axis only
projection = np.array([ [1,0,0], [0,1,0] ])
xdata,ydata = [],[]

plt.title("Render 3D Cube in 2D Space")
for x in load:
    for angle in range(360):
        rotationY = np.array([ [np.cos(angle),0,np.sin(angle)],
                        [0,1,0],
                        [-np.sin(angle),0,np.cos(angle)] ])
        rotationX = np.array([ [1,0,0],
                        [0,np.cos(angle),-np.sin(angle)],
                        [0,np.sin(angle),np.cos(angle)] ])

        #   Drawing each points
        rotated = np.dot(rotationY,x)
        rotated = np.dot(rotationX,rotated)
        projected2d = np.dot(projection,rotated)
        #projected2d = np.dot(projection,x) -With no rotations
    line = ax.plot(projected2d[0],projected2d[1],c = "blue",marker = "o")
def animate(i):
    x0,y0 = i
    xdata.append(x0)
    ydata.append(y0)
    line.set_data(xdata,ydata)
    return line
anim = FuncAnimation(fig,animate,interval =200,frames = 30)

plt.grid()
#plt.draw()
plt.show()

https://imgur.com/LR6oPtt

Answer 1

The FuncAnimation constructor takes a callable function (in your case animate ) which gets the current frame number as an argument (here i ) and updates the plot. This means, you should store all your intermediate points in an array ( frames ) and then later access those (you could also compute the projection on the fly, but I would not recommend this). The animation will then loop through the frames and apply the function to every frame.

Also, you should use radians (angles from 0 to 2π) for your rotations.

Here's a version that should work:

# list of the angles in radians
angles = np.linspace(0, 2*np.pi, 360)

# storage of single frames - one value per point and angle.
frames = np.zeros((len(load),len(angles),2))

# loops through all points and angles to store for later usage.
for i, x in enumerate(load):
    for j, angle in enumerate(angles):
        rotationY = np.array([[np.cos(angle),0,np.sin(angle)],
                        [0,1,0],
                        [-np.sin(angle),0,np.cos(angle)] ])
        rotationX = np.array([ [1,0,0],
                        [0,np.cos(angle),-np.sin(angle)],
                        [0,np.sin(angle),np.cos(angle)] ])

        rotated = np.dot(rotationY, x)
        rotated = np.dot(rotationX, rotated)
        projected2d = np.dot(projection, rotated)

        # store the point.
        frames[i,j,:] = projected2d

# draws the initial point.
line, = ax.plot(frames[:,0,0], frames[:,0,1], c="blue", marker="o", ls='')


# defines what happens at frame 'i' - you want to update with the current
# frame that we have stored before.
def animate(i):
    line.set_data(frames[:,i,0], frames[:,i,1])
    return line # not really necessary, but optional for blit algorithm

# the number of frames is the number of angles that we wanted.
anim = FuncAnimation(fig, animate, interval=200, frames=len(angles))