I've got this code:
import matplotlib.pyplot as plt
import mpl_toolkits.mplot3d.axes3d as plt3d
import mpl_toolkits.mplot3d.art3d as artplt3d
import matplotlib.animation as animation
import numpy as np
import math
def animateBeta():
def translate(segment_, xTr_, yTr_, zTr_):
translationMatrix = np.array([
[1, 0, xTr_],
[0, 1, yTr_],
[0, 0, zTr_]
])
return np.matmul(translationMatrix, segment_)
def rotate(vec_, xRotate_, yRotate_, zRotate_):
xMat = np.array([
[1,0,0],
[0,math.cos(xRotate_), -math.sin(xRotate_)],
[0, math.sin(xRotate_), math.cos(xRotate_)]
])
yMat = np.array([
[math.cos(yRotate_), 0, math.sin(yRotate_)],
[0, 1, 0],
[-math.sin(yRotate_), 0, math.cos(yRotate_)]
])
zMat = np.array([
[math.cos(zRotate_), -math.sin(zRotate_), 0],
[math.sin(zRotate_), math.cos(zRotate_), 0],
[0, 0, 1]
])
rotationMatrix = np.matmul(zMat, np.matmul(yMat, xMat))
return np.matmul(rotationMatrix, vec_)
segment = [
[0,0],
[0,0],
[1, -1]
]
fig = plt.figure()
ax = plt3d.Axes3D(fig)
line, = ax.plot(segment[0], segment[1], zs=segment[2], color = 'b')
artplt3d.line_2d_to_3d(line)
print(line.__class__)
def animate(i):
s0 = [0,0,1]
s1 = [0,0,-1]
s1 = translate(rotate(translate(s1, -s0[0], -s0[1], -s0[2]), -i*(math.pi/180),0,-i*(math.pi/180)), s0[0], s0[1], s0[2])
segment = np.concatenate((np.reshape(s0, (3,-1)),np.reshape(s1, (3,-1))), axis=1)
#data = ax.plot(segment[0], segment[1], segment[2], color = 'b')
line.set_3d_properties(zs=segment[2])
line.set_data_3d(segment[0], segment[1], segment[2])
anim = animation.FuncAnimation(fig, animate, interval = 1)
plt.show()
animateBeta()
It works when using the commented data = ax.plot(segment[0], segment[1], segment[2], color = 'b')
line instead of the following two, (but I'm trying to make it so that I don't have the previous lines drawn when drawing new ones on top).
If you use the code as-is, the animation just seems odd.
I have a theory that line_2d_to_3d
isn't working as intended but I'm not sure.
Okay so I was using ax.plot instead of plot3D, and I was under the IMPRESSION that the draw was more correct when using ax.plot