3D图形的绘制

一.3D可视化图表

1.3D柱状图、3D直方图

import random
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from mpl_toolkits.mplot3d import Axes3D

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
for z in range(1, 4):
    xs = range(1, 9)
    ys = 10 * np.random.rand(8)
    color = plt.cm.plasma(random.choice(range(plt.cm.plasma.N)))
    #zdir判断方向
    ax.bar(xs, ys, zs=z, zdir='y', color=color)
plt.show()

#3D直方图
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D

np.random.seed(20190415)
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x, y = np.random.rand(2, 100) * 4
hist, xedges, yedges = np.histogram2d(x, y, bins=4, range=[[0, 4], [0, 4]])
xpos, ypos = np.meshgrid(xedges[:-1] + 0.25, yedges[:-1] + 0.25, indexing="ij")
xpos = xpos.ravel()
ypos = ypos.ravel()
zpos = 0
dx = dy = 0.5 * np.ones_like(zpos)
dz = hist.ravel()
ax.bar3d(xpos, ypos, zpos, dx, dy, dz, color='lightgreen', zsort='average')
plt.show()

2.3D相框图、3D曲面图、3D三翼面图

#线框图
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
X, Y, Z = axes3d.get_test_data(0.04)
ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)
plt.show()

#曲面图
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
r = np.linspace(0, 1.25, 50)
p = np.linspace(0, 2*np.pi, 50)
R, P = np.meshgrid(r, p)
Z = ((R**2 - 1)**2)
X, Y = R*np.cos(P), R*np.sin(P)
ax.plot_surface(X, Y, Z, cmap=plt.cm.YlGnBu_r)
plt.show()

#三翼曲面图
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.tri as mtri
from mpl_toolkits.mplot3d import Axes3D

fig = plt.figure()
u = np.linspace(0, 2.0 * np.pi, endpoint=True, num=50)
v = np.linspace(-0.5, 0.5, endpoint=True, num=10)
u, v = np.meshgrid(u, v)
u, v = u.flatten(), v.flatten()
x = (1 + 0.5 * v * np.cos(u / 2.0)) * np.cos(u)
y = (1 + 0.5 * v * np.cos(u / 2.0)) * np.sin(u)
z = 0.5 * v * np.sin(u / 2.0)
tri = mtri.Triangulation(u, v)
ax = fig.add_subplot(111, projection='3d')
ax.plot_trisurf(x, y, z, triangles=tri.triangles, cmap=plt.cm.Spectral)
ax.set_zlim(-1, 1)
plt.show()

二.创建动画

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

fig, ax = plt.subplots()
x = np.arange(0, 2*np.pi, 0.01)
line, = ax.plot(x, np.sin(x))
def animate(i):
    line.set_ydata(np.sin(x + i/10.0))
    return line,

def init():
    line.set_ydata(np.sin(x))
    return line,

ani = animation.FuncAnimation(fig=fig, func=animate, frames=100, init_func=init, interval=20, blit=False)
#plt.show()
#生成mp4文件
ani.save('Sin(x).mp4', fps=30, extra_args=['-vcodec', 'libx264'], writer='ffmpeg_file')

来源：《python数据分析与可视化》