基于Python绘制3D立体爱心图案的示例详解

原理

1.使用python中的mtplotlib库。

2.立体爱心面公式

点画法（实心）

代码

import matplotlib.pyplot as plt #导入绘图模块
from mpl_toolkits.mplot3d import Axes3D #3d绘图模块
import numpy as np #导入数值计算拓展模块

#start generating points
x_lim=np.linspace(-10,10,150)
y_lim=np.linspace(-10,10,150)
z_lim=np.linspace(-10,10,150)
X_points=[] #用来存放绘图点X坐标
Y_points=[] #用来存放绘图点Y坐标
Z_points=[] #用来存放绘图点Z坐标
for x in x_lim:
   for y in y_lim:
       for z in z_lim:
           if (x**2+(9/4)*y**2+z**2-1)**3-(9/80)*y**2*z**3-x**2*z**3<=0:
               X_points.append(x)
               Y_points.append(y)
               Z_points.append(z)

plt.style.use('seaborn')
fig=plt.figure()
ax=fig.add_subplot(111,projection='3d')
ax.scatter(X_points,Y_points,Z_points,color="red")
plt.show()

运行效果

这个画法侧面看起来很无语。

点画法（空心）

代码

import matplotlib.pyplot as plt #导入绘图模块
from mpl_toolkits.mplot3d import Axes3D #3d绘图模块
import numpy as np #导入数值计算拓展模块

#start generating points
x_lim=np.linspace(-10,10,200)
y_lim=np.linspace(-10,10,200)
z_lim=np.linspace(-10,10,200)
X_points=[] #用来存放绘图点X坐标
Y_points=[] #用来存放绘图点Y坐标
Z_tmp=[]
Z_points=[] #用来存放绘图点Z坐标
for y in y_lim:
   for x in x_lim:
       for z in z_lim:
           k=(x**2+(9/4)*y**2+z**2-1)**3-(9/80)*y**2*z**3-x**2*z**3
           if k<=0 :
               Z_tmp.append(z)
               if y<=-0.55 or y>=0.55:
                   X_points.append(x)
                   Y_points.append(y)    
                   Z_points.append(z)
       if Z_tmp:
           X_points.append(x)
           Y_points.append(y)    
           Z_points.append(max(Z_tmp))
           X_points.append(x)
           Y_points.append(y)    
           Z_points.append(min(Z_tmp))
           Z_tmp.clear()

plt.style.use('seaborn')
fig=plt.figure()
ax=fig.add_subplot(111,projection='3d')
ax.set_zlim(-1, 1)
ax.set_xlim(-1, 1)
ax.set_ylim(-1, 1)
ax.scatter(X_points,Y_points,Z_points)

plt.show()

运行效果

折线画法 （线团）

代码

import matplotlib.pyplot as plt #导入绘图模块
from mpl_toolkits.mplot3d import Axes3D #3d绘图模块
import numpy as np #导入数值计算拓展模块

#start generating points
x_lim=np.linspace(-10,10,150)
y_lim=np.linspace(-10,10,150)
z_lim=np.linspace(-10,10,150)
X_points=[] #用来存放绘图点X坐标
Y_points=[] #用来存放绘图点Y坐标
Z_tmp=[]
Z_points=[] #用来存放绘图点Z坐标
for y in y_lim:
   for x in x_lim:
       for z in z_lim:
           k=(x**2+(9/4)*y**2+z**2-1)**3-(9/80)*y**2*z**3-x**2*z**3
           if k<=0 :
               Z_tmp.append(z)
               if y<=-0.55 or y>=0.55:
                   X_points.append(x)
                   Y_points.append(y)    
                   Z_points.append(z)
       if Z_tmp:
           X_points.append(x)
           Y_points.append(y)    
           Z_points.append(max(Z_tmp))
           X_points.append(x)
           Y_points.append(y)    
           Z_points.append(min(Z_tmp))
           Z_tmp.clear()

plt.style.use('seaborn')
fig=plt.figure()
ax=fig.add_subplot(111,projection='3d')
ax.set_zlim(-1, 1)
ax.set_xlim(-1, 1)
ax.set_ylim(-1, 1)
ax.plot(X_points,Y_points,Z_points)

plt.show()

运行效果

等高线画法（线框）

代码

from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import matplotlib.pyplot as plt
import numpy as np

def heart_3d(x, y, z):
   return (x**2+(9/4)*y**2+z**2-1)**3-x**2*z**3-(9/80)*y**2*z**3

def plot_implicit(fn, bbox=(-1.5, 1.5)):
   xmin, xmax, ymin, ymax, zmin, zmax = bbox*3
   fig = plt.figure()
   ax = fig.add_subplot(projection='3d')
   A = np.linspace(xmin, xmax, 100)  # resolution of the contour
   B = np.linspace(xmin, xmax, 10)  # number of slices
   A1, A2 = np.meshgrid(A, A)  # grid on which the contour is plotted

for z in B:  # plot contours in the XY plane
       X, Y = A1, A2
       Z = fn(X, Y, z)
       cset = ax.contour(X, Y, Z+z, [z], zdir='z', colors=('r',))

for y in B:  # plot contours in the XZ plane
       X, Z = A1, A2
       Y = fn(X, y, Z)
       cset = ax.contour(X, Y+y, Z, [y], zdir='y', colors=('red',))

for x in B:  # plot contours in the YZ plane
       Y, Z = A1, A2
       X = fn(x, Y, Z)
       cset = ax.contour(X+x, Y, Z, [x], zdir='x', colors=('red',))

# must set plot limits because the contour will likely extend
   # way beyond the displayed level. Otherwise matplotlib extends the plot limits
   # to encompass all values in the contour.
   ax.set_zlim3d(zmin, zmax)
   ax.set_xlim3d(xmin, xmax)
   ax.set_ylim3d(ymin, ymax)

plt.show()

if __name__ == '__main__':
   plot_implicit(heart_3d)

运行效果

以上代码整理于网络，需要的小伙伴可以参考一下

来源：https://blog.csdn.net/zulumasaya/article/details/126714799