基于Python绘制3D立体爱心图案的示例详解
作者:弦masamasa
这篇文章主要为大家详细介绍了利用Python实现绘制3D立体爱心图案的四种不同方法,文中的示例代码讲解详细,感兴趣的小伙伴可以动手尝试一下
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
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