一、绘制3D坐标系 具体代码如下: import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D # 创建图形和坐标轴 fig = plt.figure() ax = fig.add_subplot(111, projection='3d') # 定义坐标轴范围 ax.set_xlim([0, 10]) ax.set_ylim([0, 10]) ax.set_zlim([0, 10]) ...
x, y, z = lorenz_attractor(x0, y0, z0, sigma, beta, rho, dt, num_steps) # 绘制3D图形 fig = plt.figure() ax = fig.add_subplot(111, projection='3d') ax.plot(x, y, z, lw=0.5) ax.set_xlabel('X') ax.set_ylabel('Y') ax.set_zlabel('Z')ax.set_title('Lorenz Attractor...
fig=plt.figure() ax=fig.add_subplot(111, projection='3d') 编辑 二、直线绘制(Line plots) 基本用法: 1 ax.plot(x,y,z,label=' ') code: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 importmatplotlib as mpl frommpl_toolkits.mplot3dimportAxes3D importnumpy as np import...
return x1, y1, z1, x2, y2, z2fig = plt.figure()ax = fig.add_subplot(111, projection=’3d’)def update(frame):x1, y1, z1, x2, y2, z2 = generate_data(frame)ax.scatter(x1, y1, z1, color=’red’, label=’Trajectory 1’)ax.scatter(x2, y2, z2, color=’blue’, lab...
ax = fig.add_subplot(111, projection='3d') 二、直线绘制(Line plots) 基本用法: 1 ax.plot(x,y,z,label=' ') code: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 import matplotlib as mpl from mpl_toolkits.mplot3d import Axes3D import numpy as np import matplotlib.pyplot...
3D 帽子图2 30import numpy as np import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D fig = plt.figure() # 指定图形类型为 3d 类型ax = fig.add_subplot(111, projection='3d') # X, Y valueX = np.arange(-5, 5, 0.25) ...
ax = fig.add_subplot(111, projection='3d') 二、直线绘制(Line plots) 基本用法: 1ax.plot(x,y,z,label=' ') code: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 import matplotlib as mpl from mpl_toolkits.mplot3d import Axes3D ...
from mpl_toolkits.mplot3d import axes3d 1)这是在 3-D 空间上绘图所需的模块。 ax1 = fig.add_subplot(111, projection='3d') 2)在图形上创建一个子图并将投影参数设置为 3d。 ax1.scatter(x, y, z, c = 'm', marker = 'o') ...
ax = fig.add_subplot(111, projection='3d')# 设置 X、Y、Z 轴坐标数据 x = [1, 2, 3, 4...
帽子图1 3D 帽子图2importnumpyasnp importmatplotlib.pyplotasplt frommpl_toolkits.mplot3dimportAxes3D fig = plt.figure # 指定图形类型为 3d 类型 ax = fig.add_subplot(111, projection='3d') # X, Y value X = np.arange(-5,5,0.25) ...