{"id":1089849,"date":"2025-01-08T13:57:10","date_gmt":"2025-01-08T05:57:10","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1089849.html"},"modified":"2025-01-08T13:57:12","modified_gmt":"2025-01-08T05:57:12","slug":"python%e5%a6%82%e4%bd%95%e7%bb%98%e5%88%b6%e4%b8%89%e7%bb%b4%e5%9b%be%e5%83%8f-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1089849.html","title":{"rendered":"python\u5982\u4f55\u7ed8\u5236\u4e09\u7ef4\u56fe\u50cf"},"content":{"rendered":"

\"python\u5982\u4f55\u7ed8\u5236\u4e09\u7ef4\u56fe\u50cf\"<\/p>\n

Python\u5982\u4f55\u7ed8\u5236\u4e09\u7ef4\u56fe\u50cf<\/strong>\uff1a\u4f7f\u7528Matplotlib\u5e93\u3001\u4f7f\u7528Mayavi\u5e93\u3001\u4f7f\u7528Plotly\u5e93\u3001\u4f7f\u7528Vispy\u5e93<\/strong>\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Matplotlib\u5e93\u6765\u7ed8\u5236\u4e09\u7ef4\u56fe\u50cf\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528Matplotlib\u5e93<\/h3>\n<\/p>\n

Matplotlib\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u7ed8\u56fe\u5e93\u4e4b\u4e00\uff0c\u5b83\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u529f\u80fd\u6765\u521b\u5efa\u5404\u79cd\u56fe\u8868\u548c\u56fe\u50cf\uff0c\u5305\u62ec\u4e09\u7ef4\u56fe\u50cf\u3002Matplotlib\u7684mpl_toolkits.mplot3d<\/code>\u6a21\u5757\u5141\u8bb8\u6211\u4eec\u8f7b\u677e\u5730\u521b\u5efa\u548c\u5b9a\u5236\u4e09\u7ef4\u56fe\u50cf\u3002<\/p>\n<\/p>\n

1. \u5b89\u88c5Matplotlib<\/h4>\n<\/p>\n

\u5728\u5f00\u59cb\u7ed8\u5236\u4e09\u7ef4\u56fe\u50cf\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5Matplotlib\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install matplotlib<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u521b\u5efa\u4e09\u7ef4\u5750\u6807\u8f74<\/h4>\n<\/p>\n
\u5728Matplotlib\u4e2d\uff0c\u4e09\u7ef4\u56fe\u50cf\u9700\u8981\u4e00\u4e2a\u4e09\u7ef4\u5750\u6807\u8f74\uff0c\u4f7f\u7528Axes3D<\/code>\u7c7b\u6765\u521b\u5efa\u3002\u4e0b\u9762\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
from mpl_toolkits.mplot3d import Axes3D<\/p>\n
fig = plt.figure()<\/p>\n
ax = fig.add_subplot(111, projection='3d')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u7ed8\u5236\u4e09\u7ef4\u6563\u70b9\u56fe<\/h4>\n<\/p>\n
\u4e09\u7ef4\u6563\u70b9\u56fe\u662f\u6700\u5e38\u89c1\u7684\u4e09\u7ef4\u56fe\u50cf\u4e4b\u4e00\u3002\u4e0b\u9762\u662f\u4e00\u4e2a\u7ed8\u5236\u4e09\u7ef4\u6563\u70b9\u56fe\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
from mpl_toolkits.mplot3d import Axes3D<\/p>\n
import numpy as np<\/p>\n
fig = plt.figure()<\/p>\n
ax = fig.add_subplot(111, projection='3d')<\/p>\n
\u751f\u6210\u968f\u673a\u6570\u636e<\/strong><\/h2>\n
x = np.random.rand(100)<\/p>\n
y = np.random.rand(100)<\/p>\n
z = np.random.rand(100)<\/p>\n
ax.scatter(x, y, z)<\/p>\n
ax.set_xlabel('X Label')<\/p>\n
ax.set_ylabel('Y Label')<\/p>\n
ax.set_zlabel('Z Label')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528scatter<\/code>\u51fd\u6570\u7ed8\u5236\u4e09\u7ef4\u6563\u70b9\u56fe\uff0c\u5e76\u4e14\u4e3a\u6bcf\u4e2a\u8f74\u8bbe\u7f6e\u4e86\u6807\u7b7e\u3002<\/p>\n<\/p>\n
4. \u7ed8\u5236\u4e09\u7ef4\u66f2\u9762\u56fe<\/h4>\n<\/p>\n
\u4e09\u7ef4\u66f2\u9762\u56fe\u7528\u4e8e\u8868\u793a\u4e09\u7ef4\u7a7a\u95f4\u4e2d\u7684\u66f2\u9762\u3002\u4e0b\u9762\u662f\u4e00\u4e2a\u7ed8\u5236\u4e09\u7ef4\u66f2\u9762\u56fe\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
from mpl_toolkits.mplot3d import Axes3D<\/p>\n
import numpy as np<\/p>\n
fig = plt.figure()<\/p>\n
ax = fig.add_subplot(111, projection='3d')<\/p>\n
\u751f\u6210\u7f51\u683c\u6570\u636e<\/strong><\/h2>\n
x = np.linspace(-5, 5, 100)<\/p>\n
y = np.linspace(-5, 5, 100)<\/p>\n
x, y = np.meshgrid(x, y)<\/p>\n
z = np.sin(np.sqrt(x<strong>2 + y<\/strong>2))<\/p>\n
ax.plot_surface(x, y, z, cmap='viridis')<\/p>\n
ax.set_xlabel('X Label')<\/p>\n
ax.set_ylabel('Y Label')<\/p>\n
ax.set_zlabel('Z Label')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528plot_surface<\/code>\u51fd\u6570\u7ed8\u5236\u4e09\u7ef4\u66f2\u9762\u56fe\uff0c\u5e76\u4f7f\u7528cmap<\/code>\u53c2\u6570\u8bbe\u7f6e\u989c\u8272\u6620\u5c04\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528Mayavi\u5e93<\/h3>\n<\/p>\n
Mayavi\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u4e09\u7ef4\u6570\u636e\u53ef\u89c6\u5316\u5e93\uff0c\u7279\u522b\u9002\u7528\u4e8e\u79d1\u5b66\u8ba1\u7b97\u548c\u5de5\u7a0b\u5e94\u7528\u3002Mayavi\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u4e09\u7ef4\u7ed8\u56fe\u529f\u80fd\uff0c\u4e14\u6613\u4e8e\u4f7f\u7528\u3002<\/p>\n<\/p>\n
1. \u5b89\u88c5Mayavi<\/h4>\n<\/p>\n
\u5728\u4f7f\u7528Mayavi\u4e4b\u524d\uff0c\u9700\u8981\u5b89\u88c5Mayavi\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install mayavi<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u7ed8\u5236\u4e09\u7ef4\u6563\u70b9\u56fe<\/h4>\n<\/p>\n
\u4e0b\u9762\u662f\u4e00\u4e2a\u4f7f\u7528Mayavi\u7ed8\u5236\u4e09\u7ef4\u6563\u70b9\u56fe\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
from mayavi import mlab<\/p>\n
import numpy as np<\/p>\n
\u751f\u6210\u968f\u673a\u6570\u636e<\/strong><\/h2>\n
x = np.random.rand(100)<\/p>\n
y = np.random.rand(100)<\/p>\n
z = np.random.rand(100)<\/p>\n
mlab.points3d(x, y, z, scale_factor=0.1)<\/p>\n
mlab.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528mlab.points3d<\/code>\u51fd\u6570\u7ed8\u5236\u4e09\u7ef4\u6563\u70b9\u56fe\uff0c\u5e76\u8bbe\u7f6e\u4e86\u7f29\u653e\u56e0\u5b50\u3002<\/p>\n<\/p>\n
3. \u7ed8\u5236\u4e09\u7ef4\u66f2\u9762\u56fe<\/h4>\n<\/p>\n
\u4e0b\u9762\u662f\u4e00\u4e2a\u4f7f\u7528Mayavi\u7ed8\u5236\u4e09\u7ef4\u66f2\u9762\u56fe\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
from mayavi import mlab<\/p>\n
import numpy as np<\/p>\n
\u751f\u6210\u7f51\u683c\u6570\u636e<\/strong><\/h2>\n
x, y = np.mgrid[-5:5:100j, -5:5:100j]<\/p>\n
z = np.sin(np.sqrt(x<strong>2 + y<\/strong>2))<\/p>\n
mlab.surf(x, y, z, colormap='viridis')<\/p>\n
mlab.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528mlab.surf<\/code>\u51fd\u6570\u7ed8\u5236\u4e09\u7ef4\u66f2\u9762\u56fe\uff0c\u5e76\u4f7f\u7528colormap<\/code>\u53c2\u6570\u8bbe\u7f6e\u989c\u8272\u6620\u5c04\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528Plotly\u5e93<\/h3>\n<\/p>\n
Plotly\u662f\u4e00\u4e2a\u4ea4\u4e92\u5f0f\u7ed8\u56fe\u5e93\uff0c\u652f\u6301\u591a\u79cd\u56fe\u8868\u7c7b\u578b\uff0c\u5305\u62ec\u4e09\u7ef4\u56fe\u50cf\u3002Plotly\u7684\u4e09\u7ef4\u56fe\u50cf\u5177\u6709\u9ad8\u5ea6\u7684\u4ea4\u4e92\u6027\uff0c\u53ef\u4ee5\u901a\u8fc7\u9f20\u6807\u62d6\u52a8\u3001\u7f29\u653e\u548c\u65cb\u8f6c\u67e5\u770b\u4e0d\u540c\u7684\u89c6\u89d2\u3002<\/p>\n<\/p>\n
1. \u5b89\u88c5Plotly<\/h4>\n<\/p>\n
\u5728\u4f7f\u7528Plotly\u4e4b\u524d\uff0c\u9700\u8981\u5b89\u88c5Plotly\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install plotly<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u7ed8\u5236\u4e09\u7ef4\u6563\u70b9\u56fe<\/h4>\n<\/p>\n
\u4e0b\u9762\u662f\u4e00\u4e2a\u4f7f\u7528Plotly\u7ed8\u5236\u4e09\u7ef4\u6563\u70b9\u56fe\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import plotly.graph_objs as go<\/p>\n
import numpy as np<\/p>\n
\u751f\u6210\u968f\u673a\u6570\u636e<\/strong><\/h2>\n
x = np.random.rand(100)<\/p>\n
y = np.random.rand(100)<\/p>\n
z = np.random.rand(100)<\/p>\n
trace = go.Scatter3d(x=x, y=y, z=z, mode='markers')<\/p>\n
layout = go.Layout(scene=dict(xaxis_title='X', yaxis_title='Y', zaxis_title='Z'))<\/p>\n
fig = go.Figure(data=[trace], layout=layout)<\/p>\n
fig.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528go.Scatter3d<\/code>\u51fd\u6570\u7ed8\u5236\u4e09\u7ef4\u6563\u70b9\u56fe\uff0c\u5e76\u8bbe\u7f6e\u8f74\u6807\u7b7e\u3002<\/p>\n<\/p>\n
3. \u7ed8\u5236\u4e09\u7ef4\u66f2\u9762\u56fe<\/h4>\n<\/p>\n
\u4e0b\u9762\u662f\u4e00\u4e2a\u4f7f\u7528Plotly\u7ed8\u5236\u4e09\u7ef4\u66f2\u9762\u56fe\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import plotly.graph_objs as go<\/p>\n
import numpy as np<\/p>\n
\u751f\u6210\u7f51\u683c\u6570\u636e<\/strong><\/h2>\n
x = np.linspace(-5, 5, 100)<\/p>\n
y = np.linspace(-5, 5, 100)<\/p>\n
x, y = np.meshgrid(x, y)<\/p>\n
z = np.sin(np.sqrt(x<strong>2 + y<\/strong>2))<\/p>\n
trace = go.Surface(z=z, x=x, y=y)<\/p>\n
layout = go.Layout(scene=dict(xaxis_title='X', yaxis_title='Y', zaxis_title='Z'))<\/p>\n
fig = go.Figure(data=[trace], layout=layout)<\/p>\n
fig.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528go.Surface<\/code>\u51fd\u6570\u7ed8\u5236\u4e09\u7ef4\u66f2\u9762\u56fe\uff0c\u5e76\u8bbe\u7f6e\u8f74\u6807\u7b7e\u3002<\/p>\n<\/p>\n
\u56db\u3001\u4f7f\u7528Vispy\u5e93<\/h3>\n<\/p>\n
Vispy\u662f\u4e00\u4e2a\u9ad8\u6027\u80fd\u7684\u56fe\u5f62\u5e93\uff0c\u7279\u522b\u9002\u7528\u4e8e\u5904\u7406\u5927\u91cf\u6570\u636e\u548c\u590d\u6742\u7684\u4e09\u7ef4\u56fe\u5f62\u3002Vispy\u57fa\u4e8eOpenGL\uff0c\u63d0\u4f9b\u4e86\u5feb\u901f\u4e14\u9ad8\u6548\u7684\u7ed8\u56fe\u529f\u80fd\u3002<\/p>\n<\/p>\n
1. \u5b89\u88c5Vispy<\/h4>\n<\/p>\n
\u5728\u4f7f\u7528Vispy\u4e4b\u524d\uff0c\u9700\u8981\u5b89\u88c5Vispy\u5e93\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install vispy<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u7ed8\u5236\u4e09\u7ef4\u6563\u70b9\u56fe<\/h4>\n<\/p>\n
\u4e0b\u9762\u662f\u4e00\u4e2a\u4f7f\u7528Vispy\u7ed8\u5236\u4e09\u7ef4\u6563\u70b9\u56fe\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import vispy<\/p>\n
from vispy import scene<\/p>\n
import numpy as np<\/p>\n
canvas = scene.SceneCanvas(keys='interactive', show=True)<\/p>\n
view = canvas.central_widget.add_view()<\/p>\n
\u751f\u6210\u968f\u673a\u6570\u636e<\/strong><\/h2>\n
x = np.random.rand(100)<\/p>\n
y = np.random.rand(100)<\/p>\n
z = np.random.rand(100)<\/p>\n
pos = np.vstack([x, y, z]).T<\/p>\n
scatter = scene.visuals.Markers()<\/p>\n
scatter.set_data(pos, face_color='red', size=5)<\/p>\n
view.add(scatter)<\/p>\n
view.camera = 'turntable'<\/p>\n
if __name__ == '__mAI<\/a>n__':<\/p>\n
    vispy.app.run()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528scene.visuals.Markers<\/code>\u51fd\u6570\u7ed8\u5236\u4e09\u7ef4\u6563\u70b9\u56fe\uff0c\u5e76\u5c06\u5176\u6dfb\u52a0\u5230\u89c6\u56fe\u4e2d\u3002<\/p>\n<\/p>\n
3. \u7ed8\u5236\u4e09\u7ef4\u66f2\u9762\u56fe<\/h4>\n<\/p>\n
\u4e0b\u9762\u662f\u4e00\u4e2a\u4f7f\u7528Vispy\u7ed8\u5236\u4e09\u7ef4\u66f2\u9762\u56fe\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import vispy<\/p>\n
from vispy import scene<\/p>\n
import numpy as np<\/p>\n
canvas = scene.SceneCanvas(keys='interactive', show=True)<\/p>\n
view = canvas.central_widget.add_view()<\/p>\n
\u751f\u6210\u7f51\u683c\u6570\u636e<\/strong><\/h2>\n
x = np.linspace(-5, 5, 100)<\/p>\n
y = np.linspace(-5, 5, 100)<\/p>\n
x, y = np.meshgrid(x, y)<\/p>\n
z = np.sin(np.sqrt(x<strong>2 + y<\/strong>2))<\/p>\n
vertices = np.c_[x.ravel(), y.ravel(), z.ravel()]<\/p>\n
faces = []<\/p>\n
for i in range(x.shape[0] - 1):<\/p>\n
    for j in range(y.shape[1] - 1):<\/p>\n
        faces.append([i * x.shape[1] + j, (i + 1) * x.shape[1] + j, i * x.shape[1] + (j + 1)])<\/p>\n
        faces.append([(i + 1) * x.shape[1] + j, (i + 1) * x.shape[1] + (j + 1), i * x.shape[1] + (j + 1)])<\/p>\n
mesh = scene.visuals.Mesh(vertices=vertices, faces=faces, color='blue', edge_color='black')<\/p>\n
view.add(mesh)<\/p>\n
view.camera = 'turntable'<\/p>\n
if __name__ == '__main__':<\/p>\n
    vispy.app.run()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528scene.visuals.Mesh<\/code>\u51fd\u6570\u7ed8\u5236\u4e09\u7ef4\u66f2\u9762\u56fe\uff0c\u5e76\u5c06\u5176\u6dfb\u52a0\u5230\u89c6\u56fe\u4e2d\u3002<\/p>\n<\/p>\n
\u603b\u7ed3<\/h3>\n<\/p>\n
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