作者:catmelo 本文版权归作者所有
本文参考官方文档:http://matplotlib.org/mpl_toolkits/mplot3d/tutorial.html
起步
新建一个matplotlib.figure.Figure对象,然后向其添加一个Axes3D类型的axes对象。
其中Axes3D对象的创建,类似其他axes对象,只不过使用projection='3d'
关键词。
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import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D fig = plt.figure() ax = fig.add_subplot( 111 , projection = '3d' ) |
3D曲线图
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import matplotlib as mpl from mpl_toolkits.mplot3d import Axes3D import numpy as np import matplotlib.pyplot as plt mpl.rcParams[ 'legend.fontsize' ] = 10 fig = plt.figure() ax = fig.gca(projection = '3d' ) theta = np.linspace( - 4 * np.pi, 4 * np.pi, 100 ) z = np.linspace( - 2 , 2 , 100 ) r = z * * 2 + 1 x = r * np.sin(theta) y = r * np.cos(theta) ax.plot(x, y, z, label = 'parametric curve' ) ax.legend() ax.set_xlabel( 'X Label' ) ax.set_ylabel( 'Y Label' ) ax.set_zlabel( 'Z Label' ) plt.show() |
简化用法:
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from pylab import * from mpl_toolkits.mplot3d import Axes3D plt.gca(projection = '3d' ) plt.plot([ 1 , 2 , 3 ],[ 3 , 4 , 1 ],[ 8 , 4 , 1 ], '--' ) plt.xlabel( 'X' ) plt.ylabel( 'Y' ) #plt.zlabel('Z') #无法使用 |
3D散点图
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import numpy as np from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt def randrange(n, vmin, vmax): return (vmax - vmin) * np.random.rand(n) + vmin fig = plt.figure() ax = fig.add_subplot( 111 , projection = '3d' ) n = 100 for c, m, zl, zh in [( 'r' , 'o' , - 50 , - 25 ), ( 'b' , '^' , - 30 , - 5 )]: xs = randrange(n, 23 , 32 ) ys = randrange(n, 0 , 100 ) zs = randrange(n, zl, zh) ax.scatter(xs, ys, zs, c = c, marker = m) ax.set_xlabel( 'X Label' ) ax.set_ylabel( 'Y Label' ) ax.set_zlabel( 'Z Label' ) plt.show() |
以上就是matplotlib绘制三维图的示例的详细内容,更多关于matplotlib绘制三维图的资料请关注服务器之家其它相关文章!
原文链接:https://www.cnblogs.com/catmelo/p/4162101.html