/pipisorry/article/details/40008005
Matplotlib mplot3d 工具包简介
The mplot3d toolkit adds simple 3D plotting capabilities to matplotlib by supplying an axes object that can create a 2D projection of a 3D scene. The resulting graph will have the same look and feel as regular 2D plots.
创建Axes3D对象
An Axes3D object is created just like any other axes using the projection=‘3d’ keyword. Create a new matplotlib.figure.Figure and add a new axes to it of type Axes3D:
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection=’3d’)
New in version 1.0.0: This approach is the preferred method of creating a 3D axes.
Note: Prior to version 1.0.0, the method of creating a 3D axes was di erent. For those using older versions of matplotlib, change ax = fig.add_subplot(111, projection=’3d’) to ax = Axes3D(fig).
要注意的地方
Axes3D展示三维图形时，其初始视图中x,y轴与我们一般看的视图（自己画的时候的视图）是反转的，matlab也是一样。
可以通过设置初始视图来改变角度：ax.view_init(30, 35)
Note: 不过这样图形可能会因为旋转而有阴影，也可以通过代码中XY轴互换来实现视图中XY互换。不知道有没有其它方法，如matlab中就有surf(x,y,z);set(gca,'xdir','reverse','ydir','reverse')这样命令来实现这个功能[关于matlab三维图坐标轴原点位置的问题]。
lz总结绘制三维图形一般流程
创建Axes3D对象
fig = plt.figure()ax = Axes3D(fig)
再进行坐标范围设定什么的（可选）
# 计算坐标极限值xs = list(itertools.chain.from_iterable([xi[0]forxiinx]))x_max, x_min = max(xs), min(xs)ys = list(itertools.chain.from_iterable([xi[1]forxiinx]))y_max, y_min = max(ys), min(ys)zs = list(itertools.chain.from_iterable([xi[2]forxiinx]))z_max, z_min = max(zs), min(zs)margin = 0.1
再进行绘制，如
plt.scatter(x_new[0],x_new[1],c='r',marker='*',s=50,label='new x')
ax.scatter(xs, ys, zs,c=c,marker=marker,s=50,label=label)
ax.plot_surface(X, Y, Z,rstride=1,cstride=1,label='Discrimination Interface')
再进行一些坐标什么的设置
# 设置图形展示效果ax.set_xlim(x_min - margin, x_max + margin)ax.set_ylim(y_min - margin, y_max + margin)ax.set_zlim(z_min - margin, z_max + margin)ax.set_xlabel('x')ax.set_ylabel('y')ax.set_zlabel('z')ax.legend(loc='lower right')ax.set_title('Plot of class0 vs. class1')ax.view_init(30, 35)
最后显示出来
plt.show()
皮皮blog
绘制不同三维图形
Line plots线图
Scatter plots散点图
Axes3D.scatter(xs, ys, zs=0, zdir=u'z', s=20, c=u'b', depthshade=True, *args, **kwargs)
Create a scatter plot
Keyword arguments are passed on toscatter().Returns a Patch3DCollectionNote:scatter(x,y,s=20,c=u'b',marker=u'o',cmap=None,norm=None,vmin=None,vmax=None,alpha=None,linewidths=None,verts=None,**kwargs)
Wireframe plots线框图
Surface plots曲面图
参数
x, y, z: x,y,z轴对应的数据。注意z的数据的z.shape是(len(y), len(x))，不然会报错：ValueError: shape mismatch: objects cannot be broadcast to a single shape
rstride Array row stride (step size), defaults to 10
cstride Array column stride (step size), defaults to 10
示例1：
import numpy as npimport matplotlib.pyplot as pltfrom mpl_toolkits.mplot3d import Axes3Dfig = plt.figure()ax = Axes3D(fig)X = np.arange(-4, 4, 0.25)Y = np.arange(-4, 4, 0.25)X, Y = np.meshgrid(X, Y)R = np.sqrt(X**2 + Y**2)Z = np.sin(R)ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=plt.cm.hot)ax.contourf(X, Y, Z, zdir='z', offset=-2, cmap=plt.cm.hot)ax.set_zlim(-2,2)# savefig('../figures/plot3d_ex.png',dpi=48)plt.show()
结果图形输出：
示例2：
import numpy as npimport matplotlib.pyplot as pltfrom mpl_toolkits.mplot3d import Axes3Dfig = plt.figure()ax = Axes3D(fig)x = np.arange(0, 200)y = np.arange(0, 100)x, y = np.meshgrid(x, y)z = np.random.randint(0, 200, size=(100, 200))%3print(z.shape)# ax.scatter(x, y, z, c='r', marker='.', s=50, label='')ax.plot_surface(x, y, z,label='')plt.show()
[surface-plots]
[Matplotlib tutorial - 3D Plots]
Tri-Surface plots三面图
Contour plots等高线图
Filled contour plots填充等高线图
Polygon plots多边形图
Axes3D.add_collection3d(col, zs=0, zdir=u'z')
Add a 3D collection object to the plot.
2D collection types are converted to a 3D version bymodifying the object and adding z coordinate information.
Supported are:
PolyCollectionLineCollecitonPatchCollection绘图原理是：设置好多面体（如正文体）的顶点坐标和所有面对应的顶点，加上一些属性（如颜色、宽度、透明度）
绘制正方体和四面体示例
#!/usr/bin/env python# -*- coding: utf-8 -*-"""__title__ = ''__author__ = '皮'__mtime__ = '9/27/-027'__email__ = 'pipisorry@'"""importmatplotlib.pyplotaspltfrommpl_toolkits.mplot3d.art3dimportPoly3DCollectionfig = plt.figure()ax = fig.gca(projection='3d')# 正文体顶点和面verts = [(0, 0, 0), (0, 1, 0), (1, 1, 0), (1, 0, 0), (0, 0, 1), (0, 1, 1), (1, 1, 1), (1, 0, 1)]faces = [[0, 1, 2, 3], [4, 5, 6, 7], [0, 1, 5, 4], [1, 2, 6, 5], [2, 3, 7, 6], [0, 3, 7, 4]]# 四面体顶点和面# verts = [(0, 0, 0), (1, 0, 0), (1, 1, 0), (1, 0, 1)]# faces = [[0, 1, 2], [0, 1, 3], [0, 2, 3], [1, 2, 3]]# 获得每个面的顶点poly3d = [[verts[vert_id]forvert_idinface]forfaceinfaces]# print(poly3d)# 绘制顶点x, y, z = zip(*verts)ax.scatter(x, y, z)# 绘制多边形面ax.add_collection3d(Poly3DCollection(poly3d,facecolors='w',linewidths=1,alpha=0.3))# ax.add_collection3d(Line3DCollection(poly3d, colors='k', linewidths=0.5, linestyles=':'))
# 设置图形坐标范围ax.set_xlabel('X')ax.set_xlim3d(-0.5, 1.5)ax.set_ylabel('Y')ax.set_ylim3d(-0.5, 1.5)ax.set_zlabel('Z')ax.set_zlim3d(-0.5, 1.5)plt.show()
绘制结果截图
[Transparency for Poly3DCollection plot in matplotlib]
Bar plots条形图
2D plots in 3D三维图中的二维图
Text文本图
Subplotting子图
皮皮blog
matplotlib.mplot3d绘图实例
matplotlib绘制2维高斯分布
import matplotlib.pyplot as pltfrom mpl_toolkits.mplot3d import Axes3Dfig = plt.figure()ax = Axes3D(fig)rv = stats.multivariate_normal([0, 0], cov=1)x, y = np.mgrid[-3:3:.15, -3:3:.15]ax.plot_surface(x, y, rv.pdf(np.dstack((x, y))), rstride=1, cstride=1)ax.set_zlim(0, 0.2)# savefig('../figures/plot3d_ex.png',dpi=48)plt.show()
matplotlib绘制平行z轴的平面
（垂直xy平面的平面）
方程：0*Z + A[0]X + A[1]Y + A[-1] = 0
X = np.arange(x_min-margin,x_max+margin, 0.05)Z = np.arange(z_min-margin,z_max+margin, 0.05)X, Z = np.meshgrid(X, Z)Y = -1 /A[1] * (A[0] * X +A[-1])ax.plot_surface(X, Y, Z,rstride=1,cstride=1,label='Discrimination Interface')
from:/pipisorry/article/details/40008005
ref:mplot3d tutorial(inside source code)
mplot3d API
[mplot3d¶]
