在matplotlib中将错误栏添加到3D绘图中

时间:2014-10-07 21:16:16

标签: python matplotlib 3d

我找不到在matplotlib中的3D散点图中绘制错误栏的方法。 基本上,对于下面的代码

from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
X, Y, Z = axes3d.get_test_data(1)
ax.scatter(X, Y, zs = Z, zdir = 'z')

我正在寻找像

这样的东西
ax.errorbar(X,Y, zs = Z, dY, dX, zserr = dZ)

有没有办法在mplot3d中执行此操作?如果没有,是否有其他库具有此功能?

2 个答案:

答案 0 :(得分:5)

论坛http://mple.m-artwork.eu/home/posts/simple3dplotwith3derrorbars

上有明显的例子

以下是代码,但不是内置功能:

import numpy as np
import matplotlib.pyplot as plt
import mpl_toolkits.mplot3d.axes3d as axes3d

fig = plt.figure(dpi=100)
ax = fig.add_subplot(111, projection='3d')



#data
fx = [0.673574075,0.727952994,0.6746285]
fy = [0.331657721,0.447817839,0.37733386]
fz = [18.13629648,8.620699842,9.807536512]

#error data
xerror = [0.041504064,0.02402152,0.059383144]
yerror = [0.015649804,0.12643117,0.068676131]
zerror = [3.677693713,1.345712547,0.724095592]

#plot points
ax.plot(fx, fy, fz, linestyle="None", marker="o")

#plot errorbars
for i in np.arange(0, len(fx)):
    ax.plot([fx[i]+xerror[i], fx[i]-xerror[i]], [fy[i], fy[i]], [fz[i], fz[i]], marker="_")
    ax.plot([fx[i], fx[i]], [fy[i]+yerror[i], fy[i]-yerror[i]], [fz[i], fz[i]], marker="_")
    ax.plot([fx[i], fx[i]], [fy[i], fy[i]], [fz[i]+zerror[i], fz[i]-zerror[i]], marker="_")

#configure axes
ax.set_xlim3d(0.55, 0.8)
ax.set_ylim3d(0.2, 0.5)
ax.set_zlim3d(8, 19)

plt.show()

答案 1 :(得分:0)

我最终为 matplotlib 编写了方法:official example for 3D errorbars

enter image description here

import matplotlib.pyplot as plt
import numpy as np

ax = plt.figure().add_subplot(projection='3d')

# setting up a parametric curve
t = np.arange(0, 2*np.pi+.1, 0.01)
x, y, z = np.sin(t), np.cos(3*t), np.sin(5*t)

estep = 15
i = np.arange(t.size)
zuplims = (i % estep == 0) & (i // estep % 3 == 0)
zlolims = (i % estep == 0) & (i // estep % 3 == 2)

ax.errorbar(x, y, z, 0.2, zuplims=zuplims, zlolims=zlolims, errorevery=estep)

ax.set_xlabel("X label")
ax.set_ylabel("Y label")
ax.set_zlabel("Z label")

plt.show()