使用列表绘制3D表面图 [英] Plotting 3D surface graphs with lists

问题描述

我正在尝试绘制3D表面图形，其中xlist和ylist是一维列表，而zlist是列表列表.

  xlist = [0，0.1，0.22173，0.3，0.4，0.5，0.6]ylist = [0，0.1,0.4,1,2,5]zlists = [[0，0.0100954，0.05117122，0.0952171，0.1628218419，0.1245，0.0731856]，[[0，0.0101496，0.0516，0.09716544，0.16126，0.1025817，0.059077]，[[0，0.01096289，0.05788095，0.137201，0.1133218，0.0638898，0.0334927]，[[0，0.0155434802394，0.10213，0.120433828182，0.0620560791526，0.0318，0.019]，[[0，0.031145105337，0.12922959，0.064018969907，0.021701508055，0.006237178，0.002]，[[0，0.11832666，0.02912328，0.00511592，0.0004291，0.00005，0.000006]] 

我发现了一个名为Axes3D.plot_surface的合适函数，该函数可以将数据转换为曲面图:

顺便说一句，源代码="http://matplotlib.org/mpl_toolkits/mplot3d/tutorial.html#surface-plots" rel ="nofollow noreferrer"> plot_surface文档也使用了 meshgrid .那是找到这个答案的另一种方式.

I am trying to plot a 3D surface graph with an xlist and a ylist which are one dimensional lists and zlist which is a list of lists.

xlist=  [0, 0.1,    0.22173,    0.3,    0.4,    0.5,    0.6]
ylist = [0, 0.1,0.4,1,2,5]

zlists = [[0,   0.0100954,  0.05117122, 0.0952171,  0.1628218419,   0.1245, 0.0731856],
         [[0,   0.0101496,  0.0516, 0.09716544, 0.16126,    0.1025817,  0.059077],
         [[0,   0.01096289, 0.05788095, 0.137201,   0.1133218,  0.0638898,  0.0334927],
         [[0,   0.0155434802394,    0.10213,    0.120433828182, 0.0620560791526,    0.0318, 0.019],
         [[0,   0.031145105337, 0.12922959, 0.064018969907, 0.021701508055, 0.006237178,    0.002], 
         [[0,   0.11832666, 0.02912328, 0.00511592, 0.0004291,  0.00005,    0.000006]]

I have found a suitable function called Axes3D.plot_surface that can convert the data into a surface plot: http://matplotlib.org/mpl_toolkits/mplot3d/tutorial.html#surface-plots

However it requires the xlist and ylist to be 2D arrays too. How could I transform the xlist and ylist into the required 2D array formats to be able to use readily for the Axes3D.plot_surface function.

解决方案

Use np.meshgrid to generate 2D grid arrays from xlist and ylist:

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

xlist =  [0, 0.1,    0.22173,    0.3,    0.4,    0.5,    0.6]
ylist = [0, 0.1, 0.4, 1, 2, 5]

Z = np.array([ 
    [0,   0.0100954,  0.05117122, 0.0952171,  0.1628218419,   0.1245, 0.0731856],
    [0,   0.0101496,  0.0516, 0.09716544, 0.16126,    0.1025817,  0.059077],
    [0,   0.01096289, 0.05788095, 0.137201,   0.1133218,  0.0638898,  0.0334927],
    [0,   0.0155434802394,    0.10213,    0.120433828182, 0.0620560791526,    0.0318, 0.019],
    [0,   0.031145105337, 0.12922959, 0.064018969907, 0.021701508055, 0.006237178,    0.002], 
    [0,   0.11832666, 0.02912328, 0.00511592, 0.0004291,  0.00005,    0.000006]])

fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection='3d')

X, Y = np.meshgrid(xlist, ylist)
ax.plot_surface(X, Y, Z, alpha=0.5, rstride=1, cstride=1)
ax.scatter(xlist[3], ylist[3], Z[3,3], s=50, c='r')
plt.show()

By the way, the source code for the example shown in the plot_surface documentation uses meshgrid too. That would be another way to find this answer.

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