python matplotlib plot3d輪廓長度

Question

有沒有辦法用matplotlib獲得輪廓長度的散點圖？我有列（x_vals，y_vals，z_vals），我想獲得z_val = z_0的輪廓長度。

Answer 1

其主要思想是設置一個輪廓線所需的水平，從輪廓線中提取座標並獲得它的總長度。

import numpy as np 
from mpl_toolkits.mplot3d import Axes3D 
import matplotlib.pyplot as plt 
from scipy.interpolate import griddata 

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) 

# define grid 
xi = np.linspace(np.min(xs),np.max(xs),n) 
yi = np.linspace(np.min(ys),np.max(ys),n) 
zi = griddata((xs, ys), zs, (xi[None,:], yi[:,None]), method='cubic') 

# set desire levels and plot contour 
levels = [(np.min(zs)+np.max(zs))/2.] 
cs = plt.contour(xi,yi,zi,linewidths=1.25,colors='k', levels=levels) 

# get x,y of contour lines' segments and calc contour lines length 
print "x, y of contour lines ", levels 
length = 0 
x0,y0 = cs.allsegs[0][0][0] 
startx = x0 
starty = y0 
print x0, y0 
for coords in cs.allsegs[0][0][1:]: 
    x1,y1 = coords[0], coords[1] 
    length += np.sqrt((x1-x0)**2 + (y1-y0)**2) 
    x0,y0 = x1,y1 
    print x0,y0 

length += np.sqrt((startx-x0)**2 + (starty-y0)**2) 
print "length: ", length 

plt.show() 

輸出示例：

x, y of contour lines [-17.507777689387403] 
23.4999959668 10.5371953741 
23.5817457231 10.497649817 
23.6719663171 10.4697921243 
23.762186911 10.4360099894 
23.852407505 10.3946824087 
23.9426280989 10.3407058644 
24.0328486928 10.2723811242 
24.1230692868 10.1944775666 
24.2132898807 10.1068535535 
24.3035104746 10.0100558541 
24.3937310686 9.90574448784 
24.4839516625 9.79553098263 
24.5741722565 9.67298314465 
24.5768503134 9.66917600432 
24.6643928504 9.60388531053 
24.7546134443 9.52506691946 
24.8448340383 9.43215297781 
24.9350546322 9.32232950793 
25.0252752261 9.19236277318 
25.1154958201 9.03870318233 
25.205716414 8.85776647714 
25.2704564726 8.71121323379 
25.295937008 8.68421625849 
25.3861576019 8.58769144841 
25.4763781958 8.48390641242 
25.5665987898 8.36983000445 
25.6568193837 8.23868454477 
25.7470399776 8.08554200856 
25.8372605716 7.90529576185 
25.9035308097 7.75325046325 
25.9274811655 7.71825086423 
26.0177017595 7.5871801381 
26.1079223534 7.45184378689 
26.1981429473 7.3106545718 
26.2883635413 7.16154945578 
26.3785841352 7.0017709519 
26.4688047291 6.82751937848 
26.4848907014 6.79528769271 
26.5590253231 6.59847581588 
26.649245917 6.34538263269 
26.739466511 6.07013541536 
26.8082579554 5.83732492217 
26.7438422237 4.87936215163 
26.739466511 4.86265749258 
26.649245917 4.53024953676 
26.5590253231 4.20849894529 
26.4792050487 3.92139938109 
26.4688047291 3.8934269156 
26.3785841352 3.6842175811 
26.2883635413 3.52455851848 
26.1981429473 3.39886137161 
26.1079223534 3.2971242973 
26.0177017595 3.21266028078 
25.9274811655 3.14082302724 
25.8372605716 3.07008168517 
25.7470399776 2.98668089345 
25.725548407 2.96343661055 
25.6568193837 2.75631666794 
25.5665987898 2.54190386724 
25.4763781958 2.38569318308 
25.3861576019 2.27114415544 
25.295937008 2.18527424797 
25.205716414 2.11775204404 
25.1154958201 2.06220926565 
25.0252752261 2.01460543416 
25.0068077972 2.00547384001 
length: 19.003201041