Matplotlib 3d 图:跨 2 个表面获取单一颜色图

Matplotlib 3d plot: get single colormap across 2 surfaces

我正在用 matplotlib 制作一个有 2 个表面的 3d 图(见下面的例子)。到目前为止,两个表面都有自己的颜色图,底部为蓝色,顶部为黄色。

但是,我想要两个表面都有一个颜色图,即最底部是蓝色,最顶部是黄色,两个表面的接触点都是绿色。

我怎样才能做到这一点?我是否需要在绘图之前以某种方式组合两个表面,或者我是否需要限制两个表面的颜色图(下部从蓝色到绿色,上部从绿色到黄色)?

感谢您的帮助。

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

ky = np.linspace(-np.pi*2/3,np.pi*2/3,100)
kz = np.linspace(-np.pi*2/3,np.pi*2/3,100)

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

KY, KZ = np.meshgrid(ky, kz)
E = np.cos(KY)*np.cos(KZ)
ax.plot_surface(KY, KZ, E-1, rstride=1, cstride=1, cmap=cm.viridis)   #surface 1
ax.plot_surface(KY, KZ, -E+1, rstride=1, cstride=1, cmap=cm.viridis)  #surface 2
ax.view_init(elev=7, azim=-69)
plt.show()

您可以为颜色图显式设置 vminvmax 以强制颜色范围。

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

ky = np.linspace(-np.pi*2/3,np.pi*2/3,100)
kz = np.linspace(-np.pi*2/3,np.pi*2/3,100)

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

KY, KZ = np.meshgrid(ky, kz)
E = np.cos(KY)*np.cos(KZ)
ax.plot_surface(KY, KZ, E-1, rstride=1, cstride=1, cmap=cm.viridis, vmin=-2, vmax=2)   #surface 1
ax.plot_surface(KY, KZ, -E+1, rstride=1, cstride=1, cmap=cm.viridis, vmin=-2, vmax=2)  #surface 2
ax.view_init(elev=7, azim=-69)
plt.show()

要使范围与两个曲面中的实际 Z 值紧密相关,您可以使用

vmin=np.amin(E-1), vmax=np.amax(-E+1)

您也可以通过定义自己的颜色图来创建此效果,这些颜色图在顶部从黄色变为绿色,在底部从绿色变为蓝色。

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import axes3d
from matplotlib import cm
from matplotlib.colors import ListedColormap

ky = np.linspace(-np.pi*2/3,np.pi*2/3,100)
kz = np.linspace(-np.pi*2/3,np.pi*2/3,100)

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

KY, KZ = np.meshgrid(ky, kz)
E = np.cos(KY)*np.cos(KZ)

viridis = cm.get_cmap('viridis', 512)
topcolors = viridis(np.linspace(0.5, 1, 256))
topcm = ListedColormap(topcolors)
bottomcolors = viridis(np.linspace(0, 0.5, 256))
bottomcm = ListedColormap(bottomcolors)

ax.plot_surface(KY, KZ, E-1, rstride=1, cstride=1, cmap=bottomcm)   #surface 1
ax.plot_surface(KY, KZ, -E+1, rstride=1, cstride=1, cmap=topcm)  #surface 2
ax.view_init(elev=7, azim=-69)
plt.show()