matplotlib：3d圖橫穿邊界（石墨烯色散）

Question

我有下面的代碼，試圖繪製一個函數+/- f，它定義了動量空間中的石墨烯色散。

# 3D Plot of graphene dispersion 

from matplotlib import pyplot as plt 
from mpl_toolkits.mplot3d import Axes3D 
from matplotlib import cm 
from matplotlib.ticker import LinearLocator, FormatStrFormatter 
import numpy as np 

def sqrt(x): 
    return np.sqrt(x) 

def cos(x): 
    return np.cos(x) 

# Constants 
a = 1.0 
d = a*np.sqrt(3) 
t = 2.7 
t2 = 0.5 

print "The display is not up to the mark! Modification needed.\n" 


fig = plt.figure() 
ax = fig.gca(projection='3d') 
x = np.arange(-2.0*np.pi, 2.0*np.pi, 0.1) 
y = np.arange(-2.0*np.pi, 2.0*np.pi, 0.1) 
x, y = np.meshgrid(x, y) 

f=t*sqrt(3.0+2.0*cos(a*x)+4.0*cos(a/2.0*x)*cos(d/2.0*y)) 

surf = ax.plot_surface(x, y, f, rstride=1, cstride=1, cmap=cm.jet, linewidth=0, antialiased=False) 


f=-f 
surf = ax.plot_surface(x, y, f, rstride=1, cstride=1, cmap=cm.jet, linewidth=0, antialiased=False) 
ax.set_zlim3d(-3.0, 3.0) 
fig.colorbar(surf, shrink=1.0, aspect=5) 

plt.show() 

，給了我一個情節是溢出z軸邊界：

然而，保持相同的功能定義和使用gnuplot的或數學我是能夠生產這種

and this

最後兩個中的任何一個可以通過使用python和matplotlib來重現嗎？

Answer 1

由於您明確地設置了數據範圍內的z限制（ax.set_zlim3d(-3.0, 3.0)），所以我不太清楚您想要什麼，但是通過註釋掉此行（並選取更好的顏色映射）：

# 3D Plot of graphene dispersion 

from matplotlib import pyplot as plt 
from mpl_toolkits.mplot3d import Axes3D 
from matplotlib import cm 
from matplotlib.ticker import LinearLocator, FormatStrFormatter 
import numpy as np 

sqrt = np.sqrt 
cos = np.cos 

# Constants 
a = 1.0 
d = a*np.sqrt(3) 
t = 2.7 
t2 = 0.5 

fig = plt.figure() 
ax = fig.gca(projection='3d') 
x = np.arange(-2.0*np.pi, 2.0*np.pi, 0.1) 
y = np.arange(-2.0*np.pi, 2.0*np.pi, 0.1) 
x, y = np.meshgrid(x, y) 

f=t*sqrt(3.0+2.0*cos(a*x)+4.0*cos(a/2.0*x)*cos(d/2.0*y)) 

surf = ax.plot_surface(x, y, f, rstride=1, cstride=1, cmap=plt.get_cmap('PuOr'), 
         linewidth=0, antialiased=False) 


f=-f 
surf = ax.plot_surface(x, y, f, rstride=1, cstride=1, cmap=plt.get_cmap('PuOr'), 
         linewidth=0, antialiased=False) 
#ax.set_zlim3d(-3.0, 3.0) 
fig.colorbar(surf, shrink=1.0, aspect=5) 

plt.show() 

（還要注意的是，你並不需要定義一個包裝函數創建一個別名np.sqrt等功能在Python第一類對象，你可以簡單地分配名稱：sqrt = np.sqrt。）