Blender + Python:用少量有效数据绘制势能面示意图的方法

Blender is a free and open-source 3D computer graphics software toolset used for creating animated films, visual effects, art, 3D printed models, motion graphics, interactive 3D applications, virtual reality, and computer games. Blender's features include 3D modelling, UV unwrapping, texturing, raster graphics editing, rigging and skinning, fluid and smoke simulation, particle simulation, soft body simulation, sculpting, animating, match moving, rendering, motion graphics, video editing, and compositing.

import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import make_interp_spline
from sklearn.kernel_ridge import KernelRidge
from scipy import interpolate

with open("surface.xyz","r") as f:
    s = f.read()
    
xyz = s.splitlines()

x = []
y = []
z = []
for inf in range(len(xyz)):
    x.append(float(xyz[inf].split()[0]))
    y.append(float(xyz[inf].split()[1]))
    z.append(float(xyz[inf].split()[2]))
print(max(x),min(x),max(y),min(y),max(z),min(z))

dim = int(np.sqrt(len(xyz)))
X = np.asarray(x).reshape([dim, dim])
Y = np.asarray(y).reshape([dim, dim])
Z = np.asarray(z).reshape([dim, dim])

#fig = plt.figure()  
#ax = plt.axes(projection='3d')
#plt.axis('off')
#ax.plot_surface(X, Y, Z, rstride = 1, cstride = 1, cmap = plt.get_cmap('gnuplot'))
#plot.show()


x_0 = np.linspace(min(x),max(x),200)
y_0 = np.linspace(min(y),max(y),200)
X_0, Y_0 = np.meshgrid(x_0, y_0,indexing='ij')
f = interpolate.Rbf(X, Y, Z, function='multiquadric',smooth=0.3)
Z_1 = f(X_0, Y_0)
Z_1.shape


fig = plt.figure()  
ax = plt.axes(projection='3d')
plt.axis('off')

ax.plot_surface(X_0, Y_0, Z_1, rstride = 1, cstride = 1, color="#cccccc")
plt.show()