如何使用matplotlib

Question

我试图颜色的汽缸的每一个人脸上的颜色添加到汽缸的每一个人的脸，但我不知道如何去了解它，我曾尝试以下：

for i in range(10): 
    col.append([]) 


for i in range(10): 
    for j in range(20): 

     col[i].append(plt.cm.Blues(0.4)) 

ax.plot_surface(X, Y, Z,facecolors = col,edgecolor = "red") 

我想要为每个面分配自己的颜色，所以我想我会为2d数组中的每个面提供一组颜色。 但是，这给出了一个错误：

in plot_surface 
    colset.append(fcolors[rs][cs]) 
IndexError: list index out of range 

下面是完整的代码：

import numpy as np 
from matplotlib import cm 
from matplotlib import pyplot as plt 
from mpl_toolkits.mplot3d import Axes3D 
from scipy.linalg import norm 
from mpl_toolkits.mplot3d.art3d import Poly3DCollection 


fig = plt.figure() 
ax = fig.add_subplot(111, projection='3d') 
origin = np.array([0, 0, 0]) 

#axis and radius 
p0 = np.array([1, 3, 2]) 
p1 = np.array([8, 5, 9]) 
R = 5 

#vector in direction of axis 
v = p1 - p0 

#find magnitude of vector 
mag = norm(v) 

#unit vector in direction of axis 
v = v/mag 

#make some vector not in the same direction as v 
not_v = np.array([1, 0, 0]) 
if (v == not_v).all(): 
not_v = np.array([0, 1, 0]) 

#make vector perpendicular to v 
n1 = np.cross(v, not_v) 
#normalize n1 
n1 /= norm(n1) 

#make unit vector perpendicular to v and n1 
n2 = np.cross(v, n1) 

#surface ranges over t from 0 to length of axis and 0 to 2*pi 
t = np.linspace(0, mag, 200) 
theta = np.linspace(0, 2 * np.pi, 100) 

#use meshgrid to make 2d arrays 
t, theta = np.meshgrid(t, theta) 

#generate coordinates for surface 
X, Y, Z = [p0[i] + v[i] * t + R * np.sin(theta) * n1[i] + R * np.cos(theta) *  n2[i] for i in [0, 1, 2]] 
col = [] 
for i in range(10): 
    col.append([]) 
for i in range(10): 
    for j in range(20): 

     col[i].append(plt.cm.Blues(0.4)) 

ax.plot_surface(X, Y, Z,facecolors = col,edgecolor = "red") 

#plot axis 
ax.plot(*zip(p0, p1), color = 'red') 
ax.set_xlim(0, 10) 
ax.set_ylim(0, 10) 
ax.set_zlim(0, 10) 
plt.axis('off') 
ax.axes.get_xaxis().set_visible(False) 
ax.axes.get_yaxis().set_visible(False) 
plt.show() 

Answer 1

你Z数组大小100x200的，但你只指定10x20颜色。使col（用正确的尺寸），更快的方法可能是这样的：

col1 = plt.cm.Blues(np.linspace(0,1,200)) # linear gradient along the t-axis 
col1 = np.repeat(col1[np.newaxis,:, :], 100, axis=0) # expand over the theta-axis 

col2 = plt.cm.Blues(np.linspace(0,1,100)) # linear gradient along the theta-axis 
col2 = np.repeat(col2[:, np.newaxis, :], 200, axis=1) # expand over the t-axis 

ax=plt.subplot(121, projection='3d') 
ax.plot_surface(X, Y, Z, facecolors=col1) 

ax=plt.subplot(122, projection='3d') 
ax.plot_surface(X, Y, Z, facecolors=col2) 

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