Python 颜色渐变三维平滑曲线 3D plot Color Gradient

需求
给定若干三维坐标点，用平滑曲线将他们连接起来，并且颜色与第三维的绝对值相关
参考文档
https://cloud.tencent.com/developer/ask/132612

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from scipy.interpolate import interp1d
import numpy as np

# sample points
x = [3, 6, 3, 6, 3, 1]
y = [4, 7, 2, 1, 4, 3]
z = [4, 9, 7, 5, 9, 6]

# 首尾相连
for i in (x, y, z):
    i.append(i[0])

print(x)

'''

"""
A value in x_new is above the interpolation
=> the range of interp_i_x must within np.linspace(min(x), max(x), 7) 

"""

# interp_i_x = np.linspace(min(x), max(x), 100)
# interp_i_y = np.linspace(min(y), max(y), 100)
# interp_i_z = np.linspace(min(z), max(z), 100)
# xi = interp1d(np.linspace(min(x), max(x), 7), x, kind='quadratic')(interp_i_x)
# yi = interp1d(np.linspace(min(y), max(y), 7), y, kind='quadratic')(interp_i_y)
# zi = interp1d(np.linspace(min(z), max(z), 7), z, kind='quadratic')(interp_i_z)
'''


def interp_helper(values, num=50, kind='quadratic'):
    interp_i = np.linspace(min(values), max(values), num)
    return interp1d(np.linspace(min(values), max(values), len(values)), values, kind=kind)(interp_i)


x_new, y_new, z_new = (interp_helper(i, 100) for i in (x, y, z))


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

zmax = np.array(z_new).max()
zmin = np.array(z_new).min()

for i in range(len(z_new) - 1):
    ax.plot(x_new[i:i + 2], y_new[i:i + 2], z_new[i:i + 2],
            color=plt.cm.jet(int((np.array(z_new[i:i + 2]).mean() - zmin) * 255 / (zmax - zmin))))
plt.show()