具有Colorbar的Matplotlib 3D散点图 [英] Matplotlib 3D Scatter Plot with Colorbar

问题描述

从Matplotlib文档页面上的示例借用，稍微修改代码，

Borrowing from the example on the Matplotlib documentation page and slightly modifying the code,

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

def randrange(n, vmin, vmax):
    return (vmax-vmin)*np.random.rand(n) + vmin

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
n = 100
for c, m, zl, zh in [('r', 'o', -50, -25), ('b', '^', -30, -5)]:
    xs = randrange(n, 23, 32)
    ys = randrange(n, 0, 100)
    zs = randrange(n, zl, zh)
    cs = randrange(n, 0, 100)
    ax.scatter(xs, ys, zs, c=cs, marker=m)
ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')

plt.show()

将给出每个点具有不同颜色的3D散点图（跑了在此示例中为dom颜色）。向图中添加颜色条的正确方法是什么，因为添加了 plt.colorbar（）或 ax.colorbar（）似乎不起作用。

Will give a 3D scatter plot with different colors for each point (random colors in this example). What's the correct way to add a colorbar to the figure, since adding in plt.colorbar() or ax.colorbar() doesn't seem to work.

推荐答案

这会产生一个颜色条（尽管可能不是您所需要的颜色条）：

This produces a colorbar (though possibly not the one you need):

替换此行：

ax.scatter(xs, ys, zs, c=cs, marker=m)

with

p = ax.scatter(xs, ys, zs, c=cs, marker=m)

然后使用

fig.colorbar(p)

接近尾声

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