带颜色条的 3D 散点图

发布于 2024-10-27 23:34:38 字数 860 浏览 2 评论 0原文

借用 Matplotlib 文档页面上的示例并稍微修改代码，

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()

将为每个点提供不同颜色的 3D 散点图（本例中为随机颜色）。向图中添加颜色条的正确方法是什么，因为添加 plt.colorbar() 或 ax.colorbar() 似乎不起作用。

原文

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()

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.

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べ繥欢鉨o。 2024-11-03 23:34:38

这会产生一个颜色条（尽管可能不是您需要的颜色条）：

替换这一行：

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

然后

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

使用

fig.colorbar(p)

在末尾附近

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

Replace this line:

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

with

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

then use

fig.colorbar(p)

near the end

回复收藏 0 原文

旧人 2024-11-03 23:34:38

使用上面的答案并没有解决我的问题。颜色条颜色图未链接到轴（另请注意不正确的颜色条限制）：

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

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

data = np.random.rand(3, 100)
x, y, z = data  # for show
c = np.arange(len(x)) / len(x)  # create some colours

p = ax.scatter(x, y, z, c=plt.cm.magma(0.5*c))
ax.set_xlabel('$\psi_1
 
解决方案（请参阅此处也）是在ax.scatter中使用cmap：
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

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

data = np.random.rand(3, 100)
x, y, z = data  # for show
c = np.arange(len(x)) / len(x)  # create some colours

p = ax.scatter(x, y, z, c=0.5*c, cmap=plt.cm.magma)
ax.set_xlabel('$\psi_1
 
)
ax.set_ylabel('$\Phi
 
解决方案（请参阅此处也）是在ax.scatter中使用cmap：

 
)
ax.set_zlabel('$\psi_2
 
解决方案（请参阅此处也）是在ax.scatter中使用cmap：

 
)

ax.set_box_aspect([np.ptp(i) for i in data])  # equal aspect ratio

fig.colorbar(p, ax=ax)

 
解决方案（请参阅此处也）是在ax.scatter中使用cmap：

 
)
ax.set_ylabel('$\Phi
 
)
ax.set_ylabel('$\Phi
 
解决方案（请参阅此处也）是在ax.scatter中使用cmap：

 
)
ax.set_zlabel('$\psi_2
 
解决方案（请参阅此处也）是在ax.scatter中使用cmap：

 
)

ax.set_box_aspect([np.ptp(i) for i in data])  # equal aspect ratio

fig.colorbar(p, ax=ax)

解决方案（请参阅此处也）是在ax.scatter中使用cmap：

) ax.set_zlabel('$\psi_2

) ax.set_ylabel('$\Phi

解决方案（请参阅此处也）是在ax.scatter中使用cmap：

) ax.set_zlabel('$\psi_2

解决方案（请参阅此处也）是在ax.scatter中使用cmap：

) ax.set_box_aspect([np.ptp(i) for i in data]) # equal aspect ratio fig.colorbar(p, ax=ax)

解决方案（请参阅此处也）是在ax.scatter中使用cmap：

) ax.set_box_aspect([np.ptp(i) for i in data]) # equal aspect ratio fig.colorbar(p, ax=ax)

) ax.set_ylabel('$\Phi

解决方案（请参阅此处也）是在ax.scatter中使用cmap：

) ax.set_zlabel('$\psi_2

解决方案（请参阅此处也）是在ax.scatter中使用cmap：

) ax.set_box_aspect([np.ptp(i) for i in data]) # equal aspect ratio fig.colorbar(p, ax=ax)

解决方案（请参阅此处也）是在ax.scatter中使用cmap：

Using the above answer did not solve my problem. The colorbar colormap was not linked to the axes (note also the incorrect colorbar limits):

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

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

data = np.random.rand(3, 100)
x, y, z = data  # for show
c = np.arange(len(x)) / len(x)  # create some colours

p = ax.scatter(x, y, z, c=plt.cm.magma(0.5*c))
ax.set_xlabel('$\psi_1

The solution (see here also) is to use cmap in ax.scatter:
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

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

data = np.random.rand(3, 100)
x, y, z = data  # for show
c = np.arange(len(x)) / len(x)  # create some colours

p = ax.scatter(x, y, z, c=0.5*c, cmap=plt.cm.magma)
ax.set_xlabel('$\psi_1

)
ax.set_ylabel('$\Phi

The solution (see here also) is to use cmap in ax.scatter:


)
ax.set_zlabel('$\psi_2

The solution (see here also) is to use cmap in ax.scatter:


)

ax.set_box_aspect([np.ptp(i) for i in data])  # equal aspect ratio

fig.colorbar(p, ax=ax)


The solution (see here also) is to use cmap in ax.scatter:


)
ax.set_ylabel('$\Phi

)
ax.set_ylabel('$\Phi

The solution (see here also) is to use cmap in ax.scatter:


)
ax.set_zlabel('$\psi_2

The solution (see here also) is to use cmap in ax.scatter:


)

ax.set_box_aspect([np.ptp(i) for i in data])  # equal aspect ratio

fig.colorbar(p, ax=ax)