具有颜色渐变的3d散点图，其中颜色取决于计数 [英] 3d scatter plot with color gradient where color depends on count

问题描述

我有一个数据帧，其中的点包括该点的x，y和z坐标以及计数，每个数据点的数字在1到187之间。
我想将 count与颜色渐变相关联，其中1例如是绿色，而187是红色，然后绘制具有x，y和z坐标的数据点的散点图，其中每个颜色数据点是计数的编码信息。
我发现颜色渐变代码非常令人困惑，您能帮我吗？

I have dataframe with points which include x, y and z coordinate of the point and "count", which is number between 1 and 187 for each data point. I would like to associate "count" with color gradient, with 1 being for instance color green, and 187 color red, and then to make scatter plot of data points with x, y and z coordinate, where color of every data point is coded information for the "count". I find code for color gradients very confusing, can you please help me?

编辑：zelusp完全回答了我的问题，谢谢。

zelusp completely answered my question, thank you.

编辑1：我想知道是否应该编写单独的问题，但是由于它是关于同一段代码的，也许我只需编辑上一个问题就可以回答。
最近我更换了笔记本电脑，并在新计算机上安装了Ubuntu 18.04。这段代码可在Ubuntu 16.04上完美运行，但不适用于我的新计算机。
我的代码是：

I wondered if I should write separate question, but as it's about the same piece of code maybe I could reach for answer just editing previous question. Recently I changed my laptop, and installed Ubuntu 18.04 on my new machine. This piece of code worked perfectly on Ubuntu 16.04, but doesn't work on my new machine. My code is:

cmap = plt.cm.rainbow
norm = mpl.colors.Normalize(vmin=np.min(df3.h_count), vmax=np.max(df3.h_count))

fig=plt.figure()
ax1=fig.add_subplot(111, projection='3d')
ax1.scatter(df3.zm_bin, df3.sfr_bin, 12.+np.log10(df3.medijana), s=10, c=cmap(norm(df3.h_count)), marker='o') 
ax1.set_xlim(8,12.5)
ax1.set_xlabel('Log(Mz)')
ax1.set_ylabel('LogSFR') #treba invertovati
ax1.set_zlabel('12+log(Z)')
ax1.invert_yaxis()

sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm)
sm.set_array([])
fig.colorbar(sm)

错误我得到的是这样的：

The error I'm getting is this:

Traceback (most recent call last):
  File "load_subhalos.py", line 233, in <module>
    ax1.scatter(df3.zm_bin, df3.sfr_bin, 12.+np.log10(df3.medijana), s=10, c=cmap(norm(df3.h_count)), marker='o') 
  File "/usr/local/lib/python2.7/dist-packages/matplotlib/colors.py", line 938, in __call__
    result, is_scalar = self.process_value(value)
  File "/usr/local/lib/python2.7/dist-packages/matplotlib/colors.py", line 924, in process_value
    result = np.ma.array(data, mask=mask, dtype=dtype, copy=True)
  File "/usr/local/lib/python2.7/dist-packages/numpy/ma/core.py", line 6358, in array
    ndmin=ndmin, shrink=shrink, order=order)
  File "/usr/local/lib/python2.7/dist-packages/numpy/ma/core.py", line 2784, in __new__
    order=order, subok=True, ndmin=ndmin)
TypeError: float() argument must be a string or a number

我没有更改代码中的任何内容，唯一的变化是新机器和操作系统。您知道我为什么会遇到这个问题吗？

I didn't change anything in the code, the only change is new machine and OS. Do you know why I'm having this problem?

推荐答案

我建议您浏览一下matplotlib上的以下文章：

I recommend you take a tour through these posts on matplotlib:

• 具有颜色渐变的Matplotlib 3D散点图，它几乎是您的问题的副本


• 如何选择良好的色彩图我建议您尝试使用 YlOrRd 色彩图，因为它会是容易阅读


• 如何在matplotlib中将数字转换为色标？
  特别注意 cmap 和 norm 变量的使用以及它们如何使用在 cmap（norm（df.c.values））中使用。

• Matplotlib 3D scatter plot with color gradient which is a near duplicate of your question
• How to choose a good colormap I would advise you try to use the YlOrRd color map since it it will be a little easier to read
• How can I convert numbers to a color scale in matplotlib? pay special attention to the use of the cmap, and norm variables and how they are used in cmap(norm(df.c.values)).

请牢记以下几点：

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

#%% Generate mock data
number_of_datapoints = 30
x = np.random.rand(number_of_datapoints)
y = np.random.rand(number_of_datapoints)
z = np.random.rand(number_of_datapoints)

count_min = 1
count_max = 187
data = np.random.randint(count_min, count_max, number_of_datapoints) # these are your counts

#%% Create Color Map
colormap = plt.get_cmap("YlOrRd")
norm = matplotlib.colors.Normalize(vmin=min(data), vmax=max(data))

#%% 3D Plot
fig = plt.figure()
ax3D = fig.add_subplot(111, projection='3d')
ax3D.scatter(x, y, z, s=10, c=colormap(norm(data)), marker='o')  
plt.show()

您可能还对 colorspacious

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