Python Matplotlib散点图：根据条件指定色点
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Python Matplotlib scatter plot: Specify color points depending on conditions
提问by Argumanez
I have two numpy arrays, x and y, with 7000 elements each. I want to make a scatter plot of them giving each point a different color depending on these conditions:
我有两个 numpy 数组 x 和 y，每个数组有 7000 个元素。我想制作它们的散点图，根据这些条件为每个点赋予不同的颜色：
-BLACK if x[i]<10.
-RED if x[i]>=10 and y[i]<=-0.5
-BLUE if x[i]>=10 and y[i]>-0.5
I tried creating a list of the same length as the data with the color I want to assign to each point and then plot the data with a loop, but it takes me a long time to run it. Here's my code:
我尝试创建一个与数据长度相同的列表，并使用我想要分配给每个点的颜色，然后用循环绘制数据，但运行它需要很长时间。这是我的代码：
import numpy as np
import matplotlib.pyplot as plt
#color list with same length as the data
col=[]
for i in range(0,len(x)):
if x[i]<10:
col.append('k')
elif x[i]>=10 and y[i]<=-0.5:
col.append('r')
else:
col.append('b')
#scatter plot
for i in range(len(x)):
plt.scatter(x[i],y[i],c=col[i],s=5, linewidth=0)
#add horizontal line and invert y-axis
plt.gca().invert_yaxis()
plt.axhline(y=-0.5,linewidth=2,c='k')
Before that, I tried creating the same color list in the same way, but plotting the data without the loop:
在此之前，我尝试以相同的方式创建相同的颜色列表，但在没有循环的情况下绘制数据：
#scatter plot
plt.scatter(x,y,c=col,s=5, linewidth=0)
Even though this plots the data much, much faster than using the for loop, some of the scattered points appear with a wrong color. Why not using a loop to plot the data leads to incorrect color of some points?
尽管这比使用 for 循环绘制数据快得多，但一些分散的点出现了错误的颜色。为什么不使用循环来绘制数据会导致某些点的颜色不正确？
I also tried defining three sets of data, one for each color, and adding them to the plot separately. But this is not what I am looking for.
我还尝试定义三组数据，每种颜色一组，并将它们分别添加到绘图中。但这不是我要找的。
Is there a way to specify in the scatter plots arguments the list of colors I want to use for each point in order not to use the for loop?
有没有办法在散点图参数中指定我想用于每个点的颜色列表，以便不使用 for 循环？
PS: This is the plot I get when I don't use the for loop (wrong one):
PS：这是我不使用 for 循环时得到的图（错误的）：
And this one when I use the for loop (correct):
当我使用 for 循环时（正确）：
回答by DavidG
This can be done using numpy.where. Since I do not your exact x and y values I will have to use some fake data:
这可以使用numpy.where. 由于我没有您确切的 x 和 y 值，因此我将不得不使用一些假数据：
import numpy as np
import matplotlib.pyplot as plt
#generate some fake data
x = np.random.random(10000)*10
y = np.random.random(10000)*10
col = np.where(x<1,'k',np.where(y<5,'b','r'))
plt.scatter(x, y, c=col, s=5, linewidth=0)
plt.show()
This produces the plot below:
这产生了下面的情节：
The line col = np.where(x<1,'k',np.where(y<5,'b','r'))is the important one. This produces a list, the same size as x and y. It fills this list with 'k','b'or 'r'depending on the condition that is written before it. So if x is less than 1, 'k'will be appended to list, else if y is less than 5 'b'will be appended and if neither of those conditions are met, 'r'will be appended to the list. This way, you do not have to use a loop to plot your graph.
线col = np.where(x<1,'k',np.where(y<5,'b','r'))是最重要的。这将生成一个列表，其大小与 x 和 y 相同。它使用'k','b'或'r'取决于写入它之前的条件填充此列表。因此，如果 x 小于 1，'k'将被附加到列表中，否则如果 y 小于 5，'b'则将被附加，如果这两个条件都不满足，'r'则将被附加到列表中。这样，您不必使用循环来绘制图形。
For your specific data you will have to change the values in the conditions of np.where.
对于您的特定数据，您必须更改 条件中的值np.where。
