设置与pyplot.scatter中的颜色匹配的图例 [英] setting a legend matching the colours in pyplot.scatter

问题描述

假设我的数据按以下方式组织:

Suppose my data is organized in the following way:

x_values = [6.2, 3.6, 7.3, 3.2, 2.7]
y_values = [1.5, 3.2, 5.4, 3.1, 2.8]
colours = [1, 1, 0, 1, -1]
labels = ["a", "a", "b", "a", "c"]

我想用这个做一个散点图:

I want to make a scatterplot with this:

axis = plt.gca()
axis.scatter(x_values, y_values, c=colours)

我想要一个具有3个类别的图例:"a"，"b"和"c".

I want a legend with 3 categories: "a", "b" and "c".

鉴于此列表中的类别与 colours 列表中的点的顺序相匹配，我可以使用 labels 列表来制作此图例吗?

Can I use the labels list to make this legend, given that the categories in this list match the order of the points in the colours list?

我是否需要为每个类别分别运行 scatter 命令?

Do I need to run the scatter command separately for each category?

推荐答案

如果要使用色图，则可以为 colors 列表中的每个唯一条目创建一个图例条目，如下所示.这种方法适用于任何数量的值.图例句柄是 plot 的标记，以便它们与散点匹配.

If you want to use a colormap you can create a legend entry for each unique entry in the colors list as shown below. This approach works well for any number of values. The legend handles are the markers of a plot, such that they match with the scatter points.

import matplotlib.pyplot as plt

x_values = [6.2, 3.6, 7.3, 3.2, 2.7]
y_values = [1.5, 3.2, 5.4, 3.1, 2.8]
colors = [1, 1, 0, 1, -1]
labels = ["a", "a", "b", "a", "c"]
clset = set(zip(colors, labels))

ax = plt.gca()
sc = ax.scatter(x_values, y_values, c=colors, cmap="brg")

handles = [plt.plot([],color=sc.get_cmap()(sc.norm(c)),ls="", marker="o")[0] for c,l in clset ]
labels = [l for c,l in clset]
ax.legend(handles, labels)

plt.show()

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