根据颜色图设置线条颜色 [英] Set line colors according to colormap

问题描述

我有一系列的行存储在这样的列表中:

I have a series of lines stored in a list like so:

line_list = [line_1, line_2, line_3, ..., line_M]

其中每个line_i是一个由两个子子列表组成的子列表，一个用于x坐标，另一个用于y坐标:

where each line_i is a sub-list composed of two sub-sub-lists, one for the x coordinates and the other for the y coordinates:

line_i = [[x_1i, x2_i, .., x_Ni], [y_1i, y_2i, .., y_Ni]]

我还有一个列表，其长度与由浮点数组成的line_list相同，

I also have a list of the same length as line_list composed of floats,:

floats_list = [0.23, 4.5, 1.6, ..., float_M]

我想绘制每条线，给它一种颜色，该颜色取自颜色图，并与其索引在floats_list列表中的位置有关.因此，line_j的颜色将由数字floats_list[j]决定.我还需要在侧面显示一个彩条

I want to plot each line giving it a color taken from a color map and related to the position of its index in the floats_list list. So line_j will have its color determined by the number floats_list[j]. I also need a colorbar shown to the side

该代码想要这样的东西，除了它应该可以工作:)

The code would like something like this, except it should work :)

import matplotlib.pyplot as plt

line1 = [[0.5,3.6,4.5],[1.2,2.0,3.6]]
line2 = [[1.5,0.4,3.1,4.9],[5.1,0.2,7.4,0.3]]
line3 = [[1.5,3.6],[8.4,2.3]]

line_list = [line1,line2,line3]
floats_list = [1.2,0.3,5.6]

# Define colormap.
cm = plt.cm.get_cmap('RdYlBu')

# plot all lines.
for j,lin in enumerate(line_list): 
    plt.plot(lin[0], lin[1], c=floats_list[j])

# Show colorbar.
plt.colorbar()

plt.show()

推荐答案

为此最容易使用LineCollection.实际上，它希望这些行的格式与您已有的格式相似.要用第三个变量为线条着色，只需指定array=floats_list.例如:

It's easiest to use a LineCollection for this. In fact, it expects the lines to be in a similar format to what you already have. To color the lines by a third variable, just specify the array=floats_list. As an example:

import numpy
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection

# The line format you curently have:
lines = [[(0, 1, 2, 3, 4), (4, 5, 6, 7, 8)],
         [(0, 1, 2, 3, 4), (0, 1, 2, 3, 4)],
         [(0, 1, 2, 3, 4), (8, 7, 6, 5, 4)],
         [(4, 5, 6, 7, 8), (0, 1, 2, 3, 4)]]

# Reformat it to what `LineCollection` expects:
lines = [zip(x, y) for x, y in lines]

z = np.array([0.1, 9.4, 3.8, 2.0])

fig, ax = plt.subplots()
lines = LineCollection(lines, array=z, cmap=plt.cm.rainbow, linewidths=5)
ax.add_collection(lines)
fig.colorbar(lines)

# Manually adding artists doesn't rescale the plot, so we need to autoscale
ax.autoscale()

plt.show()

与重复调用plot相比，此方法有两个主要优点.

There are two main advantages of this over repeatedly calling plot.

1. 渲染速度. Collections的渲染速度比许多类似的艺术家快得多.
2. 根据颜色图通过另一个变量为数据着色更容易(和/或稍后更新颜色图).

1. Rendering speed. Collections render much faster than a large number of similar artists.
2. It's easier to color the data by another variable according to a colormap (and/or update the colormap later).

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