根据颜色图设置线条颜色

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()

答

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.

渲染速度. Collections的渲染速度比许多类似的艺术家快得多.
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).

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

根据颜色图设置线条颜色

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