海洋线条图设置标记的透明度

Question

如何在seaborn.lineplot中分别设置标记和线条的透明度

我有一组点，我想画一条线条图连接所有这些点。我希望线条比标记更透明。如何做到这一点？

这是我的目标：

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下面是我的代码：

import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd

matplotlib.rcParams['legend.handlelength'] = 0
matplotlib.rcParams['legend.numpoints'] = 1

data = [{'method': 'end-to-end', 'k': 1, 'time': 181.0, 'auc': 69.76}, {'method': 'end-to-end', 'k': 2, 'time': 193.0, 'auc': 71.12}, {'method': 'end-to-end', 'k': 3, 'time': 256.0, 'auc': 71.84}, {'method': 'end-to-end', 'k': 4, 'time': 302.0, 'auc': 71.87}, {'method': 'end-to-end', 'k': 5, 'time': 365.0, 'auc': 71.89}, {'method': 'end-to-end', 'k': 8, 'time': 602.0, 'auc': 71.87}, {'method': 'end-to-end', 'k': 10, 'time': 743.0, 'auc': 71.84}, {'method': 'first', 'k': 1, 'time': 82.0, 'auc': 69.01}, {'method': 'first', 'k': 2, 'time': 105.0, 'auc': 69.45}, {'method': 'first', 'k': 3, 'time': 171.0, 'auc': 70.11}, {'method': 'first', 'k': 4, 'time': 224.0, 'auc': 70.36}, {'method': 'first', 'k': 5, 'time': 279.0, 'auc': 70.74}, {'method': 'first', 'k': 8, 'time': 517.0, 'auc': 70.81}, {'method': 'first', 'k': 10, 'time': 654.0, 'auc': 70.98}]

data = pd.DataFrame(data)
g = sns.lineplot(x='time', y='auc', data=data, markers=['o','v'], markersize=7, sort=False, hue='method', style="method", dashes=False, linestyle=None)
plt.legend(loc='lower right')

Answer 1

Seaborn似乎使颜色变得更浅。您可以循环遍历生成的点并更改它们的亮度。(点存储在ax.collections中。)亮度范围从0 (黑色)到1 (白色)。

由于现在点和线具有不同的颜色，并且线是在点的顶部绘制的，所以结果看起来有点奇怪。您可以更改这些行的zorder以将它们移到后面。

应再次创建图例(通过ax.legend)以显示新的标记颜色。

import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd

sns.set_style('darkgrid')
flights = sns.load_dataset('flights')
## markers = [".",",","o","v","^","<",">","1","2","3","4","8","s","p","P","*","h","H","+","x","X","D","d","|","_",0,1,2,3,4,5,6,7,8,9,10,11]
markers = ["o", "v", "^", "<", ">", "8", "s", "*", "h", "H", "P", "p"]
ax = sns.pointplot(data=flights, x='year', y='passengers', hue='month', markers=markers, palette='Set3')
for dots in ax.collections:
    color = dots.get_facecolor()
    dots.set_color(sns.set_hls_values(color, l=0.5))
    dots.set_alpha(1)
for line in ax.lines:
    line.set_zorder(0)
ax.legend(bbox_to_anchor=(1.01, 1.02), loc='upper left')
plt.tight_layout()
plt.show()

​

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#更新

上面的答案是在您添加代码之前编写的。对于代码中的示例，您可以调用lineplot两次。(请注意，“轴级函数”返回一个ax，而'figure level functions'返回一个类似于网格的数据结构，例如FacetGrid。因此，习惯上只使用g作为图形级函数的返回值名称，使用类似于ax的名称作为轴级函数的名称。这样的命名使我们更容易看到如何应用现有的示例代码。)

import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd

matplotlib.rcParams['legend.handlelength'] = 0
matplotlib.rcParams['legend.numpoints'] = 1

data = [{'method': 'end-to-end', 'k': 1, 'time': 181.0, 'auc': 69.76}, {'method': 'end-to-end', 'k': 2, 'time': 193.0, 'auc': 71.12}, {'method': 'end-to-end', 'k': 3, 'time': 256.0, 'auc': 71.84}, {'method': 'end-to-end', 'k': 4, 'time': 302.0, 'auc': 71.87}, {'method': 'end-to-end', 'k': 5, 'time': 365.0, 'auc': 71.89}, {'method': 'end-to-end', 'k': 8, 'time': 602.0, 'auc': 71.87}, {'method': 'end-to-end', 'k': 10, 'time': 743.0, 'auc': 71.84}, {'method': 'first', 'k': 1, 'time': 82.0, 'auc': 69.01}, {'method': 'first', 'k': 2, 'time': 105.0, 'auc': 69.45}, {'method': 'first', 'k': 3, 'time': 171.0, 'auc': 70.11}, {'method': 'first', 'k': 4, 'time': 224.0, 'auc': 70.36}, {'method': 'first', 'k': 5, 'time': 279.0, 'auc': 70.74}, {'method': 'first', 'k': 8, 'time': 517.0, 'auc': 70.81}, {'method': 'first', 'k': 10, 'time': 654.0, 'auc': 70.98}]

data = pd.DataFrame(data)
sns.set_style('ticks')

ax = sns.lineplot(x='time', y='auc', data=data, markers=['o','v'], markersize=7, sort=False, hue='method', style='method',  dashes=False, linestyle='', alpha=1)
sns.lineplot(x='time', y='auc', data=data, sort=False, hue='method',   dashes=False,  alpha=0.3, legend=False, ax=ax)
ax.legend(loc='lower right')
plt.show()

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