如何在matplotlib中的自定义图例中添加图案填充？

Question

编辑：FWIW我正在Illustrator中修复图例，但希望自动执行，因为我要绘制大约20个图

我遵循了this的非常有用的答案，即将自定义图例添加到不支持其自身图例的matplotlib小提琴图中。效果很好，除了我尝试添加图案填充时。

这是标签的代码（我尝试了两种不同的方式添加补丁）：

    labels = [ 'Low entropy bin', 'Medium entropy bin', 'High entropy bin' ]
    legend_patches = 3*[matplotlib.patches.Patch( color='#DCDCDC', hatch='//' )]
    for i in legend_patches:
       i.set_hatch( '//' )

孵化小提琴本身的代码很好用：

parts = plt.violinplot( data, showmeans=False, showextrema=True, showmedians=True )

hatch_dict = { 0:'', 1:'///', 2:'xx' }

for t in range(0, 3):
    third = range( 0, len( labels ) )[ t*(int(len(labels)/3)):(((t+1)*int(len(labels)/3))) ]
    for i in third:
        face = parts['bodies'][i]
        face.set_hatch( hatch_dict[t] )

垃圾箱所涉及的数据（未显示）已经用其他类别进行了颜色编码，因此我真的想在不同的阴影处显示垃圾箱。

Answer 1

您快到了-只需要注意带有补丁的color参数。有两个子组件： edge （edgecolor）和 face （facecolor）；使用该补丁艺术家设置，color=定义了这两种颜色。然后，阴影线和背景将显示为相同的颜色，您将看不到彼此。

底线：对补丁构造函数使用类似的内容：

p = matplotlib.patches.Patch(facecolor='#DCDCDC', hatch=hatch_dict[i])

此图的完整代码：

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches

# generate some data
n = 50
sigmas = np.array([0.1, 0.05, 0.15])
means  = np.array([0.2, 0.5, 0.75])
data = sigmas * np.random.randn(n, 3) + means

labels = [ 'Low entropy bin', 'Medium entropy bin', 'High entropy bin' ]

parts = plt.violinplot( data, showmeans=False, showextrema=True, showmedians=True)

# set up color and hatching on the violins
hatch_dict = { 0:'', 1:'///', 2:'xx' }
for i, face in enumerate(parts['bodies']):
    face.set_hatch(hatch_dict[i])
    face.set_facecolor('#DCDCDC')

# for completeness update all the lines (you already had this styling applied)
for elem in ['cbars', 'cmedians', 'cmaxes', 'cmins']:
    parts[elem].set_edgecolor('0.5')

# construct proxy artist patches
leg_artists = []
for i in xrange(len(hatch_dict)):
    p = matplotlib.patches.Patch(facecolor='#DCDCDC', hatch=hatch_dict[i])
    # can also explicitly declare 2nd color like this
    #p = matplotlib.patches.Patch(facecolor='#DCDCDC', hatch=hatch_dict[i], edgecolor='0.5')

    leg_artists.append(p)

# and add them to legend.
ax = plt.gca()
ax.legend(leg_artists, labels, loc='upper left')