有条件地移动饼图中单个数据标签的位置

Question

以下示例代码将生成我将用作示例的圆环图：

import matplotlib.pyplot as plt
%matplotlib inline

# Following should supposedly set the font correctly:
plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['font.sans-serif'] = ['Muli'] + plt.rcParams['font.sans-serif']
plt.rcParams['font.weight'] = 'extra bold'

size_of_groups=[12,11,30,0.3]

colors = ['#a1daaa','#bbbbb4','#444511','#1afff2']

import matplotlib as mpl
mpl.rcParams['text.color'] = '#273859'

# Create a pieplot
my_pie,texts,_ = plt.pie(size_of_groups,radius = 1.2,colors=colors,autopct="%.1f%%",
textprops = {'color':'w',                                                                                           
             'size':15  #, 'weight':"extra bold"
            }, pctdistance=0.75, labeldistance=0.7) #pctdistance and labeldistance change label positions.
labels=['High','Low','Normal','NA']
plt.legend(my_pie,labels,loc='lower center',ncol=2,bbox_to_anchor=(0.5, -0.2))
plt.setp(my_pie, width=0.6, edgecolor='white') 
fig1 = plt.gcf()
fig1.show()

上面的输出是这样的：

大多数情况下，这很棒。最后我得到了一个漂亮的圆环图！

但还有最后一件事需要巧妙处理 - 当圆环图的部分非常小时（例如 0.6%），我需要将标签移出图表，并可能改为黑色。

我设法使用 plt.text 对条形图执行类似的操作，但我认为这对于饼图根本不可行。我认为以前肯定有人解决过类似的问题，但我无法轻易找到任何像样的解决方案。

Answer 1

这是一种移动小于某个给定数量（代码示例中为 5 度）的补丁的所有百分比文本的方法。请注意，当多个小块彼此靠近时，这也会失败。

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

size_of_groups = [12, 11, 30, 0.3]
colors = ['#a1daaa', '#bbbbb4', '#444511', '#1afff2']
my_pie, texts, pct_txts = plt.pie(size_of_groups, radius=1.2, colors=colors, autopct="%.1f%%",
                                  textprops={'color': 'w', 'size': 15}, pctdistance=0.75,
                                  labeldistance=0.7)
labels = ['High', 'Low', 'Normal', 'NA']
plt.legend(my_pie, labels, loc='lower center', ncol=2, bbox_to_anchor=(0.5, -0.2))
plt.setp(my_pie, width=0.6, edgecolor='white')

for patch, txt in zip(my_pie, pct_txts):
    if (patch.theta2 - patch.theta1) <= 5:
        # the angle at which the text is normally located
        angle = (patch.theta2 + patch.theta1) / 2.
        # new distance to the pie center
        x = patch.r * 1.2 * np.cos(angle * np.pi / 180)
        y = patch.r * 1.2 * np.sin(angle * np.pi / 180)
        # move text to new position
        txt.set_position((x, y))
        txt.set_color('black')
plt.tight_layout()
plt.show()