Dfyjkt

I am trying to make the following pie chart prettier:

In particular, I have an obvious problem with the labels. I want to rotate them and center them above their corresponding pie slice, but I am only able to rotate them. Moreover, the rotation requires a lot of tweaking by setting
pie_properties[1][0].set_rotation(30) with a different degrees values for every label.

Is there a way to make it automatically, or at least in a simpler way?

Here is my code:

import matplotlib.pyplot as plt
import numpy as np


fig, ax = plt.subplots()

### Data structure: 
# Network type:
group_names = ['Group 1', 'Group 2', 'Group 3']
group_vals = [43,49,38]
group_colors = ['w']*3

#Information level:
info_names = ['Subgroup 1', 'Subgroup 2', 
 'Subgroup 1', 'Subgroup 2',
 'SSubgroup 1', 'Subgroup 2']
info_vals = np.array([[27,16],[26,23],[14,24]])
my_blue = [x/255 for x in [30,144,255]]
info_colors = [my_blue,'gray',
 my_blue,'gray',
 my_blue,'gray']

corr_vals = np.array([[10,3,7,3,4], [4,4,4,2,2],
 [10,5,5,3,3], [10,5,5,1,2],
 [4,4,2,2,2], [12,2,2,1,7]])
pale_green = [x/255 for x in [152,251,152]]
pale_red = [x/255 for x in [240,128,128]]
pale_gray = [x/255 for x in [169,169,169]]
corr_colors = ['green',pale_green,pale_gray,pale_red,'red', 'green',pale_green,pale_gray,pale_red,'red',
 'green',pale_green,pale_gray,pale_red,'red', 'green',pale_green,pale_gray,pale_red,'red',
 'green',pale_green,pale_gray,pale_red,'red', 'green',pale_green,pale_gray,pale_red,'red',]

#inner layer
pie_properties = ax.pie(group_vals, radius=1, colors=group_colors, 
 labels=group_names, labeldistance=0.7,
 wedgeprops=dict(width=0.3, edgecolor='k'))
pie_properties[1][0].set_rotation(-45) #<===rotation
pie_properties[1][1].set_rotation(90)
pie_properties[1][2].set_rotation(-135)

#middle layer
pie_properties = ax.pie(info_vals.flatten(), radius=1+0.4, colors=info_colors,
 labels=info_names, labeldistance=0.7,
 wedgeprops=dict(width=0.4, edgecolor='w'))
pie_properties[1][0].set_rotation(-45)
pie_properties[1][1].set_rotation(15)
pie_properties[1][2].set_rotation(65)
pie_properties[1][3].set_rotation(125)
pie_properties[1][4].set_rotation(-160)
pie_properties[1][5].set_rotation(-125)

#outer layer
ax.pie(corr_vals.flatten(), radius=1+0.4+0.5, colors=corr_colors,
 wedgeprops=dict(width=0.5, edgecolor='w'))


ax.set(aspect="equal")
plt.show()

I suppose you can calculate the angle needed with a little bit of triginometry. Since the label is placed at the mean angular extent of the pie wedge, calculating the angle is easy. Depending on whether the text is in the lower or upper half, you may add or subtract 90 degrees.

import matplotlib.pyplot as plt
import numpy as np

fig, ax = plt.subplots()

group_names = ['Group 1', 'Group 2', 'Group 3']
group_vals = [43,49,38]
group_colors = ['w']*3

info_names = ['Subgroup 1', 'Subgroup 2', 
 'Subgroup 1', 'Subgroup 2',
 'Subgroup 1', 'Subgroup 2']
info_vals = np.array([[27,16],[26,23],[14,24]])
my_blue = np.array([30,144,255])/255
info_colors = [my_blue,'gray']*3

corr_vals = np.array([[10,3,7,3,4], [4,4,4,2,2],
 [10,5,5,3,3], [10,5,5,1,2],
 [4,4,2,2,2], [12,2,2,1,7]])
pale_green = np.array([152,251,152])/255
pale_red = np.array([240,128,128])/255
pale_gray = np.array([169,169,169])/255
corr_colors = ['green',pale_green,pale_gray,pale_red,'red']*6

def rotatetext(text):
 angle = np.rad2deg(np.arctan2(*text.get_position()[::-1]))
 text.set(rotation = angle - 90*np.sign(angle), 
 rotation_mode="anchor", ha="center", va="center")

#inner layer
pie_properties = ax.pie(group_vals, radius=1/1.9, colors=group_colors, 
 labels=group_names, labeldistance=.8,
 wedgeprops=dict(width=0.3/1.9, edgecolor='k'))

for text in pie_properties[1]:
 rotatetext(text)

#middle layer
pie_properties = ax.pie(info_vals.flatten(), radius=(1+0.4)/1.9, colors=info_colors,
 labels=info_names, labeldistance=.82,
 wedgeprops=dict(width=0.4/1.9, edgecolor='w'))

for text in pie_properties[1]:
 rotatetext(text)

#outer layer
ax.pie(corr_vals.flatten(), radius=(1+0.4+0.5)/1.9, colors=corr_colors,
 wedgeprops=dict(width=0.5/1.9, edgecolor='w'))

ax.set(xlim=(-1,1), ylim=(-1,1))
ax.set(aspect="equal")
plt.show()

The best radial position however needs manual tweaking. Here I chose 0.80 and 0.82 respectively, but that'll sure depend on the figure- and font-size.