"""
=================
Nested pie charts
=================

The following examples show two ways to build a nested pie chart
in Matplotlib. Such charts are often referred to as donut charts.

"""

import matplotlib.pyplot as plt
import numpy as np

###############################################################################
# The most straightforward way to build a pie chart is to use the
# `~matplotlib.axes.Axes.pie` method.
#
# In this case, pie takes values corresponding to counts in a group.
# We'll first generate some fake data, corresponding to three groups.
# In the inner circle, we'll treat each number as belonging to its
# own group. In the outer circle, we'll plot them as members of their
# original 3 groups.
#
# The effect of the donut shape is achieved by setting a ``width`` to
# the pie's wedges through the *wedgeprops* argument.


fig, ax = plt.subplots()

size = 0.3
vals = np.array([[60., 32.], [37., 40.], [29., 10.]])

cmap = plt.colormaps["tab20c"]
outer_colors = cmap(np.arange(3)*4)
inner_colors = cmap([1, 2, 5, 6, 9, 10])

ax.pie(vals.sum(axis=1), radius=1, colors=outer_colors,
       wedgeprops=dict(width=size, edgecolor='w'))

ax.pie(vals.flatten(), radius=1-size, colors=inner_colors,
       wedgeprops=dict(width=size, edgecolor='w'))

ax.set(aspect="equal", title='Pie plot with `ax.pie`')
plt.show()

###############################################################################
# However, you can accomplish the same output by using a bar plot on
# axes with a polar coordinate system. This may give more flexibility on
# the exact design of the plot.
#
# In this case, we need to map x-values of the bar chart onto radians of
# a circle. The cumulative sum of the values are used as the edges
# of the bars.

fig, ax = plt.subplots(subplot_kw=dict(projection="polar"))

size = 0.3
vals = np.array([[60., 32.], [37., 40.], [29., 10.]])
# Normalize vals to 2 pi
valsnorm = vals/np.sum(vals)*2*np.pi
# Obtain the ordinates of the bar edges
valsleft = np.cumsum(np.append(0, valsnorm.flatten()[:-1])).reshape(vals.shape)

cmap = plt.colormaps["tab20c"]
outer_colors = cmap(np.arange(3)*4)
inner_colors = cmap([1, 2, 5, 6, 9, 10])

ax.bar(x=valsleft[:, 0],
       width=valsnorm.sum(axis=1), bottom=1-size, height=size,
       color=outer_colors, edgecolor='w', linewidth=1, align="edge")

ax.bar(x=valsleft.flatten(),
       width=valsnorm.flatten(), bottom=1-2*size, height=size,
       color=inner_colors, edgecolor='w', linewidth=1, align="edge")

ax.set(title="Pie plot with `ax.bar` and polar coordinates")
ax.set_axis_off()
plt.show()

#############################################################################
#
# .. admonition:: References
#
#    The use of the following functions, methods, classes and modules is shown
#    in this example:
#
#    - `matplotlib.axes.Axes.pie` / `matplotlib.pyplot.pie`
#    - `matplotlib.axes.Axes.bar` / `matplotlib.pyplot.bar`
#    - `matplotlib.projections.polar`
#    - ``Axes.set`` (`matplotlib.artist.Artist.set`)
#    - `matplotlib.axes.Axes.set_axis_off`
