"""
==========================
Labeling a pie and a donut
==========================

Welcome to the matplotlib bakery. We will create a pie and a donut
chart through the :meth:`pie method <matplotlib.axes.Axes.pie>` and
show how to label them with a :meth:`legend <matplotlib.axes.Axes.legend>`
as well as with :meth:`annotations <matplotlib.axes.Axes.annotate>`.
"""

###############################################################################
# As usual we would start by defining the imports and create a figure with
# subplots.
# Now it's time for the pie. Starting with a pie recipe, we create the data
# and a list of labels from it.
#
# We can provide a function to the ``autopct`` argument, which will expand
# automatic percentage labeling by showing absolute values; we calculate
# the latter back from relative data and the known sum of all values.
#
# We then create the pie and store the returned objects for later.
# The first returned element of the returned tuple is a list of the wedges.
# Those are
# :class:`matplotlib.patches.Wedge <matplotlib.patches.Wedge>` patches, which
# can directly be used as the handles for a legend. We can use the
# legend's ``bbox_to_anchor`` argument to position the legend outside of
# the pie. Here we use the axes coordinates ``(1, 0, 0.5, 1)`` together
# with the location ``"center left"``; i.e.
# the left central point of the legend will be at the left central point of the
# bounding box, spanning from ``(1, 0)`` to ``(1.5, 1)`` in axes coordinates.

import numpy as np
import matplotlib.pyplot as plt

fig, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal"))

recipe = ["375 g flour",
          "75 g sugar",
          "250 g butter",
          "300 g berries"]

data = [float(x.split()[0]) for x in recipe]
ingredients = [x.split()[-1] for x in recipe]


def func(pct, allvals):
    absolute = int(pct/100.*np.sum(allvals))
    return "{:.1f}%\n({:d} g)".format(pct, absolute)


wedges, texts, autotexts = ax.pie(data, autopct=lambda pct: func(pct, data),
                                  textprops=dict(color="w"))

ax.legend(wedges, ingredients,
          title="Ingredients",
          loc="center left",
          bbox_to_anchor=(1, 0, 0.5, 1))

plt.setp(autotexts, size=8, weight="bold")

ax.set_title("Matplotlib bakery: A pie")

plt.show()


###############################################################################
# Now it's time for the donut. Starting with a donut recipe, we transcribe
# the data to numbers (converting 1 egg to 50 g), and directly plot the pie.
# The pie? Wait... it's going to be donut, is it not?
# Well, as we see here, the donut is a pie, having a certain ``width`` set to
# the wedges, which is different from its radius. It's as easy as it gets.
# This is done via the ``wedgeprops`` argument.
#
# We then want to label the wedges via
# :meth:`annotations <matplotlib.axes.Axes.annotate>`. We first create some
# dictionaries of common properties, which we can later pass as keyword
# argument. We then iterate over all wedges and for each
#
# * calculate the angle of the wedge's center,
# * from that obtain the coordinates of the point at that angle on the
#   circumference,
# * determine the horizontal alignment of the text, depending on which side
#   of the circle the point lies,
# * update the connection style with the obtained angle to have the annotation
#   arrow point outwards from the donut,
# * finally, create the annotation with all the previously
#   determined parameters.


fig, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal"))

recipe = ["225 g flour",
          "90 g sugar",
          "1 egg",
          "60 g butter",
          "100 ml milk",
          "1/2 package of yeast"]

data = [225, 90, 50, 60, 100, 5]

wedges, texts = ax.pie(data, wedgeprops=dict(width=0.5), startangle=-40)

bbox_props = dict(boxstyle="square,pad=0.3", fc="w", ec="k", lw=0.72)
kw = dict(arrowprops=dict(arrowstyle="-"),
          bbox=bbox_props, zorder=0, va="center")

for i, p in enumerate(wedges):
    ang = (p.theta2 - p.theta1)/2. + p.theta1
    y = np.sin(np.deg2rad(ang))
    x = np.cos(np.deg2rad(ang))
    horizontalalignment = {-1: "right", 1: "left"}[int(np.sign(x))]
    connectionstyle = "angle,angleA=0,angleB={}".format(ang)
    kw["arrowprops"].update({"connectionstyle": connectionstyle})
    ax.annotate(recipe[i], xy=(x, y), xytext=(1.35*np.sign(x), 1.4*y),
                horizontalalignment=horizontalalignment, **kw)

ax.set_title("Matplotlib bakery: A donut")

plt.show()

###############################################################################
# And here it is, the donut. Note however, that if we were to use this recipe,
# the ingredients would suffice for around 6 donuts - producing one huge
# donut is untested and might result in kitchen errors.


#############################################################################
#
# ------------
#
# References
# """"""""""
#
# The use of the following functions, methods, classes and modules is shown
# in this example:

import matplotlib
matplotlib.axes.Axes.pie
matplotlib.pyplot.pie
matplotlib.axes.Axes.legend
matplotlib.pyplot.legend
