content: """
  Illustrate different ways of using the various fill functions.
  """
  import numpy as np
  import matplotlib.pyplot as plt
  
  import example_utils
  
  def main():
      fig, axes = example_utils.setup_axes()
  
      fill_example(axes[0])
      fill_between_example(axes[1])
      stackplot_example(axes[2])
  
      example_utils.title(fig, 'fill/fill_between/stackplot: Filled polygons',
                          y=0.95)
      fig.savefig('fill_example.png', facecolor='none')
      plt.show()
  
  def fill_example(ax):
      # Use fill when you want a simple filled polygon between vertices
      x, y = fill_data()
      ax.fill(x, y, color='lightblue')
      ax.margins(0.1)
      example_utils.label(ax, 'fill')
  
  def fill_between_example(ax):
      # Fill between fills between two curves or a curve and a constant value
      # It can be used in several ways. We'll illustrate a few below.
      x, y1, y2 = sin_data()
  
      # The most basic (and common) use of fill_between
      err = np.random.rand(x.size)**2 + 0.1
      y = 0.7 * x + 2
      ax.fill_between(x, y + err, y - err, color='orange')
  
      # Filling between two curves with different colors when they cross in
      # different directions
      ax.fill_between(x, y1, y2, where=y1>y2, color='lightblue')
      ax.fill_between(x, y1, y2, where=y1<y2, color='forestgreen')
  
      # Note that this is fillbetween*x*!
      ax.fill_betweenx(x, -y1, where=y1>0, color='red', alpha=0.5)
      ax.fill_betweenx(x, -y1, where=y1<0, color='blue', alpha=0.5)
  
      ax.margins(0.15)
      example_utils.label(ax, 'fill_between/x')
  
  def stackplot_example(ax):
      # Stackplot is equivalent to a series of ax.fill_between calls
      x, y = stackplot_data()
      ax.stackplot(x, y.cumsum(axis=0), alpha=0.5)
      example_utils.label(ax, 'stackplot')
  
  #-- Data generation ----------------------
  
  def stackplot_data():
      x = np.linspace(0, 10, 100)
      y = np.random.normal(0, 1, (5, 100))
      y = y.cumsum(axis=1)
      y -= y.min(axis=0, keepdims=True)
      return x, y
  
  def sin_data():
      x = np.linspace(0, 10, 100)
      y = np.sin(x)
      y2 = np.cos(x)
      return x, y, y2
  
  def fill_data():
      t = np.linspace(0, 2*np.pi, 100)
      r = np.random.normal(0, 1, 100).cumsum()
      r -= r.min()
      return r * np.cos(t), r * np.sin(t)
  
  main()
  