title: How to add specific axes to matplotlib subplot?
body: <p>I am trying to make a matrix plot with matplotlib.</p>
  
  <p>The individual plots are made with a specific module <code>windrose</code> which subclasses <code>PolarAxes</code>. However there does not seem to be any projection defined in the module to be called as subplot kwargs. The standard <code>polar</code> projection does not work since some of the subclass arguments are missing.</p>
  
  <p>I have tested several approaches without success (even with seaborn map considering this post: <a href="https://stackoverflow.com/a/25702476/3416205">https://stackoverflow.com/a/25702476/3416205</a>). Hereunder is the closest I have tried. Is there any way to do what I want without properly creating a new matplotlib projection associated with the specific <code>WindroseAxes</code>?</p>
  
  <pre><code>import pandas as pd
  import matplotlib.pyplot as plt
  import matplotlib.gridspec as gridspec
  from windrose import WindroseAxes
  
  df = pd.read_csv('https://raw.githubusercontent.com/AntoineGautier/Data/master/tmp.csv')
  fig = plt.figure()
  gs = gridspec.GridSpec(4, 2)
  
  def wind_plot(x, y, title=None, axes=None, fig=None):
      ax = WindroseAxes.from_ax()
      ax.set_position(axes.get_position(fig))
      ax.bar(x, y, normed=True, opening=0.8, edgecolor='white', bins=[0, 2.5, 5, 7.5, 10])
      ax.set_title(title)
  
  for (id_s, s) in enumerate(pd.unique(df.saison)):
      for (id_jn, jn) in enumerate(pd.unique(df.jn)):
          tmp = df.query('saison==@s &amp; jn==@jn')
          _ = plt.subplot(gs[id_s, id_jn], polar=True)
          wind_plot(tmp.wd, tmp.ws, title=s + ' - ' + jn, axes=_, fig=fig)
  
  plt.show()
  </code></pre>