title: How can I get the matplotlib rgb color, given the colormap name, BoundryNorm, and 'c='?
body: <p>How can I get the matplotlib rgb value for a number, NUM, given:</p>
  
  <ol>
  <li>A colormap ('autumn_r' which is yellow-to-red in the example below)</li>
  <li>BoundryNorm values("2 to 10" in the example below)</li>
  <li>The number NUM</li>
  </ol>
  
  <p>In my example, I would like:</p>
  
  <ol>
  <li>Given any value 2 or less, returns the rgb value for yellow.  </li>
  <li>Given any value 10 or more, returns the rgb value for red.  </li>
  <li>Given values in the range 3 &lt;= NUM &lt;= 9, a color between yellow and red will be chosen from the specified colormap</li>
  </ol>
  
  <p>The code below shows the use of the colormap and defining my boundry values.  Now I just need a function which will return my rgb value instead of doing a scatter plot.  The scatter plot is for visualization only so I could see that the Normalization was working as I had wished. </p>
  
  <pre><code>import matplotlib.pyplot as plt
  import matplotlib as mpl
  from matplotlib import cm
  import numpy as np
  import copy
  
  # setup the plot
  fig, ax = plt.subplots(1,1, figsize=(6,6))
  
  # define the data
  NUM_VALS = 20
  NORM_ENDS = (2,10)
  x = np.random.uniform(0, NUM_VALS, size=NUM_VALS)
  y = np.random.uniform(0, NUM_VALS, size=NUM_VALS)
  tag = copy.deepcopy(y)
  
  # define the colormap
  cmap = plt.get_cmap('autumn_r')
  cmaplist = [cmap(i) for i in range(cmap.N)]
  
  # create the new map
  cmap = cmap.from_list('Custom cmap', cmaplist[0:], cmap.N)
  
  # define the bins and normalize
  bounds = np.linspace(NORM_ENDS[0], NORM_ENDS[1], NORM_ENDS[1]-NORM_ENDS[0]+1)
  norm = mpl.colors.BoundaryNorm(bounds, cmap.N)
  
  # make the scatter
  scat = ax.scatter(x,y,s=300, c=tag,cmap=cmap,norm=norm)
  
  # create a second axes for the colorbar
  ax2 = fig.add_axes([0.90, 0.1, 0.03, 0.8])
  cb = mpl.colorbar.ColorbarBase(ax2, cmap=cmap, norm=norm, spacing='proportional', ticks=bounds, boundaries=bounds, format='%1i')
  
  ax.set_title('Well defined discrete colors')
  ax2.set_ylabel('Very custom cbar [-]', size=12)
  
  plt.show()
  </code></pre>