title: matplotlib bar3d clipping problems
body: <p>I am trying to create a 3D bar graph with Matplotlib 1.2.0 and Python 2.7.3. I followed the advice in <a href="http://www.mail-archive.com/matplotlib-users@lists.sourceforge.net/msg19740.html" rel="noreferrer">http://www.mail-archive.com/matplotlib-users@lists.sourceforge.net/msg19740.html</a> and plotted the bar one by one, but I am still getting rendering problems (i.e., bars on top of each other). </p>
  
  <p>Moreover, I get the following when I invoke my code:</p>
  
  <p>/usr/apps/python/lib/python2.7/site-packages/mpl_toolkits/mplot3d/axes3d.py:1476: RuntimeWarning: divide by zero encountered in divide for n in normals])</p>
  
  <p>/usr/apps/python/lib/python2.7/site-packages/mpl_toolkits/mplot3d/axes3d.py:1476: RuntimeWarning: invalid value encountered in divide for n in normals])</p>
  
  <p>My questions:</p>
  
  <ol>
  <li>Are these serious warnings? Do I need to look into them and try to
  eliminate them? How do I eliminate them?</li>
  <li>What is the difference between zsort='max' and zsort='average'?</li>
  <li>What else can I do to eliminate rendering problems?</li>
  </ol>
  
  <p>Thanks in advance!</p>
  
  <p>Here is my code:</p>
  
  <pre><code>import numpy as np
  import matplotlib.pyplot as plt
  from mpl_toolkits.mplot3d import Axes3D
  import matplotlib.colors as colors
  import matplotlib.cm as cmx
  
  # my data
  dat = [2.31778665482167e-310, 0.006232785101850947, 0.0285075971030949, 0.0010248181570355695, 0.0048776795767614825, 0.02877090365176044, 0.002459331469834533, 0.0008594610645495889, 0.002919824084878003, 0.000968081117692596, 0.0, 0.0, 0.0319623949119874, 0.00568752311279771, 0.009994801469036968, 0.03248018520506219, 0.006686905726805326, 0.005987863156039365, 0.0072955095915350045, 0.005568911905473998, 0.0, 0.0, 0.0, 0.028483143996551524, 0.031030793902192794, 0.06125216053962635, 0.02935971973938871, 0.028507530280092265, 0.030112963748812088, 0.028293406731749605, 0.0, 0.0, 0.0, 0.0, 0.004510645022825792, 0.028998119822468988, 0.0013993630391143715, 0.0010726572949244424, 0.002288215944285159, 0.0006513973584945584, 0.0, 1.1625e-320, 1.15348834e-316, 2.3177866547513e-310, 0.0, 0.03148966953869102, 0.005215047563268979, 0.004491716298086729, 0.006010166308872446, 0.005186976949223524, 0.0, 0.0, 0.0, 0.0, 0.0, 1.107e-320, 0.02983657915729719, 0.028893006725328373, 0.030526067389954753, 0.028629390713739978, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0015217840289869456, 0.002751587509779179, 0.001413669523724954, 1.15348834e-316, 2.3177866547513e-310, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0024680339073824705, 0.0008254364860386303, 0.0, 0.0, 0.0, 9.965e-321, 1.15348834e-316, 2.3177866547513e-310, 0.0, 0.0, 0.0, 0.002621588539481613, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 9.41e-321, 1.15348834e-316, 2.3177866547513e-310]
  dat = np.reshape(dat,[10,10],order='F')
  
  lx = len(dat[0])
  ly = len(dat[:,0])
  n = lx*ly
  
  # generate colors
  cm = plt.get_cmap('jet')
  vv = range(len(dat))
  cNorm = colors.Normalize(vmin=0, vmax=vv[-1])
  scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=cm)
  colorVals = [scalarMap.to_rgba(i) for i in range(ly)]
  
  # generate plot data
  xpos = np.arange(0,lx,1)  
  ypos = np.arange(0,ly,1)
  xpos, ypos = np.meshgrid(xpos+0.25, ypos+0.25)
  xpos = xpos.flatten()
  ypos = ypos.flatten()
  zpos = np.zeros(n)
  dx = 0.5*np.ones_like(zpos)
  dy = dx.copy()
  dz = dat.flatten()
  cc = np.tile(range(lx), (ly,1))
  cc = cc.T.flatten()
  
  # generate plot
  fig = plt.figure()
  ax = fig.add_subplot(111, projection='3d')
  opacity = 1
  
  for i in range(n):
      ax.bar3d(xpos[i], ypos[i], zpos[i], dx[i], dy[i], dz[i],
               color=colorVals[cc[i]], alpha=opacity, zsort='max')
  
  plt.autoscale(enable=True, axis='both', tight=True)
  plt.grid()
  plt.show(block=False)
  </code></pre>