title: How to smooth by interpolation when using pcolormesh?
body: <p>I have a basemap of the world, and it's filled with data (lintrends_mean) using pcolormesh. Because the data has relatively large grid boxes, I'd like to smooth the plot. However, I can't figure out how to do this. Setting shading='gouraud' in the plotting function blurs the edges of the grid boxes, but I'd like something nicer-looking than that since the data still appears blotchy.</p>
  
  <p>There was a similar question asked here with an answer given, but I don't understand the answer, particularly where the "newdepth" comes from. I can't comment on it for clarification either since I'm short on reputation.
  <a href="https://stackoverflow.com/questions/12081932/interpolation-with-matplotlib-pcolor">interpolation with matplotlib pcolor</a></p>
  
  <pre><code>#Set cmap properties
  bounds = np.array([0.1,0.2,0.5,1,2,3,4,6,9,13,20,35,50])
  norm = colors.LogNorm(vmin=0.01,vmax=55) #creates logarithmic scale
  #cmap.set_under('#000099') # I want to use this- edit in Paint
  cmap.set_over('#660000')  # everything above range of colormap
  
  fig = plt.figure(figsize=(15.,10.))                     #create figure &amp; size
  m = Basemap(projection='cyl',llcrnrlat=-90,urcrnrlat=90,llcrnrlon=0,urcrnrlon=360.,lon_0=180.,resolution='c') #create basemap &amp; specify data area &amp; res
  m.drawcoastlines(linewidth=1)
  m.drawcountries(linewidth=1)
  m.drawparallels(np.arange(-90,90,30.),linewidth=0.3)
  m.drawmeridians(np.arange(-180.,180.,90.),linewidth=0.3)            
  meshlon,meshlat = np.meshgrid(lon,lat)                           #meshgrid turns lats &amp; lons into 2D arrays
  x,y = m(meshlon,meshlat)                                         #assign 2D arrays to new variables
  trend = m.pcolormesh(x,y,lintrends_mean,cmap=plt.get_cmap('jet'),norm=norm) #plot the data &amp; specify colormap &amp; color range
  cbar=m.colorbar(trend,size="3%", label='Linear Trend (mm/day/decade)',ticks=bounds,extend="max")
  cbar.set_ticklabels(bounds)
  plt.title('Linear Trends of PR (CanESM2 1979-2014)',fontsize=16)
  plt.xlabel('Longitude',fontsize=10)
  plt.ylabel('Latitude',fontsize=10)
  plt.show()
  </code></pre>
  
  <p><a href="https://i.stack.imgur.com/fh4if.png" rel="noreferrer"><img src="https://i.stack.imgur.com/fh4if.png" alt="enter image description here"></a></p>