code: def printOverlaps(comparedTo, coincs, seen):
    
    inputOverlap = 0
    cellOverlap = 0
    for y in comparedTo:
      closestInputs = []
      closestCells = []
      if len(seen)>0:
        inputOverlap = max([len(seen[m][1].intersection(y[4])) for m in xrange(len(seen))])
        cellOverlap = max([len(seen[m][0].intersection(y[1])) for m in xrange(len(seen))])
        for m in xrange( len(seen) ):
          if len(seen[m][1].intersection(y[4]))==inputOverlap:
            closestInputs.append(seen[m][2])
          if len(seen[m][0].intersection(y[1]))==cellOverlap:
            closestCells.append(seen[m][2])
      seen.append((y[1], y[4], y[0]))
          
      print 'Pattern',y[0]+1,':',' '.join(str(len(z[1].intersection(y[1]))).rjust(2) for z in coincs),'input overlap:', inputOverlap, ';', len(closestInputs), 'closest encodings:',','.join(str(m+1) for m in closestInputs).ljust(15), \
      'cell overlap:', cellOverlap, ';', len(closestCells), 'closest set(s):',','.join(str(m+1) for m in closestCells)
    
    return seen
docs: Compare the results and return True if success, False if failure
      
    Parameters:
    --------------------------------------------------------------------
    coincs:               Which cells are we comparing?
    comparedTo:           The set of 40 cells we being compared to (they have no overlap with seen)
    seen:                 Which of the cells we are comparing to have already been encountered.
                          This helps glue together the unique and reused coincs