new_contents: """
  Test some recommendation with the movielen data 
  """
  
  from apgl.util.PathDefaults import PathDefaults 
  import nimfa
  import numpy 
  import numpy as np
  import scipy.sparse as sp
  from os.path import dirname, abspath, sep
  from warnings import warn
  
  try:
      import matplotlib.pylab as plb
  except ImportError, exc:
      warn("Matplotlib must be installed to run Recommendations example.")
  
  
  def readCoauthors(): 
      """
      Take a list of coauthors and read in the complete graph into a sparse 
      matrix R such that R_ij = k means author i has worked with j, k times.  
      """
      edgeFileName = PathDefaults.getOutputDir() + "edges.txt"    
          
      #First read the ids and figure out how big the matrix is 
      print("Starting to read edges")
      edges = numpy.loadtxt(edgeFileName, delimiter=",")
      
      print(edges.shape)
      
  
  readCoauthors()
subject: Read the coauthors graph.