text: '''
  Python 2.7
  The clustergrammer python module can be installed using pip:
  pip install clustergrammer
  
  or by getting the code from the repo:
  https://github.com/MaayanLab/clustergrammer-py
  '''
  
  from clustergrammer import Network
  net = Network()
  
  # load matrix tsv file
  net.load_file('txt/rc_two_cats.txt')
  # net.load_file('txt/ccle_example.txt')
  # net.load_file('txt/rc_val_cats.txt')
  # net.load_file('txt/number_labels.txt')
  # net.load_file('txt/mnist.txt')
  # net.load_file('txt/tuple_cats.txt')
  # net.load_file('txt/example_tsv.txt')
  
  # net.enrichrgram('KEA_2015')
  
  # optional filtering and normalization
  ##########################################
  # net.filter_sum('row', threshold=20)
  # net.normalize(axis='col', norm_type='zscore', keep_orig=True)
  # net.filter_N_top('row', 250, rank_type='sum')
  # net.filter_threshold('row', threshold=3.0, num_occur=4)
  # net.swap_nan_for_zero()
  # net.set_cat_color('col', 1, 'Category: one', 'blue')
  
    # net.make_clust()
    # net.dendro_cats('row', 5)
  
  net.cluster(dist_type='cos',views=['N_row_sum', 'N_row_var'] , dendro=True,
                 sim_mat=True, filter_sim=0.1, calc_cat_pval=False, enrichrgram=
                 False, run_clustering=True)
  
  # write jsons for front-end visualizations
  net.write_json_to_file('viz', 'json/mult_view.json', 'indent')
  net.write_json_to_file('sim_row', 'json/mult_view_sim_row.json', 'no-indent')
  net.write_json_to_file('sim_col', 'json/mult_view_sim_col.json', 'no-indent')
  