text: import pandas as pd
  import matplotlib
  matplotlib.use('Agg')
  import matplotlib.pyplot as plt
  from naacl.framework import util
  import os
  
  results='results/'
  
  
  # change font size
  matplotlib.rcParams.update({'font.size': 12})
  
  
  f=plt.figure()
  
  #anew joint
  df=util.load_tsv(results+'anew_joint.tsv')
  plt.plot(df.index, df['Average.M'], label='MTLNN on EN', color='blue',
  			linestyle='-',
  			marker='o')
  
  #anew separate
  df=util.load_tsv(results+'anew_separate.tsv')
  plt.plot(df.index, df['Average.M'], label='sepNN on EN', color='blue',
  			linestyle='--',
  			marker='o')
  
  
  #warriner joint
  df=util.load_tsv(results+'warriner_joint.tsv')
  plt.plot(df.index, df['Average.M'], label='MTLNN on EN+', color='red',
  			linestyle='-',
  			marker='^')
  
  #warriner separate
  df=util.load_tsv(results+'warriner_separate.tsv')
  plt.plot(df.index, df['Average.M'], label='sepNN on EN+', color='red',
  			linestyle='--',
  			marker='^')
  
  
  # for file in os.listdir(results):
  # 	if file.endswith('.tsv'):
  # 		print(file)
  # 		df=util.load_tsv(results+file)
  # 		# plt.plot([0.]+list(df.index), [0.]+list(df['Average.M']), label=file[:-4])
  # 		plt.plot(list(df.index), list(df['Average.M']), label=file[:-4])
  
  # plt.ylim([.70, .85])
  plt.xlabel('Training Steps')
  plt.ylabel('Pearson Correlation')
  plt.grid()
  plt.legend(borderpad=1)
  f.savefig('plot.pdf')