training_data.close() #percept.finish_training() # Step 3 - classify percept.finish_training() test_data = open("data/eng.testb") id_str = '_'.join([f.id for f in fs.features]) results_file = "eng_leftout_greedy" + "_" + str(ROUNDS) + "_" + id_str + ".out" fnum = 0 while results_file in os.listdir("results"): results_file = results_file.split('.')[0] + str(fnum) + ".out" fnum += 1 results_file = "results/" + results_file output = open(results_file, 'w') test_lines = [] for line in test_data: line = line.strip() if line == '': tags_star = percept.test_greedy([obj[0] for obj in test_lines], [obj[1] for obj in test_lines]) #print "classified and result:" #print [obj[0] for obj in test_lines] #print tags_star for tl, tt in izip(test_lines, tags_star): output.write(' '.join(tl) + ' ' + tt + '\n') output.write('\n') test_lines = [] else: line = line.split(' ') test_lines.append(line) output.close() test_data.close()