text: import os
  from random import shuffle
  import random
  import shutil
  
  
  jex_path = "eurovoc"
  config_dir = "config_splits"
  classifiers_dir = "classifiers_splits"
  results_dir = "results"
  SEEDS = [110, 221]
  
  
  def create_splits(directory):
      if not os.path.exists(os.path.join(jex_path, directory, "workspace", "splits")):
          os.makedirs(os.path.join(jex_path, directory, "workspace", "splits"))
      else:
          shutil.rmtree(os.path.join(jex_path, directory, "workspace", "splits"))
          os.makedirs(os.path.join(jex_path, directory, "workspace", "splits"))
  
      list_samples = []
  
      with open(os.path.join(jex_path, directory, "workspace", "corpus.cf"), "r", encoding="utf-8") as file:
          for labels in file:
              document = file.readline()
  
              list_samples.append((document, labels))
  
      for i, seed in enumerate(SEEDS):
          random.seed(seed)
          shuffle(list_samples)
  
          ratio = int(len(list_samples) * 0.9)
          train = list_samples[:ratio]
          test = list_samples[ratio:]
  
          if not os.path.exists(os.path.join(jex_path, directory, "workspace", "splits", "split_train_{}".format(i))):
              os.makedirs(os.path.join(jex_path, directory, "workspace", "splits", "split_train_{}".format(i)))
  
          if not os.path.exists(os.path.join(jex_path, directory, "workspace", "splits", "split_test_{}".format(i))):
              os.makedirs(os.path.join(jex_path, directory, "workspace", "splits", "split_test_{}".format(i)))
  
          with open(os.path.join(jex_path, directory, "workspace", "splits", "split_train_{}".format(i), "train.cf"), "w", encoding="utf-8") as file:
              for document, label in train:
                  file.write(label)
                  file.write(document)
  
          with open(os.path.join(jex_path, directory, "workspace", "splits", "split_test_{}".format(i), "test.cf"), "w", encoding="utf-8") as file:
              for document, label in test:
                  file.write(label)
                  file.write(document)
  
  
  def create_configs(directory):
      if not os.path.exists(os.path.join(jex_path, directory, "workspace", config_dir)):
          os.makedirs(os.path.join(jex_path, directory, "workspace", config_dir))
  
      for i in range(len(SEEDS)):
          with open(os.path.join(jex_path, directory, "workspace", config_dir, "PreProcess.properties".format(i)), "w") as file:
              file.write("inputDir = {}/{}/workspace/cf\n".format(jex_path, directory))
              file.write("stopwords =  {}/{}/resources/stopwords.txt\n".format(jex_path, directory))
              file.write("output = {}/{}/workspace/corpus.cf\n".format(jex_path, directory, i))
              file.write("forTraining = true\n")
              file.write("MultiWordsFile = {}/{}/resources/stopwords_multi.txt\n".format(jex_path, directory))
  
          if not os.path.exists(os.path.join(jex_path, directory, "workspace", config_dir, "split_{}".format(i))):
              os.makedirs(os.path.join(jex_path, directory, "workspace", config_dir, "split_{}".format(i)))
  
          with open(os.path.join(jex_path, directory, "workspace", config_dir, "split_{}".format(i), "Train.properties"), "w") as file:
              file.write("input = {}/{}/workspace/splits/split_train_{}/train.cf\n".format(jex_path, directory, i))
              file.write("classifiersDir = {}/{}/workspace/{}/classifiers_{}/\n".format(jex_path, directory, classifiers_dir, i))
              file.write("dict = {}/{}/workspace/dict_{}\n".format(jex_path, directory, i))
              file.write("dumpReadable = true\n")
              file.write("RefCorpusWordMinFreq = 4\n")
              file.write("LlhThreshold = 5\n")
              file.write("beta = 10\n")
              file.write("minDocLength = 100\n")
              file.write("minNumTrainingDocsPerDescriptor = 4\n")
              file.write("minWeightOfAssociates = 2\n")
              file.write("minNumAssociatesPerDescriptor = 1\n")
              file.write("maxNumAssociatesPerDescriptor = 5000\n")
              file.write("ThesaurusInfo = {}/{}/resources/ThesaurusStructure/\n".format(jex_path, directory))
              file.write("DeprecatedFile = {}/{}/workspace/deprecated_{}.txt\n".format(jex_path, directory, i))
  
          with open(os.path.join(jex_path, directory, "workspace", config_dir, "split_{}".format(i), "Evaluate.properties"), "w") as file:
              file.write("input = {}/{}/workspace/splits/split_test_{}/test.cf\n".format(jex_path, directory, i))
              file.write("output = {}/{}/workspace/{}/evaluate-result_{}.txt\n".format(jex_path, directory, results_dir, i))
              file.write("dict = {}/{}/workspace/dict_{}\n".format(jex_path, directory, i))
              file.write("blacklist = {}/{}/resources/blacklist.txt\n".format(jex_path, directory))
              file.write("classifiersDir = {}/{}/workspace/{}/classifiers_{}/\n".format(jex_path, directory, classifiers_dir, i))
              file.write("minNumCommonTokens = 1\n")
              file.write("rank = 6\n")
              file.write("displayClassifierInfo = true\n")
  
          with open(os.path.join(jex_path, directory, "workspace", config_dir, "split_{}".format(i), "Index.properties"), "w") as file:
              file.write("input = {}/{}/workspace/splits/split_test_{}/test.cf\n".format(jex_path, directory, i))
              file.write("output = {}/{}/workspace/{}/Assign_Result_{}.xml\n".format(jex_path, directory, results_dir, i))
              file.write("dict = {}/{}/workspace/dict_{}\n".format(jex_path, directory, i))
              file.write("blacklist = {}/{}/resources/blacklist.txt\n".format(jex_path, directory))
              file.write("classifiersDir = {}/{}/workspace/{}/classifiers_{}/\n".format(jex_path, directory, classifiers_dir, i))
              file.write("minNumDesc = 1\n")
              file.write("rank = 6\n")
              file.write("minNumCommonTokens = 1\n")
  
  
  def preprocess_files(directory):
      os.system("java -Dlogback.configurationFile={} -Xms1400M -jar {} {}".format(
          os.path.join(jex_path, directory, "workspace", "config", "logback.xml"),
          os.path.join(jex_path, directory, "lib", "CreateCompactFormat.jar"),
          os.path.join(jex_path, directory, "workspace", config_dir, "PreProcess.properties"),
      ))
  
  
  def train_models(directory):
      for i in range(len(SEEDS)):
          if not os.path.exists(os.path.join(jex_path, directory, "workspace", classifiers_dir, "classifiers_{}".format(i))):
              os.makedirs(os.path.join(jex_path, directory, "workspace", classifiers_dir, "classifiers_{}".format(i)))
  
          os.system("java -Dlogback.configurationFile={} -Xms1400M -jar {} {}".format(
              os.path.join(jex_path, directory, "workspace", "config", "logback.xml"),
              os.path.join(jex_path, directory, "lib", "EuroVocIndexer.jar"),
              os.path.join(jex_path, directory, "workspace", config_dir, "split_{}".format(i), "Train.properties"),
          ))
  
  
  def evaluate_models(directory):
      if not os.path.exists(os.path.join(jex_path, directory, "workspace", results_dir)):
          os.makedirs(os.path.join(jex_path, directory, "workspace", results_dir))
  
      for i in range(len(SEEDS)):
          os.system("java -Dlogback.configurationFile={} -Xms1400M -jar {} {}".format(
              os.path.join(jex_path, directory, "workspace", "config", "logback.xml"),
              os.path.join(jex_path, directory, "lib", "EuroVocIndexer.jar"),
              os.path.join(jex_path, directory, "workspace", config_dir, "split_{}".format(i), "Evaluate.properties"),
          ))
  
  
  def index_test(directory):
      if not os.path.exists(os.path.join(jex_path, directory, "workspace", results_dir)):
          os.makedirs(os.path.join(jex_path, directory, "workspace", results_dir))
  
      for i in range(len(SEEDS)):
          os.system("java -Dlogback.configurationFile={} -Xms1400M -jar {} {}".format(
              os.path.join(jex_path, directory, "workspace", "config", "logback.xml"),
              os.path.join(jex_path, directory, "lib", "EuroVocIndexer.jar"),
              os.path.join(jex_path, directory, "workspace", config_dir, "split_{}".format(i), "Index.properties"),
          ))
  
  
  def run_jex():
      for directory in os.listdir(jex_path):
          create_configs(directory)
  
          preprocess_files(directory)
  
          create_splits(directory)
  
          train_models(directory)
  
          evaluate_models(directory)
  
          index_test(directory)
  
  
  if __name__ == '__main__':
  
      run_jex()
  
  
  
  