#OUTDIR="exp/test/pvector-2"
  #DATADIR="data"
  #NEW_LSTDIR="${OUTDIR}/lst"

  #VECTOR_FILES_BEGIN="${DATADIR}/pvectors_1rst/pvectors_teacher"
  #VECTOR_FILES_END=".txt"
  #VECTOR_FILE="" # To specify if there's only one
  #VECTOR_FILES_ONE=false # Specify there's only one file

  #KMIN=2
  #KMAX=100
  
  # -- LOAD CONFIG FILE
  CONFIG_FILE="config.sh"
  
  if [ $# -eq 1 ]
  then
      CONFIG_FILE="$1"
  else
      echo "Need to have one and only one argument"
      exit -1
  fi
  
  source $CONFIG_FILE
  
  # -- DEFAULTS VALUES CONFIGURATION
  if [ -z "$VECTOR_FILES_ONE" ]
  then
      VECTOR_FILES_ONE=false
  fi
  
  
  
  # -- MAKE DIRECTORIES

  if [ ! -d "$OUTDIR" ];
  then
      mkdir -p $OUTDIR
  fi

  if [ ! -d "${NEW_LSTDIR}" ];
  then
      mkdir -p ${NEW_LSTDIR}
  fi

  # -- KFOLD MIN and MAX
  if [ -z "$MIN_KFOLD" ]
  then
      MIN_KFOLD=1
  fi
  
  if [ -z "$MAX_KFOLD" ]
  then
      MAX_KFOLD=4
  fi

  # -- BEGIN BY KFOLD

  for kfold in $(seq ${MIN_KFOLD} ${MAX_KFOLD})

  do

      # Some usefull variable
      CHAR_INFO="${DATADIR}/character_information.csv"
      TRAIN_TYPE_LST="${NEW_LSTDIR}/train_${kfold}_type.lst"
      VAL_TYPE_LST="${NEW_LSTDIR}/val_${kfold}_type.lst"

      TRAIN_LANG_LST="${NEW_LSTDIR}/train_${kfold}_lang.lst"
      VAL_LANG_LST="${NEW_LSTDIR}/val_${kfold}_lang.lst"

      # Configuration for the run clustering file

      if [ ${VECTOR_FILES_ONE} == false ]

      then

          VECTOR_FILE="${VECTOR_FILES_BEGIN}_${kfold}${VECTOR_FILES_END}"

      fi

      TRAIN_LST="${DATADIR}/pvectors_1rst/lst/train_${kfold}.lst"
      VAL_LST="${DATADIR}/pvectors_1rst/lst/val_${kfold}.lst"
      EXP_DIR="${OUTDIR}/${kfold}"

      METAS_TYPE="${NEW_LSTDIR}/metas_${kfold}_type.lst"

      METAS_CHARACTER="${DATADIR}/masseffect.lst"

      METAS_LANG="${NEW_LSTDIR}/metas_${kfold}_lang.lst"

      
      
      if [ ! -d "${EXP_DIR}" ];
      then
          mkdir -p ${EXP_DIR}
      fi

      # EXTRACT TYPE INFORMATION

      echo "Extracting character information"

      echo "Replace in train"

      python3 "bin/replace_label.py" \

          "${METAS_CHARACTER}" \
          "${CHAR_INFO}" \
          --field "type" \
          --lst "${TRAIN_LST}" \
          --outfile "${TRAIN_TYPE_LST}"

      echo "Replace in val"

      python3 "bin/replace_label.py" \

          "${METAS_CHARACTER}" \
          "${CHAR_INFO}" \
          --field "type" \
          --lst "${VAL_LST}" \
          --outfile "${VAL_TYPE_LST}"

      echo "Merge them"

      cat "${TRAIN_TYPE_LST}" "${VAL_TYPE_LST}" > "${METAS_TYPE}"

      
      # EXTRACT LANGUAGE INFORMATION
      echo "Language info for train"
      awk '$2=$1' FS=, OFS=, ${TRAIN_LST} > ${TRAIN_LANG_LST}
      echo "Language info for val"
      awk '$2=$1' FS=, OFS=, ${VAL_LST} > ${VAL_LANG_LST}   
      
      echo "Merge them"
      cat "${TRAIN_LANG_LST}" "${VAL_LANG_LST}" > "${METAS_LANG}"
      
      echo "Then Run Clustering"

      source "run-clustering.sh"

  done

  # Regroup measures with respect to character classes
  echo "Regrouping measures with respect to character classes"
  python3 "bin/regroup-measures.py" ${OUTDIR}
  
  # Regroup measures with respect to type classes
  echo "Regrouping measures with respect to type classes"
  python3 "bin/regroup-measures.py" ${OUTDIR} --suffix "_type" --measurefile "measures_type.json"