#!/bin/bash
  # set -e
  
  # Copyright 2014  Johns Hopkins University (Author: Vijayaditya Peddinti)
  # Apache 2.0.
  # This script processes RIRs available from available databases into 
  # 8Khz wav files so that these can be used to corrupt the Fisher data.
  # The databases used are:
  # RWCP :  http://research.nii.ac.jp/src/en/RWCP-SSD.html (this data is mirrored @ openslr.org. Thanks to Mitsubishi Electric Research Laboratories)
  # AIRD : Aachen Impulse response database (http://www.ind.rwth-aachen.de/en/research/tools-downloads/aachen-impulse-response-database/)
  # Reverb2014 : http://reverb2014.dereverberation.com/download.html
  # OpenAIR : http://www.openairlib.net/auralizationdb
  # MARDY : http://www.commsp.ee.ic.ac.uk/~sap/resources/mardy-multichannel-acoustic-reverberation-database-at-york-database/
  # QMUL impulse response dataset : http://c4dm.eecs.qmul.ac.uk/rdr/handle/123456789/6
  # Impulse responses from Varechoic chamber at Bell Labs : http://www1.icsi.berkeley.edu/Speech/papers/gelbart-ms/pointers/
  # Concert Hall impulse responses, Aalto University : http://legacy.spa.aalto.fi/projects/poririrs/
   
  stage=0 
  download_rirs=true # download the RIRs
  sampling_rate=8000 # sampling rate to be used for the RIRs
  log_dir=log # directory to store the log files
  RIR_home=db/RIR_databases/ # parent directory of the RIR databases files
  db_string="'aalto' 'air' 'rwcp' 'rvb2014' 'c4dm' 'varechoic' 'mardy' 'openair'" # RIR dbs to be used in the experiment
  
  . ./cmd.sh
  . ./path.sh
  . utils/parse_options.sh
  
  echo $*
  if [ $# -ne 1 ]; then
    echo "$0 outputdir"
    exit 1;
  fi
  
  output_dir=$1
  mkdir -p $output_dir/info ${output_dir}_non_normalized/info
  mkdir -p $log_dir
  rm -f $log_dir/type*.list
  
  if [ -z "$db_string" ]; then
    echo "$0 : Please specify the db_string.";
    exit 1;
  fi
  
  # write the file_splitter to create job files for queue.pl
  # we use this to parallelize the audio corruption and download jobs
  cat << EOF > $log_dir/file_splitter.py
  #!/usr/bin/env python
  import os.path, sys, math
  
  num_lines_per_file = int(sys.argv[1])
  input_file = sys.argv[2]
  [file_base_name, ext] = os.path.splitext(input_file)
  lines = open(input_file).readlines();
  num_lines = len(lines)
  num_jobs = int(math.ceil(num_lines/ float(num_lines_per_file)))
  
  # filtering commands into seperate task files
  for i in xrange(1, num_jobs+1) :
    cur_lines = map(lambda index: lines[index], range(i - 1, num_lines , num_jobs))
    file = open("{0}.{1}{2}".format(file_base_name, i, ext), 'w')
    file.write("which python
  ")
    file.write("".join(cur_lines))
    file.close()
  print num_jobs
  EOF
  chmod +x $log_dir/file_splitter.py
  
  if [ $stage -le 1 ]; then
    echo "Extracting the impulse responses from the databases $db_string"
    num_db_jobs=`echo $db_string|wc -w`
    $decode_cmd JOB=1:$num_db_jobs $log_dir/log/DBprocess.JOB.log \
      db=\(0 $db_string \)  \&\& \
      local/multi_condition/rirs/prep_\$\{db\[JOB\]\}.sh --file-splitter "$log_dir/file_splitter.py 10 " --download $download_rirs --sampling-rate $sampling_rate $RIR_home ${output_dir}_non_normalized $log_dir ||exit 1;
  fi
  
  if [ $stage -le 2 ]; then
    echo "Normalizing the extracted room impulse responses and noises, per type"
    echo "Note: Due to wav-format mismatch between sox and scipy, there might be warnings generated during file normalization."
    echo "      'WavFileWarning: Unknown wave file format' warnings are benign."
    # normalizing the RIR files 
    for i in `ls $log_dir/*type*.rir.list`; do
      echo "Processing files in $i"
      python local/multi_condition/normalize_wavs.py --is-room-impulse-response true $i $i.normval || exit 1;
      norm_coefficient=`cat $i.normval`
      echo "" > $i.normalized
      while read file_name; do
        if [ ! -z $file_name ]; then
          output_file_name=${output_dir}/`basename $file_name`
          sox --volume $norm_coefficient -t wav $file_name -t wav $output_file_name 2>/dev/null
          echo $output_file_name >> $i.normalized
        fi
      done < $i
    done
  
    # normalizing the noise files  
    for i in `ls $log_dir/*type*.noise.list`; do
      echo "Processing files in $i"
      python local/multi_condition/normalize_wavs.py --is-room-impulse-response false $i $i.normval || exit 1;
      norm_coefficient=`cat $i.normval`
      echo "" > $i.normalized
      while read file_name; do
        if [ ! -z $file_name ]; then
          output_file_name=${output_dir}/`basename $file_name`
          sox --volume $norm_coefficient -t wav $file_name -t wav $output_file_name 2>/dev/null
          echo $output_file_name >> $i.normalized
        fi
      done < $i
    done
  fi
  
  # copying the noise-rir pairing files
  cp ${output_dir}_non_normalized/info/* $output_dir/info
  
  # rename file location in the noise-rir pairing files 
  for file in `ls $output_dir/info/noise_impulse*`; do
    perl -i -pe "s/_non_normalized//g" $file
  done
  
  # generating the rir-list with probabilities alloted for each rir
  db_string_python=$(echo $db_string|sed -e "s/'\s\+'/','/g")
  python -c "
  import glob, string, re
  dbs=[$db_string_python]
  rirs = []
  for db in dbs:
    files = glob.glob('$log_dir/{0}*type*.rir.list.normalized'.format(string.upper(db)))
    for file in files:
      for line in open(file).readlines():
        if len(line.strip()) > 0:
          rirs.append(line.strip())
  final_rir_list_file = open('$output_dir/info/impulse_files', 'w')
  final_rir_list_file.write('
  '.join(rirs))
  final_rir_list_file.close()
  "
  
  wc -l  $output_dir/info/impulse_files