################################################################################
#           The Neural Network (NN) based Speech Synthesis System
#                https://svn.ecdf.ed.ac.uk/repo/inf/dnn_tts/
#                
#                Centre for Speech Technology Research                 
#                     University of Edinburgh, UK                       
#                      Copyright (c) 2014-2015
#                        All Rights Reserved.                           
#                                                                       
# The system as a whole and most of the files in it are distributed
# under the following copyright and conditions
#
#  Permission is hereby granted, free of charge, to use and distribute  
#  this software and its documentation without restriction, including   
#  without limitation the rights to use, copy, modify, merge, publish,  
#  distribute, sublicense, and/or sell copies of this work, and to      
#  permit persons to whom this work is furnished to do so, subject to   
#  the following conditions:
#  
#   - Redistributions of source code must retain the above copyright  
#     notice, this list of conditions and the following disclaimer.   
#   - Redistributions in binary form must reproduce the above         
#     copyright notice, this list of conditions and the following     
#     disclaimer in the documentation and/or other materials provided 
#     with the distribution.                                          
#   - The authors' names may not be used to endorse or promote products derived 
#     from this software without specific prior written permission.   
#                                  
#  THE UNIVERSITY OF EDINBURGH AND THE CONTRIBUTORS TO THIS WORK        
#  DISCLAIM ALL WARRANTIES WITH REGARD TO THIS SOFTWARE, INCLUDING      
#  ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS, IN NO EVENT   
#  SHALL THE UNIVERSITY OF EDINBURGH NOR THE CONTRIBUTORS BE LIABLE     
#  FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES    
#  WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN   
#  AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION,          
#  ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF       
#  THIS SOFTWARE.
################################################################################

#  quick and dirty utility to print out binary files, for debugging

import sys
# import numpy
from io_funcs.binary_io import BinaryIOCollection

if __name__ == '__main__':

    ## shall we read the logging config file from command line?
    if len(sys.argv) < 3:
        print 'usage: python view.py dimension filename(s)'
        sys.exit(1)

    dimension = int(sys.argv[1])
    fnames = sys.argv[2:]

    print fnames
    
    io_funcs = BinaryIOCollection()
    for f in fnames:
        features = io_funcs.load_binary_file(f, dimension)

    print features.shape
    # print features
