/*    This file is part of the Gudhi Library. The Gudhi library
 *    (Geometric Understanding in Higher Dimensions) is a generic C++
 *    library for computational topology.
 *
 *    Author(s):       Pawel Dlotko
 *
 *    Copyright (C) 2015  INRIA (France)
 *
 *    This program is free software: you can redistribute it and/or modify
 *    it under the terms of the GNU General Public License as published by
 *    the Free Software Foundation, either version 3 of the License, or
 *    (at your option) any later version.
 *
 *    This program is distributed in the hope that it will be useful,
 *    but WITHOUT ANY WARRANTY; without even the implied warranty of
 *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *    GNU General Public License for more details.
 *
 *    You should have received a copy of the GNU General Public License
 *    along with this program.  If not, see <http://www.gnu.org/licenses/>.
 */

#include <gudhi/Persistence_vectors.h>



using namespace Gudhi;
using namespace Gudhi::Persistence_representations;

#include <iostream>
#include <sstream>


int main( int argc , char** argv )
{
	std::cout << "This program compute distance of persistence vectors stored in a file (the file needs to be created beforehand). \n";	
	std::cout << "The first parameter of a program is an interger p. The program compute l^p distance of the vectors. For l^infty distance choose p = -1. \n";
	std::cout << "The remaining parameters of this programs are names of files with persistence vectors.\n";
	
	if ( argc < 3 )
	{
		std::cout << "Wrong number of parameters, the program will now terminate \n";
		return 1;
	}
	
	int pp = atoi( argv[1] );
	double p = std::numeric_limits<double>::max();
	if ( pp != -1 )
	{
		p = pp;
	}
	

	std::vector< const char* > filenames;
	for ( int i = 2 ; i < argc ; ++i )
	{
		filenames.push_back( argv[i] );
	}
	std::vector< Vector_distances_in_diagram< Euclidean_distance > > vectors;
	vectors.reserve( filenames.size() );
	for ( size_t file_no = 0 ; file_no != filenames.size() ; ++file_no )
	{
		//cerr << filenames[file_no] << endl;
		Vector_distances_in_diagram< Euclidean_distance > l;
		l.load_from_file( filenames[file_no] );
		vectors.push_back( l );
	}
		
	//and now we will compute the scalar product of landscapes.
	
	//first we prepare an array:
	std::vector< std::vector< double > > distance( filenames.size() );
	for ( size_t i = 0 ; i != filenames.size() ; ++i )
	{
		std::vector< double > v( filenames.size() , 0 );
		distance[i] = v;
	}
		
	//and now we can compute the distances:
	for ( size_t i = 0 ; i != vectors.size() ; ++i )
	{
		for ( size_t j = i+1 ; j != vectors.size() ; ++j )
		{
			distance[i][j] = distance[j][i] = vectors[i].distance( vectors[j] , p ) ;
		}
	}
	
	//and now output the result to the screen and a file:
	std::ofstream out;
	out.open( "distance" );
	for ( size_t i = 0 ; i != distance.size() ; ++i )
	{
		for ( size_t j = 0 ; j != distance.size() ; ++j )
		{
			std::cout << distance[i][j] << " ";
			out << distance[i][j] << " ";
		}
		std::cout << std::endl;
		out << std::endl;
	}
	out.close();
		
	return 0;
}