/* -*- mia-c++  -*-
 *
 * This file is part of MIA - a toolbox for medical image analysis 
 * Copyright (c) Leipzig, Madrid 1999-2015 Gert Wollny
 *
 * MIA 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 MIA; if not, see <http://www.gnu.org/licenses/>.
 *
 */

#define VSTREAM_DOMAIN "2dmyopgt"
#include <iomanip>
#include <ostream>
#include <fstream>
#include <map>
#include <ctime>
#include <cstdlib>
#include <libxml++/libxml++.h>
#include <mia/core.hh>

#include <mia/core/errormacro.hh>
#include <mia/2d/imageio.hh>
#include <mia/2d/filter.hh>
#include <mia/2d/ground_truth_evaluator.hh>
#include <mia/2d/nonrigidregister.hh>
#include <mia/2d/segsetwithimages.hh>
#include <mia/2d/transformfactory.hh>


using namespace std;
using namespace mia;

const SProgramDescription g_description = {
        {pdi_group, "Registration of series of 2D images"}, 
	{pdi_short, "Run a registration of a series of 2D images."}, 
	{pdi_description, "This program implements the non-linear registration based on Pseudo Ground "
	 "Thruth for motion compensation of series of myocardial perfusion images given as a "
	 "data set as decribed in Chao Li and Ying Sun, 'Nonrigid Registration of Myocardial Perfusion "
	 "MRI Using Pseudo Ground Truth' , In Proc. Medical Image Computing and Computer-Assisted "
	 "Intervention MICCAI 2009, 165-172, 2009. Note that for this nonlinear motion correction "
	 "a preceding linear registration step is usually required."},
	{pdi_example_descr, "Register the perfusion series given in 'segment.set' by using Pseudo Ground "
	 "Truth estimation. Skip two images at the beginning and otherwiese use the default parameters. "
	 "Store the result in 'registered.set'."}, 
	{pdi_example_code, "-i segment.set -o registered.set -k 2"}
};


C2DFullCostList create_costs(double imageweight)
{
	C2DFullCostList result; 
	stringstream image_descr; 
	image_descr << "image:weight=" << imageweight; 
	result.push(C2DFullCostPluginHandler::instance().produce(image_descr.str())); 
	return result; 
}

P2DTransformationFactory create_transform_creator(size_t c_rate,double divcurlweight)
{
	stringstream transf; 
	transf << "spline:rate=" << c_rate << ",penalty=[divcurl:weight=" << divcurlweight << "]"; 
	return C2DTransformCreatorHandler::instance().produce(transf.str()); 
}

void run_registration_pass(CSegSetWithImages&  input_set, const C2DImageSeries& references, 
			   int skip_images, PMinimizer minimizer, size_t mg_levels, 
			   double c_rate, double divcurlweight, double imageweight) 
{
	CSegSetWithImages::Frames& frames = input_set.get_frames();
	C2DImageSeries input_images = input_set.get_images(); 
	auto costs  = create_costs(imageweight); 
	auto transform_creator = create_transform_creator(c_rate, divcurlweight); 
	C2DNonrigidRegister nrr(costs, minimizer,  transform_creator, mg_levels);

	// this loop could be parallized 
	for (size_t i = 0; i < input_images.size() - skip_images; ++i) {
		cvmsg() << "Register frame " << i << "\n"; 
		P2DTransformation transform = nrr.run(input_images[i + skip_images], references[i]);
		input_images[i + skip_images] = (*transform)(*input_images[i + skip_images]);
		frames[i + skip_images].inv_transform(*transform);
	}
	input_set.set_images(input_images); 
}


int do_main( int argc, char *argv[] )
{
	// IO parameters 
	string in_filename;
	string out_filename;
	string registered_filebase("reg");

	// this parameter is currently not exported - reading the image data is 
	// therefore done from the path given in the segmentation set 
	bool override_src_imagepath = true;
	size_t skip_images = 0; 

	// registration parameters
	PMinimizer minimizer;
	double c_rate = 32; 
	double c_rate_divider = 4; 
	double divcurlweight = 20.0; 
	double divcurlweight_divider = 4.0; 
	double imageweight = 1.0; 
	size_t mg_levels = 3; 
	size_t current_pass = 0; 
	size_t max_pass = 4; 

	// Pseudo Ground Thruth estimation parameters 
	double alpha = 1.0;
	double beta = 1.0;
	double rho_thresh = 0.85;

	CCmdOptionList options(g_description);

	options.set_group("\nFile-IO"); 
	options.add(make_opt( in_filename, "in-file", 'i', "input perfusion data set", CCmdOptionFlags::required_input));
	options.add(make_opt( out_filename, "out-file", 'o', "output perfusion data set", CCmdOptionFlags::required_output));
	options.add(make_opt( registered_filebase, "registered", 'r', "file name base for registered files, the "
			      "image file type is the same as given in the input data set"));

	options.set_group("\nRegistration"); 
	options.add(make_opt( minimizer, "gsl:opt=gd,step=0.1", "optimizer", 'O', "Optimizer used for minimization"));
	options.add(make_opt( c_rate, "start-c-rate", 'a', 
				    "start coefficinet rate in spines, gets divided by --c-rate-divider with every pass"));
	options.add(make_opt( c_rate_divider, "c-rate-divider", 0, 
				    "cofficient rate divider for each pass"));
	options.add(make_opt( divcurlweight, "start-divcurl", 'd',
				    "start divcurl weight, gets divided by --divcurl-divider with every pass")); 
	options.add(make_opt( divcurlweight_divider, "divcurl-divider", 0,
				    "divcurl weight scaling with each new pass")); 
	options.add(make_opt( imageweight, "imageweight", 'w', "image cost weight")); 
	options.add(make_opt( mg_levels, "mg-levels", 'l', "multi-resolution levels"));
	options.add(make_opt( max_pass, "passes", 'P', "registration passes")); 

	options.set_group("\nPseudo Ground Thruth estimation"); 
	options.add(make_opt( alpha, "alpha", 'A', "spacial neighborhood penalty weight"));
	options.add(make_opt( beta, "beta", 'B', "temporal second derivative penalty weight"));
	options.add(make_opt( rho_thresh, "rho-thresh", 'R', 
				    "crorrelation threshhold for neighborhood analysis"));
	options.add(make_opt( skip_images, "skip", 'k', "skip images at the beginning of the series "
				    "e.g. because as they are of other modalities")); 
	
	if (options.parse(argc, argv) != CCmdOptionList::hr_no)
		return EXIT_SUCCESS; 
	// load input data set
	CSegSetWithImages  input_set(in_filename, override_src_imagepath);
	C2DImageSeries input_images = input_set.get_images(); 

	// sanity check 
	if (input_images.size() < 5 + skip_images) {
		throw create_exception<invalid_argument>( "input set has only ", input_images.size(), " frames, but at least ", 
						5 + skip_images, " frames are required for the registration to make sense"); 
	}
	
	// copy true perfusion set to temporary series
	vector<P2DImage> series(input_images.size() - skip_images);
	copy(input_images.begin() + skip_images, input_images.end(), series.begin()); 


	// prepare PGT evaluator 
	C2DGroundTruthEvaluator gte(alpha, beta, rho_thresh);
	vector<P2DImage> pgt;
	
	// run registration passes 
	do {
		cvmsg() << "Registration pass " << current_pass++ << "\n"; 

		gte(series, pgt);
		run_registration_pass(input_set, pgt,  skip_images,  minimizer, 
				      mg_levels, c_rate, divcurlweight, imageweight); 
		
		divcurlweight /= divcurlweight_divider; 
		if (c_rate > 1) 
			c_rate /= c_rate_divider; 
	} while (current_pass < max_pass); 

	// copy back registration results 
	copy(series.begin(), series.end(), input_images.begin() + skip_images); 
	
	// save results
	input_set.rename_base(registered_filebase); 
	input_set.save_images(out_filename); 
	
	unique_ptr<xmlpp::Document> outset(input_set.write());
	ofstream outfile(out_filename.c_str(), ios_base::out );
	if (outfile.good())
		outfile << outset->write_to_string_formatted();
	
	return outfile.good() ? EXIT_SUCCESS : EXIT_FAILURE;
}

#include <mia/internal/main.hh>
MIA_MAIN(do_main); 
