#include <iostream>
#include <Eigen/Dense>
#include <boost/program_options.hpp>
#include <list>
#include "tools/easylogging++.h"
#include "model/ranksvmtn.h"
#include "tools/fileDataProvider.h"
#include "model/rankaccu.h"

INITIALIZE_EASYLOGGINGPP

using namespace Eigen;
namespace po = boost::program_options;

po::variables_map vm;

typedef int (*mainFunc)(DataProvider &dp);

int train(DataProvider &dp) {
    RSVM *rsvm;
    rsvm = RSVM::loadModel(vm["model"].as<std::string>());

    dp.open();
    DataList D;

    LOG(INFO)<<"Training started";
    dp.getDataSet(D);
    LOG(INFO)<<"Read "<<D.getSize()<<" entries with "<< D.getfSize()<<" features";
    rsvm->train(D);
    std::vector<double> L;
    rsvm->predict(D,L);

    rank_accu(D,L);

    LOG(INFO)<<"Training finished,saving model";

    dp.close();
    rsvm->saveModel(vm["output"].as<std::string>().c_str());
    delete rsvm;
    return 0;
}

int predict(DataProvider &dp) {
    RSVM *rsvm;
    rsvm = RSVM::loadModel(vm["model"].as<std::string>().c_str());

    dp.open();
    DataList D;
    std::vector<double> L;
    LOG(INFO)<<"Prediction started";

    dp.getDataSet(D);
    LOG(INFO)<<"Read "<<D.getSize()<<" entries with "<< D.getfSize()<<" features";
    rsvm->predict(D,L);

    if (vm.count("validate"))
    {
        rank_accu(D,L);
    }

    if (vm.count("output"))
    {
        LOG(INFO)<<"Finished,saving prediction";
        std::ofstream fout(vm["output"].as<std::string>().c_str());

        for (int i=0; i<L.size();++i)
            fout<<L[i]<<std::endl;
        fout.close();
    }
    else if (!vm.count("validate"))
    {
        LOG(INFO)<<"Finished";
        for (int i=0; i<L.size();++i)
            std::cout<<L[i]<<std::endl;
    }
    dp.close();
    delete rsvm;
    return 0;
}

int main(int argc, char **argv) {
    // Defining program options
    po::options_description desc("Allowed options");
    desc.add_options()
            ("help,h", "produce help message")
            ("train,T", "training model")
            ("validate,V", "validate model")
            ("predict,P", "use model for prediction")
            ("model,m", po::value<std::string>(), "set input model file")
            ("output,o", po::value<std::string>(), "set output model/prediction file")
            ("feature,i", po::value<std::string>(), "set input feature file");

    // Parsing program options
    po::store(po::parse_command_line(argc, argv, desc), vm);
    po::notify(vm);

    // Print help if necessary
    if (vm.count("help") || !(vm.count("train") || vm.count("validate") || vm.count("predict"))) {
        std::cout << desc;
        return 0;
    }
    mainFunc mainf;
    if (vm.count("train")) {
        mainf = &train;
    }
    else if (vm.count("validate")||vm.count("predict")) {
        mainf = &predict;
    }
    else return 0;
    DataProvider* dp;
    dp = new FileDP(vm["feature"].as<std::string>());
    mainf(*dp);
    delete dp;
    return 0;
}