/***********************************************************************
Moses - factored phrase-based language decoder
Copyright (C) 2010 University of Edinburgh

This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.

This library 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
Lesser General Public License for more details.

You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
***********************************************************************/
#define BOOST_TEST_MODULE BackwardTest
#include <boost/test/unit_test.hpp>

#include "lm/config.hh"
#include "lm/left.hh"
#include "lm/model.hh"
#include "lm/state.hh"

#include "moses/Sentence.h"
#include "moses/TypeDef.h"

#include "moses/StaticData.h"
#include "moses/parameters/AllOptions.h"

//#include "BackwardLMState.h"
#include "moses/LM/Backward.h"
#include "moses/LM/BackwardLMState.h"
#include "moses/Util.h"

#include "lm/state.hh"
#include "lm/left.hh"

#include <vector>

using namespace Moses;
//using namespace std;
/*
template <class M> void Foo() {


  Moses::BackwardLanguageModel<M> *backwardLM;
  // = new Moses::BackwardLanguageModel<M>( filename, factorType, lazy );


}
template <class M> void Everything() {
  //  Foo<M>();
}
*/

namespace Moses
{

// Apparently some Boost versions use templates and are pretty strict about types matching.
#define SLOPPY_CHECK_CLOSE(ref, value, tol) BOOST_CHECK_CLOSE(static_cast<double>(ref), static_cast<double>(value), static_cast<double>(tol));

AllOptions::ptr DefaultOptions(new AllOptions);

class BackwardLanguageModelTest
{

public:
  BackwardLanguageModelTest() :
    dummyInput(new Sentence(DefaultOptions)),
    backwardLM(
      static_cast< BackwardLanguageModel<lm::ngram::ProbingModel> * >(
        ConstructBackwardLM(
          "LM1=1.0",
          boost::unit_test::framework::master_test_suite().argv[1],
          0,
          false)
      )
    ) {
    // This space intentionally left blank
  }

  ~BackwardLanguageModelTest() {
    delete dummyInput;
    delete backwardLM;
  }

  void testEmptyHypothesis() {
    FFState *ffState = const_cast< FFState * >(backwardLM->EmptyHypothesisState( *dummyInput ));

    BOOST_CHECK( ffState != NULL );

    delete ffState;
  }

  void testCalcScore() {

    double p_the      = -1.383059;
    double p_licenses = -2.360783;
    double p_for      = -1.661813;
    double p_most     = -2.360783;
    //      double p_software = -1.62042;

    double p_the_licenses  = -0.9625873;
    double p_licenses_for  = -1.661557;
    double p_for_most      = -0.4526253;
    //      double p_most_software = -1.70295;

    double p_the_licenses_for  = p_the_licenses + p_licenses_for;
    //      double p_licenses_for_most = p_licenses_for + p_for_most;

    // the
    {
      Phrase phrase;
      BOOST_CHECK( phrase.GetSize() == 0 );

      std::vector<FactorType> outputFactorOrder;
      outputFactorOrder.push_back(0);

      phrase.CreateFromString(
        Input,
        outputFactorOrder,
        "the",
        NULL);

      BOOST_CHECK( phrase.GetSize() == 1 );

      float fullScore;
      float ngramScore;
      size_t oovCount;
      backwardLM->CalcScore(phrase, fullScore, ngramScore, oovCount);

      BOOST_CHECK( oovCount == 0 );
      SLOPPY_CHECK_CLOSE( TransformLMScore(p_the), fullScore, 0.01);
      SLOPPY_CHECK_CLOSE( TransformLMScore( 0.0 ), ngramScore, 0.01);
    }

    // the licenses
    {
      Phrase phrase;
      BOOST_CHECK( phrase.GetSize() == 0 );

      std::vector<FactorType> outputFactorOrder;
      outputFactorOrder.push_back(0);

      phrase.CreateFromString(
        Input,
        outputFactorOrder,
        "the licenses",
        NULL);

      BOOST_CHECK( phrase.GetSize() == 2 );

      float fullScore;
      float ngramScore;
      size_t oovCount;
      backwardLM->CalcScore(phrase, fullScore, ngramScore, oovCount);

      BOOST_CHECK( oovCount == 0 );
      SLOPPY_CHECK_CLOSE( TransformLMScore(p_licenses + p_the_licenses), fullScore, 0.01);
      // Check ngramScore is 0.0
      BOOST_CHECK_GT(0.0001, ngramScore);
      BOOST_CHECK_LT(-0.0001, ngramScore);
    }

    // the licenses for
    {
      Phrase phrase;
      BOOST_CHECK( phrase.GetSize() == 0 );

      std::vector<FactorType> outputFactorOrder;
      outputFactorOrder.push_back(0);

      phrase.CreateFromString(
        Input,
        outputFactorOrder,
        "the licenses for",
        NULL);

      BOOST_CHECK( phrase.GetSize() == 3 );

      float fullScore;
      float ngramScore;
      size_t oovCount;
      backwardLM->CalcScore(phrase, fullScore, ngramScore, oovCount);

      BOOST_CHECK( oovCount == 0 );
      SLOPPY_CHECK_CLOSE( TransformLMScore( p_the_licenses_for ), ngramScore, 0.01);
      SLOPPY_CHECK_CLOSE( TransformLMScore(p_for + p_licenses_for + p_the_licenses), fullScore, 0.01);
    }

    // the licenses for most
    {
      Phrase phrase;
      BOOST_CHECK( phrase.GetSize() == 0 );

      std::vector<FactorType> outputFactorOrder;
      outputFactorOrder.push_back(0);

      phrase.CreateFromString(
        Input,
        outputFactorOrder,
        "the licenses for most",
        NULL);

      BOOST_CHECK( phrase.GetSize() == 4 );

      float fullScore;
      float ngramScore;
      size_t oovCount;
      backwardLM->CalcScore(phrase, fullScore, ngramScore, oovCount);

      BOOST_CHECK( oovCount == 0 );
      SLOPPY_CHECK_CLOSE( TransformLMScore( p_the_licenses + p_licenses_for ), ngramScore, 0.01);
      SLOPPY_CHECK_CLOSE( TransformLMScore(p_most + p_for_most + p_licenses_for + p_the_licenses), fullScore, 0.01);
    }

  }

  void testEvaluate() {

    FFState *nextState;
    FFState *prevState = const_cast< FFState * >(backwardLM->EmptyHypothesisState( *dummyInput ));

    double p_most     = -2.360783;
    double p_for      = -1.661813;
    double p_licenses = -2.360783;
    double p_the      = -1.383059;
    double p_eos      = -1.457693;

    double p_most_for      = -0.4526253;
    double p_for_licenses  = -1.661557;
    double p_licenses_the = -0.9625873;
    double p_the_eos = -1.940311;


    // the
    {
      Phrase phrase;
      BOOST_CHECK( phrase.GetSize() == 0 );

      std::vector<FactorType> outputFactorOrder;
      outputFactorOrder.push_back(0);

      phrase.CreateFromString(
        Input,
        outputFactorOrder,
        "the",
        NULL);

      BOOST_CHECK( phrase.GetSize() == 1 );

      float score;
      nextState = backwardLM->Evaluate(phrase, prevState, score);

      // p(the) * p(</s> | the) / p(</s>)
      SLOPPY_CHECK_CLOSE( (p_the + p_the_eos - p_eos), score, 0.01);

      delete prevState;
      prevState = nextState;

    }

    // the licenses
    {
      Phrase phrase;
      BOOST_CHECK( phrase.GetSize() == 0 );

      std::vector<FactorType> outputFactorOrder;
      outputFactorOrder.push_back(0);

      phrase.CreateFromString(
        Input,
        outputFactorOrder,
        "licenses",
        NULL);

      BOOST_CHECK( phrase.GetSize() == 1 );

      float score;
      nextState = backwardLM->Evaluate(phrase, prevState, score);

      // p(licenses) * p(licenses | the) / p(the)
      SLOPPY_CHECK_CLOSE( (p_licenses + p_licenses_the - p_the), score, 0.01);

      delete prevState;
      prevState = nextState;

    }

    // the licenses for
    {
      Phrase phrase;
      BOOST_CHECK( phrase.GetSize() == 0 );

      std::vector<FactorType> outputFactorOrder;
      outputFactorOrder.push_back(0);

      phrase.CreateFromString(
        Input,
        outputFactorOrder,
        "for",
        NULL);

      BOOST_CHECK( phrase.GetSize() == 1 );

      float score;
      nextState = backwardLM->Evaluate(phrase, prevState, score);

      // p(for) * p(for | licenses) / p(licenses)
      SLOPPY_CHECK_CLOSE( (p_for + p_for_licenses - p_licenses), score, 0.01);

      delete prevState;
      prevState = nextState;

    }

    // the licenses for most
    {
      Phrase phrase;
      BOOST_CHECK( phrase.GetSize() == 0 );

      std::vector<FactorType> outputFactorOrder;
      outputFactorOrder.push_back(0);

      phrase.CreateFromString(
        Input,
        outputFactorOrder,
        "most",
        NULL);

      BOOST_CHECK( phrase.GetSize() == 1 );

      float score;
      nextState = backwardLM->Evaluate(phrase, prevState, score);

      // p(most) * p(most | for) / p(for)
      SLOPPY_CHECK_CLOSE( (p_most + p_most_for - p_for), score, 0.01);

      delete prevState;
      prevState = nextState;

    }

    delete prevState;
  }

private:
  const Sentence *dummyInput;
  BackwardLanguageModel<lm::ngram::ProbingModel> *backwardLM;

};


}

const char *FileLocation()
{
  if (boost::unit_test::framework::master_test_suite().argc < 2) {
    BOOST_FAIL("Jamfile must specify arpa file for this test, but did not");
  }
  return boost::unit_test::framework::master_test_suite().argv[1];
}

BOOST_AUTO_TEST_CASE(ProbingAll)
{

  BackwardLanguageModelTest test;
  test.testEmptyHypothesis();
  test.testCalcScore();
  test.testEvaluate();

}