// file: $isip/class/pr/MaximumLikelihoodLinearRegression/mllr_04.cc
// version: $Id: mllr_04.cc 9457 2004-04-19 15:06:59Z gao $
//

// isip include files
//
#include "MaximumLikelihoodLinearRegression.h"

// method: sofSize
//
// arguments: none 
//
// return: size of object
//
// this method returns the size of the object in the Sof file and is
// used for binary write
//
int32 MaximumLikelihoodLinearRegression::sofSize() const {

  // start with the space required for the algorithm name
  //
  int32 bytes = ALGO_MAP.elementSofSize();

  // add the space required for the implementation name
  //
  bytes += IMPL_MAP.elementSofSize();

  // add the space required for the supvisison mode name
  //
  bytes += SUP_MODE_MAP.elementSofSize();

  // add the space required for the sequence mode name
  //
  bytes += SEQ_MODE_MAP.elementSofSize();  

  // add the space required for rdt
  //
  bytes += rdt_d.sofSize();

  // add the space required for statistical model adaptation
  //
  bytes += sm_adapt_d.sofSize();

  // add the space required for the debug level
  //
  bytes += debug_level_d.sofSize();

  // return the size
  //
  return bytes;
}

// method: write
//
// arguments:
//  Sof& sof: (input) sof file object
//  int32 tag: (input) sof object instance tag
//  const String& name: (input) sof object instance name
//
// return: a bool8 value indicating status
//
// this method has the object write itself to an Sof file
//
bool8 MaximumLikelihoodLinearRegression::write(Sof& sof_a, int32 tag_a,
				      const String& name_a) const {

  // declare local variable
  //
  int32 obj_size;
  
  // write the instance of the object into the Sof file
  //
  if (sof_a.isText()) {

    // set the size to be dynamic
    //
    obj_size = Sof::ANY_SIZE;
  }
  else {

    // set the size to be the size of the object written to the Sof file
    //
    obj_size = sofSize();
  }

  // write the object into the sof file's index
  //
  if (!sof_a.put(name_a, tag_a, obj_size)) {
    return false;
  }
  
  // write data and exit gracefully
  //
  return writeData(sof_a);
}

// method: writeData
//
// arguments:
//  Sof& sof: (input) sof file object
//  const String& pname: (input) parameter name
//
// return: a bool8 value indicating status
//
// this method branches on the algorithm name
//
bool8 MaximumLikelihoodLinearRegression::writeData(Sof& sof_a,
					  const String& pname_a) const {
  
  // declare local variables
  //
  bool8 status = false;
  
  // write a start string if necessary
  //
  sof_a.writeLabelPrefix(pname_a);

  // write the stopmode (from the base class)
  //
  //  STOPMODE_MAP.writeElementData(sof_a, PARAM_STOPMODE, (int32)stopmode_d);
    
  // write the runmode (from the base class)
  //
  //  RUNMODE_MAP.writeElementData(sof_a, PARAM_RUNMODE, (int32)runmode_d);

  // write the algorithm name
  //
  ALGO_MAP.writeElementData(sof_a, PARAM_ALGORITHM, (int32)algorithm_d);
    
  // write the implementation type
  //
  IMPL_MAP.writeElementData(sof_a, PARAM_IMPLEMENTATION,
			    (int32)implementation_d);

  // write the supervision mode type
  //
  SUP_MODE_MAP.writeElementData(sof_a, PARAM_SUPERVISION_MODE,
				(int32)supervision_mode_d);

  // write the sequence mode type
  //
  SEQ_MODE_MAP.writeElementData(sof_a, PARAM_SEQUENCE_MODE,
				(int32)sequence_mode_d);

  // write the regression decision tree object
  //
  rdt_d.writeData(sof_a, PARAM_RDT);

  // write the statistical model adaptation object
  //
  sm_adapt_d.writeData(sof_a, PARAM_SM_ADAPT);
  
  // put an end string if necessary
  //
  sof_a.writeLabelSuffix(pname_a);
  
  // exit gracefully
  //
  return status;
}