// file: $isip/class/pr/RegressionDecisionTreeNode/rdtnod_04.cc
// version: $Id: rdtnod_04.cc 9459 2004-04-19 16:06:08Z gao $
//

// isip include files
//
#include "RegressionDecisionTreeNode.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 RegressionDecisionTreeNode::sofSize() const {

  // start with the space required for the datapoints
  //
  int32 bytes = gaussian_models_d.sofSize();

  // add the space required for the average mean
  //
  bytes += average_mean_d.sofSize();

  // add the space required for average mean
  //
  bytes += average_mean_d.sofSize();
  
  // add the space required for the culster score
  //
  bytes += cluster_score_d.sofSize();

  // add the space required for the culster accumulation
  //
  bytes += cluster_accumulate_d.sofSize();

  // add the space required for the number of components
  //
  bytes += number_components_d.sofSize();

  // add the space required for the node index
  //
  bytes += node_index_d.sofSize();  

  // add the space required for the average covariance
  //
  bytes += average_covariance_d.sofSize();

  // add the space required for the speech flag
  //
  bytes += speech_flag_d.sofSize();

  // add the space required for the split flag
  //
  bytes += split_flag_d.sofSize();

  // add the space required for the parent node index
  //
  bytes += parent_node_index_d.sofSize();

  // add the space required for the transform flag
  //
  bytes += transform_flag_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: bool8 value indicating status
//
// this method has the object write itself to an Sof file
//
bool8 RegressionDecisionTreeNode::write(Sof& sof_a, int32 tag_a,
					const String& name_a) const {

  int32 obj_size = 0;
  
  // write the instance of the object into the Sof file
  //
  if (sof_a.isText()) {

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

    // the size index and the size of each element
    //
    obj_size = sofSize();
  }

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

// method: writeData
//
// arguments:
//  Sof& sof: (input) sof file object
//  const String& pname: (input) parameter name
//
// return: bool8 value indicating status
//
// this method has the object write itself to an Sof file. it assumes
// that the Sof file is already positioned correctly.
//
bool8 RegressionDecisionTreeNode::writeData(Sof& sof_a,
					    const String& pname_a) const {
  
  // write a start string if necessary
  //
  sof_a.writeLabelPrefix(pname_a);

  // write the datapoints
  //
  gaussian_models_d.writeData(sof_a, PARAM_DATAPOINTS);

  // write the average mean for this node
  //
  average_mean_d.writeData(sof_a, PARAM_AVERAGE_MEAN);

  // write the cluster score for this node
  //
  cluster_score_d.writeData(sof_a, PARAM_CLUSTER_SCORE);

  // write the cluster accumulation value for this node
  //
  cluster_accumulate_d.writeData(sof_a, PARAM_CLUSTER_ACCUMULATE);

  // write the node number of components
  //
  number_components_d.writeData(sof_a, PARAM_NUMBER_COMPONENTS);

  // write the node index
  //
  node_index_d.writeData(sof_a, PARAM_NODE_INDEX);

  // write the node average covariance
  //
  average_covariance_d.writeData(sof_a, PARAM_AVERAGE_COVARIANCE);

  // write the node speech flag
  //
  speech_flag_d.writeData(sof_a, PARAM_SPEECH_FLAG);

  // write the node split flag
  //
  split_flag_d.writeData(sof_a, PARAM_SPLIT_FLAG);

  // write the parent node index
  //
  parent_node_index_d.writeData(sof_a, PARAM_PARENT_NODE_INDEX);

  // write the node transform flag
  //
  transform_flag_d.writeData(sof_a, PARAM_TRANSFORM_FLAG);

  // write the node statistical models
  //
  stat_models_d.writeData(sof_a, PARAM_STAT_MODELS);

  // write the node w transform matrix
  //
  w_transform_d.writeData(sof_a, PARAM_W_TRANSFORM);    
  
  // put an end string if necessary
  //
  sof_a.writeLabelSuffix(pname_a);
  
  // write the debug level
  //
  debug_level_d.writeData(sof_a, PARAM_DBGL);

  // exit gracefully
  //
  return true;
}