bool KMeans::saveModelToFile( std::fstream &file ) const{
if( !file.is_open() ){
errorLog << "saveModelToFile(fstream &file) - Failed to save model, file is not open!" << std::endl;
return false;
}
file << "GRT_KMEANS_MODEL_FILE_V1.0\n";
if( !saveClustererSettingsToFile( file ) ){
errorLog << "saveModelToFile(fstream &file) - Failed to save clusterer settings to file!" << std::endl;
return false;
}
if( trained ){
file << "Clusters:\n";
for(UINT k=0; k<numClusters; k++){
for(UINT n=0; n<numInputDimensions; n++){
file << clusters[k][n] << "\t";
}file << std::endl;
}
}
return true;
}
bool SelfOrganizingMap::save( std::fstream &file ) const{
if( !trained ){
errorLog << "save(fstream &file) - Can't save model to file, the model has not been trained!" << std::endl;
return false;
}
file << "GRT_SELF_ORGANIZING_MAP_MODEL_FILE_V1.0\n";
if( !saveClustererSettingsToFile( file ) ){
errorLog << "save(fstream &file) - Failed to save cluster settings to file!" << std::endl;
return false;
}
file << "NetworkTypology: " << networkTypology << std::endl;
file << "AlphaStart: " << alphaStart << std::endl;
file << "AlphaEnd: " << alphaEnd << std::endl;
if( trained ){
file << "Neurons: \n";
for(UINT i=0; i<neurons.getNumRows(); i++){
for(UINT j=0; j<neurons.getNumCols(); j++){
if( !neurons[i][j].save( file ) ){
errorLog << "save(fstream &file) - Failed to save neuron to file!" << std::endl;
return false;
}
}
}
}
return true;
}
bool HierarchicalClustering::saveModelToFile( std::fstream &file ) const{
if( !file.is_open() ){
errorLog << "saveModelToFile(string filename) - Failed to open file!" << std::endl;
return false;
}
file << "GRT_HIERARCHICAL_CLUSTERING_FILE_V1.0\n";
if( !saveClustererSettingsToFile( file ) ){
errorLog << "saveModelToFile(fstream &file) - Failed to save cluster settings to file!" << std::endl;
return false;
}
if( trained ){
file << "M: " << M << std::endl;
file << "N: " << N << std::endl;
file << "NumLevels: " << clusters.getSize() << std::endl;
for(UINT i=0; i<clusters.getSize(); i++){
file << "Level: " << clusters[i].getLevel() << std::endl;
file << "NumClusters: " << clusters[i].getNumClusters() << std::endl;
}
}
return true;
}
bool GaussianMixtureModels::saveModelToFile( std::fstream &file ) const{
if( !file.is_open() ){
errorLog << "saveModelToFile(string filename) - Failed to open file!" << std::endl;
return false;
}
file << "GRT_GAUSSIAN_MIXTURE_MODELS_FILE_V1.0\n";
if( !saveClustererSettingsToFile( file ) ){
errorLog << "saveModelToFile(fstream &file) - Failed to save cluster settings to file!" << std::endl;
return false;
}
if( trained ){
file << "Mu:\n";
for(UINT k=0; k<numClusters; k++){
for(UINT n=0; n<numInputDimensions; n++){
file << mu[k][n] << "\t";
}
file << std::endl;
}
file << "Sigma:\n";
for(UINT k=0; k<numClusters; k++){
for(UINT i=0; i<numInputDimensions; i++){
for(UINT j=0; j<numInputDimensions; j++){
file << sigma[k][i][j] << "\t";
}
}
file << std::endl;
}
file << "InvSigma:\n";
for(UINT k=0; k<numClusters; k++){
for(UINT i=0; i<numInputDimensions; i++){
for(UINT j=0; j<numInputDimensions; j++){
file << invSigma[k][i][j] << "\t";
}
}
file << std::endl;
}
file << "Det:\n";
for(UINT k=0; k<numClusters; k++){
file << det[k] << std::endl;
}
}
return true;
}
