bool SelfOrganizingMap::load( std::fstream &file ){
//Clear any previous model
clear();
std::string word;
file >> word;
if( word != "GRT_SELF_ORGANIZING_MAP_MODEL_FILE_V1.0" ){
errorLog << "load(fstream &file) - Failed to load file header!" << std::endl;
return false;
}
if( !loadClustererSettingsFromFile( file ) ){
errorLog << "load(fstream &file) - Failed to load cluster settings from file!" << std::endl;
return false;
}
file >> word;
if( word != "NetworkTypology:" ){
errorLog << "load(fstream &file) - Failed to load NetworkTypology header!" << std::endl;
return false;
}
file >> networkTypology;
file >> word;
if( word != "AlphaStart:" ){
errorLog << "load(fstream &file) - Failed to load AlphaStart header!" << std::endl;
return false;
}
file >> alphaStart;
file >> word;
if( word != "AlphaEnd:" ){
errorLog << "load(fstream &file) - Failed to load alphaEnd header!" << std::endl;
return false;
}
file >> alphaEnd;
//Load the model if it has been trained
if( trained ){
file >> word;
if( word != "Neurons:" ){
errorLog << "load(fstream &file) - Failed to load Neurons header!" << std::endl;
return false;
}
neurons.resize(numClusters,numClusters);
for(UINT i=0; i<neurons.getNumRows(); i++){
for(UINT j=0; j<neurons.getNumCols(); j++){
if( !neurons[i][j].load( file ) ){
errorLog << "load(fstream &file) - Failed to save neuron to file!" << std::endl;
return false;
}
}
}
}
return true;
}
bool HierarchicalClustering::loadModelFromFile( std::fstream &file ){
std::string word;
//Clear any previous model
clear();
file >> word;
if( word != "GRT_HIERARCHICAL_CLUSTERING_FILE_V1.0" ){
return false;
}
if( !loadClustererSettingsFromFile( file ) ){
errorLog << "loadModelFromFile(fstream &file) - Failed to load cluster settings from file!" << std::endl;
return false;
}
return true;
}
bool KMeans::loadModelFromFile( std::fstream &file ){
//Clear any previous model
clear();
if(!file.is_open()){
errorLog << "loadModelFromFile(string filename) - Failed to open file!" << std::endl;
return false;
}
std::string word;
file >> word;
if( word != "GRT_KMEANS_MODEL_FILE_V1.0" ){
return false;
}
if( !loadClustererSettingsFromFile( file ) ){
errorLog << "loadModelFromFile(string filename) - Failed to open file!" << std::endl;
return false;
}
if( trained ){
file >> word;
if( word != "Clusters:" ){
return false;
}
//Resize the buffers
clusters.resize(numClusters,numInputDimensions);
//Load the data
for(UINT k=0; k<numClusters; k++){
for(UINT n=0; n<numInputDimensions; n++){
file >> clusters[k][n];
}
}
}
return true;
}
bool GaussianMixtureModels::loadModelFromFile( std::fstream &file ){
//Clear any previous model
clear();
std::string word;
file >> word;
if( word != "GRT_GAUSSIAN_MIXTURE_MODELS_FILE_V1.0" ){
return false;
}
if( !loadClustererSettingsFromFile( file ) ){
errorLog << "loadModelFromFile(fstream &file) - Failed to load cluster settings from file!" << std::endl;
return false;
}
//Load the model
if( trained ){
//Setup the memory
mu.resize(numClusters, numInputDimensions);
sigma.resize(numClusters);
invSigma.resize(numClusters);
det.resize(numClusters);
//Load mu
file >> word;
if( word != "Mu:" ){
clear();
errorLog << "loadModelFromFile(fstream &file) - Failed to load Mu!" << std::endl;
return false;
}
for(UINT k=0; k<numClusters; k++){
for(UINT n=0; n<numInputDimensions; n++){
file >> mu[k][n];
}
}
//Load Sigma
file >> word;
if( word != "Sigma:" ){
clear();
errorLog << "loadModelFromFile(fstream &file) - Failed to load Sigma!" << std::endl;
return false;
}
for(UINT k=0; k<numClusters; k++){
sigma[k].resize(numInputDimensions, numInputDimensions);
for(UINT i=0; i<numInputDimensions; i++){
for(UINT j=0; j<numInputDimensions; j++){
file >> sigma[k][i][j];
}
}
}
//Load InvSigma
file >> word;
if( word != "InvSigma:" ){
clear();
errorLog << "loadModelFromFile(fstream &file) - Failed to load InvSigma!" << std::endl;
return false;
}
for(UINT k=0; k<numClusters; k++){
invSigma[k].resize(numInputDimensions, numInputDimensions);
for(UINT i=0; i<numInputDimensions; i++){
for(UINT j=0; j<numInputDimensions; j++){
file >> invSigma[k][i][j];
}
}
}
//Load Det
file >> word;
if( word != "Det:" ){
clear();
errorLog << "loadModelFromFile(fstream &file) - Failed to load Det!" << std::endl;
return false;
}
for(UINT k=0; k<numClusters; k++){
file >> det[k];
}
//Setup the cluster labels
clusterLabels.resize(numClusters);
for(UINT i=0; i<numClusters; i++){
clusterLabels[i] = i+1;
}
clusterLikelihoods.resize(numClusters,0);
clusterDistances.resize(numClusters,0);
}
return true;
}
