////////////////////////////////////////////////////////////////////////////////////////////////////
///// skill.h
void SkillLevel::serialize(JsonOut &json) const
{
json.start_object();
json.member("level", level() );
json.member("exercise", exercise(true) );
json.member("istraining", isTraining() );
json.member("lastpracticed", int ( lastPracticed() ) );
json.end_object();
}
void DestinNetworkAlt::init(SupportedImageWidths width, unsigned int layers,
unsigned int centroid_counts [], bool isUniform,
int extRatio, unsigned int layer_widths[]){
callback = NULL;
initTemperatures(layers, centroid_counts);
DestinConfig *dc = CreateDefaultConfig(layers);
dc->addCoeff = 0; // disabled addition of centroids
dc->beta = 0.01;
std::copy(centroid_counts, centroid_counts + layers, dc->centroids); // initial number of centroids
dc->extRatio = extRatio;
dc->freqCoeff = 0.05;
dc->freqTreshold = 0; // disabled deletion of centroids
dc->gamma = gamma;
dc->isUniform = isUniform;
dc->lambdaCoeff = lambdaCoeff;
std::copy(centroid_counts, centroid_counts + layers, dc->layerMaxNb); // max number of centroids
if(layer_widths != NULL){ // provide support for non standard heirarchy
std::copy(layer_widths, layer_widths + layers, dc->layerWidths);
}
if(width % dc->layerWidths[0] == 0){
int ratio = width / dc->layerWidths[0];
dc->inputDim = ratio * ratio;
} else {
DestroyConfig(dc);
throw std::runtime_error("Input image width must be evenly divisible by the bottom layer width.");
}
dc->nClasses = 0;
dc->nMovements = 0; //this class does not use movements
dc->starvCoeff = 0.05;
std::copy(temperatures, temperatures + layers, dc->temperatures);
destin = InitDestinWithConfig(dc);
destin->rindex=0;
if(destin == NULL){
throw std::runtime_error("Could not create the destin structure. Perhaps the given layer widths is not supported.");
}
DestroyConfig(dc);
setBeliefTransform(DST_BT_NONE);
ClearBeliefs(destin);
SetLearningStrat(destin, CLS_FIXED);
destin->fixedLearnRate = 0.1;
isTraining(true);
}