//
//Saving the Neural network to an xml file
//
void NN_File::saveToFile(const std::string & fileName)
{
TiXmlDocument doc;
TiXmlElement * pRoot = new TiXmlElement("neuralnetwork");
doc.LinkEndChild(pRoot);
addStructure(pRoot);
addWeights(pRoot);
doc.SaveFile(fileName);
}
bool TestModel::execute(bool inThread)
{
Log(lDebug)<<"Executing the TestModel plugin by Totte Karlsson";
RoadRunner rr;
rr.load(mModel);
rr::SimulateOptions opt;
opt.start = 0;
opt.duration = 10;
opt.steps = 14;
TelluriumData data(rr.simulate(&opt));
mTestData.setValue(data);
//Add noise
const PluginManager* PM = this->getPluginManager();
Plugin* noise = PM->getPlugin("AddNoise");
if(!noise)
{
stringstream msg;
msg<<"The TestModel plugin dependes on the AddNoise plugin, which is not yet loaded.";
throw(Exception(msg.str()));
}
mTestDataWithNoise.setValue(mTestData.getValue());
noise->setPropertyValue("Sigma", mSigma.getValueHandle());
noise->setPropertyValue("InputData", mTestDataWithNoise.getValueHandle());
noise->execute();
mTestDataWithNoise.setValue(noise->getPropertyValueHandle("InputData"));
//Add weights
addWeights();
return true;
}
//--------------------------------------------------------------
void ofxFatLine::add(const vector<ofVec3f> &thePoints, const vector<ofFloatColor> &theColors, const vector<double> &theWeights){
addVertices(thePoints);
addColors(theColors);
addWeights(theWeights);
update();
}
