void add_mtime(reclist& thisi, dvec& b, dvec& c, bool debug) {
if((b.size()==0) & (c.size()==0)) return;
double maxtime = thisi.back()->time();
double mintime = thisi.at(0)->time();
std::sort(b.begin(), b.end());
std::sort(c.begin(), c.end());
b.insert(b.end(), c.begin(), c.end() );
std::sort(b.begin(), b.end());
b.erase(unique(b.begin(), b.end()), b.end());
std::size_t i = 0;
bool dropmin = true;
bool dropmax = true;
// add mtimes from argument
for(i=0; i < b.size(); ++i) {
if(b.at(i) <= mintime) {
if(debug && dropmin) {
Rcpp::Rcout << "dropping mtimes <= min observation time" << std::endl;
dropmin = false;
}
continue;
}
if(b.at(i) >= maxtime) {
if(debug && dropmax) {
Rcpp::Rcout << "dropping mtimes >= to max observation time" << std::endl;
dropmax = false;
}
break;
}
rec_ptr obs = boost::make_shared<datarecord>(100,b[i],0,-100,0);
obs->output(false);
obs->from_data(false);
thisi.push_back(obs);
}
std::sort(thisi.begin(), thisi.end(), CompByTimePosRec);
}
void DNN::backPropSet(const dvec& input,const dvec& output)
{
unsigned int i;
feedForward(input);
unsigned int L = activations.size() - 1;
/*
* Start with the final layer
*/
std::vector<Matrix> d(L+1);
/*
* Copy contents
*/
Matrix out(output.size(),1);
for(i=0;i<output.size();++i) out(i,0) = output.at(i);
/*
* Final layer error
*/
Matrix DC = Matrix::apply(quad_dC_dA,activations.at(L),out);
d.at(L) = Matrix::had(DC,activations.at(L));
/*
* Backpropagate
*/
for(i=L;i>0;--i)
{
Matrix wd = weights.at(i-1).T() * d.at(i);
d.at(i-1) = Matrix::had( wd, activations.at(i-1) );
}
/*
* Calculate the gradient cost for this set
*/
for(i=L;i>0;--i)
{
bGradient.at(i-1) = bGradient.at(i-1) + d.at(i);
Matrix wg = d.at(i) * activations.at(i-1).T();
wGradient.at(i-1) = wGradient.at(i-1) + wg;
}
}
void DNN::feedForward(const dvec & inputs)
{
unsigned int layers = activations.size();
unsigned int i;
for(i=0;i<inputs.size();++i)
{
activations.at(0)(i,0) = sigmoid(inputs.at(i));
}
for(i=1;i<layers;++i)
{
activations.at(i) = (weights.at(i-1)*activations.at(i-1) + bias.at(i-1)).apply(sigmoid);
}
}