void printLists (const list<int>& l1, const list<int>& l2)
{
cout << "list1: ";
copy (l1.cbegin(), l1.cend(), ostream_iterator<int>(cout," "));
cout << endl << "list2: ";
copy (l2.cbegin(), l2.cend(), ostream_iterator<int>(cout," "));
cout << endl << endl;
}
bool ProcessList::any_of_process_is_running(const list<wstring> & processes)
{
auto running_processes = get_processes();
return any_of(processes.cbegin(), processes.cend(),
[&](auto process) { return find(running_processes.cbegin(), running_processes.cend(), process) != running_processes.cend(); });
}
bool Person::isFriend(const Person &p) const
{
for (auto it = following.cbegin(); it != following.cend(); ++it) {
if (*it == p.follower)
return true;
}
return false;
}
void PCAKNN::train(const list<Interval> &intervals, const bool console_output) {
if (intervals.size() == 0) return;
projections.clear(); n = 0;
width = intervals.front().start->face.cols;
height = intervals.front().start->face.rows;
list<Interval>::const_iterator itr;
vector<Face>::const_iterator start, end;
//add the number of images from all intervals
for (itr = intervals.cbegin(); itr != intervals.cend(); itr++) {
n += itr->Length();
}
Mat pca_matrix(static_cast<int>(n), width*height, data_type);
int c = 0;
for (itr = intervals.cbegin(); itr != intervals.cend(); itr++) {
//for each image in the current interval
for (start = itr->start, end = itr->end; start != end; start++, ++c) {
if (console_output) printf("Preparing samples %d/%d\n", c + 1, n);
//insert current image into pca_matrix
Mat image_row = start->face.clone().reshape(1, 1);
Mat row_i = pca_matrix.row(c);
image_row.convertTo(row_i, data_type);//CV_64FC1 ?
Face f; f.name = start->name;
projections.push_back(f);//save the names for later
}
}
if (console_output) printf("TRAINING...\n");
//Perfrom principal component analysis on pca_matrix
PCA pca(pca_matrix, Mat(), CV_PCA_DATA_AS_ROW, pca_matrix.rows);
//extract mean/eigenvalues
mean = pca.mean.reshape(1, 1);
ev = pca.eigenvalues.clone();
transpose(pca.eigenvectors, w);
//project each face into subspace and save them with the name above for recognition
for (unsigned int i = 0; i<n; ++i) {
if (console_output) printf("Projecting %d/%d\n", i + 1, n);//project so subspace
projections[i].face = subspaceProject(w, mean, pca_matrix.row(i));
}
}
void RemoveDup(list< int >& lList)
{
cout << "Before : ";
copy(lList.cbegin(), lList.cend(), ostream_iterator< int >(cout, " "));
set< int > sSet;
for (list< int >::iterator it = lList.begin(); it != lList.end();)
{
auto rtn = sSet.insert(*it);
if (false == rtn.second)
{
lList.erase(it++);
}
else
++it;
}
cout << endl << "After : ";
copy(lList.cbegin(), lList.cend(), ostream_iterator< int >(cout, " "));
}
list<float> NRZ_L_Enc::encode(const list<bool>& in) {
list<float> output;
for(auto citer = in.cbegin(); citer != in.cend(); ++citer) {
if(*citer) {
output.push_back(-amplitude);
}
else {
output.push_back(amplitude);
}
}
return output;
}
void ode_solver::print_trace(ostream& out,
string const & key,
int const idx,
list<pair<interval, IVector>> const & trajectory) const {
out << "{" << endl;
out << "\t" << "\"key\": \"" << key << "\"," << endl;
out << "\t" << "\"mode\": \"" << m_mode << "\"," << endl;
out << "\t" << "\"step\": \"" << m_step << "\"," << endl;
out << "\t" << "\"values\": [" << endl;
if (!trajectory.empty()) {
auto iter = trajectory.cbegin();
print_datapoint(out, iter->first, iter->second[idx]);
for (++iter; iter != trajectory.cend(); iter++) {
out << ", " << endl;
print_datapoint(out, iter->first, iter->second[idx]);
}
out << endl;
}
out << "\t" << "]" << endl;
out << "}" << endl;
}
// copy of above function for list<>.
// todo: make this a templated function
bool basicEffect::bindWithShapes(list<basicShape *>& _shapes){
if(_shapes.size()==0) return false;
bool success = true;
for(auto _shape=_shapes.cbegin(); _shape!=_shapes.cend(); ++_shape){
if( *_shape == NULL ){
success = false;
continue;
}
// prevent adding the same shape several times
for(auto it=shapes.begin(); it!=shapes.end(); ++it){
if( *_shape == *it ) continue; // already exists
}
//shapes.push_back( *_shape );
shapes.insert(shapes.end(), *_shape);
}
updateBoundingBox();
return success;
}
void WriteJson::parse(const list<double> &values, const string &&type) {
parseContainers(values.cbegin(), values.cend(), type);
}
bool lessForCollection (const list<int>& l1, const list<int>& l2)
{
return lexicographical_compare
(l1.cbegin(), l1.cend(), // first range
l2.cbegin(), l2.cend()); // second range
}
void print_list(const list<int>& x) {
for (auto it = x.cbegin(); it != x.cend(); ++it)
std::cout << *it << " ";
std::cout << std::endl;
}
