huancun::huancun(QObject *parent) :
QObject(parent)
{
U_A = "Mozilla/5.0 (Windows NT 6.1; WOW64; Trident/7.0; rv:11.0) like Gecko (bigrats web browser 0.4.7.9r)";
manager=new QNetworkAccessManager;
jar =new QNetworkCookieJar;
manager->setCookieJar(jar);
reply=NULL;
dlmg=new downloadmg;
connect(dlmg,SIGNAL(stoped()),this,SIGNAL(stoped()));
connect(dlmg,SIGNAL(finished()),this,SIGNAL(finished()));
connect(dlmg,SIGNAL(onefinished(QString&)),this,SIGNAL(onefinished(QString&)));
connect(dlmg,SIGNAL(progress(int)),this,SIGNAL(progress(int)));
connect(dlmg,SIGNAL(error()),this,SIGNAL(error()));
num=-1;
goon=0;//永远是0
all=0;
urls="";
playrf="";
name="noname";
format="normal";//默认优先清晰度
getfiletype=0;
downloading=false;
isstop=false;
}
void ILoopController::stop() {
if (loop_) {
loop_->stop();
}
stoped();
}
void Executer::cleanUp() {
delete engine;
engine = nullptr;
delete wthread;
wthread = nullptr;
emit(stoped());
}
void World::init() {
qsrand(QDateTime::currentDateTime().toTime_t());
b2Vec2 gravity(0.0, GRAVITY);
b2world = new b2World(gravity);
b2world->SetContinuousPhysics(true);
b2world->SetAutoClearForces(true);
contactListener = new ContactListener(this);
b2world->SetContactListener(contactListener);
track = new Track(b2world);
car = new Car(algorithm, b2world);
connect(car, SIGNAL(stoped()), SLOT(carStoped()));
emit creteNewCar();
qsrand(car->getBody()->GetMass());
}
Widget::Widget(QWidget *parent) :
QWidget(parent),
ui(new Ui::Widget)
{
ui->setupUi(this);
//rtsp://:8554/192.168.66.108
//rtsp://video.fjtu.com.cn/vs01/flws/flws_01.rm
//udp://:1234/192.168.16.228
//http://:8080/192.168.16.228
rtsp = new RtspThread(this);
connect(ui->openBtn,SIGNAL(clicked(bool)),this,SLOT(showVideo()));
connect(rtsp,SIGNAL(stoped()),this,SLOT(showVideo()));
}
/**
* Sets given model to edit widget.
*/
void LearningWidget::setModel(LearningConfigModel* model){
this->model = model;
//disables certain parts of GUI
ui->startBtn->setDisabled(true);
ui->stopBtn->setDisabled(true);
ui->resetButton->setDisabled(true);
npw->setDisabled(true);
//clears widget when NULL pointer given
if(model == NULL){
ui->itemName->setText(QString());
setPlot(NULL);
}
//fills view with model data
else{
//backups saved flag state
bool saved = model->isSaved();
//sets model values to GUI items
ui->itemName->setText(model->name());
ui->maxErrBox->setValue(model->maxErr());
ui->maxIterBox->setValue(model->maxIter());
ui->lrnCoefBox->setValue(model->lrnCoef());
ui->maxTimeBox->setValue(model->maxTime());
//generates and selects
genNetworkList();
//sets plot to show in layout
setPlot(model->plot());
//connects signals of model
connect(model, SIGNAL(update(int,long,double)), this, SLOT(updateLearning(int,long,double)), Qt::UniqueConnection);
connect(model, SIGNAL(stoped()), this, SLOT(learningStoped()), Qt::UniqueConnection);
connect(model, SIGNAL(changed(ChangeType)), this, SLOT(modelChanged(ChangeType)), Qt::UniqueConnection);
//restores saved flag state
model->setSaved(saved);
//fills or clears table when table view selected
if(ui->tableBtn->isChecked()) fillTable();
}
}
void Stopwatch::clientMessage(QJsonObject msg, int id)
{
if(msg.contains("start")){
start(false);
emit started();
sendMsgButNotTo(msg,id,true);
}
if(msg.contains("stop")){
stop(false);
emit stoped();
sendMsgButNotTo(msg,id,true);
}
if(msg.contains("resume")){
resume(false);
emit resumed();
sendMsgButNotTo(msg,id,true);
}
if(msg.contains("set")){
setTo((long)msg.value("set").toDouble(),false);
emit timeSet();
sendMsgButNotTo(msg,id,true);
}
}
void NotifyTimer::stop() {
emit stoped();
QTimer::stop();
}
void BpAlgSt::start(){
Q_ASSERT(net != NULL);
Q_ASSERT(data != NULL);
emit started();
//value initialization
running = true;
actIter = 1;
actTime = 0;
timer.restart();
double sumErr = 0;
for(int i = 0; i < data->minPatternCount(); i++){
output = net->layerOutput(data->inputVector(i));
sumErr += calcError(i);
}
actError = sumErr;
emit update(0, actTime, actError);
//learning main cycle
while(running){
for(int i = 0; i < data->minPatternCount(); i++){
//feedforward
output = net->layerOutput(data->inputVector(i));
//output layer delta calculation
calcOutputDelta(i);
//inner layer delta calculation
calcInnerDelta();
//weight adjustment
adjustWeight();
}
//current time
actTime = timer.elapsed();
//output error calculation
double sumErr = 0;
for(int i = 0; i < data->minPatternCount(); i++){
output = net->layerOutput(data->inputVector(i));
sumErr += calcError(i);
}
actError = sumErr;
//emits update signal once per each update interval
if(actIter % updateInterv == 0){
emit update(actIter, actTime, actError);
}
//stop conditions
if(actTime >= stopTimeVal) break;
if(actIter >= stopIter) break;
if(actError <= stopErrorVal) break;
actIter++;
}
//running flag to false
running = false;
//signal that tells that learning is finished
emit stoped();
}