Rect ScrollBar::GetPartRect(int p) const {
Rect h = Slider();
int sbo = style->overthumb;
int off = GetHV(h.left, h.top);
int ts = thumbsize;
if(ts < style->thumbmin)
ts = 0;
switch(p) {
case 0:
HV(h.right, h.bottom) = thumbpos - sbo + ts / 2 + off;
break;
case 1:
HV(h.left, h.top) = thumbpos + ts / 2 + sbo + off;
break;
case 2:
HV(h.left, h.top) = thumbpos - sbo + off;
HV(h.right, h.bottom) = thumbpos + ts + sbo + off;
break;
}
return h;
}
IGL_INLINE void igl::project(
const Eigen::MatrixBase<DerivedV>& V,
const Eigen::MatrixBase<DerivedM>& model,
const Eigen::MatrixBase<DerivedN>& proj,
const Eigen::MatrixBase<DerivedO>& viewport,
Eigen::PlainObjectBase<DerivedP> & P)
{
typedef typename DerivedP::Scalar PScalar;
Eigen::Matrix<PScalar,DerivedV::RowsAtCompileTime,4> HV(V.rows(),4);
HV.leftCols(3) = V.template cast<PScalar>();
HV.col(3).setConstant(1);
HV = (HV*model.template cast<PScalar>().transpose()*
proj.template cast<PScalar>().transpose()).eval();
HV = (HV.array().colwise()/HV.col(3).array()).eval();
HV = (HV.array() * 0.5 + 0.5).eval();
HV.col(0) = (HV.array().col(0) * viewport(2) + viewport(0)).eval();
HV.col(1) = (HV.array().col(1) * viewport(3) + viewport(1)).eval();
P = HV.leftCols(3);
}
double Controller::update(Angle angle, double speed, double inReward, vec inLmr, int color) {
if(t%inv_sampling_rate == 0 && !SILENT){
pi_array = join_rows(pi_array, pin->get_output());
if(gvlearn_on){
gv_array = join_rows(gv_array, gvl->w(0));
}
if(lvlearn_on){
for(int i = 0; i < lv_array.size(); i++)
lv_array.at(i) = join_rows(lv_array.at(i), lvl->w(i));
ref_array = join_rows(ref_array, lvl->RefPI());
}
}
t++;
/*** Check, if inward ***/
if(t > t_home || accum_reward(0) > 1.){
inward = 1.;
//printf("t= %u > %u or sum(R)= %g\n", t, t_home, accum_reward(0));
}
/*** Path Integration Mechanism ***/
if(pin_on)
pin->update(angle, speed);
if(gvlearn_on && gl_w > 0.)
pi_w = HV().len() * (1. - expl_factor(0))*(1.-accu(lv_value));
else
pi_w = 0.0;
pi_m = ((HV().ang()).i() - angle).S(); //NEW PI COMMAND
if(homing_on && inward!=0.){
//printf("this should not be! %g\n", inward);
pi_w = 0.5;
pi_m = ((HV().ang()).i() - angle).S();
rand_m = 0.0;//0.25;
}
if(pi_w < 0.)
pi_w = 0.;
output_hv = pi_w * pi_m;
/*** Reward and value update ***/
if(lvlearn_on){
for(int i = 0; i < num_lv_units; i++)
lv_value(i) = 1. - exp(-0.5*lvl->eligibility_value(i));
}
delta_beta = mu_beta*((1./expl_beta) + lambda * value(0) * expl_factor(0));
if(beta_on)
expl_beta += delta_beta;
if(expl_factor(0) < 0.0001 && delta_beta < 0.01)
beta_on = false;
for(int i = 0; i < num_colors; i++){
if(i == color){
reward(i) = inReward;
if(inward==0.){
value(i) = (reward(i) /*+ accu(lv_value)*/) + disc_factor * value(i);
if(!const_expl)
expl_factor(i) = exp(- expl_beta * value(i));
else
expl_factor(i) += d_expl_factor(i);
expl_factor.elem( find(expl_factor > 1.) ).ones(); //clip expl
expl_factor.elem( find(expl_factor < 0.) ).zeros(); //clip expl
}
}
else{
reward(i) = 0.0;
}
}
accum_reward += reward;
/*** Global Vector Learning Circuits TODO ***/
if(gvlearn_on){
for(int i = 0; i < num_colors; i++){
gvl->update(pin->get_output(), reward(i), expl_factor(i));
cGV.at(i) = (GV(i) - HV());
}
gl_w = (1. - inward)*GV(0).len() * (1.-expl_factor(0));
gl_m = (GV(0).ang() - angle).S(); //NEW GV COMMAND
}
//stream << cGV.at(0).ang().deg() << endl;
output_gv = gl_w * gl_m;
/*** Local Vector Learning Circuits TODO ***/
if(lvlearn_on){
lvl->update(angle, speed, inReward, inLmr);
rl_m = 0.0;
rl_w = (1. - inward);
for(int i = 0; i < num_lv_units; i++){
//cLV.at(i) = (LV(i) - HV());
if(inward == 0.){
gl_w = 0.0;
pi_w = 0.0;
rl_m += lv_value(i) * (LV().len()*(LV().ang() - angle).S() + RV().len()*(RV().ang().i() - angle).S());
}
}
//if(VERBOSE && t%100==0)
//printf("t = %u\tHV = (%f, %f)\tLV = (%f, %f)\tRV = (%f, %f)\n", t, HV().ang().deg(), HV().len(), LV().ang().deg(), LV().len(), RV().ang().deg(), RV().len());
output_lv = rl_w * rl_m;
}
else
output_lv = 0.;
/*** Random foraging ***/
if(lvlearn_on){
rand_w = (1. - inward)*0.6*expl_factor(0)*(1.-accu(lv_value));
}
else
rand_w = (1. - inward)*0.6*expl_factor(0);
rand_m = randn(0.0, 1.);
if(inward == 1)
rand_m = 0.;
output_rand = rand_w * rand_m;
/*** Navigation Control Output ***/
output = output_rand + output_hv + output_gv + output_lv;
//output = output_rand + output_hv + 0.0 + output_lv; // Route formation
return output;
}
RequestParameters HVconfigEntry::params_to_insert() const{
return {to_string(HVPMConnection_id()),to_string(HV())};
}
