// constructive heuristics for orthogonal representation OR
void LongestPathCompaction::constructiveHeuristics(
PlanRep &PG,
OrthoRep &OR,
const RoutingChannel<int> &rc,
GridLayoutMapped &drawing)
{
OGDF_ASSERT(OR.isOrientated());
// x-coordinates of vertical segments
CompactionConstraintGraph<int> Dx(OR, PG, odEast, rc.separation());
Dx.insertVertexSizeArcs(PG, drawing.width(), rc);
NodeArray<int> xDx(Dx.getGraph(), 0);
computeCoords(Dx, xDx);
// y-coordinates of horizontal segments
CompactionConstraintGraph<int> Dy(OR, PG, odNorth, rc.separation());
Dy.insertVertexSizeArcs(PG, drawing.height(), rc);
NodeArray<int> yDy(Dy.getGraph(), 0);
computeCoords(Dy, yDy);
// final coordinates of vertices
for(node v : PG.nodes) {
drawing.x(v) = xDx[Dx.pathNodeOf(v)];
drawing.y(v) = yDy[Dy.pathNodeOf(v)];
}
}
// improvement heuristics for orthogonal drawing
void LongestPathCompaction::improvementHeuristics(
PlanRep &PG,
OrthoRep &OR,
const RoutingChannel<int> &rc,
GridLayoutMapped &drawing)
{
OGDF_ASSERT(OR.isOrientated());
int costs, lastCosts;
int steps = 0, maxSteps = m_maxImprovementSteps;
if (maxSteps == 0) maxSteps = numeric_limits<int>::max();
// OPTIMIZATION POTENTIAL:
// update constraint graphs "incrementally" by only re-inserting
// visibility arcs
costs = 0;
do {
lastCosts = costs;
++steps;
// x-coordinates of vertical segments
CompactionConstraintGraph<int> Dx(OR, PG, odEast, rc.separation());
Dx.insertVertexSizeArcs(PG, drawing.width(), rc);
Dx.insertVisibilityArcs(PG, drawing.x(),drawing.y());
NodeArray<int> xDx(Dx.getGraph(), 0);
computeCoords(Dx, xDx);
// final x-coordinates of vertices
for(node v : PG.nodes) {
drawing.x(v) = xDx[Dx.pathNodeOf(v)];
}
// y-coordinates of horizontal segments
CompactionConstraintGraph<int> Dy(OR, PG, odNorth, rc.separation());
Dy.insertVertexSizeArcs(PG, drawing.height(), rc);
Dy.insertVisibilityArcs(PG, drawing.y(),drawing.x());
NodeArray<int> yDy(Dy.getGraph(), 0);
computeCoords(Dy, yDy);
// final y-coordinates of vertices
for(node v : PG.nodes) {
drawing.y(v) = yDy[Dy.pathNodeOf(v)];
}
costs = Dx.computeTotalCosts(xDx) + Dy.computeTotalCosts(yDy);
} while (steps < maxSteps && (steps == 1 || costs < lastCosts));
}
//[[Rcpp::export]]
mat one_pred_gp_gdp(mat X, vec y, mat param_row) {
vec param = vectorise(param_row);
double s2 = param[0];
double phi = param[1];
double tau = param[2];
vec d = param.tail(param.size()-3);
int n = X.n_rows;
mat XdX = xDx(X,d % d);
mat K = tau * exp(-phi*XdX);
mat Xt = X.t();
mat I = eye(n,n);
mat S_i = (K.i() + I / s2).i();
vec mu = S_i*y / s2;
vec pred_y = mvrnorm(mu,S_i);
return reshape(pred_y,1,n);
}
double log_like_plus_log_prior(vec y, mat X, vec param, mat I, vec priors) {
double ls2 = param[0];
double w = param[1];
double ltau = param[2];
vec d_vec = param.tail( param.size()-3 );
vec d2 = d_vec % d_vec;
mat D_mat = xDx(X,d2); // ORIGINAL and best so far
//mat D_mat = xDx(X,d2/sum(d2));
double a_s2 = priors[0];//2;
double b_s2 = priors[1];//5;
double a_phi = priors[2];//0;
double b_phi = priors[3];//5;
double a_tau = priors[4];//2;
double b_tau = priors[5];//5;
double a_d = priors[6]; //1;
double b_d = priors[7]; //1;
double s2 = exp(ls2);
double phi = (b_phi*exp(w) + a_phi) / (exp(w)+1); // inverse logit
double tau = exp(ltau);
mat K = tau * exp(-phi*D_mat);
double ldet_K,sign;
mat s2I_plus_K = s2*I + K;
log_det(ldet_K, sign, s2I_plus_K);
double sum_log_dj_prior = sum( (-b_d-1) * log(1+abs(d_vec) / (a_d * b_d)) );
double log_prior = ( w-2*log(exp(w)+1) ) - a_s2*ls2 - b_s2/s2 - a_tau*ltau - b_tau/tau + sum_log_dj_prior;
double log_like = (-.5 * ldet_K - .5 * y.t() * s2I_plus_K.i() * y)[0];
return log_like + log_prior;
}
