void Function::gradient(const IntervalVector& x, IntervalVector& g) const {
assert(g.size()==nb_var());
assert(x.size()==nb_var());
Gradient().gradient(*this,x,g);
// if (!df) ((Function*) this)->df=new Function(*this,DIFF);
// g=df->eval_vector(x);
}
void Function::jacobian(const IntervalVector& x, IntervalMatrix& J) const {
assert(J.nb_cols()==nb_var());
assert(x.size()==nb_var());
assert(J.nb_rows()==image_dim());
// calculate the gradient of each component of f
for (int i=0; i<image_dim(); i++) {
(*this)[i].gradient(x,J[i]);
}
}
void Function::jacobian(const IntervalVector& box, IntervalMatrix& J, const VarSet& set) const {
assert(J.nb_cols()==set.nb_var);
assert(box.size()==nb_var());
assert(J.nb_rows()==image_dim());
IntervalVector g(nb_var());
// calculate the gradient of each component of f
for (int i=0; i<image_dim(); i++) {
(*this)[i].gradient(box,g);
J.set_row(i,set.var_box(g));
}
}
void Function::hansen_matrix(const IntervalVector& box, IntervalMatrix& H) const {
int n=nb_var();
int m=expr().dim.vec_size();
assert(H.nb_cols()==n);
assert(box.size()==n);
assert(expr().dim.is_vector());
assert(H.nb_rows()==m);
IntervalVector x=box.mid();
IntervalMatrix J(m,n);
// test!
// int tab[box.size()];
// box.sort_indices(false,tab);
// int var;
for (int var=0; var<n; var++) {
//var=tab[i];
x[var]=box[var];
jacobian(x,J);
H.set_col(var,J.col(var));
}
}
void Function::hansen_matrix(const IntervalVector& box, IntervalMatrix& H, const VarSet& set) const {
int n=set.nb_var;
int m=image_dim();
assert(H.nb_cols()==n);
assert(box.size()==nb_var());
assert(H.nb_rows()==m);
IntervalVector var_box=set.var_box(box);
IntervalVector param_box=set.param_box(box);
IntervalVector x=var_box.mid();
IntervalMatrix J(m,n);
for (int var=0; var<n; var++) {
//var=tab[i];
x[var]=var_box[var];
jacobian(set.full_box(x,param_box),J,set);
H.set_col(var,J.col(var));
}
}
void Function::gradient(const IntervalVector& x, IntervalVector& g) const {
assert(g.size()==nb_var());
assert(x.size()==nb_var());
Gradient().gradient(*this,x,g);
}