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#ifndef PROBLEM_HH
#define PROBLEM_HH
#include "glob.hh"
#include "list.hh"
#include "vray.hh"
#include "pcol.hh"
#include "matrix.hh"
/// helper struct for #Spacing_problem#
struct Colinfo {
const PCol *col;
bool fixed;
Real fixpos;
Colinfo();
void print() const;
Real minright()const { return col->width().max; }
Real minleft()const { return -col->width().min; }
};
/// spacing for one line.
class Spacing_problem {
svec<const Idealspacing*> ideals;
svec<Colinfo> cols;
/// the index of #c# in #cols#
int col_id(const PCol *c) const;
/// generate an (nonoptimal) solution
Vector find_initial_solution() const;
/// check if problem is too tight
bool check_feasible() const;
/// does #this# contain the column #w#?
bool contains(const PCol *w);
/// make the energy function
void make_matrices(Matrix &quad, Vector &lin,Real&) const;
/// generate the LP constraints
void make_constraints(Mixed_qp& lp) const;
public:
/// solve the spacing problem
svec<Real> solve() const;
/**
return the column positions, and the energy (last element)
*/
/// add a idealspacing to the problem.
void add_ideal(const Idealspacing *i);
/**
One pair of columns can have no, one or more idealspacings,
since they can be "summed" if the columns to which #i# refers are
not in this problem, the spacing is ignored.
*/
/// add a col to the problem
void add_column(const PCol *, bool fixed=false, Real fixpos=0.0);
/** columns have to be added left to right. The column contains
info on it's minimum width.
*/
bool check_constraints(Vector v) const;
Vector try_initial_solution() const;
void OK() const;
void print() const;
void print_ideal(const Idealspacing*)const;
};
/** the problem, given by the columns (which include constraints) and
intercolumn spacing. The problem is:
Generate a spacing which
\begin{itemize}
\item
Satisfies spacing constraints (notes can't be printed through each other)
\item
Looks good, ie tries to conform to an ideal spacing as much as possible.
\end{itemize}
This is converted by regarding idealspacing as "springs" attached
to columns. The equilibrium of one spring is the ideal
distance. The columns have a size, this imposes "hard" constraints
on the distances. This transforms the problem into a quadratic
programming problem with linear constraints.
The quality is given by the total potential energy in the
springs. The lower the energy, the better the configuration.
*/
#endif
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