RsBundle  Diff

/// Information about a minorant.
#[derive(Debug, Clone)]
struct MinorantInfo<Pr> {
    /// The minorant's index in the master problem
    index: usize,
    /// Current multiplier.
    multiplier: Real,
    /// Primal associated with this minorant.
    primal: Option<Pr>,
}

/**
 * Implementation of a bundle method.
 */

            self.show_info(term);
            if term == Step::Term {
                break;
            }
        }
        Ok(())
    }

    /// Return the current aggregated primal information for a subproblem.
    ///
    /// This function returns all currently used minorants $x_i$ along
    /// with their coefficients $\alpha_i$. The aggregated primal can
    /// be computed by combining the minorants $\bar{x} =
    /// \sum_{i=1}\^m \alpha_i x_i$.
    pub fn aggregated_primals(&mut self, subproblem : usize) -> Pr {
        let (coeffs, primals) : (Vec<_>, Vec<_>) = self.minorants[subproblem].iter().map(|m| {
            (m.multiplier, m.primal.as_ref().unwrap())
        }).unzip();
        self.problem.aggregate_primals(&coeffs, &primals)
    }

    fn show_info(&self, step: Step) {
        let time = self.start_time.elapsed();
        info!("{} {:0>2}:{:0>2}:{:0>2}.{:0>2} {:4} {:4} {:4}{:1}  {:9.4} {:9.4} {:12.6e}({:12.6e}) {:12.6e}",
              if step == Step::Term { "_endit" } else { "endit " },
              time.as_secs() / 3600,
              (time.as_secs() / 60) % 60,

            let mut minorants = result.into_iter();
            if let Some((minorant, primal)) = minorants.next() {
                self.cur_mods[i] = minorant.constant;
                self.cur_mod += self.cur_mods[i];
                self.minorants[i].push(MinorantInfo {
                    index: try!(self.master.add_minorant(i, minorant)),
                    multiplier: 0.0,
                    primal: Some(primal),
                });
            } else {
                return Err(Error::NoMinorant);
            }
        }

        Ok(())
    }


    /// Reduce size of bundle.
    fn compress_bundle(&mut self) -> Result<()> {
        for i in 0..self.problem.num_subproblems() {
            // update multiplier from master solution

            for m in self.minorants[i].iter_mut() {
                m.multiplier = self.master.multiplier(m.index);
            }
            let n = self.master.num_minorants(i);
            if n >= self.params.max_bundle_size {
                // aggregate minorants with smallest coefficients
                self.minorants[i].sort_by_key(|m| -((1e6 * m.multiplier) as isize));
                let aggr = self.minorants[i].split_off(self.params.max_bundle_size-2);
                let aggr_sum = aggr.iter().map(|m| m.multiplier).sum();
                let (aggr_mins, aggr_primals) : (Vec<_>, Vec<_>) = aggr.iter().map(|m| {
                    (m.index, m.primal.as_ref().unwrap())
                }).unzip();
                let (aggr_min, aggr_coeffs) = try!(self.master.aggregate(i, &aggr_mins));
                // append aggregated minorant
                self.minorants[i].push(MinorantInfo{
                    index: aggr_min,
                    multiplier: aggr_sum,
                    primal: Some(self.problem.aggregate_primals(&aggr_coeffs, &aggr_primals)),
                });
            }
        }
        Ok(())
    }

    /// Perform a descent step.

            self.nxt_vals[fidx] = fun_ub;

            // move center of minorant to cur_y
            nxt_minorant.move_center(-1.0, &self.nxt_d);
            self.new_cutval += nxt_minorant.constant;
            self.minorants[fidx].push(MinorantInfo{
                index: try!(self.master.add_minorant(fidx, nxt_minorant)),
                multiplier: 0.0,
                primal: Some(nxt_primal),
            });
        }

        if self.new_cutval > self.cur_val + 1e-3 {
            warn!("New minorant has higher value in center new:{} old:{}", self.new_cutval, self.cur_val);
            self.cur_val = self.new_cutval;