RsBundle  Diff

    cnt_updates: usize,
    nxt_ubs: Vec<Real>,
    cnt_remaining_ubs: usize,
    nxt_cutvals: Vec<Real>,
    cnt_remaining_mins: usize,
    nxt_d: Arc<DVector>,
    nxt_y: Arc<DVector>,
    /// True if the problem has been updated after the last evaluation.
    updated: bool,
}

impl IterData {
    fn new(num_subproblems: usize, num_variables: usize, max_iter: usize) -> Self {
        IterData {
            max_iter,
            cnt_iter: 0,
            cnt_updates: 0,
            nxt_ubs: vec![Real::infinity(); num_subproblems],
            cnt_remaining_ubs: num_subproblems,
            nxt_cutvals: vec![-Real::infinity(); num_subproblems],
            cnt_remaining_mins: num_subproblems,
            nxt_d: Arc::new(dvec![0.0; num_variables]),
            nxt_y: Arc::new(dvec![]),
            updated: true,
        }
    }
}

/// Data providing access for updating the problem.
struct UpdateData<'a, P, M>
where

        debug!("Step");
        debug!("  cur_val    ={}", self.data.cur_val);
        debug!("  nxt_mod    ={}", self.data.nxt_mod);
        debug!("  nxt_ub     ={}", nxt_ub);
        debug!("  descent_bnd={}", descent_bnd);

        itdata.updated = false;
        let step;
        if self.data.cur_val.is_infinite() {
            // This is the first evaluation. We effectively get
            // the function value at the current center but
            // we do not have a model estimate yet. Hence, we do not know
            // a good guess for the weight.
            step = Step::Descent;
            self.data.cur_val = nxt_ub;
            self.data.cur_weight = Real::infinity();
            master.set_weight(1.0)?;

            itdata.updated = true;

            debug!("First Step");
            debug!("  cur_val={}", self.data.cur_val);
            debug!("  cur_y={}", self.data.cur_y);
        } else if nxt_ub <= descent_bnd {
            step = Step::Descent;
            self.cnt_descent += 1;




            // Note that we must update the weight *before* we
            // change the internal data, so the old information
            // that caused the descent step is still available.
            self.data.cur_weight = self.weighter.descent_weight(&self.data);
            self.data.cur_y = itdata.nxt_y.as_ref().clone();
            self.data.cur_val = nxt_ub;

            step,
            &self.data,
            self.cnt_descent,
            self.cnt_null,
            itdata.cnt_updates,
        );
        itdata.cnt_iter += 1;

        // Update problem.
        if Self::update_problem(&mut self.problem, Step::Descent, &mut self.data, itdata, master)? {
            itdata.updated = true;
        }

        // Compute the new candidate. The main loop will wait for the result of
        // this solution process of the master problem.
        master.solve(self.data.cur_val)?;

        Ok(itdata.cnt_iter >= itdata.max_iter)
    }

        if self.data.cur_weight.is_infinite() {
            self.data.cur_weight = self.weighter.initial_weight(&self.data);
            master.set_weight(self.data.cur_weight)?;
            master.solve(self.data.cur_val)?;
            return Ok(false);
        }

        if self.terminator.terminate(&self.data) && !itdata.updated {
            Self::show_info(
                &self.start_time,
                Step::Term,
                &self.data,
                self.cnt_descent,
                self.cnt_null,
                itdata.cnt_updates,

    fn update_problem(
        problem: &mut P,
        step: Step,
        data: &mut SolverData,
        itdata: &mut IterData,
        master_proc: &mut MasterProcess<P, M::MasterProblem>,
    ) -> Result<bool, Error<P::Err>> {
        let (update_tx, update_rx) = channel();
        problem
            .update(
                &UpdateData {
                    cur_y: &data.cur_y,
                    nxt_y: &itdata.nxt_y,
                    step: step,
                    master_proc: master_proc,
                },
                itdata.cnt_iter,
                update_tx,
            )
            .map_err(Error::Update)?;

        let mut have_update = false;
        for update in update_rx {
            let update = update.map_err(Error::Update)?;
            have_update = true;
            match update {
                Update::AddVariables { bounds, sgext, .. } => {
                    let mut newvars = Vec::with_capacity(bounds.len());
                    for (lower, upper) in bounds {
                        if lower > upper {
                            return Err(Error::InvalidBounds { lower, upper });
                        }

                        master_proc.add_vars(newvars.iter().map(|v| (v.0, v.1, v.2)).collect(), sgext)?;
                    }
                }
            }
        }

        Ok(have_update)
    }

    /// Return the bound the function value must be below of to enforce a descent step.
    ///
    /// If the oracle guarantees that $f(\bar{y}) \le$ this bound, the
    /// bundle method will perform a descent step.
    ///