use super::PRECISION;
use super::lp::{Outcome, Row, Sense};
use super::model::Goal;
use super::problem::{Evaluator, Point};

// ---------------------------------------------------------------- nonlinear

/// Augmented-Lagrangian value of a point: objective `phi` plus the constraint terms.
fn aug(phi: f64, cons: &[f64], senses: &[Sense], lam: &[f64], mu: f64) -> f64 {
    let mut v = phi;
    for ((c, s), l) in cons.iter().zip(senses).zip(lam) {
        v += match s {
            Sense::Eq => l * c + 0.5 * mu * c * c,
            _ => {
                let t = (l + mu * c).max(0.0);
                (t * t - l * l) / (2.0 * mu)
            }
        };
    }
    v
}

/// Constraint values in the `≤ 0` / `= 0` form, and the objective to minimise.
pub(super) fn shape(p: &Point, rows: &[Row], goal: Goal) -> (f64, Vec<f64>) {
    let phi = match goal {
        Goal::Max => -p.f,
        Goal::Min => p.f,
        Goal::Value(v) => (p.f - v) * (p.f - v),
    };
    let cons = p.g.iter().zip(rows).map(|(g, r)| if r.sense == Sense::Ge { -g } else { *g }).collect();
    (phi, cons)
}

pub(super) fn violation(cons: &[f64], senses: &[Sense]) -> f64 {
    cons.iter().zip(senses).map(|(c, s)| if *s == Sense::Eq { c.abs() } else { c.max(0.0) }).fold(0.0, f64::max)
}

pub(super) fn project(x: &mut [f64], lo: &[f64], hi: &[f64]) {
    for ((v, l), h) in x.iter_mut().zip(lo).zip(hi) {
        if *v < *l {
            *v = *l;
        }
        if *v > *h {
            *v = *h;
        }
    }
}

/// Local minimisation of the model within bounds `lo..hi` from `x0`.
pub(super) fn nlp(ev: &mut Evaluator, x0: &[f64], lo: &[f64], hi: &[f64], goal: Goal) -> Outcome {
    let n = x0.len();
    let rows = ev.rows.clone();
    let senses: Vec<Sense> = rows.iter().map(|r| r.sense).collect();
    let mut x = x0.to_vec();
    project(&mut x, lo, hi);
    let mut lam = vec![0.0; rows.len()];
    let mut mu = 10.0;
    let Some(p) = ev.eval(&x) else { return Outcome::Limit };
    let (mut phi, mut cons) = shape(&p, &rows, goal);
    if !phi.is_finite() {
        return Outcome::Infeasible;
    }
    let phi0 = phi;
    let mut prev_viol = violation(&cons, &senses);
    let mut converged = false;
    let mut out_of_budget = false;
    let mut carried: Option<f64> = None;
    for _outer in 0..40 {
        // Inner: projected gradient on the augmented Lagrangian.
        let lval = |phi: f64, cons: &[f64], lam: &[f64], mu: f64| aug(phi, cons, &senses, lam, mu);
        let grad = |ev: &mut Evaluator, x: &[f64], lam: &[f64], mu: f64| -> Option<Vec<f64>> {
            let mut gr = vec![0.0; n];
            for j in 0..n {
                let xj = x.get(j).copied().unwrap_or(0.0);
                let h = 1e-6 * xj.abs().max(1.0);
                let (l, u) = (lo.get(j).copied().unwrap_or(f64::NEG_INFINITY), hi.get(j).copied().unwrap_or(f64::INFINITY));
                let (a, b) = (if xj - h >= l { xj - h } else { xj }, if xj + h <= u { xj + h } else { xj });
                if b <= a {
                    continue;
                }
                let mut xa = x.to_vec();
                let mut xb = x.to_vec();
                if let Some(v) = xa.get_mut(j) {
                    *v = a;
                }
                if let Some(v) = xb.get_mut(j) {
                    *v = b;
                }
                let (pa, ca) = shape(&ev.eval(&xa)?, &rows, goal);
                let (pb, cb) = shape(&ev.eval(&xb)?, &rows, goal);
                let d = (lval(pb, &cb, lam, mu) - lval(pa, &ca, lam, mu)) / (b - a);
                if let Some(v) = gr.get_mut(j) {
                    *v = if d.is_finite() { d } else { 0.0 };
                }
            }
            Some(gr)
        };
        let mut l_cur = lval(phi, &cons, &lam, mu);
        let Some(mut g) = grad(ev, &x, &lam, mu) else {
            out_of_budget = true;
            break;
        };
        // The step length carries over between outer iterations once known.
        let gnorm = g.iter().map(|v| v.abs()).fold(0.0, f64::max);
        let mut alpha = carried.unwrap_or(if gnorm > 0.0 { 1.0 / gnorm } else { 1.0 });
        let mut inner_done = false;
        let mut quiet = 0;
        for _inner in 0..500 {
            let mut accepted = None;
            let mut a = alpha;
            for _ in 0..40 {
                let mut xn: Vec<f64> = x.iter().zip(&g).map(|(v, d)| v - a * d).collect();
                project(&mut xn, lo, hi);
                let Some(pn) = ev.eval(&xn) else { break };
                let (phn, cn) = shape(&pn, &rows, goal);
                let ln = lval(phn, &cn, &lam, mu);
                let decrease: f64 = g.iter().zip(x.iter().zip(&xn)).map(|(d, (u, v))| d * (u - v)).sum();
                if ln.is_finite() && ln <= l_cur - 1e-4 * decrease {
                    accepted = Some((xn, phn, cn, ln));
                    break;
                }
                a *= 0.25;
            }
            if ev.exhausted() {
                out_of_budget = true;
            }
            let Some((xn, phn, cn, ln)) = accepted else {
                inner_done = true;
                break;
            };
            // Variables or objective running off towards infinity: unbounded.
            if phn.abs() > 1e15 * (1.0 + phi0.abs()) || xn.iter().zip(x0).any(|(v, s)| v.abs() > 1e15 * (1.0 + s.abs())) {
                return Outcome::Unbounded;
            }
            let s: Vec<f64> = xn.iter().zip(&x).map(|(a, b)| a - b).collect();
            let step = s.iter().map(|v| v.abs()).fold(0.0, f64::max);
            let xmax = xn.iter().map(|v| v.abs()).fold(1.0, f64::max);
            let small = step <= 1e-10 * xmax || (l_cur - ln).abs() <= 1e-13 * (1.0 + l_cur.abs());
            quiet = if small { quiet + 1 } else { 0 };
            x = xn;
            phi = phn;
            cons = cn;
            l_cur = ln;
            if quiet >= 3 {
                inner_done = true;
                break;
            }
            let Some(gn) = grad(ev, &x, &lam, mu) else {
                out_of_budget = true;
                break;
            };
            // Barzilai–Borwein step.
            let yv: Vec<f64> = gn.iter().zip(&g).map(|(a, b)| a - b).collect();
            let sy: f64 = s.iter().zip(&yv).map(|(a, b)| a * b).sum();
            let ss: f64 = s.iter().map(|v| v * v).sum();
            alpha = if sy > 0.0 { (ss / sy).clamp(1e-12, 1e12) } else { (a * 4.0).min(1e12) };
            g = gn;
            if g.iter().all(|v| *v == 0.0) {
                inner_done = true;
                break;
            }
        }
        carried = Some(alpha);
        if out_of_budget {
            break;
        }
        let viol = violation(&cons, &senses);
        let scale = rows.iter().map(|r| r.rhs_const.abs()).fold(1.0, f64::max);
        if viol <= PRECISION * scale && inner_done {
            converged = true;
            if rows.is_empty() {
                break;
            }
        }
        // Multiplier and penalty updates.
        for ((l, c), s) in lam.iter_mut().zip(&cons).zip(&senses) {
            *l = match s {
                Sense::Eq => *l + mu * c,
                _ => (*l + mu * c).max(0.0),
            };
        }
        if viol > 0.25 * prev_viol {
            mu = (mu * 10.0).min(1e10);
        }
        if converged && viol <= PRECISION * scale * 1e-2 {
            break;
        }
        prev_viol = viol;
        converged = false;
    }
    let viol = violation(&cons, &senses);
    let scale = rows.iter().map(|r| r.rhs_const.abs()).fold(1.0, f64::max);
    if viol > PRECISION * scale * 10.0 {
        return if out_of_budget { Outcome::Limit } else { Outcome::Infeasible };
    }
    Outcome::Solved(x, phi, (converged || viol <= PRECISION * scale) && !out_of_budget)
}