//! MaxHS (Maximum Satisfiability using Hitting Sets) solver.
//!
//! MaxHS is a modern MaxSAT algorithm that uses implicit hitting sets.
//! It alternates between finding minimal correction sets (MCSes) and
//! computing minimum-cost hitting sets.
//!
//! **Note**: This is a simplified placeholder implementation. A full MaxHS
//! implementation requires sophisticated MCS extraction and hitting set computation.
//!
//! Reference: Z3's maxhs implementation and the MaxHS paper by Davies & Bacchus

use crate::maxsat::{MaxSatResult, SoftClause, SoftId, Weight};
use oxiz_sat::{Lit, Solver as SatSolver, SolverResult};
use rustc_hash::{FxHashMap, FxHashSet};
use thiserror::Error;

/// Errors from MaxHS
#[derive(Error, Debug)]
pub enum MaxHsError {
    /// SAT solver error
    #[error("SAT solver error: {0}")]
    SolverError(String),
    /// Hard constraints are unsatisfiable
    #[error("hard constraints unsatisfiable")]
    Unsatisfiable,
    /// Resource limit exceeded
    #[error("resource limit exceeded")]
    ResourceLimit,
}

/// Configuration for MaxHS solver
#[derive(Debug, Clone)]
pub struct MaxHsConfig {
    /// Maximum number of iterations
    pub max_iterations: u32,
    /// Use core extraction optimization
    pub use_cores: bool,
    /// Use preprocessing
    pub preprocess: bool,
}

impl Default for MaxHsConfig {
    fn default() -> Self {
        Self {
            max_iterations: 10000,
            use_cores: true,
            preprocess: true,
        }
    }
}

/// Statistics from MaxHS solving
#[derive(Debug, Clone, Default)]
pub struct MaxHsStats {
    /// Number of SAT solver calls
    pub sat_calls: u32,
    /// Number of minimal correction sets found
    pub mcses_found: u32,
    /// Number of hitting set computations
    pub hitting_sets: u32,
    /// Total number of soft clauses
    pub total_soft: u32,
}

/// Minimal Correction Set (MCS) - a minimal set of soft clauses to remove to make the formula SAT
#[derive(Debug, Clone)]
struct Mcs {
    /// Soft clause IDs in this MCS
    clauses: FxHashSet<SoftId>,
    /// Total weight of this MCS
    #[allow(dead_code)]
    weight: Weight,
}

/// MaxHS solver
pub struct MaxHsSolver {
    /// SAT solver for finding MCSes
    sat_solver: SatSolver,
    /// Hard clauses
    hard_clauses: Vec<Vec<Lit>>,
    /// Soft clauses
    soft_clauses: Vec<SoftClause>,
    /// Map from SoftId to index
    soft_map: FxHashMap<SoftId, usize>,
    /// Configuration
    config: MaxHsConfig,
    /// Statistics
    stats: MaxHsStats,
    /// Found MCSes
    mcses: Vec<Mcs>,
    /// Current best cost
    best_cost: Weight,
}

impl MaxHsSolver {
    /// Create a new MaxHS solver
    pub fn new() -> Self {
        Self::with_config(MaxHsConfig::default())
    }

    /// Create a new MaxHS solver with configuration
    pub fn with_config(config: MaxHsConfig) -> Self {
        Self {
            sat_solver: SatSolver::new(),
            hard_clauses: Vec::new(),
            soft_clauses: Vec::new(),
            soft_map: FxHashMap::default(),
            config,
            stats: MaxHsStats::default(),
            mcses: Vec::new(),
            best_cost: Weight::Infinite,
        }
    }

    /// Add a hard clause
    pub fn add_hard(&mut self, lits: impl IntoIterator<Item = Lit>) {
        let clause: Vec<Lit> = lits.into_iter().collect();
        self.sat_solver.add_clause(clause.iter().copied());
        self.hard_clauses.push(clause);
    }

    /// Add a soft clause
    pub fn add_soft(&mut self, id: SoftId, lits: impl IntoIterator<Item = Lit>, weight: Weight) {
        let clause = SoftClause::new(id, lits, weight);
        let idx = self.soft_clauses.len();
        self.soft_map.insert(id, idx);
        self.soft_clauses.push(clause);
        self.stats.total_soft += 1;
    }

    /// Solve the MaxSAT instance
    pub fn solve(&mut self) -> Result<MaxSatResult, MaxHsError> {
        // Add hard clauses to SAT solver
        for hard_clause in &self.hard_clauses {
            self.sat_solver.add_clause(hard_clause.iter().copied());
        }

        // Add all soft clauses to SAT solver initially
        for clause in &self.soft_clauses {
            self.sat_solver.add_clause(clause.lits.iter().copied());
        }

        // Main MaxHS loop
        for _ in 0..self.config.max_iterations {
            self.stats.sat_calls += 1;
            let (result, _) = self.sat_solver.solve_with_assumptions(&[]);

            match result {
                SolverResult::Sat => {
                    // All soft clauses are satisfied
                    return Ok(MaxSatResult::Optimal);
                }
                SolverResult::Unsat => {
                    // Find a minimal correction set (MCS)
                    let mcs = self.find_mcs()?;

                    if mcs.clauses.is_empty() {
                        // Hard constraints are unsatisfiable
                        return Err(MaxHsError::Unsatisfiable);
                    }

                    self.stats.mcses_found += 1;
                    self.mcses.push(mcs);

                    // Compute minimum hitting set
                    let hitting_set = self.compute_hitting_set()?;

                    // Update best cost
                    let cost: Weight = hitting_set
                        .iter()
                        .filter_map(|id| self.soft_map.get(id))
                        .filter_map(|&idx| self.soft_clauses.get(idx))
                        .map(|c| &c.weight)
                        .fold(Weight::zero(), |acc, w| acc.add(w));

                    self.best_cost = cost;

                    // Block this hitting set and continue
                    self.block_hitting_set(&hitting_set);
                }
                SolverResult::Unknown => {
                    return Ok(MaxSatResult::Unknown);
                }
            }
        }

        Ok(MaxSatResult::Unknown)
    }

    /// Find a minimal correction set (MCS)
    fn find_mcs(&mut self) -> Result<Mcs, MaxHsError> {
        // An MCS is a minimal set of soft clauses whose removal makes the formula SAT
        // Start with all soft clauses as candidates, then minimize

        let mut candidate: FxHashSet<SoftId> = self.soft_clauses.iter().map(|c| c.id).collect();

        // Minimize: try removing each clause from the candidate
        for &id in &candidate.clone() {
            let mut test_candidate = candidate.clone();
            test_candidate.remove(&id);

            // Test if removing the test_candidate makes formula SAT
            let mut test_solver = SatSolver::new();

            // Add hard clauses
            for hard_clause in &self.hard_clauses {
                test_solver.add_clause(hard_clause.iter().copied());
            }

            // Add soft clauses NOT in test_candidate
            for clause in &self.soft_clauses {
                if !test_candidate.contains(&clause.id) {
                    test_solver.add_clause(clause.lits.iter().copied());
                }
            }

            let (result, _) = test_solver.solve_with_assumptions(&[]);
            if matches!(result, SolverResult::Sat) {
                // Removing test_candidate makes it SAT, so we can shrink the candidate
                candidate = test_candidate;
            }
        }

        // Compute total weight
        let weight = candidate
            .iter()
            .filter_map(|id| self.soft_map.get(id))
            .filter_map(|&idx| self.soft_clauses.get(idx))
            .map(|c| &c.weight)
            .fold(Weight::zero(), |acc, w| acc.add(w));

        Ok(Mcs {
            clauses: candidate,
            weight,
        })
    }

    /// Get soft clauses that are in conflict
    #[allow(dead_code)]
    fn get_unsat_soft_clauses(&self) -> Vec<SoftId> {
        // Simplified: return all soft clause IDs
        // A real implementation would use core extraction
        self.soft_clauses.iter().map(|c| c.id).collect()
    }

    /// Compute minimum-cost hitting set of all MCSes
    fn compute_hitting_set(&mut self) -> Result<FxHashSet<SoftId>, MaxHsError> {
        self.stats.hitting_sets += 1;

        // Hitting set constraint: for each MCS, at least one of its clauses must be in the hitting set
        // We want to minimize the total weight of clauses in the hitting set

        // For simplicity, use a greedy approach
        // A real implementation would use MaxSAT or ILP

        let mut hitting_set = FxHashSet::default();

        for mcs in &self.mcses {
            // Check if this MCS is already hit
            let is_hit = mcs.clauses.iter().any(|id| hitting_set.contains(id));

            if !is_hit {
                // Add the minimum-weight clause from this MCS
                if let Some(&min_id) = mcs.clauses.iter().min_by_key(|&&id| {
                    self.soft_map
                        .get(&id)
                        .and_then(|&idx| self.soft_clauses.get(idx))
                        .map(|c| &c.weight)
                }) {
                    hitting_set.insert(min_id);
                }
            }
        }

        Ok(hitting_set)
    }

    /// Block a hitting set from being found again
    fn block_hitting_set(&mut self, hitting_set: &FxHashSet<SoftId>) {
        // Remove the clauses in the hitting set from SAT solver
        // In practice, this is done by creating a new SAT solver instance
        // or by adding blocking clauses

        // For simplicity, we'll rebuild the SAT solver
        self.sat_solver = SatSolver::new();

        // Add hard clauses
        for hard_clause in &self.hard_clauses {
            self.sat_solver.add_clause(hard_clause.iter().copied());
        }

        // Add soft clauses not in hitting set
        for clause in &self.soft_clauses {
            if !hitting_set.contains(&clause.id) {
                self.sat_solver.add_clause(clause.lits.iter().copied());
            }
        }
    }

    /// Get the best cost found
    pub fn best_cost(&self) -> &Weight {
        &self.best_cost
    }

    /// Get statistics
    pub fn stats(&self) -> &MaxHsStats {
        &self.stats
    }
}

impl Default for MaxHsSolver {
    fn default() -> Self {
        Self::new()
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_maxhs_solver_new() {
        let solver = MaxHsSolver::new();
        assert_eq!(solver.stats().sat_calls, 0);
        assert_eq!(*solver.best_cost(), Weight::Infinite);
    }

    #[test]
    fn test_maxhs_simple() {
        let mut solver = MaxHsSolver::new();

        // Add soft clauses
        solver.add_soft(SoftId(0), [Lit::from_dimacs(1)], Weight::from(1));
        solver.add_soft(SoftId(1), [Lit::from_dimacs(-1)], Weight::from(1));

        let result = solver.solve();
        if let Err(ref e) = result {
            eprintln!("MaxHS error: {:?}", e);
        }
        assert!(result.is_ok(), "Solve failed: {:?}", result);

        // Should have cost 1 (one clause must be violated)
        assert_eq!(*solver.best_cost(), Weight::from(1));
    }

    #[test]
    fn test_maxhs_config() {
        let config = MaxHsConfig {
            max_iterations: 5000,
            use_cores: false,
            preprocess: false,
        };

        let solver = MaxHsSolver::with_config(config);
        assert_eq!(solver.config.max_iterations, 5000);
        assert!(!solver.config.use_cores);
    }
}
