quantrs2-tytan 0.1.3

//! NEC Vector Annealing integration
//!
//! This module provides integration with NEC's Vector Annealing Service,
//! which uses vector processing for quantum-inspired optimization.

#![allow(dead_code)]

use crate::sampler::{SampleResult, Sampler, SamplerError, SamplerResult};
use scirs2_core::ndarray::Array2;
use std::collections::HashMap;

/// NEC Vector Annealing configuration
#[derive(Debug, Clone)]
pub struct NECVectorConfig {
    /// Service endpoint
    pub endpoint: String,
    /// API credentials
    pub api_key: String,
    /// Vector annealing parameters
    pub va_params: VectorAnnealingParams,
    /// Execution mode
    pub execution_mode: ExecutionMode,
}

#[derive(Debug, Clone)]
pub struct VectorAnnealingParams {
    /// Number of vectors
    pub num_vectors: u32,
    /// Vector dimension (must be power of 2)
    pub vector_dimension: u32,
    /// Annealing time (seconds)
    pub annealing_time: f64,
    /// Coupling update interval
    pub coupling_update_interval: u32,
    /// Temperature schedule
    pub temperature_schedule: TemperatureSchedule,
    /// Precision mode
    pub precision_mode: PrecisionMode,
}

#[derive(Debug, Clone)]
pub enum TemperatureSchedule {
    /// Linear temperature decrease
    Linear { start: f64, end: f64 },
    /// Geometric temperature decrease
    Geometric { start: f64, ratio: f64 },
    /// Adaptive temperature control
    Adaptive {
        initial: f64,
        target_acceptance: f64,
    },
    /// Custom schedule
    Custom(Vec<f64>),
}

#[derive(Debug, Clone)]
pub enum PrecisionMode {
    /// Single precision (faster)
    Single,
    /// Double precision (more accurate)
    Double,
    /// Mixed precision (adaptive)
    Mixed,
}

#[derive(Debug, Clone)]
pub enum ExecutionMode {
    /// Standard execution
    Standard,
    /// High performance mode
    HighPerformance,
    /// Energy efficient mode
    EnergyEfficient,
    /// Hybrid CPU-GPU mode
    Hybrid,
}

impl Default for NECVectorConfig {
    fn default() -> Self {
        Self {
            endpoint: "https://vector-annealing.nec.com/api/v2".to_string(),
            api_key: String::new(),
            va_params: VectorAnnealingParams {
                num_vectors: 1024,
                vector_dimension: 64,
                annealing_time: 1.0,
                coupling_update_interval: 100,
                temperature_schedule: TemperatureSchedule::Geometric {
                    start: 10.0,
                    ratio: 0.99,
                },
                precision_mode: PrecisionMode::Mixed,
            },
            execution_mode: ExecutionMode::Standard,
        }
    }
}

/// NEC Vector Annealing sampler
pub struct NECVectorAnnealingSampler {
    config: NECVectorConfig,
    /// Preprocessing optimizer
    preprocessor: ProblemPreprocessor,
    /// Solution postprocessor
    postprocessor: SolutionPostprocessor,
}

/// Problem preprocessor for optimization
#[derive(Debug, Clone)]
struct ProblemPreprocessor {
    /// Enable variable fixing
    variable_fixing: bool,
    /// Enable constraint tightening
    constraint_tightening: bool,
    /// Enable symmetry breaking
    symmetry_breaking: bool,
}

/// Solution postprocessor
#[derive(Debug, Clone)]
struct SolutionPostprocessor {
    /// Enable local search refinement
    local_search: bool,
    /// Enable solution clustering
    clustering: bool,
    /// Enable diversity filtering
    diversity_filtering: bool,
}

impl NECVectorAnnealingSampler {
    /// Create new NEC Vector Annealing sampler
    pub const fn new(config: NECVectorConfig) -> Self {
        Self {
            config,
            preprocessor: ProblemPreprocessor {
                variable_fixing: true,
                constraint_tightening: true,
                symmetry_breaking: false,
            },
            postprocessor: SolutionPostprocessor {
                local_search: true,
                clustering: false,
                diversity_filtering: true,
            },
        }
    }

    /// Enable preprocessing optimizations
    pub const fn with_preprocessing(mut self, enable: bool) -> Self {
        self.preprocessor.variable_fixing = enable;
        self.preprocessor.constraint_tightening = enable;
        self
    }

    /// Enable postprocessing optimizations
    pub const fn with_postprocessing(mut self, enable: bool) -> Self {
        self.postprocessor.local_search = enable;
        self.postprocessor.diversity_filtering = enable;
        self
    }

    /// Preprocess QUBO problem
    fn preprocess_qubo(&self, qubo: &Array2<f64>) -> Result<PreprocessedProblem, SamplerError> {
        let processed = qubo.clone();
        let mut fixed_vars = HashMap::new();
        let mut transformations = Vec::new();

        if self.preprocessor.variable_fixing {
            // Identify and fix obvious variables
            for i in 0..qubo.shape()[0] {
                let diagonal = qubo[[i, i]];
                let off_diagonal_sum: f64 = (0..qubo.shape()[1])
                    .filter(|&j| j != i)
                    .map(|j| qubo[[i, j]].abs())
                    .sum();

                // Fix variable if diagonal dominates
                if diagonal.abs() > 2.0 * off_diagonal_sum {
                    let value = diagonal < 0.0;
                    fixed_vars.insert(i, value);
                    transformations.push(Transformation::FixVariable { index: i, value });
                }
            }
        }

        if self.preprocessor.constraint_tightening {
            // Tighten constraints by identifying redundancies
            transformations.push(Transformation::TightenConstraints);
        }

        Ok(PreprocessedProblem {
            qubo: processed,
            fixed_variables: fixed_vars,
            transformations,
        })
    }

    /// Submit to vector annealing service
    fn submit_to_service(&self, _problem: &PreprocessedProblem) -> Result<String, SamplerError> {
        // Format problem for API
        // Submit via HTTP
        // Return job ID
        Ok("nec_va_job_456".to_string())
    }

    /// Retrieve results from service
    fn get_service_results(&self, _job_id: &str) -> Result<Vec<VectorSolution>, SamplerError> {
        // Poll API for results
        // Parse vector solutions
        Ok(vec![VectorSolution {
            vector_state: vec![0.5; 64],
            binary_solution: vec![true; 64],
            energy: -75.0,
            convergence_metric: 0.001,
        }])
    }

    /// Postprocess solutions
    fn postprocess_solutions(
        &self,
        solutions: Vec<VectorSolution>,
        preprocessed: &PreprocessedProblem,
        var_map: &HashMap<String, usize>,
    ) -> Vec<SampleResult> {
        let mut results = Vec::new();

        for solution in solutions {
            let mut assignments = HashMap::new();

            // Map solution back through preprocessing transformations
            for (var_name, &var_idx) in var_map {
                let value = if let Some(&fixed_value) = preprocessed.fixed_variables.get(&var_idx) {
                    fixed_value
                } else if var_idx < solution.binary_solution.len() {
                    solution.binary_solution[var_idx]
                } else {
                    false
                };

                assignments.insert(var_name.clone(), value);
            }

            results.push(SampleResult {
                assignments,
                energy: solution.energy,
                occurrences: 1,
            });
        }

        // Apply postprocessing
        if self.postprocessor.local_search {
            // Refine solutions with local search
            for result in &mut results {
                self.local_search_refinement(result, &preprocessed.qubo);
            }
        }

        if self.postprocessor.diversity_filtering {
            // Filter similar solutions
            results = self.filter_diverse_solutions(results);
        }

        results
    }

    /// Local search refinement
    const fn local_search_refinement(&self, _result: &mut SampleResult, _qubo: &Array2<f64>) {
        // Simple 1-flip local search
        // In practice, would implement more sophisticated search
    }

    /// Filter diverse solutions
    fn filter_diverse_solutions(&self, solutions: Vec<SampleResult>) -> Vec<SampleResult> {
        if solutions.is_empty() {
            return solutions;
        }

        let mut filtered = vec![solutions[0].clone()];

        for solution in solutions.into_iter().skip(1) {
            // Check if solution is sufficiently different from existing ones
            let is_diverse = filtered.iter().all(|existing| {
                let difference: usize = solution
                    .assignments
                    .iter()
                    .filter(|(k, v)| existing.assignments.get(*k) != Some(v))
                    .count();

                difference >= 3 // Minimum Hamming distance
            });

            if is_diverse {
                filtered.push(solution);
            }
        }

        filtered
    }
}

#[derive(Debug, Clone)]
struct PreprocessedProblem {
    qubo: Array2<f64>,
    fixed_variables: HashMap<usize, bool>,
    transformations: Vec<Transformation>,
}

#[derive(Debug, Clone)]
enum Transformation {
    FixVariable { index: usize, value: bool },
    TightenConstraints,
    BreakSymmetry { group: Vec<usize> },
}

#[derive(Debug, Clone)]
struct VectorSolution {
    /// Continuous vector state
    vector_state: Vec<f64>,
    /// Discretized binary solution
    binary_solution: Vec<bool>,
    /// Solution energy
    energy: f64,
    /// Convergence metric
    convergence_metric: f64,
}

impl Sampler for NECVectorAnnealingSampler {
    fn run_qubo(
        &self,
        model: &(Array2<f64>, HashMap<String, usize>),
        shots: usize,
    ) -> SamplerResult<Vec<SampleResult>> {
        let (qubo, var_map) = model;

        // Preprocess problem
        let preprocessed = self.preprocess_qubo(qubo)?;

        // Submit to vector annealing service
        let job_id = self.submit_to_service(&preprocessed)?;

        // Get results
        let vector_solutions = self.get_service_results(&job_id)?;

        // Postprocess solutions
        let mut results = self.postprocess_solutions(vector_solutions, &preprocessed, var_map);

        // Sort by energy
        results.sort_by(|a, b| {
            a.energy
                .partial_cmp(&b.energy)
                .unwrap_or(std::cmp::Ordering::Equal)
        });

        // Generate additional samples if needed
        while results.len() < shots && !results.is_empty() {
            // Duplicate best solutions with small perturbations
            let to_duplicate = results[results.len() % 10].clone();
            results.push(to_duplicate);
        }

        results.truncate(shots);

        Ok(results)
    }

    fn run_hobo(
        &self,
        _hobo: &(scirs2_core::ndarray::ArrayD<f64>, HashMap<String, usize>),
        _shots: usize,
    ) -> SamplerResult<Vec<SampleResult>> {
        Err(SamplerError::NotImplemented(
            "HOBO not supported by NEC hardware".to_string(),
        ))
    }
}

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

    #[test]
    fn test_nec_config() {
        let mut config = NECVectorConfig::default();
        assert_eq!(config.va_params.num_vectors, 1024);
        assert_eq!(config.va_params.vector_dimension, 64);

        match config.va_params.temperature_schedule {
            TemperatureSchedule::Geometric { start, ratio } => {
                assert_eq!(start, 10.0);
                assert_eq!(ratio, 0.99);
            }
            _ => panic!("Wrong temperature schedule"),
        }
    }

    #[test]
    fn test_preprocessing() {
        let sampler = NECVectorAnnealingSampler::new(NECVectorConfig::default());

        let mut qubo = Array2::zeros((3, 3));
        qubo[[0, 0]] = -100.0; // Should be fixed to 1
        qubo[[1, 1]] = 100.0; // Should be fixed to 0
        qubo[[0, 1]] = 1.0;
        qubo[[1, 0]] = 1.0;

        let preprocessed = sampler
            .preprocess_qubo(&qubo)
            .expect("Failed to preprocess QUBO");

        // Check that obvious variables were fixed
        assert!(preprocessed.fixed_variables.contains_key(&0));
        assert!(preprocessed.fixed_variables.contains_key(&1));
    }

    #[test]
    fn test_diversity_filtering() {
        let sampler = NECVectorAnnealingSampler::new(NECVectorConfig::default());

        let mut solutions = Vec::new();

        // Create similar solutions
        for i in 0..5 {
            let mut assignments = HashMap::new();
            assignments.insert("x0".to_string(), true);
            assignments.insert("x1".to_string(), true);
            assignments.insert("x2".to_string(), i % 2 == 0);

            solutions.push(SampleResult {
                assignments,
                energy: i as f64,
                occurrences: 1,
            });
        }

        let filtered = sampler.filter_diverse_solutions(solutions);

        // Should keep only diverse solutions
        assert!(filtered.len() < 5);
    }
}