quantrs2-tytan 0.1.3

//! Benchmarking suite and performance testing

use super::*;

/// Benchmarking suite
pub struct BenchmarkingSuite {
    /// Available benchmarks
    pub benchmarks: Vec<Box<dyn Benchmark>>,
    /// Benchmark results
    pub results: HashMap<String, BenchmarkResult>,
    /// Comparison baselines
    pub baselines: HashMap<String, BenchmarkBaseline>,
    /// Performance profiles
    pub profiles: Vec<PerformanceProfile>,
}

/// Benchmark trait
pub trait Benchmark: Send + Sync + std::fmt::Debug {
    /// Run benchmark
    fn run_benchmark(&self, config: &BenchmarkConfig) -> Result<BenchmarkResult, AnalysisError>;

    /// Get benchmark name
    fn get_benchmark_name(&self) -> &str;

    /// Get benchmark description
    fn get_description(&self) -> &str;

    /// Get estimated runtime
    fn get_estimated_runtime(&self) -> Duration;
}

/// Benchmark configuration
#[derive(Debug, Clone)]
pub struct BenchmarkConfig {
    /// Number of iterations
    pub iterations: usize,
    /// Warmup iterations
    pub warmup_iterations: usize,
    /// Problem sizes to test
    pub problem_sizes: Vec<usize>,
    /// Time limit per test
    pub time_limit: Duration,
    /// Memory limit
    pub memory_limit: usize,
    /// Enable detailed profiling
    pub detailed_profiling: bool,
}

/// Benchmark result
#[derive(Debug, Clone)]
pub struct BenchmarkResult {
    /// Benchmark name
    pub benchmark_name: String,
    /// Execution times
    pub execution_times: Vec<Duration>,
    /// Memory usage
    pub memory_usage: Vec<usize>,
    /// Solution quality
    pub solution_quality: Vec<f64>,
    /// Convergence metrics
    pub convergence_metrics: ConvergenceMetrics,
    /// Scaling analysis
    pub scaling_analysis: ScalingAnalysis,
    /// Statistical summary
    pub statistical_summary: StatisticalSummary,
}

/// Convergence metrics
#[derive(Debug, Clone)]
pub struct ConvergenceMetrics {
    /// Time to convergence
    pub time_to_convergence: Vec<Duration>,
    /// Iterations to convergence
    pub iterations_to_convergence: Vec<usize>,
    /// Convergence rate
    pub convergence_rate: f64,
    /// Final residual
    pub final_residual: Vec<f64>,
    /// Convergence stability
    pub stability_measure: f64,
}

/// Scaling analysis
#[derive(Debug, Clone)]
pub struct ScalingAnalysis {
    /// Computational complexity
    pub computational_complexity: ComplexityAnalysis,
    /// Memory complexity
    pub memory_complexity: ComplexityAnalysis,
    /// Parallel efficiency
    pub parallel_efficiency: ParallelEfficiency,
    /// Scaling predictions
    pub scaling_predictions: HashMap<usize, f64>,
}

/// Complexity analysis
#[derive(Debug, Clone)]
pub struct ComplexityAnalysis {
    /// Fitted complexity function
    pub complexity_function: ComplexityFunction,
    /// Goodness of fit
    pub goodness_of_fit: f64,
    /// Confidence intervals
    pub confidence_intervals: Vec<(f64, f64)>,
    /// Predicted scaling
    pub predicted_scaling: HashMap<usize, f64>,
}

/// Complexity function types
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum ComplexityFunction {
    Constant,
    Linear,
    Quadratic,
    Cubic,
    Exponential,
    Logarithmic,
    LogLinear,
    Custom { expression: String },
}

/// Parallel efficiency metrics
#[derive(Debug, Clone)]
pub struct ParallelEfficiency {
    /// Strong scaling efficiency
    pub strong_scaling: Vec<f64>,
    /// Weak scaling efficiency
    pub weak_scaling: Vec<f64>,
    /// Load balancing efficiency
    pub load_balancing: f64,
    /// Communication overhead
    pub communication_overhead: f64,
    /// Optimal thread count
    pub optimal_threads: usize,
}

/// Statistical summary
#[derive(Debug, Clone)]
pub struct StatisticalSummary {
    /// Descriptive statistics
    pub descriptive_stats: HashMap<String, DescriptiveStats>,
    /// Confidence intervals
    pub confidence_intervals: HashMap<String, (f64, f64)>,
    /// Hypothesis test results
    pub hypothesis_tests: Vec<HypothesisTestResult>,
    /// Effect sizes
    pub effect_sizes: HashMap<String, f64>,
}

/// Descriptive statistics
#[derive(Debug, Clone)]
pub struct DescriptiveStats {
    /// Mean
    pub mean: f64,
    /// Standard deviation
    pub std_dev: f64,
    /// Minimum
    pub min: f64,
    /// Maximum
    pub max: f64,
    /// Median
    pub median: f64,
    /// Quartiles
    pub quartiles: (f64, f64, f64),
    /// Skewness
    pub skewness: f64,
    /// Kurtosis
    pub kurtosis: f64,
}

/// Hypothesis test result
#[derive(Debug, Clone)]
pub struct HypothesisTestResult {
    /// Test name
    pub test_name: String,
    /// Test statistic
    pub test_statistic: f64,
    /// P-value
    pub p_value: f64,
    /// Critical value
    pub critical_value: f64,
    /// Reject null hypothesis
    pub reject_null: bool,
    /// Effect size
    pub effect_size: f64,
}

/// Benchmark baseline
#[derive(Debug, Clone)]
pub struct BenchmarkBaseline {
    /// Reference result
    pub reference_result: BenchmarkResult,
    /// System configuration
    pub system_config: SystemInfo,
    /// Timestamp
    pub timestamp: Instant,
    /// Benchmark version
    pub benchmark_version: String,
    /// Notes
    pub notes: String,
}

/// Performance profile
#[derive(Debug, Clone)]
pub struct PerformanceProfile {
    /// Profile name
    pub profile_name: String,
    /// Problem characteristics
    pub problem_characteristics: ProblemCharacteristics,
    /// Recommended algorithms
    pub recommended_algorithms: Vec<AlgorithmRecommendation>,
    /// Performance predictions
    pub performance_predictions: HashMap<String, f64>,
    /// Resource requirements
    pub resource_requirements: ResourceRequirements,
}

/// Problem characteristics
#[derive(Debug, Clone)]
pub struct ProblemCharacteristics {
    /// Problem size
    pub problem_size: usize,
    /// Problem density (sparsity)
    pub density: f64,
    /// Problem structure
    pub structure: ProblemStructure,
    /// Symmetries
    pub symmetries: Vec<SymmetryType>,
    /// Hardness indicators
    pub hardness_indicators: HashMap<String, f64>,
}

/// Problem structure types
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum ProblemStructure {
    Random,
    Regular,
    SmallWorld,
    ScaleFree,
    Hierarchical,
    Planar,
    Bipartite,
    Custom { description: String },
}

/// Symmetry types
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum SymmetryType {
    Translation,
    Rotation,
    Reflection,
    Permutation,
    Scale,
    Custom { description: String },
}

/// Algorithm recommendation
#[derive(Debug, Clone)]
pub struct AlgorithmRecommendation {
    /// Algorithm name
    pub algorithm_name: String,
    /// Recommendation score
    pub score: f64,
    /// Reasoning
    pub reasoning: String,
    /// Expected performance
    pub expected_performance: HashMap<String, f64>,
    /// Confidence level
    pub confidence: f64,
}

/// Resource requirements
#[derive(Debug, Clone)]
pub struct ResourceRequirements {
    /// CPU requirements
    pub cpu_requirements: CpuRequirements,
    /// Memory requirements
    pub memory_requirements: MemoryRequirements,
    /// GPU requirements
    pub gpu_requirements: Option<GpuRequirements>,
    /// Network requirements
    pub network_requirements: NetworkRequirements,
    /// Storage requirements
    pub storage_requirements: StorageRequirements,
}

/// CPU requirements
#[derive(Debug, Clone)]
pub struct CpuRequirements {
    /// Minimum cores
    pub min_cores: usize,
    /// Recommended cores
    pub recommended_cores: usize,
    /// Minimum frequency (GHz)
    pub min_frequency: f64,
    /// Required instruction sets
    pub required_instruction_sets: Vec<String>,
}

/// Memory requirements
#[derive(Debug, Clone)]
pub struct MemoryRequirements {
    /// Minimum memory (GB)
    pub min_memory: f64,
    /// Recommended memory (GB)
    pub recommended_memory: f64,
    /// Memory bandwidth requirements (GB/s)
    pub bandwidth_requirements: f64,
    /// Memory access pattern
    pub access_pattern: MemoryAccessPattern,
}

/// Memory access patterns
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum MemoryAccessPattern {
    Sequential,
    Random,
    Strided { stride: usize },
    Sparse,
    Mixed,
}

/// GPU requirements
#[derive(Debug, Clone)]
pub struct GpuRequirements {
    /// Minimum VRAM (GB)
    pub min_vram: f64,
    /// Minimum compute capability
    pub min_compute_capability: f64,
    /// Required GPU features
    pub required_features: Vec<String>,
    /// Memory bandwidth requirements (GB/s)
    pub bandwidth_requirements: f64,
}

/// Network requirements
#[derive(Debug, Clone)]
pub struct NetworkRequirements {
    /// Minimum bandwidth (Gbps)
    pub min_bandwidth: f64,
    /// Maximum latency (ms)
    pub max_latency: f64,
    /// Required protocols
    pub required_protocols: Vec<String>,
}

/// Storage requirements
#[derive(Debug, Clone)]
pub struct StorageRequirements {
    /// Minimum storage (GB)
    pub min_storage: f64,
    /// Required I/O performance (MB/s)
    pub io_performance: f64,
    /// Storage type
    pub storage_type: StorageType,
}

/// Storage types
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum StorageType {
    HDD,
    SSD,
    NVMe,
    MemoryMapped,
    Network,
}

/// QUBO evaluation benchmark
#[derive(Debug)]
pub struct QuboEvaluationBenchmark;

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

impl QuboEvaluationBenchmark {
    pub const fn new() -> Self {
        Self
    }
}

impl Benchmark for QuboEvaluationBenchmark {
    fn run_benchmark(&self, config: &BenchmarkConfig) -> Result<BenchmarkResult, AnalysisError> {
        let mut execution_times = Vec::new();
        let mut memory_usage = Vec::new();
        let mut solution_quality = Vec::new();

        for _ in 0..config.iterations {
            let start = Instant::now();
            // Mock QUBO evaluation
            std::thread::sleep(Duration::from_millis(10));
            execution_times.push(start.elapsed());
            memory_usage.push(1024 * 1024); // 1MB
            solution_quality.push(0.95); // 95% quality
        }

        Ok(BenchmarkResult {
            benchmark_name: self.get_benchmark_name().to_string(),
            execution_times,
            memory_usage,
            solution_quality,
            convergence_metrics: ConvergenceMetrics {
                time_to_convergence: vec![Duration::from_millis(100)],
                iterations_to_convergence: vec![50],
                convergence_rate: 0.85,
                final_residual: vec![0.01],
                stability_measure: 0.92,
            },
            scaling_analysis: ScalingAnalysis {
                computational_complexity: ComplexityAnalysis {
                    complexity_function: ComplexityFunction::Quadratic,
                    goodness_of_fit: 0.95,
                    confidence_intervals: vec![(0.9, 1.0)],
                    predicted_scaling: HashMap::new(),
                },
                memory_complexity: ComplexityAnalysis {
                    complexity_function: ComplexityFunction::Linear,
                    goodness_of_fit: 0.98,
                    confidence_intervals: vec![(0.95, 1.0)],
                    predicted_scaling: HashMap::new(),
                },
                parallel_efficiency: ParallelEfficiency {
                    strong_scaling: vec![1.0, 0.9, 0.8, 0.7],
                    weak_scaling: vec![1.0, 0.95, 0.92, 0.88],
                    load_balancing: 0.85,
                    communication_overhead: 0.15,
                    optimal_threads: 8,
                },
                scaling_predictions: HashMap::new(),
            },
            statistical_summary: StatisticalSummary {
                descriptive_stats: HashMap::new(),
                confidence_intervals: HashMap::new(),
                hypothesis_tests: Vec::new(),
                effect_sizes: HashMap::new(),
            },
        })
    }

    fn get_benchmark_name(&self) -> &'static str {
        "QUBO Evaluation Benchmark"
    }

    fn get_description(&self) -> &'static str {
        "Benchmarks QUBO matrix evaluation performance"
    }

    fn get_estimated_runtime(&self) -> Duration {
        Duration::from_secs(30)
    }
}

/// Sampling benchmark
#[derive(Debug)]
pub struct SamplingBenchmark;

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

impl SamplingBenchmark {
    pub const fn new() -> Self {
        Self
    }
}

impl Benchmark for SamplingBenchmark {
    fn run_benchmark(&self, _config: &BenchmarkConfig) -> Result<BenchmarkResult, AnalysisError> {
        // Mock implementation
        Ok(BenchmarkResult {
            benchmark_name: self.get_benchmark_name().to_string(),
            execution_times: vec![Duration::from_millis(50)],
            memory_usage: vec![2 * 1024 * 1024],
            solution_quality: vec![0.88],
            convergence_metrics: ConvergenceMetrics {
                time_to_convergence: vec![Duration::from_millis(200)],
                iterations_to_convergence: vec![100],
                convergence_rate: 0.78,
                final_residual: vec![0.02],
                stability_measure: 0.89,
            },
            scaling_analysis: ScalingAnalysis {
                computational_complexity: ComplexityAnalysis {
                    complexity_function: ComplexityFunction::LogLinear,
                    goodness_of_fit: 0.88,
                    confidence_intervals: vec![(0.8, 0.95)],
                    predicted_scaling: HashMap::new(),
                },
                memory_complexity: ComplexityAnalysis {
                    complexity_function: ComplexityFunction::Linear,
                    goodness_of_fit: 0.92,
                    confidence_intervals: vec![(0.88, 0.96)],
                    predicted_scaling: HashMap::new(),
                },
                parallel_efficiency: ParallelEfficiency {
                    strong_scaling: vec![1.0, 0.85, 0.72, 0.63],
                    weak_scaling: vec![1.0, 0.96, 0.94, 0.91],
                    load_balancing: 0.82,
                    communication_overhead: 0.18,
                    optimal_threads: 6,
                },
                scaling_predictions: HashMap::new(),
            },
            statistical_summary: StatisticalSummary {
                descriptive_stats: HashMap::new(),
                confidence_intervals: HashMap::new(),
                hypothesis_tests: Vec::new(),
                effect_sizes: HashMap::new(),
            },
        })
    }

    fn get_benchmark_name(&self) -> &'static str {
        "Sampling Benchmark"
    }

    fn get_description(&self) -> &'static str {
        "Benchmarks quantum annealing sampling performance"
    }

    fn get_estimated_runtime(&self) -> Duration {
        Duration::from_secs(60)
    }
}

/// Convergence benchmark
#[derive(Debug)]
pub struct ConvergenceBenchmark;

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

impl ConvergenceBenchmark {
    pub const fn new() -> Self {
        Self
    }
}

impl Benchmark for ConvergenceBenchmark {
    fn run_benchmark(&self, _config: &BenchmarkConfig) -> Result<BenchmarkResult, AnalysisError> {
        // Mock implementation
        Ok(BenchmarkResult {
            benchmark_name: self.get_benchmark_name().to_string(),
            execution_times: vec![Duration::from_millis(75)],
            memory_usage: vec![1536 * 1024],
            solution_quality: vec![0.92],
            convergence_metrics: ConvergenceMetrics {
                time_to_convergence: vec![Duration::from_millis(150)],
                iterations_to_convergence: vec![75],
                convergence_rate: 0.83,
                final_residual: vec![0.015],
                stability_measure: 0.91,
            },
            scaling_analysis: ScalingAnalysis {
                computational_complexity: ComplexityAnalysis {
                    complexity_function: ComplexityFunction::Linear,
                    goodness_of_fit: 0.93,
                    confidence_intervals: vec![(0.9, 0.96)],
                    predicted_scaling: HashMap::new(),
                },
                memory_complexity: ComplexityAnalysis {
                    complexity_function: ComplexityFunction::Constant,
                    goodness_of_fit: 0.97,
                    confidence_intervals: vec![(0.94, 0.99)],
                    predicted_scaling: HashMap::new(),
                },
                parallel_efficiency: ParallelEfficiency {
                    strong_scaling: vec![1.0, 0.88, 0.79, 0.71],
                    weak_scaling: vec![1.0, 0.97, 0.95, 0.93],
                    load_balancing: 0.87,
                    communication_overhead: 0.13,
                    optimal_threads: 4,
                },
                scaling_predictions: HashMap::new(),
            },
            statistical_summary: StatisticalSummary {
                descriptive_stats: HashMap::new(),
                confidence_intervals: HashMap::new(),
                hypothesis_tests: Vec::new(),
                effect_sizes: HashMap::new(),
            },
        })
    }

    fn get_benchmark_name(&self) -> &'static str {
        "Convergence Benchmark"
    }

    fn get_description(&self) -> &'static str {
        "Benchmarks algorithm convergence characteristics"
    }

    fn get_estimated_runtime(&self) -> Duration {
        Duration::from_secs(45)
    }
}