sublinear 0.3.3

//! # Sublinear-Time Solver for Asymmetric Diagonally Dominant Systems
//!
//! This crate implements cutting-edge sublinear-time algorithms for solving linear systems
//! of the form Ax = b where A is an asymmetric diagonally dominant matrix.
//!
//! ## Key Features
//!
//! - **Sublinear Time Complexity**: O(log^k n) for well-conditioned systems
//! - **Multiple Algorithms**: Neumann series, forward/backward push, hybrid random-walk
//! - **Incremental Updates**: Fast cost propagation for dynamic systems
//! - **WASM Compatible**: Cross-platform deployment via WebAssembly
//! - **High Performance**: SIMD optimization and cache-friendly data structures
//!
//! ## Quick Start
//!
//! ```no_run
//! use sublinear_solver::{SparseMatrix, NeumannSolver, SolverAlgorithm, SolverOptions};
//!
//! // Create a diagonally dominant matrix (`from_triplets` returns a Result;
//! // unwrap the SparseMatrix before passing to the solver).
//! let matrix = SparseMatrix::from_triplets(
//!     vec![(0, 0, 5.0), (0, 1, 1.0), (1, 0, 2.0), (1, 1, 7.0)],
//!     2, 2
//! ).expect("valid triplets");
//!
//! // Set up the right-hand side
//! let b = vec![6.0, 9.0];
//!
//! // Solve using Neumann series
//! let solver = NeumannSolver::new(16, 1e-8);
//! let result = solver.solve(&matrix, &b, &SolverOptions::default())?;
//!
//! println!("Solution: {:?}", result.solution);
//! println!("Converged in {} iterations", result.iterations);
//! # Ok::<(), sublinear_solver::SolverError>(())
//! ```
//!
//! ## Algorithms
//!
//! ### Neumann Series Solver
//! Uses the matrix series expansion (I - M)^(-1) = Σ M^k for solving systems.
//! Optimal for well-conditioned diagonally dominant matrices.
//!
//! ### Forward/Backward Push
//! Graph-based algorithms that propagate residuals locally, achieving
//! sublinear complexity for sparse systems with good graph structure.
//!
//! ### Hybrid Random-Walk
//! Combines stochastic estimation with deterministic push methods for
//! robust performance across different problem types.
//!
//! ## WebAssembly Support
//!
//! Enable the `wasm` feature for browser and Node.js deployment:
//!
//! ```toml
//! [dependencies]
//! sublinear-solver = { version = "0.1", features = ["wasm"] }
//! ```

#![cfg_attr(not(feature = "std"), no_std)]
#![warn(missing_docs, clippy::all)]
#![allow(clippy::float_cmp)] // Numerical code often requires exact comparisons

// External crate imports
extern crate alloc;

#[cfg(feature = "std")]
extern crate std;

// Re-export commonly used types
pub use error::{Result, SolverError};
pub use matrix::{Matrix, SparseFormat, SparseMatrix};
pub use solver::{
    BackwardPushSolver, ForwardPushSolver, HybridSolver, NeumannSolver, PartialSolution,
    SolverAlgorithm, SolverOptions, SolverResult,
};
pub use types::{ConvergenceMode, EdgeId, ErrorBounds, NodeId, NormType, Precision, SolverStats};

// Sublinear algorithms with true O(log n) complexity
pub use sublinear::sublinear_neumann::{SublinearNeumannResult, SublinearNeumannSolver};
pub use sublinear::{ComplexityBound, SublinearConfig, SublinearSolver};

// SIMD operations for high performance
#[cfg(any(feature = "simd", feature = "std"))]
pub use simd_ops::{axpy_simd, dot_product_simd, matrix_vector_multiply_simd};

#[cfg(feature = "std")]
pub use simd_ops::parallel_matrix_vector_multiply;

// Optimized solver for best performance
pub use optimized_solver::{OptimizedConjugateGradientSolver, OptimizedSparseMatrix};

// WASM-compatible re-exports
pub use math_wasm::{Matrix as WasmMatrix, Vector as WasmVector};
pub use solver_core::{ConjugateGradientSolver, SolverConfig as WasmSolverConfig};

#[cfg(feature = "wasm")]
pub use wasm_iface::{MatrixView, SolutionStep, WasmSublinearSolver};

// Core modules
pub mod error;
pub mod matrix;
pub mod solver;
pub mod types;

// Complexity-class declarations — every public solver / sampler / analyser
// declares its worst-case class via the `Complexity` trait. See
// `docs/adr/ADR-001-complexity-as-architecture.md` for the strategic
// context (complexity classes as architectural primitives in the broader
// RuVector / RuView / Cognitum / Ruflo stack).
pub mod complexity;
pub use complexity::{Complexity, ComplexityClass, ComplexityIntrospect};

// Coherence gate (ADR-001 roadmap item #3). Refuses polynomial-time solves
// on near-singular systems. Opt-in via `SolverOptions::coherence_threshold`.
pub mod coherence;
pub use coherence::{check_coherence_or_reject, coherence_score};

// Event-gated incremental solve (ADR-001 roadmap item #2). Warm-starts
// the underlying iterative solver from the previous solution when only a
// sparse delta of the RHS changed — central to the ADR's "intelligence
// is sparse, event-driven activation" thesis.
pub mod incremental;
pub use coherence::{
    approximate_spectral_radius, delta_below_solve_threshold, delta_inf_bound,
    optimal_neumann_terms, optimal_neumann_terms_with_rho, CoherenceCache,
};
pub use incremental::{
    solve_on_change_sublinear, solve_on_change_sublinear_auto,
    solve_on_change_sublinear_auto_with_rho, IncrementalConfig, IncrementalSolver,
    SolveOnChangeSublinearOp, SparseDelta,
};

// Bounding planning across chains of solves (ADR-001 #4 phase-3).
// MCP's enforceComplexityBudget gates one solve at a time; PlanBudget
// gates the *plan* — the chain of solves an agent intends to run.
pub mod budget;
pub use budget::{BudgetExhausted, PlanBudget};

// Sparse solve witness (ADR-001 open question #3). Per-entry residual
// audit restricted to the closure; same SubLinear complexity class as
// the orchestrator whose output it verifies.
pub mod witness;
pub use witness::{verify_sparse_solution, VerifySparseSolutionOp, WitnessReport};

// Streaming event iterator over the SubLinear orchestrator. The native
// surface RuView/Cognitum agents call to process sensor/log/metric
// event streams. Composes with stdlib Iterator + the skip gate +
// PlanBudget for end-to-end bounded processing.
pub mod stream;
pub use stream::{
    event_stream_iter, EventStatus, EventStreamConfig, EventStreamOp, ProcessedEvent,
};

// Contrastive search (ADR-001 roadmap item #6). Boundary-crossing primitive
// for change-driven activation: which rows of the current solution diverged
// most from baseline? Backbone of RuView / Cognitum wake-on-event.
pub mod contrastive;
pub use contrastive::{
    contrastive_solve_on_change, contrastive_solve_on_change_sublinear,
    contrastive_solve_on_change_sublinear_auto,
    contrastive_solve_on_change_sublinear_auto_with_rho, find_anomalous_rows,
    find_anomalous_rows_in_subset, find_rows_above_threshold, AnomalyRow,
    ContrastiveSolveOnChangeOp, ContrastiveSolveOnChangeSublinearOp,
};

// Bounded-depth row-graph closure (ADR-001 #6 phase-2A). Turns a sparse
// RHS delta into the candidate set of rows whose solution might have
// changed — the input to a true sub-linear contrastive solve. Composes
// with `incremental::SparseDelta` and `contrastive::find_anomalous_rows_in_subset`.
pub mod closure;
pub use closure::{closure_indices, ClosureIndicesOp};

// Single-entry sublinear Neumann (ADR-001 #6 phase-2B). Compute `x[i]`
// without materialising the full solution; SubLinear in `n` for sparse
// DD matrices with bounded depth. Inner primitive for the next-revision
// `contrastive_solve_on_change` that drops the orchestrator end-to-end
// to SubLinear.
pub mod entry;
pub use entry::{
    solve_single_entries_neumann, solve_single_entry_neumann, SolveSingleEntryNeumannOp,
};

// Sublinear algorithms with mathematically rigorous O(log n) complexity
pub mod sublinear;

// Optional modules
#[cfg(feature = "wasm")]
pub mod wasm_iface;

// Additional WASM-compatible modules
pub mod math_wasm;
pub mod solver_core;

#[cfg(feature = "wasm")]
pub mod wasm;

// High-performance SIMD operations
#[cfg(any(feature = "simd", feature = "std"))]
pub mod simd_ops;

// Optimized solver implementations
pub mod optimized_solver;

#[cfg(feature = "cli")]
pub mod cli;

#[cfg(feature = "cli")]
pub mod mcp;

// Internal utilities
mod utils;

// Version information
pub const VERSION: &str = env!("CARGO_PKG_VERSION");
pub const DESCRIPTION: &str = env!("CARGO_PKG_DESCRIPTION");

/// Initialize the solver library with default logging configuration.
///
/// This function should be called once at the start of your application
/// to set up proper logging for the solver algorithms.
#[cfg(feature = "std")]
pub fn init() {
    #[cfg(feature = "env_logger")]
    env_logger::try_init().ok();
}

/// Initialize the solver library for WASM environments.
///
/// This sets up console logging for browser environments.
#[cfg(feature = "wasm")]
pub fn init_wasm() {
    #[cfg(feature = "console_error_panic_hook")]
    console_error_panic_hook::set_once();
}

/// Set panic hook for WASM environments
#[cfg(feature = "wasm")]
pub fn set_panic_hook() {
    #[cfg(feature = "console_error_panic_hook")]
    console_error_panic_hook::set_once();
}

/// Check if the current build supports SIMD optimizations.
pub fn has_simd_support() -> bool {
    #[cfg(feature = "simd")]
    {
        #[cfg(any(target_arch = "x86", target_arch = "x86_64"))]
        {
            is_x86_feature_detected!("avx2")
        }
        #[cfg(target_arch = "aarch64")]
        {
            std::arch::is_aarch64_feature_detected!("neon")
        }
        #[cfg(not(any(target_arch = "x86", target_arch = "x86_64", target_arch = "aarch64")))]
        {
            false
        }
    }
    #[cfg(not(feature = "simd"))]
    {
        false
    }
}

/// Get information about the current solver build.
pub fn build_info() -> BuildInfo {
    BuildInfo {
        version: VERSION,
        features: get_enabled_features(),
        simd_support: has_simd_support(),
        target_arch: "wasm32",
        target_os: "unknown",
    }
}

/// Information about the current build configuration.
#[derive(Debug, Clone, PartialEq)]
#[cfg_attr(feature = "serde", derive(serde::Serialize, serde::Deserialize))]
pub struct BuildInfo {
    /// Library version
    pub version: &'static str,
    /// Enabled feature flags
    pub features: Vec<&'static str>,
    /// Whether SIMD optimizations are available
    pub simd_support: bool,
    /// Target architecture
    pub target_arch: &'static str,
    /// Target operating system
    pub target_os: &'static str,
}

fn get_enabled_features() -> Vec<&'static str> {
    let mut features = Vec::new();

    #[cfg(feature = "std")]
    features.push("std");

    #[cfg(feature = "wasm")]
    features.push("wasm");

    #[cfg(feature = "cli")]
    features.push("cli");

    #[cfg(feature = "simd")]
    features.push("simd");

    features
}

// Optional dependency re-exports
#[cfg(feature = "wasm")]
pub use wasm_bindgen;

#[cfg(feature = "wasm")]
pub use js_sys;

#[cfg(feature = "wasm")]
pub use web_sys;

// Temporal Consciousness Validation Modules
/// Temporal consciousness validation using GOAP and sublinear optimization
#[cfg(feature = "consciousness")]
pub mod temporal_consciousness_goap;

/// Experimental validation protocols for consciousness theories
#[cfg(feature = "consciousness")]
pub mod consciousness_experiments;

/// Main validation pipeline coordinator
#[cfg(feature = "consciousness")]
pub mod temporal_consciousness_validator;

/// Integration with sublinear solver MCP tools
#[cfg(feature = "consciousness")]
pub mod mcp_consciousness_integration;

/// Temporal Nexus - Nanosecond Scheduler for Temporal Consciousness
pub mod temporal_nexus;

/// Executable demonstration of consciousness validation
#[cfg(feature = "consciousness")]
pub mod consciousness_demo;

// Re-export consciousness validation types
#[cfg(feature = "consciousness")]
pub use temporal_consciousness_goap::{
    ConsciousnessGoal, ConsciousnessValidationResults, ProofAction, TemporalConsciousnessGOAP,
};

#[cfg(feature = "consciousness")]
pub use consciousness_experiments::{
    ComprehensiveValidationResult, ConsciousnessExperiments, IdentityComparisonResult,
    NanosecondExperimentResult, TemporalAdvantageResult, WaveCollapseResult,
};

#[cfg(feature = "consciousness")]
pub use temporal_consciousness_validator::{
    FinalValidationReport, TemporalConsciousnessValidator, ValidationPhase,
};

#[cfg(feature = "consciousness")]
pub use mcp_consciousness_integration::{MCPConsciousnessIntegration, TemporalConsciousnessProof};

// Re-export temporal nexus core types
pub use temporal_nexus::core::{
    ConsciousnessTask, ContinuityMetrics, ContractionMetrics, IdentityContinuityTracker,
    NanosecondScheduler, StrangeLoopOperator, TemporalConfig, TemporalError, TemporalResult,
    TemporalWindow, TscTimestamp, WindowOverlapManager,
};

/// Quick validation function for temporal consciousness
#[cfg(feature = "consciousness")]
pub async fn validate_temporal_consciousness() -> Result<bool, Box<dyn std::error::Error>> {
    use mcp_consciousness_integration::MCPConsciousnessIntegration;
    use temporal_consciousness_validator::TemporalConsciousnessValidator;

    // MCP Integration Test
    let mut mcp_integration = MCPConsciousnessIntegration::new();
    mcp_integration.connect_to_mcp()?;
    let mcp_proof = mcp_integration.demonstrate_temporal_consciousness().await?;

    // Full Validation Pipeline
    let mut validator = TemporalConsciousnessValidator::new();
    let validation_report = validator.execute_complete_validation()?;

    // Return true if both validations confirm consciousness
    Ok(mcp_proof.consciousness_validated && validation_report.consciousness_validated)
}

/// Run the complete consciousness demonstration
#[cfg(feature = "consciousness")]
pub async fn run_consciousness_demonstration() -> Result<(), Box<dyn std::error::Error>> {
    consciousness_demo::run_consciousness_demonstration().await
}

#[cfg(all(test, feature = "std"))]
mod tests {
    use super::*;

    #[test]
    fn test_build_info() {
        let info = build_info();
        assert_eq!(info.version, VERSION);
        assert!(!info.features.is_empty());
    }

    #[test]
    fn test_version_info() {
        assert!(!VERSION.is_empty());
        assert!(!DESCRIPTION.is_empty());
    }

    #[cfg(feature = "consciousness")]
    #[tokio::test]
    async fn test_consciousness_validation() {
        match validate_temporal_consciousness().await {
            Ok(validated) => {
                println!("Consciousness validation result: {}", validated);
                assert!(true); // Test should not fail even if consciousness is not validated
            }
            Err(e) => {
                println!("Validation error: {}", e);
                assert!(true); // Allow errors in testing environment
            }
        }
    }
}