//! Bifrost v2 — The Bridge of Souls.
//! Implements Phase 10 [S4] Hilbert Projection & Privacy Sync.

use mimirs_core::AgentId;
use rand::Rng;
use serde::{Deserialize, Serialize};
use std::time::SystemTime;

/// I1: Direct Hilbert Pulse (ψ queries)
/// High-frequency state vector transmission for real-time resonance sensing.
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct HilbertPulse {
    pub agent_id: AgentId,
    pub psi: Vec<f64>, // Normalized state vector ψ
    pub timestamp_ns: u64,
}

impl HilbertPulse {
    pub fn new(agent_id: AgentId, psi: Vec<f64>) -> Self {
        let timestamp_ns = SystemTime::now()
            .duration_since(SystemTime::UNIX_EPOCH)
            .unwrap_or_default()
            .as_nanos() as u64;
        Self {
            agent_id,
            psi,
            timestamp_ns,
        }
    }
}

/// B2: Privacy-Preserving Eigenstate Sync
/// Shared structural metadata with ε-noise injected singular values.
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct EigenstateFrame {
    pub agent_id: AgentId,
    pub eigenvectors: Vec<Vec<f64>>, // Top-k structural directions
    pub singular_values: Vec<f64>,   // ε-noise injected for privacy
}

impl EigenstateFrame {
    /// Constructs a new privacy-preserved frame.
    /// DERIVATION: Singular Value Noise λ' = λ + N(0, ε).
    /// This prevents an attacker from reconstructing the identity manifold's
    /// exact covariance structure while allowing structural alignment.
    pub fn new_with_privacy(
        agent_id: AgentId,
        eigenvectors: Vec<Vec<f64>>,
        singular_values: Vec<f64>,
        epsilon: f64,
    ) -> Self {
        let mut rng = rand::thread_rng();
        let private_values: Vec<f64> = singular_values
            .into_iter()
            .map(|v| (v + rng.gen_range(-epsilon..epsilon)).max(0.0))
            .collect();

        Self {
            agent_id,
            eigenvectors,
            singular_values: private_values,
        }
    }

    /// Returns a resonance score with another frame.
    /// Measures structural overlap in Hilbert space.
    pub fn resonance(&self, other: &Self) -> f64 {
        // DERIVATION: For low-rank approximations A = Σ λ_i v_i v_iᵀ and B = Σ μ_j u_j u_jᵀ,
        // the resonance (inner product) is tr(AᵀB) = Σ Σ λ_i μ_j (v_iᵀ u_j)².
        // Here we simplify to the diagonal sum Σ λ_i μ_i (v_iᵀ u_i)² for efficiency.
        let mut total_score = 0.0;
        let k = self.eigenvectors.len().min(other.eigenvectors.len());

        if k == 0 {
            return 0.0;
        }

        for i in 0..k {
            let dot: f64 = self.eigenvectors[i]
                .iter()
                .zip(other.eigenvectors[i].iter())
                .map(|(a, b)| a * b)
                .sum();
            total_score += (dot * dot) * (self.singular_values[i] * other.singular_values[i]);
        }

        debug_assert!(total_score.is_finite());
        total_score
    }
}
