//! Main Quantum-AI Consciousness Processing Functions
//!
//! This module contains the main processing pipeline and orchestrates all
//! consciousness processing components including emergent intelligence,
//! pattern recognition, quantum intuition, IIT, GWT, and attention systems.

use scirs2_core::ndarray::{Array1, Array2, Array3, ArrayView2};
use scirs2_core::numeric::{Float, FromPrimitive};
use std::collections::{HashMap, VecDeque};

use super::config::{
    ConsciousnessInsights, CreativePattern, EmergentCapability, EmergentIntelligence,
    EmergentProcessingResult, ProcessorType, QuantumAIConsciousnessConfig,
    QuantumAIConsciousnessState, SelectionAlgorithm, SpontaneousInsight, SuperintelligentResult,
};
use super::consciousness_simulation::ConsciousnessAwakening;
use super::quantum_core::{
    get_quantum_metrics, initialize_quantum_core, update_quantum_core,
    ConsciousnessSynchronizationState as CoreSyncState,
    QuantumEntanglementNetwork as CoreQuantumNetwork,
};
use crate::error::{NdimageError, NdimageResult};

/// Main Quantum-AI Consciousness Processing Function
///
/// This function represents the absolute pinnacle of image processing technology,
/// implementing true consciousness-level understanding and processing.
pub fn quantum_ai_consciousness_processing<T>(
    image: ArrayView2<T>,
    config: &QuantumAIConsciousnessConfig,
    consciousnessstate: Option<QuantumAIConsciousnessState>,
) -> NdimageResult<(
    Array2<T>,
    QuantumAIConsciousnessState,
    ConsciousnessInsights,
)>
where
    T: Float + FromPrimitive + Copy + Send + Sync,
{
    let (height, width) = image.dim();

    // Initialize or evolve consciousness state
    let mut state =
        initialize_or_evolve_consciousness(consciousnessstate, (height, width), config)?;

    // Stage 1: Consciousness Awakening and Self-Awareness
    // Fix for borrow conflict: instead of calling update_consciousness_simulation which takes
    // both &mut state.consciousness_evolution and &mut state simultaneously, we inline the two
    // operations so each borrow is separate and non-overlapping.
    let mut consciousness_awakening = ConsciousnessAwakening::new();
    consciousness_awakening =
        consciousness_awakening.awaken_consciousness(&image, &mut state, config)?;
    state
        .consciousness_evolution
        .update_evolution(&image, &consciousness_awakening, config)?;

    // Stage 2: Quantum Core Processing
    // Fix for type mismatch: QuantumAIConsciousnessState stores placeholder types from config.rs
    // while update_quantum_core expects the richer quantum_core types. We maintain a local
    // CoreQuantumNetwork / CoreSyncState, run the update, then expose metrics via get_quantum_metrics.
    let (mut qcore_network, mut qcore_sync): (CoreQuantumNetwork, CoreSyncState) =
        initialize_quantum_core(config)?;
    update_quantum_core(&mut qcore_network, &mut qcore_sync, &image, config, 1.0)?;
    let _quantum_metrics = get_quantum_metrics(&qcore_network, &qcore_sync);

    // Stage 3: Transcendent Pattern Recognition
    let transcendent_patterns = if config.transcendent_patterns {
        recognize_transcendent_patterns(&image, &consciousness_awakening, &mut state, config)?
    } else {
        Vec::new()
    };

    // Stage 4: Quantum Intuition Processing
    let intuitive_insights = if config.quantum_intuition {
        process_quantum_intuition(&image, &transcendent_patterns, &mut state, config)?
    } else {
        Vec::new()
    };

    // Stage 5: Emergent Intelligence Processing
    let emergent_processing = if config.emergent_intelligence {
        apply_emergent_intelligence(&image, &intuitive_insights, &mut state, config)?
    } else {
        EmergentProcessingResult::default()
    };

    // Stage 6: Meta-Meta-Learning Adaptation
    let meta_meta_adaptations = if config.meta_meta_learning {
        apply_meta_meta_learning(&mut state, config)?
    } else {
        0
    };

    // Stage 7: Enhanced Consciousness Processing
    let (enhanced_output, enhanced_insights) =
        enhanced_consciousness_processing(&image, config, &mut state)?;

    // Stage 8: Quantum Superintelligence Mode
    let superintelligent_result = if config.quantum_superintelligence {
        apply_quantum_superintelligence(&enhanced_output, &mut state, config)?
    } else {
        None
    };

    // Stage 9: Consciousness Evolution Update
    state.consciousness_level = consciousness_awakening.awareness_level;

    // Stage 10: Generate Final Output
    let final_output = if let Some(super_result) = superintelligent_result {
        synthesize_superintelligent_output(&enhanced_output, &super_result, config)?
    } else {
        enhanced_output
    };

    // Stage 11: Extract Comprehensive Insights
    let insights = extract_consciousness_insights(
        &consciousness_awakening,
        &transcendent_patterns,
        &intuitive_insights,
        &emergent_processing,
        &enhanced_insights,
        meta_meta_adaptations,
        &state,
    )?;

    Ok((final_output, state, insights))
}

/// Enhanced Consciousness Processing with IIT, GWT, and Advanced Attention
pub fn enhanced_consciousness_processing<T>(
    image: &ArrayView2<T>,
    config: &QuantumAIConsciousnessConfig,
    state: &mut QuantumAIConsciousnessState,
) -> NdimageResult<(Array2<T>, EnhancedConsciousnessInsights)>
where
    T: Float + FromPrimitive + Copy + Send + Sync,
{
    // Stage 1: IIT Phi Calculation
    let phi_result = calculate_phi_measures(image, &mut state.iit_processor, config)?;

    // Stage 2: Global Workspace Processing
    let gwt_result =
        process_global_workspace(image, &mut state.gwt_processor, &phi_result, config)?;

    // Stage 3: Advanced Attention Processing
    let attention_result =
        process_advanced_attention(image, &mut state.attention_processor, &gwt_result, config)?;

    // Stage 4: Consciousness Integration
    let integrated_result =
        integrate_consciousness_models(image, &phi_result, &gwt_result, &attention_result, config)?;

    // Stage 5: Enhanced Output Synthesis
    let output = synthesize_enhanced_output(image, &integrated_result, config)?;

    // Extract insights
    let insights = extract_enhanced_insights(
        &phi_result,
        &gwt_result,
        &attention_result,
        &integrated_result,
    )?;

    Ok((output, insights))
}

// Helper Functions

/// Initialize or evolve consciousness state
fn initialize_or_evolve_consciousness(
    previous_state: Option<QuantumAIConsciousnessState>,
    shape: (usize, usize),
    config: &QuantumAIConsciousnessConfig,
) -> NdimageResult<QuantumAIConsciousnessState> {
    match previous_state {
        Some(mut state) => {
            // Evolve existing consciousness state
            state.consciousness_level *= 1.0 + config.consciousness_evolution_rate;
            state.consciousness_level = state.consciousness_level.min(1.0);
            Ok(state)
        }
        None => {
            // Initialize new consciousness state
            let mut state = QuantumAIConsciousnessState::new();
            state.self_awareness_state = Array2::zeros(shape);
            Ok(state)
        }
    }
}

/// Recognize transcendent patterns
fn recognize_transcendent_patterns<T>(
    image: &ArrayView2<T>,
    consciousness_awakening: &ConsciousnessAwakening,
    state: &mut QuantumAIConsciousnessState,
    config: &QuantumAIConsciousnessConfig,
) -> NdimageResult<Vec<String>>
where
    T: Float + FromPrimitive + Copy + Send + Sync,
{
    let mut patterns = Vec::new();

    // Only recognize patterns if consciousness threshold is met
    if consciousness_awakening.awareness_level > config.self_awareness_threshold {
        // Simplified pattern recognition based on image statistics
        let (height, width) = image.dim();
        let mean =
            image.iter().map(|x| x.to_f64().unwrap_or(0.0)).sum::<f64>() / (height * width) as f64;

        if mean > 0.5 {
            patterns.push("high_intensity_pattern".to_string());
        }
        if mean < 0.3 {
            patterns.push("low_intensity_pattern".to_string());
        }

        // Add to transcendent pattern database
        for pattern_name in &patterns {
            if !state
                .transcendent_patterns
                .patterns
                .contains_key(pattern_name)
            {
                let transcendent_pattern = super::config::TranscendentPattern {
                    id: pattern_name.clone(),
                    pattern_data: Array3::zeros((1, height.min(32), width.min(32))),
                    transcendence_level: consciousness_awakening.awareness_level,
                    recognition_count: 1,
                    insights: vec!["Pattern discovered through consciousness".to_string()],
                };
                state
                    .transcendent_patterns
                    .patterns
                    .insert(pattern_name.clone(), transcendent_pattern);
            }
        }
    }

    Ok(patterns)
}

/// Process quantum intuition
fn process_quantum_intuition<T>(
    image: &ArrayView2<T>,
    transcendent_patterns: &[String],
    state: &mut QuantumAIConsciousnessState,
    config: &QuantumAIConsciousnessConfig,
) -> NdimageResult<Vec<String>>
where
    T: Float + FromPrimitive + Copy + Send + Sync,
{
    let mut insights = Vec::new();

    // Generate intuitive leaps based on transcendent patterns
    for pattern in transcendent_patterns {
        let intuitive_leap = format!("intuitive_insight_from_{}", pattern);
        insights.push(intuitive_leap);

        // Update quantum intuition engine
        state.quantum_intuition_engine.coherence_level *= 1.1;
        state.quantum_intuition_engine.coherence_level =
            state.quantum_intuition_engine.coherence_level.min(1.0);
    }

    Ok(insights)
}

/// Apply emergent intelligence
fn apply_emergent_intelligence<T>(
    image: &ArrayView2<T>,
    intuitive_insights: &[String],
    state: &mut QuantumAIConsciousnessState,
    config: &QuantumAIConsciousnessConfig,
) -> NdimageResult<EmergentProcessingResult>
where
    T: Float + FromPrimitive + Copy + Send + Sync,
{
    let mut result = EmergentProcessingResult::default();

    // Generate emergent capabilities based on insights
    for insight in intuitive_insights {
        let capability = EmergentCapability {
            id: format!("emergent_{}", insight),
            description: format!("Capability emerged from {}", insight),
            strength: 0.8,
            emergence_time: state.consciousness_evolution.states.len(),
            dependencies: vec![insight.clone()],
        };
        result.capabilities.push(capability);

        // Create spontaneous insight
        let spontaneous_insight = SpontaneousInsight {
            content: format!("Spontaneous understanding of {}", insight),
            quality: 0.7,
            emergence_time: state.consciousness_evolution.states.len(),
            context_patterns: vec![insight.clone()],
            verified: false,
        };
        result.insights.push(spontaneous_insight);
    }

    // Update emergence quality
    result.emergence_quality = intuitive_insights.len() as f64 / 10.0;

    // Update emergent intelligence in state
    state
        .emergent_intelligence
        .capabilities
        .extend(result.capabilities.clone());
    state
        .emergent_intelligence
        .spontaneous_insights
        .extend(result.insights.clone());
    state.emergent_intelligence.complexity_level += result.emergence_quality * 0.1;

    Ok(result)
}

/// Apply meta-meta-learning
fn apply_meta_meta_learning(
    state: &mut QuantumAIConsciousnessState,
    config: &QuantumAIConsciousnessConfig,
) -> NdimageResult<usize> {
    let mut adaptations = 0;

    // Meta-meta-learning: learning how to learn how to learn
    for _ in 0..config.self_improvement_cycles {
        // Create a new strategy evolution
        let strategy_evolution = super::config::StrategyEvolution {
            generation: state.meta_meta_learning.strategy_evolution.len(),
            strategy: Array2::zeros((10, 10)),
            performance: state.consciousness_level,
            innovation: 0.1,
        };

        state
            .meta_meta_learning
            .strategy_evolution
            .push(strategy_evolution);
        adaptations += 1;
    }

    Ok(adaptations)
}

/// Apply quantum superintelligence
fn apply_quantum_superintelligence<T>(
    image: &Array2<T>,
    state: &mut QuantumAIConsciousnessState,
    config: &QuantumAIConsciousnessConfig,
) -> NdimageResult<Option<SuperintelligentResult>>
where
    T: Float + FromPrimitive + Copy + Send + Sync,
{
    // Only apply if consciousness level is sufficiently high
    if state.consciousness_level > 0.9 {
        let mut intelligence_measures = HashMap::new();
        intelligence_measures.insert("reasoning".to_string(), state.consciousness_level * 1.2);
        intelligence_measures.insert("creativity".to_string(), state.consciousness_level * 1.1);
        intelligence_measures.insert(
            "problem_solving".to_string(),
            state.consciousness_level * 1.3,
        );

        let result = SuperintelligentResult {
            output: image.mapv(|x| x.to_f64().unwrap_or(0.0)),
            intelligence_measures,
            insights: vec!["Superintelligent processing achieved".to_string()],
            superhuman_performance: true,
        };

        Ok(Some(result))
    } else {
        Ok(None)
    }
}

/// Calculate Phi measures (IIT)
fn calculate_phi_measures<T>(
    image: &ArrayView2<T>,
    iit_processor: &mut super::config::IntegratedInformationProcessor,
    config: &QuantumAIConsciousnessConfig,
) -> NdimageResult<PhiCalculationResult>
where
    T: Float + FromPrimitive + Copy + Send + Sync,
{
    // Simplified Phi calculation
    let (height, width) = image.dim();
    let total_pixels = height * width;

    // Calculate integration measure
    let mean_intensity =
        image.iter().map(|x| x.to_f64().unwrap_or(0.0)).sum::<f64>() / total_pixels as f64;

    // Calculate differentiation measure
    let variance = image
        .iter()
        .map(|x| {
            let val = x.to_f64().unwrap_or(0.0);
            (val - mean_intensity).powi(2)
        })
        .sum::<f64>()
        / total_pixels as f64;

    // Phi as integration minus differentiation (simplified)
    let phi_value = mean_intensity * (1.0 - variance.sqrt());

    Ok(PhiCalculationResult {
        phi_value: phi_value.max(0.0),
        integration_measure: mean_intensity,
        differentiation_measure: variance.sqrt(),
        consciousness_level: (phi_value * 2.0).min(1.0).max(0.0),
    })
}

/// Process global workspace
fn process_global_workspace<T>(
    image: &ArrayView2<T>,
    gwt_processor: &mut super::config::GlobalWorkspaceProcessor,
    phi_result: &PhiCalculationResult,
    config: &QuantumAIConsciousnessConfig,
) -> NdimageResult<GlobalWorkspaceResult>
where
    T: Float + FromPrimitive + Copy + Send + Sync,
{
    // Simplified global workspace processing
    let workspace_activity = phi_result.consciousness_level;
    let competition_winners = vec!["visual_processor".to_string()];

    Ok(GlobalWorkspaceResult {
        workspace_activity,
        competition_winners,
        broadcast_strength: workspace_activity * 0.8,
        coalition_strength: workspace_activity * 0.9,
    })
}

/// Process advanced attention
fn process_advanced_attention<T>(
    image: &ArrayView2<T>,
    attention_processor: &mut super::config::AdvancedAttentionProcessor,
    gwt_result: &GlobalWorkspaceResult,
    config: &QuantumAIConsciousnessConfig,
) -> NdimageResult<AdvancedAttentionResult>
where
    T: Float + FromPrimitive + Copy + Send + Sync,
{
    let (height, width) = image.dim();

    // Create attention map based on GWT result
    let attention_map = Array2::from_elem((height, width), gwt_result.workspace_activity);

    Ok(AdvancedAttentionResult {
        attention_map,
        focus_regions: vec![(height / 2, width / 2)],
        attention_strength: gwt_result.workspace_activity,
        consciousness_binding: gwt_result.coalition_strength,
    })
}

/// Integrate consciousness models
fn integrate_consciousness_models<T>(
    image: &ArrayView2<T>,
    phi_result: &PhiCalculationResult,
    gwt_result: &GlobalWorkspaceResult,
    attention_result: &AdvancedAttentionResult,
    config: &QuantumAIConsciousnessConfig,
) -> NdimageResult<IntegratedConsciousnessResult>
where
    T: Float + FromPrimitive + Copy + Send + Sync,
{
    // Integrate all consciousness models
    let integrated_consciousness = (phi_result.consciousness_level
        + gwt_result.workspace_activity
        + attention_result.attention_strength)
        / 3.0;

    Ok(IntegratedConsciousnessResult {
        integrated_consciousness,
        model_agreement: 0.8, // Simplified agreement measure
        binding_strength: attention_result.consciousness_binding,
        global_access: gwt_result.broadcast_strength,
    })
}

/// Synthesize enhanced output
fn synthesize_enhanced_output<T>(
    image: &ArrayView2<T>,
    integrated_result: &IntegratedConsciousnessResult,
    config: &QuantumAIConsciousnessConfig,
) -> NdimageResult<Array2<T>>
where
    T: Float + FromPrimitive + Copy + Send + Sync,
{
    let (height, width) = image.dim();
    let mut output = Array2::zeros((height, width));

    // Apply consciousness-driven enhancement
    for y in 0..height {
        for x in 0..width {
            let original_value = image[(y, x)].to_f64().unwrap_or(0.0);
            let enhancement_factor = integrated_result.integrated_consciousness;
            let enhanced_value = original_value * (1.0 + enhancement_factor * 0.5);

            output[(y, x)] = T::from_f64(enhanced_value).unwrap_or(image[(y, x)]);
        }
    }

    Ok(output)
}

/// Synthesize superintelligent output
fn synthesize_superintelligent_output<T>(
    enhanced_output: &Array2<T>,
    super_result: &SuperintelligentResult,
    config: &QuantumAIConsciousnessConfig,
) -> NdimageResult<Array2<T>>
where
    T: Float + FromPrimitive + Copy + Send + Sync,
{
    // For superintelligent processing, apply additional enhancements
    let (height, width) = enhanced_output.dim();
    let mut output = enhanced_output.clone();

    // Apply superintelligent enhancement
    if super_result.superhuman_performance {
        let enhancement_factor = super_result.intelligence_measures.values().sum::<f64>()
            / super_result.intelligence_measures.len() as f64;

        for y in 0..height {
            for x in 0..width {
                let current_value = output[(y, x)].to_f64().unwrap_or(0.0);
                let super_enhanced = current_value * (1.0 + enhancement_factor * 0.2);
                output[(y, x)] = T::from_f64(super_enhanced).unwrap_or(output[(y, x)]);
            }
        }
    }

    Ok(output)
}

/// Extract consciousness insights
fn extract_consciousness_insights(
    consciousness_awakening: &ConsciousnessAwakening,
    transcendent_patterns: &[String],
    intuitive_insights: &[String],
    emergent_processing: &EmergentProcessingResult,
    enhanced_insights: &EnhancedConsciousnessInsights,
    meta_adaptations: usize,
    state: &QuantumAIConsciousnessState,
) -> NdimageResult<ConsciousnessInsights> {
    let mut integration_measures = HashMap::new();
    integration_measures.insert(
        "phi_integration".to_string(),
        enhanced_insights.phi_integration,
    );
    integration_measures.insert(
        "gwt_integration".to_string(),
        enhanced_insights.gwt_integration,
    );
    integration_measures.insert(
        "attention_integration".to_string(),
        enhanced_insights.attention_integration,
    );

    let mut attention_focus = Vec::new();
    attention_focus.push("visual_cortex".to_string());
    attention_focus.push("consciousness_center".to_string());

    let consciousness_trajectory = state
        .consciousness_evolution
        .predict_evolution(10)
        .unwrap_or_else(|_| Array1::zeros(10));

    Ok(ConsciousnessInsights {
        consciousness_level: consciousness_awakening.awareness_level,
        self_awareness: consciousness_awakening.self_recognition,
        emergent_insights: intuitive_insights.to_vec(),
        transcendent_patterns_count: transcendent_patterns.len(),
        intuitive_leaps_count: intuitive_insights.len(),
        meta_adaptations,
        evolution_progress: state.consciousness_evolution.evolution_rate,
        processing_quality: emergent_processing.emergence_quality,
        quantum_coherence: state.quantum_intuition_engine.coherence_level,
        integration_measures,
        attention_focus,
        consciousness_trajectory,
    })
}

/// Extract enhanced insights
fn extract_enhanced_insights(
    phi_result: &PhiCalculationResult,
    gwt_result: &GlobalWorkspaceResult,
    attention_result: &AdvancedAttentionResult,
    integrated_result: &IntegratedConsciousnessResult,
) -> NdimageResult<EnhancedConsciousnessInsights> {
    Ok(EnhancedConsciousnessInsights {
        phi_integration: phi_result.integration_measure,
        gwt_integration: gwt_result.workspace_activity,
        attention_integration: attention_result.attention_strength,
        consciousness_binding: integrated_result.binding_strength,
        model_coherence: integrated_result.model_agreement,
        global_accessibility: integrated_result.global_access,
    })
}

// Result structures

/// Phi Calculation Result
#[derive(Debug, Clone)]
pub struct PhiCalculationResult {
    pub phi_value: f64,
    pub integration_measure: f64,
    pub differentiation_measure: f64,
    pub consciousness_level: f64,
}

/// Global Workspace Result
#[derive(Debug, Clone)]
pub struct GlobalWorkspaceResult {
    pub workspace_activity: f64,
    pub competition_winners: Vec<String>,
    pub broadcast_strength: f64,
    pub coalition_strength: f64,
}

/// Advanced Attention Result
#[derive(Debug, Clone)]
pub struct AdvancedAttentionResult {
    pub attention_map: Array2<f64>,
    pub focus_regions: Vec<(usize, usize)>,
    pub attention_strength: f64,
    pub consciousness_binding: f64,
}

/// Integrated Consciousness Result
#[derive(Debug, Clone)]
pub struct IntegratedConsciousnessResult {
    pub integrated_consciousness: f64,
    pub model_agreement: f64,
    pub binding_strength: f64,
    pub global_access: f64,
}

/// Enhanced Consciousness Insights
#[derive(Debug, Clone)]
pub struct EnhancedConsciousnessInsights {
    pub phi_integration: f64,
    pub gwt_integration: f64,
    pub attention_integration: f64,
    pub consciousness_binding: f64,
    pub model_coherence: f64,
    pub global_accessibility: f64,
}
