//! Graph generation logic for trait relationship visualization
//!
//! This module provides the core functionality for generating trait relationship
//! graphs from source code analysis, with support for hierarchical relationships,
//! implementations, associated types, and complex trait dependencies.

use super::graph_config::{GraphConfig, TraitNodeType, EdgeType, StabilityLevel, OptimizationLevel};
use super::graph_structures::{
    TraitGraph, TraitGraphNode, TraitGraphEdge, NodeMetadata, EdgeMetadata,
    TraitGraphMetadata, GraphStatistics, PerformanceMetrics,
};
use crate::api_reference_generator::{AssociatedType, TraitInfo};
use crate::error::{Result, SklearsError};

// SciRS2 Core imports for full compliance
use scirs2_core::ndarray::{Array, Array1, Array2, ArrayView1, ArrayView2, Axis};
use scirs2_core::random::{Random, rng};
use scirs2_core::gpu::{GpuBuffer, GpuContext, GpuKernel};
use scirs2_core::profiling::{profiling_memory_tracker, Profiler};
use scirs2_core::validation::{check_finite, check_in_bounds};

use chrono::Utc;
use std::collections::{HashMap, HashSet, VecDeque};
use std::sync::{Arc, Mutex, RwLock};
use std::time::{Duration, Instant};

/// Main generator for trait relationship graphs with advanced capabilities
#[derive(Debug)]
pub struct TraitGraphGenerator {
    /// Configuration for graph generation
    config: GraphConfig,
    /// Random number generator for stochastic algorithms
    rng: Arc<Mutex<Random>>,
    /// GPU context for acceleration (optional)
    gpu_context: Option<GpuContext>,
    /// Profiler for performance tracking
    profiler: Arc<Mutex<Profiler>>,
    /// Layout algorithms registry
    layout_algorithms: HashMap<String, Box<dyn LayoutAlgorithmImpl + Send + Sync>>,
    /// Layout computation cache
    layout_cache: Arc<RwLock<HashMap<String, LayoutResult>>>,
}

/// Trait for layout algorithm implementations
pub trait LayoutAlgorithmImpl: Send + Sync {
    fn compute_layout(&self, graph: &TraitGraph, config: &GraphConfig) -> Result<LayoutResult>;
    fn get_algorithm_name(&self) -> &str;
    fn supports_3d(&self) -> bool;
    fn get_quality_metrics(&self, result: &LayoutResult) -> LayoutQualityMetrics;
}

/// Result of layout computation
#[derive(Debug, Clone)]
pub struct LayoutResult {
    /// 2D positions for nodes
    pub positions_2d: HashMap<String, (f64, f64)>,
    /// 3D positions for nodes (if supported)
    pub positions_3d: Option<HashMap<String, (f64, f64, f64)>>,
    /// Quality metrics for the layout
    pub quality_metrics: LayoutQualityMetrics,
    /// Time taken for computation
    pub computation_time: Duration,
}

/// Quality metrics for layout evaluation
#[derive(Debug, Clone)]
pub struct LayoutQualityMetrics {
    /// Number of edge crossings
    pub edge_crossings: usize,
    /// Average edge length
    pub average_edge_length: f64,
    /// Distribution uniformity (0.0-1.0)
    pub distribution_uniformity: f64,
    /// Overall aesthetic score (0.0-1.0)
    pub aesthetic_score: f64,
}

impl std::fmt::Debug for TraitGraphGenerator {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        f.debug_struct("TraitGraphGenerator")
            .field("config", &self.config)
            .field("has_gpu_context", &self.gpu_context.is_some())
            .field("layout_algorithms_count", &self.layout_algorithms.len())
            .finish()
    }
}

impl TraitGraphGenerator {
    /// Create a new graph generator with the specified configuration
    pub fn new(config: GraphConfig) -> Result<Self> {
        let rng = Arc::new(Mutex::new(Random::seed(42)));
        let profiler = Arc::new(Mutex::new(Profiler::new()));

        // Initialize GPU context if enabled
        let gpu_context = if config.enable_gpu {
            // TODO: Implement proper GPU context initialization
            eprintln!("Warning: GPU acceleration not yet implemented, falling back to CPU");
            None
        } else {
            None
        };

        // Initialize layout algorithms
        let mut layout_algorithms: HashMap<String, Box<dyn LayoutAlgorithmImpl + Send + Sync>> = HashMap::new();
        layout_algorithms.insert("force_directed".to_string(), Box::new(ForceDirectedLayout::new()));
        layout_algorithms.insert("hierarchical".to_string(), Box::new(HierarchicalLayout::new()));
        layout_algorithms.insert("circular".to_string(), Box::new(CircularLayout::new()));
        layout_algorithms.insert("grid".to_string(), Box::new(GridLayout::new()));
        layout_algorithms.insert("radial".to_string(), Box::new(RadialLayout::new()));

        let layout_cache = Arc::new(RwLock::new(HashMap::new()));

        Ok(Self {
            config,
            rng,
            gpu_context,
            profiler,
            layout_algorithms,
            layout_cache,
        })
    }

    /// Generate a trait-specific graph focusing on a particular trait
    pub fn generate_trait_graph(
        &self,
        trait_info: &TraitInfo,
        implementations: &[String],
    ) -> Result<TraitGraph> {
        let start_time = Instant::now();

        // Start profiling
        if let Ok(mut profiler) = self.profiler.lock() {
            profiler.start_section("graph_generation");
        }

        let mut nodes = Vec::new();
        let mut edges = Vec::new();

        // Create main trait node
        let main_node = self.create_trait_node(trait_info)?;
        nodes.push(main_node);

        // Add supertrait nodes and edges
        for supertrait in &trait_info.supertraits {
            let supertrait_node = self.create_supertrait_node(supertrait)?;
            nodes.push(supertrait_node);

            let edge = TraitGraphEdge {
                from: supertrait.clone(),
                to: trait_info.name.clone(),
                edge_type: EdgeType::Inherits,
                weight: 1.0,
                thickness: Some(2.0),
                color: None,
                label: Some("inherits".to_string()),
                directed: true,
                metadata: EdgeMetadata {
                    confidence: 1.0,
                    source: "source_code".to_string(),
                    source_line: None,
                    conditional: false,
                    conditions: Vec::new(),
                    feature_flags: Vec::new(),
                    attributes: HashMap::new(),
                },
            };
            edges.push(edge);
        }

        // Add implementation nodes and edges
        for implementation in implementations {
            let impl_node = self.create_implementation_node(implementation, &trait_info.name)?;
            nodes.push(impl_node);

            let edge = TraitGraphEdge {
                from: trait_info.name.clone(),
                to: implementation.clone(),
                edge_type: EdgeType::Implements,
                weight: 0.8,
                thickness: Some(1.5),
                color: None,
                label: Some("implements".to_string()),
                directed: true,
                metadata: EdgeMetadata {
                    confidence: 0.9,
                    source: "source_code".to_string(),
                    source_line: None,
                    conditional: false,
                    conditions: Vec::new(),
                    feature_flags: Vec::new(),
                    attributes: HashMap::new(),
                },
            };
            edges.push(edge);
        }

        // Add associated type nodes if any
        for associated_type in &trait_info.associated_types {
            let assoc_node = self.create_associated_type_node(&associated_type.name, &trait_info.name)?;
            nodes.push(assoc_node);

            let edge = TraitGraphEdge {
                from: trait_info.name.clone(),
                to: associated_type.name.clone(),
                edge_type: EdgeType::AssociatedWith,
                weight: 0.6,
                thickness: Some(1.0),
                color: None,
                label: Some("defines".to_string()),
                directed: true,
                metadata: EdgeMetadata {
                    confidence: 1.0,
                    source: "source_code".to_string(),
                    source_line: None,
                    conditional: false,
                    conditions: Vec::new(),
                    feature_flags: Vec::new(),
                    attributes: HashMap::new(),
                },
            };
            edges.push(edge);
        }

        // Add method nodes if configured
        if self.config.filter_config.node_types.contains(&TraitNodeType::Method) {
            for method in &trait_info.methods {
                let method_node = self.create_method_node(&method.name, &trait_info.name)?;
                nodes.push(method_node);

                let edge = TraitGraphEdge {
                    from: trait_info.name.clone(),
                    to: method.name.clone(),
                    edge_type: EdgeType::DefinesMethod,
                    weight: 0.4,
                    thickness: Some(0.8),
                    color: None,
                    label: Some("defines".to_string()),
                    directed: true,
                    metadata: EdgeMetadata {
                        confidence: 1.0,
                        source: "source_code".to_string(),
                        source_line: None,
                        conditional: false,
                        conditions: Vec::new(),
                        feature_flags: Vec::new(),
                        attributes: HashMap::new(),
                    },
                };
                edges.push(edge);
            }
        }

        // Filter nodes and edges based on configuration
        self.apply_filters(&mut nodes, &mut edges)?;

        // Create graph metadata
        let metadata = TraitGraphMetadata {
            title: format!("Trait Graph: {}", trait_info.name),
            description: Some(format!("Relationship graph for trait {}", trait_info.name)),
            generated_at: Utc::now(),
            generator_version: env!("CARGO_PKG_VERSION").to_string(),
            source_project: None,
            git_commit: None,
            tags: vec!["trait".to_string(), "relationships".to_string()],
            custom_metadata: HashMap::new(),
        };

        // Calculate statistics
        let statistics = GraphStatistics::from_graph(&nodes, &edges);

        // Record performance metrics
        let generation_time = start_time.elapsed();
        let performance = PerformanceMetrics {
            generation_time,
            layout_time: Duration::from_secs(0), // Will be updated by layout computation
            analysis_time: Duration::from_secs(0),
            memory_usage: self.estimate_memory_usage(&nodes, &edges),
            layout_iterations: 0,
            cpu_utilization: 0.0,
            gpu_accelerated: self.gpu_context.is_some(),
            simd_optimized: self.config.enable_simd,
        };

        // End profiling
        if let Ok(mut profiler) = self.profiler.lock() {
            profiler.end_section("graph_generation");
        }

        let mut graph = TraitGraph {
            nodes,
            edges,
            metadata,
            statistics,
            performance,
        };

        // Apply layout if requested
        if self.config.enable_analysis {
            self.apply_layout(&mut graph)?;
        }

        Ok(graph)
    }

    /// Generate a comprehensive graph from multiple traits
    pub fn generate_full_graph(&self, traits: &[&TraitInfo]) -> Result<TraitGraph> {
        let start_time = Instant::now();

        let mut nodes = Vec::new();
        let mut edges = Vec::new();
        let mut processed_traits = HashSet::new();

        // Process each trait
        for trait_info in traits {
            if processed_traits.contains(&trait_info.name) {
                continue;
            }

            // Add main trait node
            let trait_node = self.create_trait_node(trait_info)?;
            nodes.push(trait_node);
            processed_traits.insert(trait_info.name.clone());

            // Process supertraits
            for supertrait in &trait_info.supertraits {
                if !processed_traits.contains(supertrait) {
                    let supertrait_node = self.create_supertrait_node(supertrait)?;
                    nodes.push(supertrait_node);
                    processed_traits.insert(supertrait.clone());
                }

                // Add inheritance edge
                let edge = TraitGraphEdge {
                    from: supertrait.clone(),
                    to: trait_info.name.clone(),
                    edge_type: EdgeType::Inherits,
                    weight: 1.0,
                    thickness: Some(2.0),
                    color: None,
                    label: Some("inherits".to_string()),
                    directed: true,
                    metadata: EdgeMetadata::default(),
                };
                edges.push(edge);
            }

            // Process associated types
            for associated_type in &trait_info.associated_types {
                let assoc_node = self.create_associated_type_node(&associated_type.name, &trait_info.name)?;
                nodes.push(assoc_node);

                let edge = TraitGraphEdge {
                    from: trait_info.name.clone(),
                    to: associated_type.name.clone(),
                    edge_type: EdgeType::AssociatedWith,
                    weight: 0.6,
                    thickness: Some(1.0),
                    color: None,
                    label: Some("defines".to_string()),
                    directed: true,
                    metadata: EdgeMetadata::default(),
                };
                edges.push(edge);
            }

            // Process methods if configured
            if self.config.filter_config.node_types.contains(&TraitNodeType::Method) {
                for method in &trait_info.methods {
                    let method_node = self.create_method_node(&method.name, &trait_info.name)?;
                    nodes.push(method_node);

                    let edge = TraitGraphEdge {
                        from: trait_info.name.clone(),
                        to: method.name.clone(),
                        edge_type: EdgeType::DefinesMethod,
                        weight: 0.4,
                        thickness: Some(0.8),
                        color: None,
                        label: Some("defines".to_string()),
                        directed: true,
                        metadata: EdgeMetadata::default(),
                    };
                    edges.push(edge);
                }
            }
        }

        // Add cross-trait relationships
        self.add_cross_trait_relationships(&mut edges, traits)?;

        // Apply filters
        self.apply_filters(&mut nodes, &mut edges)?;

        // Create comprehensive metadata
        let metadata = TraitGraphMetadata {
            title: "Comprehensive Trait Relationship Graph".to_string(),
            description: Some(format!("Complete relationship graph for {} traits", traits.len())),
            generated_at: Utc::now(),
            generator_version: env!("CARGO_PKG_VERSION").to_string(),
            source_project: None,
            git_commit: None,
            tags: vec!["traits".to_string(), "comprehensive".to_string(), "relationships".to_string()],
            custom_metadata: HashMap::new(),
        };

        let statistics = GraphStatistics::from_graph(&nodes, &edges);
        let performance = PerformanceMetrics {
            generation_time: start_time.elapsed(),
            layout_time: Duration::from_secs(0),
            analysis_time: Duration::from_secs(0),
            memory_usage: self.estimate_memory_usage(&nodes, &edges),
            layout_iterations: 0,
            cpu_utilization: 0.0,
            gpu_accelerated: self.gpu_context.is_some(),
            simd_optimized: self.config.enable_simd,
        };

        let mut graph = TraitGraph {
            nodes,
            edges,
            metadata,
            statistics,
            performance,
        };

        // Apply layout
        if self.config.enable_analysis {
            self.apply_layout(&mut graph)?;
        }

        Ok(graph)
    }

    /// Create a trait node from trait information
    fn create_trait_node(&self, trait_info: &TraitInfo) -> Result<TraitGraphNode> {
        let complexity = self.calculate_trait_complexity(trait_info);
        let stability = self.determine_stability_level(trait_info);

        let metadata = NodeMetadata {
            documentation: trait_info.docs.clone(),
            source_file: trait_info.source_file.clone(),
            source_line: trait_info.source_line,
            stability,
            complexity,
            created_at: None,
            modified_at: None,
            trait_name: Some(trait_info.name.clone()),
            generic_parameters: trait_info.generics.clone(),
            where_clauses: Vec::new(), // TODO: Extract from trait_info
            deprecation_note: None,
            feature_flags: trait_info.feature_flags.clone(),
            module_path: trait_info.module_path.clone(),
            visibility: Some(trait_info.visibility.clone()),
            attributes: HashMap::new(),
        };

        let size = self.calculate_node_size(complexity, &trait_info.methods, &trait_info.associated_types);

        Ok(TraitGraphNode {
            id: trait_info.name.clone(),
            label: trait_info.name.clone(),
            node_type: TraitNodeType::Trait,
            position_2d: None,
            position_3d: None,
            size,
            color: Some(TraitNodeType::Trait.default_color().to_string()),
            shape: Some(TraitNodeType::Trait.default_shape().to_string()),
            visible: true,
            metadata,
        })
    }

    /// Create a supertrait node
    fn create_supertrait_node(&self, supertrait_name: &str) -> Result<TraitGraphNode> {
        let metadata = NodeMetadata {
            trait_name: Some(supertrait_name.to_string()),
            stability: StabilityLevel::Stable, // Default assumption
            complexity: 5.0, // Default complexity
            ..Default::default()
        };

        Ok(TraitGraphNode {
            id: supertrait_name.to_string(),
            label: supertrait_name.to_string(),
            node_type: TraitNodeType::Trait,
            position_2d: None,
            position_3d: None,
            size: 1.0,
            color: Some(TraitNodeType::Trait.default_color().to_string()),
            shape: Some(TraitNodeType::Trait.default_shape().to_string()),
            visible: true,
            metadata,
        })
    }

    /// Create an implementation node
    fn create_implementation_node(&self, impl_name: &str, trait_name: &str) -> Result<TraitGraphNode> {
        let metadata = NodeMetadata {
            trait_name: Some(trait_name.to_string()),
            stability: StabilityLevel::Stable,
            complexity: 3.0,
            ..Default::default()
        };

        Ok(TraitGraphNode {
            id: impl_name.to_string(),
            label: impl_name.to_string(),
            node_type: TraitNodeType::Implementation,
            position_2d: None,
            position_3d: None,
            size: 0.8,
            color: Some(TraitNodeType::Implementation.default_color().to_string()),
            shape: Some(TraitNodeType::Implementation.default_shape().to_string()),
            visible: true,
            metadata,
        })
    }

    /// Create an associated type node
    fn create_associated_type_node(&self, type_name: &str, trait_name: &str) -> Result<TraitGraphNode> {
        let metadata = NodeMetadata {
            trait_name: Some(trait_name.to_string()),
            stability: StabilityLevel::Stable,
            complexity: 2.0,
            ..Default::default()
        };

        Ok(TraitGraphNode {
            id: format!("{}::{}", trait_name, type_name),
            label: type_name.to_string(),
            node_type: TraitNodeType::AssociatedType,
            position_2d: None,
            position_3d: None,
            size: 0.6,
            color: Some(TraitNodeType::AssociatedType.default_color().to_string()),
            shape: Some(TraitNodeType::AssociatedType.default_shape().to_string()),
            visible: true,
            metadata,
        })
    }

    /// Create a method node
    fn create_method_node(&self, method_name: &str, trait_name: &str) -> Result<TraitGraphNode> {
        let metadata = NodeMetadata {
            trait_name: Some(trait_name.to_string()),
            stability: StabilityLevel::Stable,
            complexity: 1.5,
            ..Default::default()
        };

        Ok(TraitGraphNode {
            id: format!("{}::{}", trait_name, method_name),
            label: method_name.to_string(),
            node_type: TraitNodeType::Method,
            position_2d: None,
            position_3d: None,
            size: 0.4,
            color: Some(TraitNodeType::Method.default_color().to_string()),
            shape: Some(TraitNodeType::Method.default_shape().to_string()),
            visible: true,
            metadata,
        })
    }

    /// Calculate trait complexity based on various factors
    fn calculate_trait_complexity(&self, trait_info: &TraitInfo) -> f64 {
        let method_complexity = trait_info.methods.len() as f64 * 2.0;
        let associated_type_complexity = trait_info.associated_types.len() as f64 * 3.0;
        let generic_complexity = trait_info.generics.len() as f64 * 1.5;
        let supertrait_complexity = trait_info.supertraits.len() as f64 * 2.5;

        let base_complexity = 1.0;
        let total = base_complexity + method_complexity + associated_type_complexity +
                   generic_complexity + supertrait_complexity;

        // Normalize to 0-100 scale
        total.min(100.0)
    }

    /// Determine stability level from trait information
    fn determine_stability_level(&self, trait_info: &TraitInfo) -> StabilityLevel {
        // Simple heuristics - in practice would analyze attributes and documentation
        if trait_info.feature_flags.contains(&"unstable".to_string()) {
            StabilityLevel::Unstable
        } else if trait_info.feature_flags.contains(&"experimental".to_string()) {
            StabilityLevel::Experimental
        } else if trait_info.docs.as_ref().map_or(false, |docs| docs.contains("deprecated")) {
            StabilityLevel::Deprecated
        } else {
            StabilityLevel::Stable
        }
    }

    /// Calculate appropriate node size based on complexity and content
    fn calculate_node_size(&self, complexity: f64, methods: &[crate::api_reference_generator::MethodInfo], associated_types: &[AssociatedType]) -> f64 {
        let base_size = 1.0;
        let complexity_factor = complexity / 50.0; // Normalize complexity
        let method_factor = methods.len() as f64 * 0.1;
        let type_factor = associated_types.len() as f64 * 0.15;

        (base_size + complexity_factor + method_factor + type_factor).max(0.3).min(3.0)
    }

    /// Apply filters to nodes and edges based on configuration
    fn apply_filters(&self, nodes: &mut Vec<TraitGraphNode>, edges: &mut Vec<TraitGraphEdge>) -> Result<()> {
        let filter_config = &self.config.filter_config;

        // Filter nodes by type
        nodes.retain(|node| filter_config.node_types.contains(&node.node_type));

        // Filter nodes by complexity
        nodes.retain(|node| {
            node.metadata.complexity >= filter_config.min_complexity &&
            node.metadata.complexity <= filter_config.max_complexity
        });

        // Filter nodes by stability
        nodes.retain(|node| filter_config.stability_levels.contains(&node.metadata.stability));

        // Filter nodes by deprecated status
        if !filter_config.include_deprecated {
            nodes.retain(|node| !node.metadata.is_deprecated());
        }

        // Filter nodes by experimental status
        if !filter_config.include_experimental {
            nodes.retain(|node| !node.metadata.is_experimental());
        }

        // Filter nodes by trait name patterns
        nodes.retain(|node| {
            if let Some(trait_name) = &node.metadata.trait_name {
                filter_config.matches_trait_name(trait_name)
            } else {
                filter_config.matches_trait_name(&node.label)
            }
        });

        // Create a set of valid node IDs
        let valid_node_ids: HashSet<String> = nodes.iter().map(|n| n.id.clone()).collect();

        // Filter edges by type
        edges.retain(|edge| filter_config.edge_types.contains(&edge.edge_type));

        // Filter edges to only include those connecting valid nodes
        edges.retain(|edge| {
            valid_node_ids.contains(&edge.from) && valid_node_ids.contains(&edge.to)
        });

        // Apply node count limit
        if nodes.len() > self.config.max_nodes {
            // Sort by importance and keep the most important nodes
            nodes.sort_by(|a, b| {
                b.importance_score().partial_cmp(&a.importance_score())
                    .unwrap_or(std::cmp::Ordering::Equal)
            });
            nodes.truncate(self.config.max_nodes);

            // Re-filter edges after node truncation
            let final_node_ids: HashSet<String> = nodes.iter().map(|n| n.id.clone()).collect();
            edges.retain(|edge| {
                final_node_ids.contains(&edge.from) && final_node_ids.contains(&edge.to)
            });
        }

        Ok(())
    }

    /// Add cross-trait relationships (usage, dependencies, etc.)
    fn add_cross_trait_relationships(&self, edges: &mut Vec<TraitGraphEdge>, traits: &[&TraitInfo]) -> Result<()> {
        // Simple implementation - look for trait names mentioned in other traits
        for trait_info in traits {
            for other_trait in traits {
                if trait_info.name == other_trait.name {
                    continue;
                }

                // Check if trait is mentioned in documentation or other contexts
                let mut has_relationship = false;

                // Check supertraits
                if trait_info.supertraits.contains(&other_trait.name) {
                    continue; // Already handled in main generation
                }

                // Check if other trait is used in generic constraints
                for generic in &trait_info.generics {
                    if generic.contains(&other_trait.name) {
                        has_relationship = true;
                        break;
                    }
                }

                // Check associated types for references
                if !has_relationship {
                    for assoc_type in &trait_info.associated_types {
                        if assoc_type.bounds.iter().any(|bound| bound.contains(&other_trait.name)) {
                            has_relationship = true;
                            break;
                        }
                    }
                }

                if has_relationship {
                    let edge = TraitGraphEdge {
                        from: trait_info.name.clone(),
                        to: other_trait.name.clone(),
                        edge_type: EdgeType::Uses,
                        weight: 0.3,
                        thickness: Some(0.5),
                        color: None,
                        label: Some("uses".to_string()),
                        directed: true,
                        metadata: EdgeMetadata {
                            confidence: 0.7,
                            source: "analysis".to_string(),
                            source_line: None,
                            conditional: true,
                            conditions: vec!["generic_constraint".to_string()],
                            feature_flags: Vec::new(),
                            attributes: HashMap::new(),
                        },
                    };
                    edges.push(edge);
                }
            }
        }

        Ok(())
    }

    /// Apply layout algorithm to position nodes
    fn apply_layout(&self, graph: &mut TraitGraph) -> Result<()> {
        let layout_start = Instant::now();

        // Check cache first
        let cache_key = self.generate_cache_key(graph);
        if let Ok(cache) = self.layout_cache.read() {
            if let Some(cached_result) = cache.get(&cache_key) {
                self.apply_layout_result(graph, cached_result);
                return Ok(());
            }
        }

        // Determine which layout algorithm to use
        let algorithm_name = match self.config.layout_algorithm {
            super::graph_config::LayoutAlgorithm::ForceDirected => "force_directed",
            super::graph_config::LayoutAlgorithm::Hierarchical => "hierarchical",
            super::graph_config::LayoutAlgorithm::Circular => "circular",
            super::graph_config::LayoutAlgorithm::Grid => "grid",
            super::graph_config::LayoutAlgorithm::Radial => "radial",
            _ => "force_directed", // Default fallback
        };

        // Get the layout algorithm
        let layout_result = if let Some(algorithm) = self.layout_algorithms.get(algorithm_name) {
            algorithm.compute_layout(graph, &self.config)?
        } else {
            return Err(SklearsError::ValidationError(
                format!("Layout algorithm '{}' not found", algorithm_name)
            ));
        };

        // Cache the result
        if let Ok(mut cache) = self.layout_cache.write() {
            cache.insert(cache_key, layout_result.clone());
        }

        // Apply layout result to graph
        self.apply_layout_result(graph, &layout_result);

        // Update performance metrics
        graph.performance.layout_time = layout_start.elapsed();
        graph.performance.layout_iterations = self.config.optimization_level.layout_iterations() as u32;

        Ok(())
    }

    /// Generate a cache key for layout results
    fn generate_cache_key(&self, graph: &TraitGraph) -> String {
        use std::collections::hash_map::DefaultHasher;
        use std::hash::{Hash, Hasher};

        let mut hasher = DefaultHasher::new();
        graph.nodes.len().hash(&mut hasher);
        graph.edges.len().hash(&mut hasher);
        format!("{:x}", hasher.finish())
    }

    /// Apply layout result to graph nodes
    fn apply_layout_result(&self, graph: &mut TraitGraph, layout_result: &LayoutResult) {
        for node in &mut graph.nodes {
            if let Some(&(x, y)) = layout_result.positions_2d.get(&node.id) {
                node.position_2d = Some((x, y));
            }

            if let Some(ref positions_3d) = layout_result.positions_3d {
                if let Some(&(x, y, z)) = positions_3d.get(&node.id) {
                    node.position_3d = Some((x, y, z));
                }
            }
        }
    }

    /// Estimate memory usage of the graph
    fn estimate_memory_usage(&self, nodes: &[TraitGraphNode], edges: &[TraitGraphEdge]) -> u64 {
        let node_size = std::mem::size_of::<TraitGraphNode>();
        let edge_size = std::mem::size_of::<TraitGraphEdge>();

        ((nodes.len() * node_size) + (edges.len() * edge_size)) as u64
    }

    /// Get configuration
    pub fn get_config(&self) -> &GraphConfig {
        &self.config
    }

    /// Update configuration
    pub fn set_config(&mut self, config: GraphConfig) {
        self.config = config;
    }

    /// Check if GPU acceleration is available
    pub fn has_gpu_acceleration(&self) -> bool {
        self.gpu_context.is_some()
    }

    /// Get layout algorithm names
    pub fn get_available_layouts(&self) -> Vec<String> {
        self.layout_algorithms.keys().cloned().collect()
    }

    /// Clear layout cache
    pub fn clear_layout_cache(&self) -> Result<()> {
        if let Ok(mut cache) = self.layout_cache.write() {
            cache.clear();
        }
        Ok(())
    }
}

// Placeholder layout algorithm implementations

/// Force-directed layout algorithm using physics simulation
#[derive(Debug)]
pub struct ForceDirectedLayout;

impl ForceDirectedLayout {
    pub fn new() -> Self {
        Self
    }
}

impl LayoutAlgorithmImpl for ForceDirectedLayout {
    fn compute_layout(&self, graph: &TraitGraph, config: &GraphConfig) -> Result<LayoutResult> {
        let start_time = Instant::now();
        let n = graph.nodes.len();

        if n == 0 {
            return Ok(LayoutResult {
                positions_2d: HashMap::new(),
                positions_3d: None,
                quality_metrics: LayoutQualityMetrics {
                    edge_crossings: 0,
                    average_edge_length: 0.0,
                    distribution_uniformity: 1.0,
                    aesthetic_score: 1.0,
                },
                computation_time: start_time.elapsed(),
            });
        }

        // Initialize random positions
        let mut rng = Random::seed(42);
        let mut positions_2d = HashMap::new();
        let mut positions_3d = if config.enable_3d {
            Some(HashMap::new())
        } else {
            None
        };

        // Place nodes in random positions
        for node in &graph.nodes {
            let x = rng.random_range(-100.0..100.0);
            let y = rng.random_range(-100.0..100.0);
            positions_2d.insert(node.id.clone(), (x, y));

            if let Some(ref mut pos_3d) = positions_3d {
                let z = rng.random_range(-100.0..100.0);
                pos_3d.insert(node.id.clone(), (x, y, z));
            }
        }

        // Simple force-directed simulation (placeholder)
        let iterations = config.optimization_level.layout_iterations();
        let k = (400.0 / n as f64).sqrt(); // Optimal distance between nodes

        for _iteration in 0..iterations {
            // Apply forces (simplified)
            // In a real implementation, this would be much more sophisticated
            for node in &graph.nodes {
                if let Some((x, y)) = positions_2d.get(&node.id).copied() {
                    let mut fx = 0.0;
                    let mut fy = 0.0;

                    // Repulsive forces from other nodes
                    for other_node in &graph.nodes {
                        if other_node.id != node.id {
                            if let Some((ox, oy)) = positions_2d.get(&other_node.id).copied() {
                                let dx = x - ox;
                                let dy = y - oy;
                                let distance = (dx * dx + dy * dy).sqrt().max(0.1);
                                let force = k * k / distance;
                                fx += force * dx / distance;
                                fy += force * dy / distance;
                            }
                        }
                    }

                    // Attractive forces from connected nodes
                    for edge in &graph.edges {
                        if edge.from == node.id || edge.to == node.id {
                            let other_id = if edge.from == node.id { &edge.to } else { &edge.from };
                            if let Some((ox, oy)) = positions_2d.get(other_id).copied() {
                                let dx = ox - x;
                                let dy = oy - y;
                                let distance = (dx * dx + dy * dy).sqrt().max(0.1);
                                let force = distance * distance / k;
                                fx += force * dx / distance;
                                fy += force * dy / distance;
                            }
                        }
                    }

                    // Apply displacement with cooling
                    let temp = 1.0 - (_iteration as f64 / iterations as f64);
                    let displacement = temp * 10.0;
                    let force_magnitude = (fx * fx + fy * fy).sqrt();
                    if force_magnitude > 0.0 {
                        let new_x = x + fx / force_magnitude * displacement.min(force_magnitude);
                        let new_y = y + fy / force_magnitude * displacement.min(force_magnitude);
                        positions_2d.insert(node.id.clone(), (new_x, new_y));
                    }
                }
            }
        }

        let quality_metrics = self.get_quality_metrics(&LayoutResult {
            positions_2d: positions_2d.clone(),
            positions_3d: positions_3d.clone(),
            quality_metrics: LayoutQualityMetrics {
                edge_crossings: 0,
                average_edge_length: 0.0,
                distribution_uniformity: 0.0,
                aesthetic_score: 0.0,
            },
            computation_time: Duration::from_secs(0),
        });

        Ok(LayoutResult {
            positions_2d,
            positions_3d,
            quality_metrics,
            computation_time: start_time.elapsed(),
        })
    }

    fn get_algorithm_name(&self) -> &str {
        "force_directed"
    }

    fn supports_3d(&self) -> bool {
        true
    }

    fn get_quality_metrics(&self, _result: &LayoutResult) -> LayoutQualityMetrics {
        // Placeholder implementation
        LayoutQualityMetrics {
            edge_crossings: 0,
            average_edge_length: 50.0,
            distribution_uniformity: 0.7,
            aesthetic_score: 0.8,
        }
    }
}

// Additional placeholder layout implementations

/// Hierarchical layout algorithm
#[derive(Debug)]
pub struct HierarchicalLayout;

impl HierarchicalLayout {
    pub fn new() -> Self {
        Self
    }
}

impl LayoutAlgorithmImpl for HierarchicalLayout {
    fn compute_layout(&self, graph: &TraitGraph, _config: &GraphConfig) -> Result<LayoutResult> {
        let start_time = Instant::now();
        let mut positions_2d = HashMap::new();

        // Simple hierarchical layout - arrange nodes in levels
        let mut y = 0.0;
        let x_spacing = 100.0;
        let y_spacing = 80.0;

        for (i, node) in graph.nodes.iter().enumerate() {
            let x = (i as f64) * x_spacing - ((graph.nodes.len() as f64 - 1.0) * x_spacing / 2.0);
            positions_2d.insert(node.id.clone(), (x, y));
        }

        Ok(LayoutResult {
            positions_2d,
            positions_3d: None,
            quality_metrics: LayoutQualityMetrics {
                edge_crossings: 0,
                average_edge_length: x_spacing,
                distribution_uniformity: 0.9,
                aesthetic_score: 0.7,
            },
            computation_time: start_time.elapsed(),
        })
    }

    fn get_algorithm_name(&self) -> &str {
        "hierarchical"
    }

    fn supports_3d(&self) -> bool {
        false
    }

    fn get_quality_metrics(&self, _result: &LayoutResult) -> LayoutQualityMetrics {
        LayoutQualityMetrics {
            edge_crossings: 0,
            average_edge_length: 100.0,
            distribution_uniformity: 0.9,
            aesthetic_score: 0.7,
        }
    }
}

/// Circular layout algorithm
#[derive(Debug)]
pub struct CircularLayout;

impl CircularLayout {
    pub fn new() -> Self {
        Self
    }
}

impl LayoutAlgorithmImpl for CircularLayout {
    fn compute_layout(&self, graph: &TraitGraph, _config: &GraphConfig) -> Result<LayoutResult> {
        let start_time = Instant::now();
        let mut positions_2d = HashMap::new();

        let n = graph.nodes.len();
        if n == 0 {
            return Ok(LayoutResult {
                positions_2d,
                positions_3d: None,
                quality_metrics: LayoutQualityMetrics {
                    edge_crossings: 0,
                    average_edge_length: 0.0,
                    distribution_uniformity: 1.0,
                    aesthetic_score: 1.0,
                },
                computation_time: start_time.elapsed(),
            });
        }

        let radius = 100.0;
        let angle_step = 2.0 * std::f64::consts::PI / n as f64;

        for (i, node) in graph.nodes.iter().enumerate() {
            let angle = i as f64 * angle_step;
            let x = radius * angle.cos();
            let y = radius * angle.sin();
            positions_2d.insert(node.id.clone(), (x, y));
        }

        Ok(LayoutResult {
            positions_2d,
            positions_3d: None,
            quality_metrics: LayoutQualityMetrics {
                edge_crossings: n / 4, // Rough estimate
                average_edge_length: radius,
                distribution_uniformity: 1.0,
                aesthetic_score: 0.6,
            },
            computation_time: start_time.elapsed(),
        })
    }

    fn get_algorithm_name(&self) -> &str {
        "circular"
    }

    fn supports_3d(&self) -> bool {
        false
    }

    fn get_quality_metrics(&self, _result: &LayoutResult) -> LayoutQualityMetrics {
        LayoutQualityMetrics {
            edge_crossings: 5,
            average_edge_length: 100.0,
            distribution_uniformity: 1.0,
            aesthetic_score: 0.6,
        }
    }
}

/// Grid layout algorithm
#[derive(Debug)]
pub struct GridLayout;

impl GridLayout {
    pub fn new() -> Self {
        Self
    }
}

impl LayoutAlgorithmImpl for GridLayout {
    fn compute_layout(&self, graph: &TraitGraph, _config: &GraphConfig) -> Result<LayoutResult> {
        let start_time = Instant::now();
        let mut positions_2d = HashMap::new();

        let n = graph.nodes.len();
        if n == 0 {
            return Ok(LayoutResult {
                positions_2d,
                positions_3d: None,
                quality_metrics: LayoutQualityMetrics {
                    edge_crossings: 0,
                    average_edge_length: 0.0,
                    distribution_uniformity: 1.0,
                    aesthetic_score: 1.0,
                },
                computation_time: start_time.elapsed(),
            });
        }

        let grid_size = (n as f64).sqrt().ceil() as usize;
        let spacing = 100.0;

        for (i, node) in graph.nodes.iter().enumerate() {
            let x = (i % grid_size) as f64 * spacing;
            let y = (i / grid_size) as f64 * spacing;
            positions_2d.insert(node.id.clone(), (x, y));
        }

        Ok(LayoutResult {
            positions_2d,
            positions_3d: None,
            quality_metrics: LayoutQualityMetrics {
                edge_crossings: n / 2, // Rough estimate
                average_edge_length: spacing,
                distribution_uniformity: 0.8,
                aesthetic_score: 0.5,
            },
            computation_time: start_time.elapsed(),
        })
    }

    fn get_algorithm_name(&self) -> &str {
        "grid"
    }

    fn supports_3d(&self) -> bool {
        false
    }

    fn get_quality_metrics(&self, _result: &LayoutResult) -> LayoutQualityMetrics {
        LayoutQualityMetrics {
            edge_crossings: 10,
            average_edge_length: 100.0,
            distribution_uniformity: 0.8,
            aesthetic_score: 0.5,
        }
    }
}

/// Radial layout algorithm
#[derive(Debug)]
pub struct RadialLayout;

impl RadialLayout {
    pub fn new() -> Self {
        Self
    }
}

impl LayoutAlgorithmImpl for RadialLayout {
    fn compute_layout(&self, graph: &TraitGraph, _config: &GraphConfig) -> Result<LayoutResult> {
        let start_time = Instant::now();
        let mut positions_2d = HashMap::new();

        // Place the most connected node at center
        let center_node = graph.nodes.iter()
            .max_by_key(|node| graph.get_degree(&node.id))
            .map(|node| node.id.clone())
            .unwrap_or_else(|| graph.nodes[0].id.clone());

        positions_2d.insert(center_node.clone(), (0.0, 0.0));

        // Place other nodes in concentric circles
        let mut radius = 80.0;
        let mut remaining_nodes: Vec<_> = graph.nodes.iter()
            .filter(|node| node.id != center_node)
            .collect();

        while !remaining_nodes.is_empty() {
            let nodes_in_ring = (2.0 * std::f64::consts::PI * radius / 60.0).floor() as usize;
            let nodes_to_place = nodes_in_ring.min(remaining_nodes.len());

            let angle_step = 2.0 * std::f64::consts::PI / nodes_to_place as f64;

            for i in 0..nodes_to_place {
                let angle = i as f64 * angle_step;
                let x = radius * angle.cos();
                let y = radius * angle.sin();
                positions_2d.insert(remaining_nodes[i].id.clone(), (x, y));
            }

            remaining_nodes.drain(0..nodes_to_place);
            radius += 80.0;
        }

        Ok(LayoutResult {
            positions_2d,
            positions_3d: None,
            quality_metrics: LayoutQualityMetrics {
                edge_crossings: graph.edges.len() / 8, // Rough estimate
                average_edge_length: radius / 2.0,
                distribution_uniformity: 0.7,
                aesthetic_score: 0.8,
            },
            computation_time: start_time.elapsed(),
        })
    }

    fn get_algorithm_name(&self) -> &str {
        "radial"
    }

    fn supports_3d(&self) -> bool {
        false
    }

    fn get_quality_metrics(&self, _result: &LayoutResult) -> LayoutQualityMetrics {
        LayoutQualityMetrics {
            edge_crossings: 3,
            average_edge_length: 80.0,
            distribution_uniformity: 0.7,
            aesthetic_score: 0.8,
        }
    }
}

#[allow(non_snake_case)]
#[cfg(test)]
mod tests {
    use super::*;
    use crate::api_reference_generator::{MethodInfo, Visibility};

    fn create_test_trait_info() -> TraitInfo {
        TraitInfo {
            name: "TestTrait".to_string(),
            docs: Some("A test trait".to_string()),
            module_path: Some("test::module".to_string()),
            visibility: Visibility::Public,
            generics: vec!["T".to_string()],
            supertraits: vec!["SuperTrait".to_string()],
            associated_types: vec![AssociatedType {
                name: "Output".to_string(),
                bounds: vec!["Clone".to_string()],
                default: None,
            }],
            methods: vec![MethodInfo {
                name: "test_method".to_string(),
                signature: "fn test_method(&self) -> Self::Output".to_string(),
                docs: None,
                is_required: true,
                is_async: false,
                is_unsafe: false,
                generics: Vec::new(),
                return_type: Some("Self::Output".to_string()),
                arguments: Vec::new(),
            }],
            source_file: Some("test.rs".to_string()),
            source_line: Some(42),
            feature_flags: Vec::new(),
        }
    }

    #[test]
    fn test_graph_generator_creation() {
        let config = GraphConfig::default();
        let generator = TraitGraphGenerator::new(config);
        assert!(generator.is_ok());
    }

    #[test]
    fn test_trait_graph_generation() {
        let config = GraphConfig::default();
        let generator = TraitGraphGenerator::new(config).expect("expected valid value");
        let trait_info = create_test_trait_info();
        let implementations = vec!["TestImpl".to_string()];

        let graph = generator.generate_trait_graph(&trait_info, &implementations);
        assert!(graph.is_ok());

        let graph = graph.expect("expected valid value");
        assert!(!graph.nodes.is_empty());
        assert!(!graph.edges.is_empty());
        assert!(graph.validate().is_ok());
    }

    #[test]
    fn test_full_graph_generation() {
        let config = GraphConfig::default();
        let generator = TraitGraphGenerator::new(config).expect("expected valid value");
        let trait_info = create_test_trait_info();
        let traits = vec![&trait_info];

        let graph = generator.generate_full_graph(&traits);
        assert!(graph.is_ok());

        let graph = graph.expect("expected valid value");
        assert!(!graph.nodes.is_empty());
    }

    #[test]
    fn test_trait_complexity_calculation() {
        let config = GraphConfig::default();
        let generator = TraitGraphGenerator::new(config).expect("expected valid value");
        let trait_info = create_test_trait_info();

        let complexity = generator.calculate_trait_complexity(&trait_info);
        assert!(complexity > 0.0);
        assert!(complexity <= 100.0);
    }

    #[test]
    fn test_layout_algorithms() {
        let force_directed = ForceDirectedLayout::new();
        assert_eq!(force_directed.get_algorithm_name(), "force_directed");
        assert!(force_directed.supports_3d());

        let hierarchical = HierarchicalLayout::new();
        assert_eq!(hierarchical.get_algorithm_name(), "hierarchical");
        assert!(!hierarchical.supports_3d());
    }

    #[test]
    fn test_node_creation() {
        let config = GraphConfig::default();
        let generator = TraitGraphGenerator::new(config).expect("expected valid value");
        let trait_info = create_test_trait_info();

        let node = generator.create_trait_node(&trait_info).expect("create_trait_node should succeed");
        assert_eq!(node.id, "TestTrait");
        assert_eq!(node.node_type, TraitNodeType::Trait);
        assert!(node.visible);
    }

    #[test]
    fn test_filters() {
        let mut config = GraphConfig::default();
        config.filter_config.max_complexity = 5.0;

        let generator = TraitGraphGenerator::new(config).expect("expected valid value");
        let trait_info = create_test_trait_info();

        let mut nodes = vec![generator.create_trait_node(&trait_info).expect("create_trait_node should succeed")];
        let mut edges = Vec::new();

        // This should work since our test trait has low complexity
        let result = generator.apply_filters(&mut nodes, &mut edges);
        assert!(result.is_ok());
    }

    #[test]
    fn test_memory_estimation() {
        let config = GraphConfig::default();
        let generator = TraitGraphGenerator::new(config).expect("expected valid value");

        let nodes = vec![TraitGraphNode::new_trait("test".to_string(), "Test".to_string())];
        let edges = vec![TraitGraphEdge::new_inheritance("a".to_string(), "b".to_string())];

        let memory = generator.estimate_memory_usage(&nodes, &edges);
        assert!(memory > 0);
    }

    #[test]
    fn test_available_layouts() {
        let config = GraphConfig::default();
        let generator = TraitGraphGenerator::new(config).expect("expected valid value");

        let layouts = generator.get_available_layouts();
        assert!(layouts.contains(&"force_directed".to_string()));
        assert!(layouts.contains(&"hierarchical".to_string()));
        assert!(layouts.contains(&"circular".to_string()));
    }
}