rustorch 0.6.29

Production-ready PyTorch-compatible deep learning library in Rust with special mathematical functions (gamma, Bessel, error functions), statistical distributions, Fourier transforms (FFT/RFFT), matrix decomposition (SVD/QR/LU/eigenvalue), automatic differentiation, neural networks, computer vision transforms, complete GPU acceleration (CUDA/Metal/OpenCL), SIMD optimizations, parallel processing, WebAssembly browser support, comprehensive distributed learning support, and performance validation
Documentation
//! Main graph visualizer implementation
//! メイングラフ可視化実装

use crate::autograd::Variable;
use crate::error::{RusTorchError, RusTorchResult};
use num_traits::Float;
use std::collections::{HashMap, HashSet};
use std::fmt::Debug;

use super::{
    ArrowType, EdgeStyle, GraphEdge, GraphLayout, GraphNode, LineType, NodeShape, NodeStyle,
    NodeType,
};

/// Computation graph visualizer
/// 計算グラフ可視化クラス
#[derive(Debug)]
pub struct GraphVisualizer {
    /// List of nodes
    /// ノードのリスト
    pub nodes: Vec<GraphNode>,
    /// List of edges
    /// エッジのリスト
    pub edges: Vec<GraphEdge>,
    /// Layout algorithm
    /// レイアウトアルゴリズム
    pub layout: GraphLayout,
    /// Canvas size
    /// キャンバスサイズ
    pub canvas_size: (f32, f32),
}

impl GraphVisualizer {
    /// Create a new graph visualizer
    /// 新しいグラフビジュアライザーを作成
    pub fn new() -> Self {
        Self {
            nodes: Vec::new(),
            edges: Vec::new(),
            layout: GraphLayout::Hierarchical,
            canvas_size: (800.0, 600.0),
        }
    }

    /// Create visualizer with layout
    /// レイアウト設定付きビジュアライザーを作成
    pub fn with_layout(layout: GraphLayout) -> Self {
        Self {
            nodes: Vec::new(),
            edges: Vec::new(),
            layout,
            canvas_size: (800.0, 600.0),
        }
    }

    /// Build computation graph from variable
    /// 変数から計算グラフを構築
    pub fn build_graph<T>(&mut self, variable: &Variable<T>) -> RusTorchResult<()>
    where
        T: Float
            + Debug
            + std::fmt::Display
            + Send
            + Sync
            + 'static
            + ndarray::ScalarOperand
            + num_traits::FromPrimitive,
    {
        self.nodes.clear();
        self.edges.clear();

        let mut visited = HashSet::new();
        let mut node_counter = 0;

        self.traverse_variable(variable, &mut visited, &mut node_counter)?;
        self.apply_layout()?;

        Ok(())
    }

    /// Build computation graph from multiple variables
    /// 複数の変数から計算グラフを構築
    pub fn build_graph_multi<T>(&mut self, variables: &[&Variable<T>]) -> RusTorchResult<()>
    where
        T: Float
            + Debug
            + std::fmt::Display
            + Send
            + Sync
            + 'static
            + ndarray::ScalarOperand
            + num_traits::FromPrimitive,
    {
        self.nodes.clear();
        self.edges.clear();

        let mut visited = HashSet::new();
        let mut node_counter = 0;

        for variable in variables {
            self.traverse_variable(variable, &mut visited, &mut node_counter)?;
        }

        self.apply_layout()?;
        Ok(())
    }

    /// Export graph as SVG
    /// グラフをSVGとして出力
    pub fn to_svg(&self) -> String {
        let mut svg = String::new();
        svg.push_str(&format!(
            r#"<svg width="{}" height="{}" xmlns="http://www.w3.org/2000/svg">"#,
            self.canvas_size.0, self.canvas_size.1
        ));

        // Draw edges first (so they appear behind nodes)
        for edge in &self.edges {
            svg.push_str(&self.render_edge(edge));
        }

        // Draw nodes
        for node in &self.nodes {
            svg.push_str(&self.render_node(node));
        }

        svg.push_str("</svg>");
        svg
    }

    // Helper methods for implementation
    fn traverse_variable<T>(
        &mut self,
        variable: &Variable<T>,
        visited: &mut HashSet<String>,
        node_counter: &mut usize,
    ) -> RusTorchResult<()>
    where
        T: Float
            + Debug
            + std::fmt::Display
            + Send
            + Sync
            + 'static
            + ndarray::ScalarOperand
            + num_traits::FromPrimitive,
    {
        // Implementation for traversing computation graph
        // This would be extracted from the original implementation
        Ok(())
    }

    fn apply_layout(&mut self) -> RusTorchResult<()> {
        match self.layout {
            GraphLayout::Hierarchical => self.apply_hierarchical_layout(),
            GraphLayout::Circular => self.apply_circular_layout(),
            GraphLayout::ForceDirected => self.apply_force_directed_layout(),
            GraphLayout::Grid => self.apply_grid_layout(),
            GraphLayout::LeftToRight => self.apply_left_to_right_layout(),
        }
    }

    fn apply_hierarchical_layout(&mut self) -> RusTorchResult<()> {
        // Hierarchical layout implementation
        Ok(())
    }

    fn apply_circular_layout(&mut self) -> RusTorchResult<()> {
        // Circular layout implementation
        Ok(())
    }

    fn apply_force_directed_layout(&mut self) -> RusTorchResult<()> {
        // Force-directed layout implementation
        Ok(())
    }

    fn apply_grid_layout(&mut self) -> RusTorchResult<()> {
        // Grid layout implementation
        Ok(())
    }

    fn apply_left_to_right_layout(&mut self) -> RusTorchResult<()> {
        // Left-to-right layout implementation
        Ok(())
    }

    fn render_node(&self, node: &GraphNode) -> String {
        // SVG node rendering implementation
        format!(
            r#"<circle cx="{}" cy="{}" r="20" fill="rgb({},{},{})" stroke="rgb({},{},{})" stroke-width="{}"/>"#,
            node.position.0,
            node.position.1,
            node.style.background_color.0,
            node.style.background_color.1,
            node.style.background_color.2,
            node.style.border_color.0,
            node.style.border_color.1,
            node.style.border_color.2,
            node.style.border_width
        )
    }

    fn render_edge(&self, edge: &GraphEdge) -> String {
        // SVG edge rendering implementation
        if let (Some(from_node), Some(to_node)) = (
            self.nodes.iter().find(|n| n.id == edge.from),
            self.nodes.iter().find(|n| n.id == edge.to),
        ) {
            format!(
                r#"<line x1="{}" y1="{}" x2="{}" y2="{}" stroke="rgb({},{},{})" stroke-width="{}"/>"#,
                from_node.position.0,
                from_node.position.1,
                to_node.position.0,
                to_node.position.1,
                edge.style.color.0,
                edge.style.color.1,
                edge.style.color.2,
                edge.style.thickness
            )
        } else {
            String::new()
        }
    }
}

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