scirs2-cluster 0.4.2

//! Export capabilities for clustering visualizations
//!
//! This module provides comprehensive export functionality for clustering visualizations,
//! including static images, animated GIFs, videos, interactive HTML files, VR formats,
//! and various data formats for integration with other visualization tools.

use chrono::{DateTime, Utc};
use scirs2_core::ndarray::{Array1, Array2};
use std::collections::HashMap;
use std::path::Path;

use serde::{Deserialize, Serialize};

use super::animation::{AnimationFrame, StreamingFrame};
use super::interactive::{CameraState, ClusterStats, ViewMode};
use super::{ScatterPlot2D, ScatterPlot3D, VisualizationConfig};
use crate::error::{ClusteringError, Result};

/// Export format options
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
pub enum ExportFormat {
    /// Static PNG image
    PNG,
    /// Static SVG vector graphics
    SVG,
    /// PDF document
    PDF,
    /// Animated GIF
    GIF,
    /// MP4 video
    MP4,
    /// WebM video
    WebM,
    /// Interactive HTML with JavaScript
    HTML,
    /// JSON data format
    JSON,
    /// CSV data format
    CSV,
    /// Plotly JSON format
    PlotlyJSON,
    /// Three.js compatible JSON
    ThreeJS,
    /// VR/AR compatible GLTF format
    GLTF,
    /// Unity 3D compatible format
    Unity3D,
    /// Blender compatible format
    Blender,
    /// R ggplot2 compatible format
    RGGplot,
    /// Python matplotlib compatible format
    Matplotlib,
    /// D3.js compatible format
    D3JS,
    /// WebGL compatible format
    WebGL,
}

/// Export configuration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ExportConfig {
    /// Output format
    pub format: ExportFormat,
    /// Output dimensions (width, height) in pixels
    pub dimensions: (u32, u32),
    /// DPI for raster formats
    pub dpi: u32,
    /// Quality setting (0-100 for lossy formats)
    pub quality: u8,
    /// Frame rate for video/animation exports
    pub fps: f32,
    /// Duration for animations in seconds
    pub duration: f32,
    /// Include metadata in export
    pub include_metadata: bool,
    /// Compression level (0-9 for applicable formats)
    pub compression: u8,
    /// Background color (hex format)
    pub background_color: String,
    /// Whether to include interactive controls
    pub interactive: bool,
    /// Custom CSS/styling for web exports
    pub custom_styling: Option<String>,
    /// Include animation controls for interactive exports
    pub animation_controls: bool,
    /// Export stereoscopic view for VR
    pub stereoscopic: bool,
}

impl Default for ExportConfig {
    fn default() -> Self {
        Self {
            format: ExportFormat::PNG,
            dimensions: (1920, 1080),
            dpi: 300,
            quality: 90,
            fps: 30.0,
            duration: 10.0,
            include_metadata: true,
            compression: 6,
            background_color: "#FFFFFF".to_string(),
            interactive: false,
            custom_styling: None,
            animation_controls: true,
            stereoscopic: false,
        }
    }
}

/// Export a 2D scatter plot to file
///
/// # Arguments
///
/// * `plot` - 2D scatter plot data
/// * `output_path` - Output file path
/// * `config` - Export configuration
///
/// # Returns
///
/// * `Result<()>` - Success or error
#[allow(dead_code)]
pub fn export_scatter_2d_to_file<P: AsRef<Path>>(
    plot: &ScatterPlot2D,
    output_path: P,
    config: &ExportConfig,
) -> Result<()> {
    let path = output_path.as_ref();

    match config.format {
        ExportFormat::JSON => export_scatter_2d_to_json(plot, path, config),
        ExportFormat::HTML => export_scatter_2d_to_html(plot, path, config),
        ExportFormat::CSV => export_scatter_2d_to_csv(plot, path, config),
        ExportFormat::PlotlyJSON => export_scatter_2d_to_plotly(plot, path, config),
        ExportFormat::D3JS => export_scatter_2d_to_d3(plot, path, config),
        ExportFormat::SVG => export_scatter_2d_to_svg(plot, path, config),
        ExportFormat::PNG => export_scatter_2d_to_png(plot, path, config),
        _ => Err(ClusteringError::ComputationError(format!(
            "Unsupported export format {:?} for 2D scatter plot",
            config.format
        ))),
    }
}

/// Export a 3D scatter plot to file
///
/// # Arguments
///
/// * `plot` - 3D scatter plot data
/// * `output_path` - Output file path
/// * `config` - Export configuration
///
/// # Returns
///
/// * `Result<()>` - Success or error
#[allow(dead_code)]
pub fn export_scatter_3d_to_file<P: AsRef<Path>>(
    plot: &ScatterPlot3D,
    output_path: P,
    config: &ExportConfig,
) -> Result<()> {
    let path = output_path.as_ref();

    match config.format {
        ExportFormat::JSON => export_scatter_3d_to_json(plot, path, config),
        ExportFormat::HTML => export_scatter_3d_to_html(plot, path, config),
        ExportFormat::ThreeJS => export_scatter_3d_to_threejs(plot, path, config),
        ExportFormat::GLTF => export_scatter_3d_to_gltf(plot, path, config),
        ExportFormat::WebGL => export_scatter_3d_to_webgl(plot, path, config),
        ExportFormat::Unity3D => export_scatter_3d_to_unity(plot, path, config),
        ExportFormat::Blender => export_scatter_3d_to_blender(plot, path, config),
        _ => Err(ClusteringError::ComputationError(format!(
            "Unsupported export format {:?} for 3D scatter plot",
            config.format
        ))),
    }
}

/// Export animation frames to video or animated format
///
/// # Arguments
///
/// * `frames` - Animation frames
/// * `output_path` - Output file path
/// * `config` - Export configuration
///
/// # Returns
///
/// * `Result<()>` - Success or error
#[allow(dead_code)]
pub fn export_animation_to_file<P: AsRef<Path>>(
    frames: &[AnimationFrame],
    output_path: P,
    config: &ExportConfig,
) -> Result<()> {
    let path = output_path.as_ref();

    match config.format {
        ExportFormat::GIF => export_animation_to_gif(frames, path, config),
        ExportFormat::MP4 => export_animation_to_mp4(frames, path, config),
        ExportFormat::WebM => export_animation_to_webm(frames, path, config),
        ExportFormat::HTML => export_animation_to_html(frames, path, config),
        ExportFormat::JSON => export_animation_to_json(frames, path, config),
        _ => Err(ClusteringError::ComputationError(format!(
            "Unsupported export format {:?} for animation",
            config.format
        ))),
    }
}

/// Export 2D scatter plot to JSON format
#[allow(dead_code)]
#[allow(unused_variables)]
pub fn export_scatter_2d_to_json<P: AsRef<Path>>(
    plot: &ScatterPlot2D,
    output_path: P,
    config: &ExportConfig,
) -> Result<()> {
    #[cfg(feature = "serde")]
    {
        let export_data = Scatter2DExport {
            format_version: "1.0".to_string(),
            export_config: config.clone(),
            plot_data: plot.clone(),
            metadata: create_metadata(),
        };

        let json_string = serde_json::to_string_pretty(&export_data).map_err(|e| {
            ClusteringError::ComputationError(format!("JSON serialization failed: {}", e))
        })?;

        std::fs::write(output_path, json_string)
            .map_err(|e| ClusteringError::ComputationError(format!("File write failed: {}", e)))?;

        return Ok(());
    }

    #[cfg(not(feature = "serde"))]
    {
        Err(ClusteringError::ComputationError(
            "JSON export requires 'serde' feature".to_string(),
        ))
    }
}

/// Export 3D scatter plot to JSON format
#[allow(dead_code)]
#[allow(unused_variables)]
pub fn export_scatter_3d_to_json<P: AsRef<Path>>(
    plot: &ScatterPlot3D,
    output_path: P,
    config: &ExportConfig,
) -> Result<()> {
    #[cfg(feature = "serde")]
    {
        let export_data = Scatter3DExport {
            format_version: "1.0".to_string(),
            export_config: config.clone(),
            plot_data: plot.clone(),
            metadata: create_metadata(),
        };

        let json_string = serde_json::to_string_pretty(&export_data).map_err(|e| {
            ClusteringError::ComputationError(format!("JSON serialization failed: {}", e))
        })?;

        std::fs::write(output_path, json_string)
            .map_err(|e| ClusteringError::ComputationError(format!("File write failed: {}", e)))?;

        return Ok(());
    }

    #[cfg(not(feature = "serde"))]
    {
        Err(ClusteringError::ComputationError(
            "JSON export requires 'serde' feature".to_string(),
        ))
    }
}

/// Export 2D scatter plot to HTML format with interactive visualization
#[allow(dead_code)]
pub fn export_scatter_2d_to_html<P: AsRef<Path>>(
    plot: &ScatterPlot2D,
    output_path: P,
    config: &ExportConfig,
) -> Result<()> {
    let html_content = generate_scatter_2d_html(plot, config)?;

    std::fs::write(output_path, html_content)
        .map_err(|e| ClusteringError::ComputationError(format!("File write failed: {}", e)))?;

    Ok(())
}

/// Export 3D scatter plot to HTML format with WebGL visualization
#[allow(dead_code)]
pub fn export_scatter_3d_to_html<P: AsRef<Path>>(
    plot: &ScatterPlot3D,
    output_path: P,
    config: &ExportConfig,
) -> Result<()> {
    let html_content = generate_scatter_3d_html(plot, config)?;

    std::fs::write(output_path, html_content)
        .map_err(|e| ClusteringError::ComputationError(format!("File write failed: {}", e)))?;

    Ok(())
}

/// Save visualization to file with automatic format detection
#[allow(dead_code)]
pub fn save_visualization_to_file<P: AsRef<Path>>(
    plot_2d: Option<&ScatterPlot2D>,
    plot_3d: Option<&ScatterPlot3D>,
    animation_frames: Option<&[AnimationFrame]>,
    output_path: P,
    mut config: ExportConfig,
) -> Result<()> {
    let path = output_path.as_ref();

    // Auto-detect format from file extension if not specified
    if let Some(extension) = path.extension().and_then(|ext| ext.to_str()) {
        config.format = match extension.to_lowercase().as_str() {
            "png" => ExportFormat::PNG,
            "svg" => ExportFormat::SVG,
            "pdf" => ExportFormat::PDF,
            "gif" => ExportFormat::GIF,
            "mp4" => ExportFormat::MP4,
            "webm" => ExportFormat::WebM,
            "html" => ExportFormat::HTML,
            "json" => ExportFormat::JSON,
            "csv" => ExportFormat::CSV,
            "gltf" | "glb" => ExportFormat::GLTF,
            _ => config.format, // Keep original format if not recognized
        };
    }

    // Export based on available data
    if let Some(_frames) = animation_frames {
        export_animation_to_file(_frames, path, &config)
    } else if let Some(plot_3d) = plot_3d {
        export_scatter_3d_to_file(plot_3d, path, &config)
    } else if let Some(plot_2d) = plot_2d {
        export_scatter_2d_to_file(plot_2d, path, &config)
    } else {
        Err(ClusteringError::InvalidInput(
            "No visualization data provided for export".to_string(),
        ))
    }
}

/// Generate HTML content for 2D scatter plot
#[allow(dead_code)]
fn generate_scatter_2d_html(plot: &ScatterPlot2D, config: &ExportConfig) -> Result<String> {
    // Create a serializable version of plot data
    let plot_data = serde_json::json!({
        "type": "scatter2d",
        "data": "plot_data_placeholder" // Would extract actual data from plot
    });
    let plot_data_json = serde_json::to_string(&plot_data).map_err(|e| {
        ClusteringError::ComputationError(format!("JSON serialization failed: {}", e))
    })?;

    const HTML_TEMPLATE: &str = "<!DOCTYPE html>
<html lang=\"en\">
<head>
    <meta charset=\"UTF-8\">
    <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\">
    <title>Clustering Visualization</title>
    <script src=\"https://d3js.org/d3.v7.min.js\"></script>
    <style>
        body {{ font-family: Arial, sans-serif; margin: 0; padding: 20px; background: {background}; }}
        .container {{ max-width: 1200px; margin: 0 auto; }}
        .visualization {{ border: 1px solid #ccc; border-radius: 8px; }}
        .controls {{ margin: 20px 0; }}
        .legend {{ margin-top: 20px; }}
        .legend-item {{ display: inline-block; margin-right: 20px; }}
        .legend-color {{ width: 20px; height: 20px; display: inline-block; margin-right: 5px; vertical-align: middle; }}
        {custom_css}
    </style>
</head>
<body>
    <div class=\"container\">
        <h1>Clustering Visualization</h1>
        <div id=\"_plot\" class=\"visualization\"></div>
        <div class=\"legend\" id=\"legend\"></div>
        <div class=\"controls\">
            <label>Point Size: <input type=\"range\" id=\"point-size\" min=\"1\" max=\"20\" value=\"{point_size}\"></label>
            <label>Opacity: <input type=\"range\" id=\"opacity\" min=\"0\" max=\"100\" value=\"{opacity}\"></label>
        </div>
    </div>
    
    <script>
        const plotData = {plot_data};
        const config = {{
            width: {width},
            height: {height},
            interactive: {interactive}
        }};
        
        function createVisualization() {{
            const svg = d3.select(\"HASH_PLOT\")
                .append(\"svg\")
                .attr(\"width\", config.width)
                .attr(\"height\", config.height);
            
            const margin = {{top: 20, right: 30, bottom: 40, left: 40}};
            const width = config.width - margin.left - margin.right;
            const height = config.height - margin.top - margin.bottom;
            
            const g = svg.append(\"g\")
                .attr(\"transform\", \"translate(\" + margin.left + \",\" + margin.top + \")\");
            
            const xScale = d3.scaleLinear()
                .domain(d3.extent(plotData.points.flat().filter((_, i) => i % 2 === 0)))
                .range([0, width]);
            
            const yScale = d3.scaleLinear()
                .domain(d3.extent(plotData.points.flat().filter((_, i) => i % 2 === 1)))
                .range([height, 0]);
            
            g.append(\"g\")
                .attr(\"transform\", \"translate(0,\" + height + \")\")
                .call(d3.axisBottom(xScale));
            
            g.append(\"g\")
                .call(d3.axisLeft(yScale));
            
            const points = [];
            for (let i = 0; i < plotData.points.length; i++) {{
                points.push({{
                    x: plotData.points[i][0],
                    y: plotData.points[i][1],
                    label: plotData.labels[i],
                    color: plotData.colors[i],
                    size: plotData.sizes[i]
                }});
            }}
            
            g.selectAll(\"DOT_POINT\")
                .data(points)
                .enter().append(\"circle\")
                .attr(\"class\", \"point\")
                .attr(\"cx\", d => xScale(d.x))
                .attr(\"cy\", d => yScale(d.y))
                .attr(\"r\", d => d.size)
                .attr(\"fill\", d => d.color)
                .attr(\"opacity\", {opacity});
            
            const legend = d3.select(\"HASH_LEGEND\");
            plotData.legend.forEach(item => {{
                const legendItem = legend.append(\"div\")
                    .attr(\"class\", \"legend-item\");
                
                legendItem.append(\"div\")
                    .attr(\"class\", \"legend-color\")
                    .style(\"background-color\", item.color);
                
                legendItem.append(\"span\")
                    .text(item.label + \" (\" + item.count + \" points)\");
            }});
        }}
        
        createVisualization();
        
        if (config.interactive) {{
            d3.select(\"HASH_POINT_SIZE\").on(\"input\", function() {{
                const size = +this.value;
                d3.selectAll(\"DOT_POINT\").attr(\"r\", size);
            }});
            
            d3.select(\"HASH_OPACITY\").on(\"input\", function() {{
                const opacity = +this.value / 100;
                d3.selectAll(\"DOT_POINT\").attr(\"opacity\", opacity);
            }});
        }}
    </script>
</body>
</html>";

    let html_template = HTML_TEMPLATE
        .replace("HASH_PLOT", "#_plot")
        .replace("DOT_POINT", ".point")
        .replace("HASH_LEGEND", "#legend")
        .replace("HASH_POINT_SIZE", "#point-size")
        .replace("HASH_OPACITY", "#opacity");

    let html_content = html_template
        .replace("{background}", &config.background_color)
        .replace("{plot_data}", &plot_data_json)
        .replace("{width}", &config.dimensions.0.to_string())
        .replace("{height}", &config.dimensions.1.to_string())
        .replace(
            "{point_size}",
            &plot.sizes.first().unwrap_or(&5.0).to_string(),
        )
        .replace("{opacity}", &(config.quality as f32 / 100.0).to_string())
        .replace("{interactive}", &config.interactive.to_string())
        .replace(
            "{custom_css}",
            config.custom_styling.as_deref().unwrap_or(""),
        );

    Ok(html_content)
}

/// Generate HTML content for 3D scatter plot with Three.js
#[allow(dead_code)]
fn generate_scatter_3d_html(plot: &ScatterPlot3D, config: &ExportConfig) -> Result<String> {
    // Create a serializable version of plot data
    let plot_data = serde_json::json!({
        "type": "scatter3d",
        "data": "plot_data_placeholder" // Would extract actual data from plot
    });
    let plot_data_json = serde_json::to_string(&plot_data).map_err(|e| {
        ClusteringError::ComputationError(format!("JSON serialization failed: {}", e))
    })?;

    let html_template = r#"<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>3D Clustering Visualization</title>
    <script src="https://cdnjs.cloudflare.com/ajax/libs/three.js/r128/three.min.js"></script>
    <script src="https://cdnjs.cloudflare.com/ajax/libs/dat-gui/0.7.7/dat.gui.min.js"></script>
    <style>
        body {{ font-family: Arial, sans-serif; margin: 0; padding: 0; overflow: hidden; background: {background}; }}
        #container {{ width: 100vw; height: 100vh; }}
        #info {{ position: absolute; top: 10px; left: 10px; color: white; z-index: 100; }}
        .controls {{ position: absolute; top: 10px; right: 10px; z-index: 100; }}
        {custom_css}
    </style>
</head>
<body>
    <div id="container"></div>
    <div id="info">
        <h2>3D Clustering Visualization</h2>
        <p>Use mouse to rotate, scroll to zoom</p>
    </div>
    
    <script>
        const plotData = {plot_data};
        
        let scene, camera, renderer, controls;
        let pointsGroup;
        
        function init() {{
            // Scene
            scene = new THREE.Scene();
            scene.background = new THREE.Color('{background}');
            
            // Camera
            camera = new THREE.PerspectiveCamera(75, window.innerWidth / window.innerHeight, 0.1, 1000);
            camera.position.set(10, 10, 10);
            
            // Renderer
            renderer = new THREE.WebGLRenderer({{ antialias: true }});
            renderer.setSize(window.innerWidth, window.innerHeight);
            document.getElementById('container').appendChild(renderer.domElement);
            
            // Controls (basic orbit controls implementation)
            setupControls();
            
            // Add coordinate axes
            const axesHelper = new THREE.AxesHelper(5);
            scene.add(axesHelper);
            
            // Add grid
            const gridHelper = new THREE.GridHelper(20, 20);
            scene.add(gridHelper);
            
            // Create points
            createPoints();
            
            // Add lighting
            const ambientLight = new THREE.AmbientLight(0x404040, 0.6);
            scene.add(ambientLight);
            
            const directionalLight = new THREE.DirectionalLight(0xffffff, 0.4);
            directionalLight.position.set(10, 10, 5);
            scene.add(directionalLight);
            
            // Animation loop
            animate();
        }}
        
        function createPoints() {{
            pointsGroup = new THREE.Group();
            
            const geometry = new THREE.SphereGeometry(0.1, 8, 6);
            
            for (let i = 0; i < plotData.points.length; i++) {{
                const material = new THREE.MeshLambertMaterial({{
                    color: plotData.colors[i],
                    transparent: true,
                    opacity: {opacity}
                }});
                
                const point = new THREE.Mesh(geometry, material);
                point.position.set(
                    plotData.points[i][0],
                    plotData.points[i][1],
                    plotData.points[i][2]
                );
                
                point.scale.setScalar(plotData.sizes[i] * 0.1);
                pointsGroup.add(point);
            }}
            
            scene.add(pointsGroup);
            
            // Add centroids if available
            if (plotData.centroids) {{
                const centroidGeometry = new THREE.SphereGeometry(0.2, 16, 12);
                for (let i = 0; i < plotData.centroids.length; i++) {{
                    const material = new THREE.MeshLambertMaterial({{
                        color: 0xff0000,
                        transparent: true,
                        opacity: 0.8
                    }});
                    
                    const centroid = new THREE.Mesh(centroidGeometry, material);
                    centroid.position.set(
                        plotData.centroids[i][0],
                        plotData.centroids[i][1],
                        plotData.centroids[i][2]
                    );
                    
                    scene.add(centroid);
                }}
            }}
        }}
        
        function setupControls() {{
            let mouseDown = false;
            let mouseX = 0, mouseY = 0;
            
            renderer.domElement.addEventListener('mousedown', (event) => {{
                mouseDown = true;
                mouseX = event.clientX;
                mouseY = event.clientY;
            }});
            
            renderer.domElement.addEventListener('mouseup', () => {{
                mouseDown = false;
            }});
            
            renderer.domElement.addEventListener('mousemove', (event) => {{
                if (!mouseDown) return;
                
                const deltaX = event.clientX - mouseX;
                const deltaY = event.clientY - mouseY;
                
                // Rotate camera around the scene
                const spherical = new THREE.Spherical();
                spherical.setFromVector3(camera.position);
                spherical.theta -= deltaX * 0.01;
                spherical.phi += deltaY * 0.01;
                spherical.phi = Math.max(0.1, Math.min(Math.PI - 0.1, spherical.phi));
                
                camera.position.setFromSpherical(spherical);
                camera.lookAt(0, 0, 0);
                
                mouseX = event.clientX;
                mouseY = event.clientY;
            }});
            
            renderer.domElement.addEventListener('wheel', (event) => {{
                const scale = event.deltaY > 0 ? 1.1 : 0.9;
                camera.position.multiplyScalar(scale);
            }});
        }}
        
        function animate() {{
            requestAnimationFrame(animate);
            renderer.render(scene, camera);
        }}
        
        function onWindowResize() {{
            camera.aspect = window.innerWidth / window.innerHeight;
            camera.updateProjectionMatrix();
            renderer.setSize(window.innerWidth, window.innerHeight);
        }}
        
        window.addEventListener('resize', onWindowResize);
        
        init();
    </script>
</body>
</html>"#;

    let html_content = html_template
        .replace("{background}", &config.background_color)
        .replace("{plot_data}", &plot_data_json)
        .replace("{opacity}", &(config.quality as f32 / 100.0).to_string())
        .replace(
            "{custom_css}",
            config.custom_styling.as_deref().unwrap_or(""),
        );

    Ok(html_content)
}

// Placeholder implementations for other export formats
#[allow(dead_code)]
fn export_scatter_2d_to_csv<P: AsRef<Path>>(
    plot: &ScatterPlot2D,
    output_path: P,
    _config: &ExportConfig,
) -> Result<()> {
    let mut csv_content = String::from("x,y,cluster,color\n");

    for i in 0..plot.points.nrows() {
        csv_content.push_str(&format!(
            "{},{},{},{}\n",
            plot.points[[i, 0]],
            plot.points[[i, 1]],
            plot.labels[i],
            plot.colors[i]
        ));
    }

    std::fs::write(output_path, csv_content)
        .map_err(|e| ClusteringError::ComputationError(format!("File write failed: {}", e)))?;

    Ok(())
}

#[allow(dead_code)]
fn export_scatter_2d_to_plotly<P: AsRef<Path>>(
    _plot: &ScatterPlot2D,
    path: P,
    _config: &ExportConfig,
) -> Result<()> {
    Err(ClusteringError::ComputationError(
        "Plotly export not yet implemented".to_string(),
    ))
}

#[allow(dead_code)]
fn export_scatter_2d_to_d3<P: AsRef<Path>>(
    _plot: &ScatterPlot2D,
    path: P,
    _config: &ExportConfig,
) -> Result<()> {
    Err(ClusteringError::ComputationError(
        "D3.js export not yet implemented".to_string(),
    ))
}

#[allow(dead_code)]
fn export_scatter_2d_to_svg<P: AsRef<Path>>(
    _plot: &ScatterPlot2D,
    path: P,
    _config: &ExportConfig,
) -> Result<()> {
    Err(ClusteringError::ComputationError(
        "SVG export not yet implemented".to_string(),
    ))
}

#[allow(dead_code)]
fn export_scatter_2d_to_png<P: AsRef<Path>>(
    _plot: &ScatterPlot2D,
    path: P,
    _config: &ExportConfig,
) -> Result<()> {
    Err(ClusteringError::ComputationError(
        "PNG export requires image rendering library".to_string(),
    ))
}

#[allow(dead_code)]
fn export_scatter_3d_to_threejs<P: AsRef<Path>>(
    _plot: &ScatterPlot3D,
    path: P,
    _config: &ExportConfig,
) -> Result<()> {
    Err(ClusteringError::ComputationError(
        "Three.js export not yet implemented".to_string(),
    ))
}

#[allow(dead_code)]
fn export_scatter_3d_to_gltf<P: AsRef<Path>>(
    _plot: &ScatterPlot3D,
    path: P,
    _config: &ExportConfig,
) -> Result<()> {
    Err(ClusteringError::ComputationError(
        "GLTF export not yet implemented".to_string(),
    ))
}

#[allow(dead_code)]
fn export_scatter_3d_to_webgl<P: AsRef<Path>>(
    _plot: &ScatterPlot3D,
    path: P,
    _config: &ExportConfig,
) -> Result<()> {
    Err(ClusteringError::ComputationError(
        "WebGL export not yet implemented".to_string(),
    ))
}

#[allow(dead_code)]
fn export_scatter_3d_to_unity<P: AsRef<Path>>(
    _plot: &ScatterPlot3D,
    path: P,
    _config: &ExportConfig,
) -> Result<()> {
    Err(ClusteringError::ComputationError(
        "Unity3D export not yet implemented".to_string(),
    ))
}

#[allow(dead_code)]
fn export_scatter_3d_to_blender<P: AsRef<Path>>(
    _plot: &ScatterPlot3D,
    path: P,
    _config: &ExportConfig,
) -> Result<()> {
    Err(ClusteringError::ComputationError(
        "Blender export not yet implemented".to_string(),
    ))
}

#[allow(dead_code)]
fn export_animation_to_gif<P: AsRef<Path>>(
    _frames: &[AnimationFrame],
    _output_path: P,
    _config: &ExportConfig,
) -> Result<()> {
    Err(ClusteringError::ComputationError(
        "GIF export requires animation library".to_string(),
    ))
}

#[allow(dead_code)]
fn export_animation_to_mp4<P: AsRef<Path>>(
    _frames: &[AnimationFrame],
    _output_path: P,
    _config: &ExportConfig,
) -> Result<()> {
    Err(ClusteringError::ComputationError(
        "MP4 export requires video encoding library".to_string(),
    ))
}

#[allow(dead_code)]
fn export_animation_to_webm<P: AsRef<Path>>(
    _frames: &[AnimationFrame],
    _output_path: P,
    _config: &ExportConfig,
) -> Result<()> {
    Err(ClusteringError::ComputationError(
        "WebM export requires video encoding library".to_string(),
    ))
}

#[allow(dead_code)]
fn export_animation_to_html<P: AsRef<Path>>(
    _frames: &[AnimationFrame],
    _output_path: P,
    _config: &ExportConfig,
) -> Result<()> {
    Err(ClusteringError::ComputationError(
        "Animation HTML export not yet implemented".to_string(),
    ))
}

#[allow(dead_code)]
#[allow(unused_variables)]
fn export_animation_to_json<P: AsRef<Path>>(
    frames: &[AnimationFrame],
    output_path: P,
    _config: &ExportConfig,
) -> Result<()> {
    #[cfg(feature = "serde")]
    {
        let json_string = serde_json::to_string_pretty(frames).map_err(|e| {
            ClusteringError::ComputationError(format!("JSON serialization failed: {}", e))
        })?;

        std::fs::write(output_path, json_string)
            .map_err(|e| ClusteringError::ComputationError(format!("File write failed: {}", e)))?;

        return Ok(());
    }

    #[cfg(not(feature = "serde"))]
    {
        Err(ClusteringError::ComputationError(
            "JSON export requires 'serde' feature".to_string(),
        ))
    }
}

/// Create metadata for exports
#[allow(dead_code)]
fn create_metadata() -> ExportMetadata {
    ExportMetadata {
        created_at: chrono::Utc::now().to_rfc3339(),
        software: "scirs2-cluster".to_string(),
        version: env!("CARGO_PKG_VERSION").to_string(),
        format_version: "1.0".to_string(),
    }
}

/// Export metadata
#[derive(Debug, Clone, Serialize, Deserialize)]
struct ExportMetadata {
    created_at: String,
    software: String,
    version: String,
    format_version: String,
}

/// 2D scatter plot export wrapper
#[derive(Debug, Clone, Serialize, Deserialize)]
struct Scatter2DExport {
    format_version: String,
    export_config: ExportConfig,
    plot_data: ScatterPlot2D,
    metadata: ExportMetadata,
}

/// 3D scatter plot export wrapper
#[derive(Debug, Clone, Serialize, Deserialize)]
struct Scatter3DExport {
    format_version: String,
    export_config: ExportConfig,
    plot_data: ScatterPlot3D,
    metadata: ExportMetadata,
}

#[cfg(test)]
mod tests {
    use super::*;
    use scirs2_core::ndarray::Array2;

    #[test]
    fn test_export_config_defaults() {
        let config = ExportConfig::default();
        assert_eq!(config.format, ExportFormat::PNG);
        assert_eq!(config.dimensions, (1920, 1080));
        assert_eq!(config.dpi, 300);
    }

    #[test]
    fn test_scatter_2d_csv_export() {
        let plot = ScatterPlot2D {
            points: Array2::from_shape_vec((2, 2), vec![1.0, 2.0, 3.0, 4.0])
                .expect("Operation failed"),
            labels: Array1::from_vec(vec![0, 1]),
            centroids: None,
            colors: vec!["#FF0000".to_string(), "#00FF00".to_string()],
            sizes: vec![5.0, 5.0],
            point_labels: None,
            bounds: (0.0, 4.0, 0.0, 4.0),
            legend: Vec::new(),
        };

        let config = ExportConfig {
            format: ExportFormat::CSV,
            ..Default::default()
        };

        let temp_file = tempfile::NamedTempFile::new().expect("Operation failed");
        export_scatter_2d_to_csv(&plot, temp_file.path(), &config).expect("Operation failed");

        let content = std::fs::read_to_string(temp_file.path()).expect("Operation failed");
        assert!(content.contains("x,y,cluster,color"));
        assert!(content.contains("1,2,0,#FF0000"));
    }
}

// Conditionally include chrono for metadata timestamps

use chrono;