Function load_digits 

pub fn load_digits() -> Result<Dataset>

Generate the digits dataset

Examples found in repository

examples/scikit_learn_benchmark.rs (line 313)

fn run_sklearn_toy_dataset_comparison() {
    println!("\n  📊 Toy Dataset Loading Comparison:");

    let datasets = vec![
        (
            "iris",
            "from sklearn.datasets import load_iris; load_iris()",
        ),
        (
            "boston",
            "from sklearn.datasets import load_boston; load_boston()",
        ),
        (
            "digits",
            "from sklearn.datasets import load_digits; load_digits()",
        ),
        (
            "wine",
            "from sklearn.datasets import load_wine; load_wine()",
        ),
        (
            "breast_cancer",
            "from sklearn.datasets import load_breast_cancer; load_breast_cancer()",
        ),
    ];

    for (name, python_code) in datasets {
        // Time Python execution
        let _start = Instant::now();
        let python_result = Command::new("python3")
            .arg("-c")
            .arg(format!(
                "import time; start=time.time(); {python_code}; print(f'{{:.4f}}', time.time()-start)"
            ))
            .output();

        match python_result {
            Ok(output) if output.status.success() => {
                let python_time = String::from_utf8_lossy(&output.stdout)
                    .trim()
                    .parse::<f64>()
                    .unwrap_or(0.0);

                // Time SciRS2 execution
                let scirs2_start = Instant::now();
                let _scirs2_result = match name {
                    "iris" => load_iris().map(|_| ()),
                    "boston" => load_boston().map(|_| ()),
                    "digits" => load_digits().map(|_| ()),
                    "wine" => load_wine(false).map(|_| ()),
                    "breast_cancer" => load_breast_cancer().map(|_| ()),
                    _ => Ok(()),
                };
                let scirs2_time = scirs2_start.elapsed().as_secs_f64();

                let speedup = python_time / scirs2_time;
                let status = if speedup > 1.2 {
                    "🚀 FASTER"
                } else if speedup > 0.8 {
                    "≈ SIMILAR"
                } else {
                    "🐌 SLOWER"
                };

                println!(
                    "    {}: SciRS2 {:.2}ms vs sklearn {:.2}ms ({:.1}x {}",
                    name,
                    scirs2_time * 1000.0,
                    python_time * 1000.0,
                    speedup,
                    status
                );
            }
            _ => {
                println!("    {name}: Failed to benchmark Python version");
            }
        }
    }
}