fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut rdr = csv::ReaderBuilder::new()
        .has_headers(true)
        .from_path("data/data.csv")?;

    let mut x_train: Vec<Vec<f64>> = Vec::new();
    let mut y_train: Vec<f64> = Vec::new();

    for result in rdr.records() {
        let record = result?;

        let x1: f64 = record[0].parse()?;
        let x2: f64 = record[1].parse()?;
        let y: f64 = record[2].parse()?;

        x_train.push(vec![x1, x2]);
        y_train.push(y);
    }

    let gp_model = friedrich::gaussian_process::GaussianProcess::default(x_train, y_train);

    let mut x_test: Vec<Vec<f64>> = Vec::new();
    let m = 1000;
    for i in -m..=m {
        for j in -m..=m {
            let x1 = i as f64 * 0.1;
            let x2 = j as f64 * 0.1;
            x_test.push(vec![x1, x2]);
        }
    }

    let y_mu = gp_model.predict(&x_test);
    let y_var = gp_model.predict_variance(&x_test);

    let mut n: usize = 0;
    for i in -m..=m {
        for j in -m..=m {
            println!(
                "{:.1}, {:.1}, {}, {}",
                i as f64 * 0.1,
                j as f64 * 0.1,
                y_mu[n],
                y_var[n].sqrt()
            );
            n += 1;
        }
    }

    // println!("{:?}", gp_model.kernel);

    Ok(())
}