russell_lab 1.15.0

Scientific laboratory for linear algebra and numerical mathematics
Documentation 
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use plotpy::{Curve, Plot, RayEndpoint};
use russell_lab::math::GOLDEN_RATIO;
use russell_lab::*;

const OUT_DIR: &str = "/tmp/russell_lab/";

// Reference: Mathematica
// data = {{0, 1}, {1, 0}, {3, 2}, {5, 4}};
// lm = LinearModelFit[data, x, x]
// NumberForm[Normal[lm], 50]

fn main() -> Result<(), StrError> {
    // model: c is the y value @ x = 0; m is the slope
    let x = [0.0, 1.0, 3.0, 5.0];
    let y = [1.0, 0.0, 2.0, 4.0];
    let (c, m) = linear_fitting(&x, &y, false)?;
    println!("c = {}, m = {}", c, m);
    approx_eq(c, 0.1864406779661015, 1e-15);
    approx_eq(m, 0.6949152542372882, 1e-15);

    // plot
    let mut curve_dat = Curve::new();
    let mut curve_fit = Curve::new();
    curve_dat
        .set_label("data")
        .set_line_style("None")
        .set_marker_style("o")
        .set_marker_line_color("red")
        .set_marker_color("red");
    curve_fit.draw_ray(0.0, c, RayEndpoint::Slope(m));
    curve_dat.draw(&x, &y);
    let mut plot = Plot::new();
    let path = format!("{}/algo_linear_fitting_1.svg", OUT_DIR);
    plot.add(&curve_dat)
        .add(&curve_fit)
        .grid_and_labels("x", "y")
        .set_figure_size_points(GOLDEN_RATIO * 280.0, 280.0)
        .save(&path)?;
    Ok(())
}