kuva

kuva is a scientific plotting library for Rust that renders plots to SVG. It targets bioinformatics use cases and ships with 25 specialised plot types — from standard scatter and bar charts to Manhattan plots, UpSet plots, phylogenetic trees, and synteny diagrams. A kuva CLI binary lets you render plots directly from the shell without writing any Rust.

Design

The API follows a builder pattern. Every plot type is constructed with ::new(), configured with method chaining, and rendered through a single pipeline:

plot struct  →  Plot enum  →  Layout  →  SVG / PNG / PDF

Quick start

#![allow(unused)]
fn main() {
use kuva::prelude::*;

let data = vec![(1.0_f64, 2.0_f64), (3.0, 5.0), (5.0, 4.0)];

let plot = ScatterPlot::new()
    .with_data(data)
    .with_color("steelblue")
    .with_size(5.0);

let plots: Vec<Plot> = vec![plot.into()];
let layout = Layout::auto_from_plots(&plots)
    .with_title("My Plot")
    .with_x_label("X")
    .with_y_label("Y");

let svg = render_to_svg(plots, layout);
std::fs::write("my_plot.svg", svg).unwrap();
}

Prelude

use kuva::prelude::* brings all 25 plot structs, Plot, Layout, Figure, Theme, Palette, render_to_svg, and everything else you typically need into scope in one line.

Every plot struct implements Into<Plot>, so you can write plot.into() instead of Plot::Scatter(plot).

For PNG or PDF output, use render_to_png and render_to_pdf (require feature flags png and pdf respectively):

#![allow(unused)]
fn main() {
use kuva::prelude::*;

let plots: Vec<Plot> = vec![/* ... */];
let layout = Layout::auto_from_plots(&plots);

// SVG — always available
let svg: String = render_to_svg(plots, layout);

// PNG — feature = "png"
let png: Vec<u8> = render_to_png(plots, layout, 2.0).unwrap();

// PDF — feature = "pdf"
let pdf: Vec<u8> = render_to_pdf(plots, layout).unwrap();
}

Regenerating documentation assets

The SVG images embedded in these docs are generated by standalone example programs in the examples/ directory. Regenerate all assets at once with:

bash scripts/gen_docs.sh

Or regenerate a single plot type:

cargo run --example scatter
cargo run --example histogram
# etc. — one example per plot type in examples/

Building the book

Install mdBook, then:

mdbook build docs    # produce docs/book/
mdbook serve docs    # live-reload preview at http://localhost:3000