ndarray integration for plotkit.

This crate activates ndarray support in plotkit-core, providing IntoSeries implementations for common ndarray one-dimensional array types. Depend on this crate (or enable the ndarray feature on the plotkit umbrella crate) to pass ndarray arrays directly to any plotkit charting function.

Supported types

Examples

use ndarray::array;
use plotkit_core::series::IntoSeries;

let arr = array![1.0, 2.0, 3.0];
let series = (&arr).into_series();
assert_eq!(series.data, vec![1.0, 2.0, 3.0]);

Rust finally has a plotting library that looks as good as matplotlib — and it's faster.

No Python subprocess. No JavaScript runtime. No system dependencies. Just add plotkit to your Cargo.toml and start making figures that belong in a journal paper.

Quick Start

plotkit::plot(&x, &y)?;
plotkit::title("sin(x)");
plotkit::savefig("plot.png")?;

Three lines. Anti-aliased text, clean axes, and a Tableau-10 color palette out of the box.

Installation

[dependencies]
plotkit = "0.4"

Optional features:

plotkit = { version = "0.4", features = ["svg", "jupyter", "ndarray", "polars"] }

Chart Types

plotkit supports 16 chart types with a matplotlib-familiar API:

Two APIs

pyplot-style (quick scripts)

use plotkit::prelude::*;

let x: Vec<f64> = (0..100).map(|i| i as f64 * 0.1).collect();
let y: Vec<f64> = x.iter().map(|&v| v.sin()).collect();

plotkit::plot(&x, &y)?;
plotkit::title("sin(x)");
plotkit::xlabel("x");
plotkit::ylabel("y");
plotkit::savefig("sine.png")?;

Figure/Axes (full control)

use plotkit::prelude::*;
use plotkit::FigureExt;

let mut fig = Figure::with_size(1200, 500);

let ax1 = fig.add_subplot(1, 2, 1);
ax1.plot(&x, &sin_y)?.label("sin(x)");
ax1.plot(&x, &cos_y)?.label("cos(x)");
ax1.set_title("Trigonometric Functions");
ax1.set_xlabel("x");
ax1.set_ylabel("y");
ax1.legend();

let ax2 = fig.add_subplot(1, 2, 2);
ax2.scatter(&x, &y)?;
ax2.set_title("Scatter Plot");

fig.save("subplots.png")?;

Twin Axes

Overlay two datasets with independent y-scales:

let mut fig = Figure::with_size(800, 600);
let ax1 = fig.add_subplot(1, 1, 1);
ax1.plot(&time, &temperature)?.label("Temperature");
ax1.set_ylabel("Temperature (°C)");

let ax2 = fig.twinx(0);
ax2.plot(&time, &pressure)?.label("Pressure");
ax2.set_ylabel("Pressure (hPa)");

ax1.legend();

Colormaps & Colorbar

14 built-in colormaps: Viridis, Plasma, Inferno, Magma, Cividis, Turbo, Coolwarm, Spectral, RdYlBu, RdYlGn, PiYG, BrBG, PRGn, RdBu.

ax.heatmap(data)?.colormap(Colormap::Viridis).colorbar(true);
ax.scatter(&x, &y)?.colormap(Colormap::Plasma).c(&values);

Scales & Axis Control

ax.set_xscale(Scale::Log10);
ax.set_yscale(Scale::SymLog { linthresh: 1.0 });
ax.set_xlim(0.1, 1000.0);
ax.set_xticks(&[0.1, 1.0, 10.0, 100.0, 1000.0]);
ax.invert_yaxis();
ax.grid(true);

Annotations

ax.text(2.0, 0.8, "Peak", None);
ax.annotate(
    "Important point",
    (3.0, 0.5),   // data point
    (4.5, 0.8),   // text position
    ArrowStyle::Arrow,
);

Themes

fig.set_theme(Theme::dark());   // Dark background, light text
fig.set_theme(Theme::default()); // Clean white background

Custom themes:

let theme = Theme {
    figure_background: Color::rgb(0xF5, 0xF5, 0xF5),
    font_family: Some("Helvetica".to_string()),
    ..Theme::default()
};
fig.set_theme(theme);

DataFrame Integration

Polars

use plotkit::prelude::*;

let df = polars::df! {
    "x" => [1.0, 2.0, 3.0, 4.0],
    "y" => [1.0, 4.0, 9.0, 16.0],
}?;

ax.plot(df.column("x")?, df.column("y")?)?;

ndarray

use ndarray::Array1;

let x = Array1::linspace(0.0, 10.0, 100);
let y = x.mapv(f64::sin);
ax.plot(&x, &y)?;

Output Formats

Architecture

plotkit is a multi-crate workspace:

The Renderer trait is the abstraction boundary — core logic never depends on a specific backend. Adding a new output format means implementing one trait.

Performance

Pure-Rust CPU renderer. No GPU, no system dependencies, no surprises.

plotkit compiles to a single static binary with zero runtime dependencies. It renders plots entirely on the CPU using optimized rasterization. There is no OpenGL context to initialize, no system font lookup to fail, and no shared library to go missing on a CI server at 2 AM.

Embedded Inter font (Regular + Bold) ensures deterministic, cross-platform text rendering — the same plot looks identical on Linux, macOS, and Windows.

Roadmap

Contributing

Contributions are welcome. Whether it's a bug report, a feature request, or a pull request — we appreciate it.

Please read CONTRIBUTING.md before getting started.

License

Licensed under either of

• MIT License
• Apache License, Version 2.0

at your option.