Adding `plotpy` library as a dependency

Run this command in a terminal, in your project's directory:

cargo add plotpy

To add it manually, edit your project's Cargo.toml file and add to the [dependencies] section:

plotpy = "1.21.0"

The plotpy library will be automatically available globally. Read the plotpy library documentation.

Back to the crate overview.

Readme

Rust plotting library using Python (Matplotlib)

Introduction
Installation
Setting Cargo.toml
Use of Jupyter via evcxr
Examples
- Barplot
- Boxplot
- Canvas
- Contour
- Curve
- Histogram
- Image
- InsetAxes
- Surface
- Text

Introduction

This crate implements functions for generating plots and drawings in Rust. It uses Python/Matplotlib but is designed specifically for Rust developers, combining the convenience of a Rust-native API with the exceptional quality of Matplotlib 😀.

Plotpy is more verbose than native Matplotlib because the aim here is to take advantage of the intelligence of the IDE (e.g., VS Code) to auto-complete the code while developing in Rust.

Plotpy generates Python code in a temporary directory (e.g., /tmp/plotpy). It then runs the code via Python 3 using Rust's std::process::Command. The result is an image file such as SVG.

For more information (and examples), check out the plotpy documentation on docs.rs.

See also the examples directory with the output of the integration tests.

Installation

This code is mainly tested on Debian/Ubuntu/Linux.

This crate needs Python3 and Matplotlib, of course.

On Debian/Ubuntu/Linux, run:

sudo apt install python3-matplotlib

Important: The Rust code will call python3 via std::process::Command. However, there is an option to call a different python executable; for instance (the code below is no tested):

let mut plot = Plot::new();
plot.set_python_exe("C:\Windows11\WhereIs\python.exe")
    .add(...)
    .save(...)?;

Setting Cargo.toml

👆 Check the crate version and update your Cargo.toml accordingly:

[dependencies]
plotpy = "*"

Use of Jupyter via evcxr

Plotpy can be used with Jupyter via evcxr. Thus, it can interactively display the plots in a Jupyter Notebook. This feature requires the installation of evcxr. See the Jupyter/evcxr article.

The following code shows a minimal example (not tested)

// set the python path
let python = "where-is-my/python";

// set the figure path and name to be saved
let path = "my-figure.svg";

// plot and show in a Jupyter notebook
let mut plot = Plot::new();
plot.set_python_exe(python)
    .set_label_x("x")
    .set_label_y("y")
    .show_in_jupyter(path)?;

Examples

Barplot

See the documentation

use plotpy::{Barplot, Plot, StrError};

fn main() -> Result<(), StrError> {
    // data
    let fruits = ["Apple", "Banana", "Orange"];
    let prices = [10.0, 20.0, 30.0];
    let errors = [3.0, 2.0, 1.0];

    // barplot object and options
    let mut bar = Barplot::new();
    bar.set_errors(&errors)
        .set_horizontal(true)
        .set_with_text("edge")
        .draw_with_str(&fruits, &prices);

    // save figure
    let mut plot = Plot::new();
    plot.set_inv_y()
        .add(&bar)
        .set_title("Fruits")
        .set_label_x("price");

    // plot.save("/tmp/plotpy/doc_tests/doc_barplot_3.svg")?;
    Ok(())
}

Boxplot

See the documentation

use plotpy::{Boxplot, Plot, StrError};

fn main() -> Result<(), StrError> {
    // data (as a nested list)
    let data = vec![
        vec![1, 2, 3, 4, 5],              // A
        vec![2, 3, 4, 5, 6, 7, 8, 9, 10], // B
        vec![3, 4, 5, 6],                 // C
        vec![4, 5, 6, 7, 8, 9, 10],       // D
        vec![5, 6, 7],                    // E
    ];

    // x ticks and labels
    let n = data.len();
    let ticks: Vec<_> = (1..(n + 1)).into_iter().collect();
    let labels = ["A", "B", "C", "D", "E"];

    // boxplot object and options
    let mut boxes = Boxplot::new();
    boxes.draw(&data);

    // save figure
    let mut plot = Plot::new();
    plot.add(&boxes)
        .set_title("boxplot documentation test")
        .set_ticks_x_labels(&ticks, &labels);

    // plot.save("/tmp/plotpy/doc_tests/doc_boxplot_2.svg")?;
    Ok(())
}

Canvas

See the documentation

use plotpy::{Canvas, Plot, PolyCode, StrError};

fn main() -> Result<(), StrError> {
    // codes
    let data = [
        (3.0, 0.0, PolyCode::MoveTo),
        (1.0, 1.5, PolyCode::Curve4),
        (0.0, 4.0, PolyCode::Curve4),
        (2.5, 3.9, PolyCode::Curve4),
        (3.0, 3.8, PolyCode::LineTo),
        (3.5, 3.9, PolyCode::LineTo),
        (6.0, 4.0, PolyCode::Curve4),
        (5.0, 1.5, PolyCode::Curve4),
        (3.0, 0.0, PolyCode::Curve4),
    ];

    // polycurve
    let mut canvas = Canvas::new();
    canvas.set_face_color("#f88989").set_edge_color("red");
    canvas.polycurve_begin();
    for (x, y, code) in data {
        canvas.polycurve_add(x, y, code);
    }
    canvas.polycurve_end(true);

    // add canvas to plot
    let mut plot = Plot::new();
    plot.add(&canvas);

    // save figure
    plot.set_range(1.0, 5.0, 0.0, 4.0)
        .set_frame_borders(false)
        .set_hide_axes(true)
        .set_equal_axes(true)
        .set_show_errors(true);

    // plot.save("/tmp/plotpy/doc_tests/doc_canvas_polycurve.svg")?;
    Ok(())
}

Contour

See the documentation

use plotpy::{generate3d, Contour, Plot, StrError};

fn main() -> Result<(), StrError> {
    // generate (x,y,z) matrices
    let n = 21;
    let (x, y, z) = generate3d(-2.0, 2.0, -2.0, 2.0, n, n, |x, y| x * x - y * y);

    // configure contour
    let mut contour = Contour::new();
    contour
        .set_colorbar_label("temperature")
        .set_colormap_name("terrain")
        .set_selected_level(0.0, true);

    // draw contour
    contour.draw(&x, &y, &z);

    // add contour to plot
    let mut plot = Plot::new();
    plot.add(&contour)
        .set_labels("x", "y");

    // plot.save("/tmp/plotpy/readme_contour.svg")?;
    Ok(())
}

Curve

See the documentation

use plotpy::{linspace, Curve, Plot, StrError};

fn main() -> Result<(), StrError> {
    // generate (x,y) points
    let x = linspace(-1.0, 1.0, 21);
    let y: Vec<_> = x.iter().map(|v| 1.0 / (1.0 + f64::exp(-5.0 * *v))).collect();

    // configure curve
    let mut curve = Curve::new();
    curve
        .set_label("logistic function")
        .set_line_alpha(0.8)
        .set_line_color("#5f9cd8")
        .set_line_style("-")
        .set_line_width(5.0)
        .set_marker_color("#eeea83")
        .set_marker_every(5)
        .set_marker_line_color("#da98d1")
        .set_marker_line_width(2.5)
        .set_marker_size(20.0)
        .set_marker_style("*");

    // draw curve
    curve.draw(&x, &y);

    // add curve to plot
    let mut plot = Plot::new();
    plot.add(&curve)
        .set_num_ticks_y(11)
        .grid_labels_legend("x", "y");

    // plot.save("/tmp/plotpy/doc_tests/doc_curve.svg")?;
    Ok(())
}

Histogram

See the documentation

use plotpy::{Histogram, Plot, StrError};

fn main() -> Result<(), StrError> {
    // set values
    let values = vec![
        vec![1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 4, 5, 6], // first series
        vec![-1, -1, 0, 1, 2, 3],                    // second series
        vec![5, 6, 7, 8],                            // third series
    ];

    // set labels
    let labels = ["first", "second", "third"];

    // configure and draw histogram
    let mut histogram = Histogram::new();
    histogram.set_colors(&["#9de19a", "#e7eca3", "#98a7f2"])
        .set_line_width(10.0)
        .set_stacked(true)
        .set_style("step");
    histogram.draw(&values, &labels);

    // add histogram to plot
    let mut plot = Plot::new();
    plot.add(&histogram)
        .set_frame_border(true, false, true, false)
        .grid_labels_legend("values", "count");

    // plot.save("/tmp/plotpy/doc_tests/doc_histogram.svg")?;
    Ok(())
}

histogram

Image

use plotpy::{Image, Plot, StrError};

fn main() -> Result<(), StrError> {
    // set values
    let data = [
        [0.8, 2.4, 2.5, 3.9, 0.0, 4.0, 0.0],
        [2.4, 0.0, 4.0, 1.0, 2.7, 0.0, 0.0],
        [1.1, 2.4, 0.8, 4.3, 1.9, 4.4, 0.0],
        [0.6, 0.0, 0.3, 0.0, 3.1, 0.0, 0.0],
        [0.7, 1.7, 0.6, 2.6, 2.2, 6.2, 0.0],
        [1.3, 1.2, 0.0, 0.0, 0.0, 3.2, 5.1],
        [0.1, 2.0, 0.0, 1.4, 0.0, 1.9, 6.3],
    ];

    // image plot and options
    let mut img = Image::new();
    img.set_colormap_name("hsv").draw(&data);

    // save figure
    let mut plot = Plot::new();
    plot.add(&img);

    // plot.save("/tmp/plotpy/doc_tests/doc_image_1.svg")?;
    Ok(())
}

InsetAxes

use plotpy::{Curve, InsetAxes, Plot, StrError};

fn main() -> Result<(), StrError> {
    // draw curve
    let mut curve = Curve::new();
    curve.draw(&[0.0, 1.0, 2.0], &[0.0, 1.0, 4.0]);

    // allocate inset and add curve to it
    let mut inset = InsetAxes::new();
    inset
        .add(&curve) // add curve to inset
        .set_range(0.5, 1.5, 0.5, 1.5) // set the range of the inset
        .draw(0.5, 0.5, 0.4, 0.3);

    // add curve and inset to plot
    let mut plot = Plot::new();
    plot.add(&curve)
        .set_range(0.0, 5.0, 0.0, 5.0)
        .add(&inset); // IMPORTANT: add inset after setting the range

    // plot.save("/tmp/plotpy/doc_tests/doc_inset_axes_add.svg")?;
    Ok(())
}

inset_axes

Surface

See the documentation

use plotpy::{Plot, StrError, Surface};

fn main() -> Result<(), StrError> {
    // star
    let r = &[1.0, 1.0, 1.0];
    let c = &[-1.0, -1.0, -1.0];
    let k = &[0.5, 0.5, 0.5];
    let mut star = Surface::new();
    star.set_colormap_name("jet")
        .draw_superquadric(c, r, k, -180.0, 180.0, -90.0, 90.0, 40, 20)?;

    // pyramids
    let c = &[1.0, -1.0, -1.0];
    let k = &[1.0, 1.0, 1.0];
    let mut pyramids = Surface::new();
    pyramids
        .set_colormap_name("inferno")
        .draw_superquadric(c, r, k, -180.0, 180.0, -90.0, 90.0, 40, 20)?;

    // rounded cube
    let c = &[-1.0, 1.0, 1.0];
    let k = &[4.0, 4.0, 4.0];
    let mut cube = Surface::new();
    cube.set_surf_color("#ee29f2")
        .draw_superquadric(c, r, k, -180.0, 180.0, -90.0, 90.0, 40, 20)?;

    // sphere
    let c = &[0.0, 0.0, 0.0];
    let k = &[2.0, 2.0, 2.0];
    let mut sphere = Surface::new();
    sphere
        .set_colormap_name("rainbow")
        .draw_superquadric(c, r, k, -180.0, 180.0, -90.0, 90.0, 40, 20)?;

    // sphere (direct)
    let mut sphere_direct = Surface::new();
    sphere_direct.draw_sphere(&[1.0, 1.0, 1.0], 1.0, 40, 20)?;

    // add features to plot
    let mut plot = Plot::new();
    plot.add(&star)
        .add(&pyramids)
        .add(&cube)
        .add(&sphere)
        .add(&sphere_direct);

    // save figure
    plot.set_equal_axes(true)
        .set_figure_size_points(600.0, 600.0);

    // plot.save("/tmp/plotpy/readme_superquadric.svg")?;
    Ok(())
}

Text

use plotpy::{Plot, Text, StrError};
use std::path::Path;

fn main() -> Result<(), StrError> {
    // configure text
    let mut text = Text::new();
    text.set_color("purple")
        .set_align_horizontal("center")
        .set_align_vertical("center")
        .set_fontsize(30.0)
        .set_bbox(true)
        .set_bbox_facecolor("pink")
        .set_bbox_edgecolor("black")
        .set_bbox_alpha(0.3)
        .set_bbox_style("roundtooth,pad=0.3,tooth_size=0.2");

    // draw text
    text.draw_3d(0.5, 0.5, 0.5, "Hello World!");

    // add text to plot
    let mut plot = Plot::new();
    plot.add(&text);

    // plot.save("/tmp/plotpy/doc_tests/doc_text.svg")?;
    Ok(())
}

text

Adding plotpy library as a dependency

Adding `plotpy` library as a dependency