This crate implements high-level functions to generate plots and drawings. Although we use Python/Matplotlib, the goal is to provide a convenient Rust library that is different than Matplotlib. The difference happens because we want convenience for the Rust developer while getting the fantastic quality of Matplotlib 😀.
Plotpy is more verbose than Matplotlib because we aim to minimize the need to memorize the functionality by taking advantage of the intelligence of the IDE (e.g., VS Code) on auto-completing the code.
Internally, we use Matplotlib via a Python 3 script. First, we generate a python code in a directory of your choice (e.g., /tmp/plotpy
), and then we call python3 using Rust's std::process::Command
.
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.
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(...)?;
👆 Check the crate version and update your Cargo.toml accordingly:
[dependencies]
plotpy = "*"
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)?;
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);
plot.set_labels("x", "y");
// save figure
plot.save("/tmp/plotpy/readme_contour.svg")?;
Ok(())
}
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)
.save("/tmp/plotpy/readme_superquadric.svg")?;
Ok(())
}