#charts #command-line #graph #generate-html

flot

Generate HTML documents with embedded charts using Flot

2 releases

Uses old Rust 2015

0.1.3 Nov 19, 2017
0.1.2 Nov 19, 2017

#1582 in Algorithms

MIT license

32KB
559 lines

A Rust library for generating Flot documents

Flot is a JavaScript library for generating attractive data plots. Although usually used to enhance interactive websites, flot-rs is a nice way for command-line programs to create standalone HTML documents with plots. By default these refer to online sources, so they can be handed over to anybody else for display.

extern crate flot;

fn main() {
    let line_data = vec![(0.0,1.0),(1.0,4.5)];
    let points_data = vec![(0.5,1.2),(0.8,4.0)];

    let page = flot::Page::new("");

    let p = page.plot("Lines and Points");
    p.lines("lines",line_data).fill(0.3).line_width(0);
    p.points("points",points_data).symbol("circle");

    page.render("simple.html").expect("i/o error");
}

A Page may contain multiple plots; plots may contain multiple series with chart types (lines,points,bars).

The result of running this program is to create 'simple.html', which can be opened in your browser.

Page can be given a title, which if non-empty will both set the title of the document and create a H1 heading. Likewise, the plot method is given a title which if non-empty will provide a centered H2 heading for the plot.

Ways of specifying Data

By default, the series constructors take anything that converts to an iterator of (f64,f64) x-y pairs. Note that the vectors line_data and points_data are consumed by these calls.

If you have a source of tuples that isn't (f64,f64), then flot::to_f64 will convert that into a form that flot-rs accepts, provided that those types convert cleanly into f64.

Alternatively, you can map a iterator of references with a function - flot::mapr produces the desired points iterator, which here we collect into a vector.

extern crate flot;

fn make_gaussian(xvalues: &[f64], m: f64, s: f64) -> Vec<(f64,f64)> {
    use std::f64::consts::PI;
    let s2 = 2.0*s*s;
    let norm = 1.0/(s2*PI).sqrt();
    flot::mapr (
        xvalues,
        move |x| norm*(-(x-m).powi(2)/s2).exp()
    ).collect()
}

fn main() {
    let page = flot::Page::new("");

    let p = page.plot("Normal distribution").size(500,300);
    let xvalues: Vec<_> = flot::range(0.0,10.0,0.1).collect();
    p.lines("norm σ=1.0",make_gaussian(&xvalues,5.0,1.0));
    p.lines("norm σ=0.7",make_gaussian(&xvalues,6.0,0.5));

    page.render("normal.html").unwrap();
}

range is a little convenience iterator for making ranges of floating-point values (subsequently I've discovered that the itertools-num crate provides something similar - see linspace).

flot::mapv is similar, except it takes an iterator of values. Here are the squares of all integers from 0 to 9:

    page.plot().legend_pos(Corner::TopLeft)
        .bars("squares",mapv(0..10,|x| x*x))
        .width(0.75);

(The iterator given to mapr and mapv can provide any values which can be converted into a f64, so the integer range works.)

Finally, flot::zip can take two iterators of references, which are zipped together into point tuples. This is useful if you have separate x and y data as slices or vectors.

Using flot-rs as a Personal Display Engine

By default, flot-rs uses the Cloudflare CDN for jQuery (3.2.1) and Flot (0.8.3), which means that these HTML documents are portable and can be viewed with anyone with an internet connenction. Browsers cache these dependencies, so that generally these documents render quickly. However, if you download Flot directly, then you can set the environment variable FLOT to its location. E.g. I have export FLOT=/home/steve/Downloads/flot.

Being a command-line person, I tend to open generated HTML documents using the appropriate command, start for Windows, open for MacOS, gnome-open for Linux. There are browser-specific options for opening documents without toolbars and such like in their own window, e.g. google-chrome --app=doc.html and firefox --chrome doc.html for Firefox.

Dependencies

~180KB