Line plots connect (x, y) data points with a continuous line, ideal for visualizing trends, time series, and functional relationships. Kuva’s LinePlot supports four built-in line styles (solid, dashed, dotted, dash-dot), area fills, step interpolation, confidence bands, and error bars.
When to Use
- Time series data and trends over time
- Continuous functional relationships (y = f(x))
- Comparing multiple series on the same axes
- Showing uncertainty with error bars or confidence bands
- Step functions and discrete-time data
- Area charts showing cumulative values
Basic Example
use kuva::plot::LinePlot;
use kuva::backend::svg::SvgBackend;
use kuva::render::render::render_multiple;
use kuva::render::layout::Layout;
use kuva::render::plots::Plot;
let data: Vec<(f64, f64)> = (0..=100)
.map(|i| {
let x = i as f64 * 0.1;
(x, x.sin())
})
.collect();
let plot = LinePlot::new()
.with_data(data)
.with_color("steelblue")
.with_stroke_width(2.0);
let plots = vec![Plot::Line(plot)];
let layout = Layout::auto_from_plots(&plots)
.with_title("Sine Wave")
.with_x_label("X")
.with_y_label("Y");
let svg = SvgBackend.render_scene(&render_multiple(plots, layout));
std::fs::write("line.svg", svg).unwrap();
Key Methods
Set the (x, y) data points to connect. Accepts any iterator of (T, U) pairs where T and U implement Into<f64>:// Integer input
.with_data(vec![(0_i32, 0_i32), (1, 2), (2, 1)])
// Float input
.with_data(vec![(0.0_f64, 0.0_f64), (1.5, 2.3), (3.0, 1.8)])
Styling
Set the line color using CSS color strings:.with_color("steelblue")
.with_color("#4682b4")
.with_color("rgb(70,130,180)")
Set the line width in pixels (default 2.0):.with_stroke_width(3.0) // Thicker line
Set the line style explicitly:use kuva::plot::LineStyle;
.with_line_style(LineStyle::Solid) // Default
.with_line_style(LineStyle::Dashed) // 8 4 dasharray
.with_line_style(LineStyle::Dotted) // 2 4 dasharray
.with_line_style(LineStyle::DashDot) // 8 4 2 4 dasharray
.with_line_style(LineStyle::Custom("10 5 2 5".into())) // Custom SVG dasharray
Shortcut for dashed line style: Shortcut for dotted line style: Shortcut for dash-dot line style: Area Fill
Fill the area between the line and the x-axis:Uses the line color at the opacity set by with_fill_opacity() (default 0.3). Set fill opacity for area charts (default 0.3):.with_fill()
.with_fill_opacity(0.5) // 50% opacity
Step Interpolation
Use step interpolation (horizontal then vertical segments):Instead of diagonal lines between points, draws horizontal segments at each y-value then vertical steps. Useful for histograms and discrete-time series. Error Bars
Add symmetric X error bars:let x_err = vec![0.1_f64, 0.15, 0.2];
.with_x_err(x_err)
Add symmetric Y error bars:let y_err = vec![0.15_f64, 0.20, 0.12];
.with_y_err(y_err)
Add asymmetric X error bars:let x_err = vec![(0.1_f64, 0.2_f64), (0.15, 0.25)];
.with_x_err_asymmetric(x_err)
Add asymmetric Y error bars:let y_err = vec![(0.1_f64, 0.3_f64), (0.2, 0.4)];
.with_y_err_asymmetric(y_err)
Confidence Bands
Add a shaded confidence region:let data: Vec<(f64, f64)> = /* your data */;
let lower: Vec<f64> = /* lower bounds */;
let upper: Vec<f64> = /* upper bounds */;
.with_band(lower, upper)
Legend
Attach a legend label for this series:.with_legend("Temperature")
Examples
Multiple Line Styles
let xs: Vec<f64> = (0..=80).map(|i| i as f64 * 0.125).collect();
let plots = vec![
Plot::Line(
LinePlot::new()
.with_data(xs.iter().map(|&x| (x, x.sin())))
.with_color("steelblue")
.with_stroke_width(2.0)
.with_legend("Solid")
),
Plot::Line(
LinePlot::new()
.with_data(xs.iter().map(|&x| (x, x.cos())))
.with_color("crimson")
.with_stroke_width(2.0)
.with_dashed()
.with_legend("Dashed")
),
Plot::Line(
LinePlot::new()
.with_data(xs.iter().map(|&x| (x, (x * 0.7).sin())))
.with_color("seagreen")
.with_stroke_width(2.0)
.with_dotted()
.with_legend("Dotted")
),
];
Area Plot
let data: Vec<(f64, f64)> = (0..=100)
.map(|i| {
let x = i as f64 * 0.1;
(x, x.sin())
})
.collect();
let plot = LinePlot::new()
.with_data(data)
.with_color("steelblue")
.with_stroke_width(2.0)
.with_fill()
.with_fill_opacity(0.3);
Step Plot
let data: Vec<(f64, f64)> = vec![
(0.0, 2.0), (1.0, 5.0), (2.0, 3.0), (3.0, 7.0),
(4.0, 4.0), (5.0, 8.0), (6.0, 5.0), (7.0, 9.0),
];
let plot = LinePlot::new()
.with_data(data)
.with_color("steelblue")
.with_stroke_width(2.0)
.with_step();
Line with Confidence Band
let xs: Vec<f64> = (0..=80).map(|i| i as f64 * 0.125).collect();
let ys: Vec<f64> = xs.iter().map(|&x| x.sin()).collect();
let lower: Vec<f64> = ys.iter().map(|&y| y - 0.3).collect();
let upper: Vec<f64> = ys.iter().map(|&y| y + 0.3).collect();
let data: Vec<(f64, f64)> = xs.into_iter().zip(ys).collect();
let plot = LinePlot::new()
.with_data(data)
.with_color("steelblue")
.with_stroke_width(2.0)
.with_band(lower, upper);
Line with Error Bars
let data: Vec<(f64, f64)> = (0..=8)
.map(|i| (i as f64, (i as f64 * 0.8).sin()))
.collect();
let y_err: Vec<f64> = vec![
0.15, 0.20, 0.12, 0.18, 0.22, 0.14, 0.19, 0.16, 0.21
];
let plot = LinePlot::new()
.with_data(data)
.with_y_err(y_err)
.with_color("steelblue")
.with_stroke_width(2.0);
Tips
Multiple series: Use different colors and line styles to distinguish overlapping series. Combine with .with_legend() for clarity.
Time series: For discrete time steps (daily, monthly data), consider using .with_step() to emphasize the stepwise nature of the data.
Smooth curves: For very smooth curves, generate more data points. For mathematical functions, use 100-200 points for most screen resolutions.
Error bars and bands must have the same length as your data points. Call .with_data() first, then add error bars or bands.
Source Location
Implementation: src/plot/line.rs
Examples: examples/line.rs