scale-size-binned-area
Binned area-proportional size scale.
Combines binning with area scaling: the domain is partitioned into n-breaks bins, and the size of each bin grows with the square root of its normalised midpoint position.
Usage
scale-size-binned-area(
n-breaks: 4,
range: (1pt, 6pt),
name: none,
limits: none,
labels: auto,
)Parameters
| Parameter | Default | Description |
|---|---|---|
n-breaks |
4 |
Number of bins to partition the domain into. |
range |
(1pt, 6pt) |
Pair of Typst lengths (min, max) bounding the output size. |
name |
none |
Legend title. Overrides any name set via labs when both are present. |
limits |
none |
Pair (lo, hi) clipping the trained domain, or none. |
labels |
auto |
Array of legend labels aligned with the bins, or auto. |
Returns
Scale object consumed by plot.
Examples
Four-bin area-proportional discretisation on a quadratic series.
#let d = range(1, 8).map(i => (x: i, y: i, w: i * i))
#plot(
data: d,
mapping: aes(x: "x", y: "y", size: "w"),
layers: (geom-point(),),
scales: (scale-size-binned-area(n-breaks: 4, range: (1pt, 12pt)),),
width: 10cm,
height: 6cm,
)
Combine more bins with a wider range for a finer banded area scale on dense data.
#let d = range(1, 16).map(i => (x: i, y: i, w: i * i))
#plot(
data: d,
mapping: aes(x: "x", y: "y", size: "w"),
layers: (geom-point(),),
scales: (scale-size-binned-area(n-breaks: 8, range: (1pt, 16pt)),),
width: 10cm,
height: 6cm,
)
