Color Scales

Map a numeric column through an interpolated color ramp with ColorScale — usable with any get_*_color accessor:

# Named palette
dgl.ScatterplotLayer(
    data=df,
    get_position=["lon", "lat"],
    get_fill_color=dgl.ColorScale("temperature", palette="viridis"),
)

# Two-color ramp with log scaling
dgl.ScatterplotLayer(
    data=df,
    get_position=["lon", "lat"],
    get_fill_color=dgl.ColorScale("population", colors=["blue", "red"], scale="log"),
)

Palettes: viridis, plasma, inferno, magma, cividis, coolwarm, RdBu, spectral, turbo.

Parameters

Parameter	Default	Description
column	(required)	Numeric column name to map
palette	—	Named palette (mutually exclusive with colors)
colors	—	2+ colors: names ("blue"), hex ("#FF0000"), or RGB ([255, 0, 0])
domain	auto	(min, max) value range; auto-detected from data if omitted
scale	"linear"	"linear" or "log"
alpha	255	Alpha channel (0–255) for all output colors

Callable accessors

For arbitrary per-row logic, pass a function instead:

dgl.ScatterplotLayer(
    data=df,
    get_position=["lon", "lat"],
    get_fill_color=lambda row: [
        int(row["temperature"] * 2.55),
        50,
        255 - int(row["temperature"] * 2.55),
        200,
    ],
)

Both ColorScale and callables work with binary transport — colors resolve in Python and pack into the buffer automatically.

Concrete data required

ColorScale and callable accessors materialize your data to compute per-row values, so they don't work with URL data. Load the data yourself first, or pre-compute a color column.