scale_color_igv ¶
scale_color_igv(
palette: Literal | None = None,
alpha: float = 1,
overflow: Literal | None = None,
name: str | None = None,
breaks: Breaks | None = None,
labels: Labels | None = None,
lablim: int | None = None,
limits: Limits | None = None,
na_value: Color | None = None,
guide: Guide | None = None,
format: str | None = None,
) -> FeatureSpec
Map color with the ggsci igv palette, from the IGV genome browser.
A discrete scale (51 colors, 2 for "alternating").
Not in lets-plot (R package ggsci).
Parameters:
-
palette((default, alternating), default:"default") –ggsci palette name.
-
alpha(float, default:1) –Opacity of the palette colors, in (0, 1].
-
overflow((generate, cycle, interpolate), default:"generate") –How to get more colors than the palette has (
"g","c","i"). Default:"generate", asscale_*_brewer()for qualitative palettes. ggsci leaves the extra categories missing; ggrust colors them and warns. -
name(str, default:None) –Legend title.
-
breaks(list, default:None) –Categories that get a legend key.
-
labels(list of str or dict, default:None) –One label per break (a dict maps breaks to labels).
-
lablim(int, default:None) –Maximum label length in characters; longer labels are cut.
-
limits(list, default:None) –The categories (and their order) of the scale. Other data gets
na_value. -
na_value(str, default:None) –Color drawn for missing data and data outside
limits. -
guide(str or FeatureSpec, default:None) –"legend","none", or aguide_legend()spec. -
format(str, default:None) –Label format: a number format (
".2f",",","%") or a template ("{.1f} %").labelstake precedence.
Returns:
-
FeatureSpec–The scale.
Raises:
-
SpecError–If
paletteis not a igv palette name,alphais not in (0, 1], oroverflowis not an overflow name. -
UnsupportedValueError–If
paletteis not a string oralphais not a number.
Examples:
>>> from ggrust import *
>>> data = {"x": list(range(30)), "y": [value % 7 for value in range(30)],
... "chromosome": [f"chr{value + 1}" for value in range(30)]}
>>> plot = ggplot(data, aes("x", "y", color="chromosome")) + geom_point(size=5)
>>> plot = plot + scale_color_igv()