rics.performance.plot#

Plotting backend for the performance framework.

Warning

This API is NOT stable.

Functions

`make_postprocessors`(kwargs)	Construct postprocessors based on kwargs.
`plot`(run_results[, x, unit, path])
`plot_params`(params, *[, path])

Classes

CatplotParams(*, data, x, y, hue, kind, ...)

class CatplotParams(*, data: pandas.core.frame.DataFrame, x: Literal['Candidate'] | Literal['Test data'], y: str, hue: Literal['Candidate'] | Literal['Test data'], kind: Literal['bar', 'box', 'boxen', 'point', 'strip', 'swarm', 'violin'], names: list[str], user_kwargs: Mapping[str, Any])[source]#

Bases: object

data: DataFrame#

x: Literal['Candidate'] | Literal['Test data']#

y: str#

hue: Literal['Candidate'] | Literal['Test data']#

kind: Literal['bar', 'box', 'boxen', 'point', 'strip', 'swarm', 'violin']#

names: list[str]#

user_kwargs: Mapping[str, Any]#

DEFAULTS: ClassVar[dict[str, Any]] = {'aspect': 2, 'errorbar': 'sd', 'estimator': 'min'}#

DEFAULTS_BY_KIND: ClassVar[dict[Literal['bar', 'box', 'boxen', 'point', 'strip', 'swarm', 'violin'], dict[str, Any]]] = {'bar': {'capsize': 0.2}, 'point': {'capsize': 0.2}}#

COMPUTED_DEFAULTS: ClassVar[tuple[str, ...]] = ('order', 'hue_order', 'log_scale')#

classmethod reserved_keys() → set[str][source]#

classmethod make(run_results: dict[str, dict[Hashable, list[float]]] | DataFrame, *, x: Literal['candidate', 'data'] | None = None, unit: Literal['s', 'ms', 'μs', 'us', 'ns'] | None = None, kind: Literal['bar', 'box', 'boxen', 'point', 'strip', 'swarm', 'violin'] = 'bar', names: Iterable[str] = (), **kwargs: Any) → Self[source]#: Create instance from run results.

to_kwargs() → dict[str, Any][source]#: Convert to seaborn.catplot() keyword arguments.

property want_log_scale_hack: bool#

plot(run_results: dict[str, dict[Hashable, list[float]]] | DataFrame, x: Literal['candidate', 'data'] | None = None, *, unit: Literal['s', 'ms', 'μs', 'us', 'ns'] | None = None, path: str | Path | None = None, **kwargs: Any) → FacetGrid[source]#

plot_params(params: CatplotParams, *, path: str | Path | None = None) → FacetGrid[source]#

make_postprocessors(kwargs: dict[str, Any]) → list[Postprocessor][source]#

Construct postprocessors based on kwargs.

Parameters:: kwargs – Keyword arguments for seaborn.catplot(). May be modified.
Returns:: A list of postprocessors.

Modules

rics.performance.plot.types

Types used by the plotting framework.