hist.basehist module#
- class hist.basehist.BaseHist(*in_args: AxisProtocol | Tuple[int, float, float] | Storage | str, storage: Storage | str | None = None, metadata: Any | None = None, data: ndarray[Any, dtype[Any]] | None = None, label: str | None = None, name: str | None = None)#
Bases:
Histogram
- property T: Self#
- density() ndarray[Any, dtype[Any]] #
Density NumPy array.
- fill(*args: Any, weight: Any | None = None, sample: Any | None = None, threads: int | None = None, **kwargs: Any) Self #
Insert data into the histogram using names and indices, return a Hist object.
- fill_flattened(*args: Any, weight: Any | None = None, sample: Any | None = None, threads: int | None = None, **kwargs: Any) Self #
- classmethod from_columns(data: Mapping[str, Any], axes: Sequence[str | AxisProtocol], *, weight: str | None = None, storage: Storage = Double()) Self #
- integrate(name: int | str, i_or_list: InnerIndexing | list[str | int] | None = None, j: InnerIndexing | None = None) Self | float | bh.accumulators.Accumulator #
- plot(*args: Any, overlay: str | None = None, **kwargs: Any) Hist1DArtists | Hist2DArtists #
Plot method for BaseHist object.
- plot1d(*, ax: matplotlib.axes.Axes | None = None, overlay: str | int | None = None, **kwargs: Any) Hist1DArtists #
Plot1d method for BaseHist object.
- plot2d(*, ax: matplotlib.axes.Axes | None = None, **kwargs: Any) Hist2DArtists #
Plot2d method for BaseHist object.
- plot2d_full(*, ax_dict: dict[str, matplotlib.axes.Axes] | None = None, **kwargs: Any) tuple[Hist2DArtists, Hist1DArtists, Hist1DArtists] #
Plot2d_full method for BaseHist object.
Pass a dict of axes to
ax_dict
, otherwise, the current figure will be used.
- plot_pie(*, ax: matplotlib.axes.Axes | None = None, **kwargs: Any) Any #
- plot_pull(func: Callable[[np.typing.NDArray[Any]], np.typing.NDArray[Any]] | str, *, ax_dict: dict[str, matplotlib.axes.Axes] | None = None, **kwargs: Any) tuple[FitResultArtists, RatiolikeArtists] #
plot_pull
method forBaseHist
object.Return a tuple of artists following a structure of
(main_ax_artists, subplot_ax_artists)
- plot_ratio(other: hist.BaseHist | Callable[[np.typing.NDArray[Any]], np.typing.NDArray[Any]] | str, *, ax_dict: dict[str, matplotlib.axes.Axes] | None = None, **kwargs: Any) tuple[MainAxisArtists, RatiolikeArtists] #
plot_ratio
method forBaseHist
object.Return a tuple of artists following a structure of
(main_ax_artists, subplot_ax_artists)
- profile(axis: int | str) Self #
Returns a profile (Mean/WeightedMean) histogram from a normal histogram with N-1 axes. The axis given is profiled over and removed from the final histogram.
- project(*args: int | str) Self | float | Any #
Projection of axis idx.
- show(**kwargs: Any) Any #
Pretty print histograms to the console.
- sort(axis: int | str, key: Callable[[int], SupportsLessThan] | Callable[[str], SupportsLessThan] | None = None, reverse: bool = False) Self #
Sort a categorical axis.
- sum(flow: bool = False) float | Any #
Compute the sum over the histogram bins (optionally including the flow bins).
- class hist.basehist.SupportsLessThan(*args, **kwargs)#
Bases:
Protocol
- hist.basehist.process_mistaken_quick_construct(axes: Sequence[AxisProtocol | Tuple[int, float, float] | ConstructProxy]) Generator[AxisProtocol | Tuple[int, float, float], None, None] #