hist.basehist module

class hist.basehist.BaseHist(*in_args: AxisTypes | Storage | str, storage: Storage | str | None = None, metadata: Any = None, data: np.typing.NDArray[Any] | None = None, label: str | None = None, name: str | None = None)

Bases: Histogram

property T: Self

density() → np.typing.NDArray[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 for BaseHist 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 for BaseHist 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.

stack(axis: int | str) → Stack

Returns a stack from a normal histogram axes.

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]