hist package#
- class hist.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.Hist(*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:
BaseHist
- class hist.NamedHist(*args: Any, **kwargs: Any)#
Bases:
BaseHist
- fill(weight: Any | None = None, sample: Any | None = None, threads: int | None = None, **kwargs: Any) Self #
Insert data into the histogram using names and return a NamedHist object. NamedHist could only be filled by names.
- fill_flattened(obj: Any | None = None, *, weight: Any | None = None, sample: Any | None = None, threads: int | None = None, **kwargs: Any) Self #
- project(*args: int | str) Self | float | Any #
Projection of axis idx.
- class hist.Stack(*args: BaseHist)#
Bases:
object
- property axes: NamedAxesTuple#
- classmethod from_dict(d: Mapping[str, BaseHist]) Self #
Create a Stack from a dictionary of histograms. The keys of the dictionary are used as names.
- classmethod from_iter(iterable: Iterable[BaseHist]) Self #
Create a Stack from an iterable of histograms.
- plot(*, ax: mpl.axes.Axes | None = None, **kwargs: Any) Any #
Plot method for Stack object.
- project(*args: int | str) Self #
Project the Stack onto a new axes.
- show(**kwargs: object) Any #
Pretty print the stacked histograms to the console.
- class hist.rebin(factor: int | None = None, *, groups: Sequence[int] | None = None)#
Bases:
object
- factor#
- group_mapping(axis: PlottableAxis) Sequence[int] #
- groups#
- hist.sum(iterable, /, start=0)#
Return the sum of a ‘start’ value (default: 0) plus an iterable of numbers
When the iterable is empty, return the start value. This function is intended specifically for use with numeric values and may reject non-numeric types.
Subpackages#
Submodules#
- hist.accumulators module
- hist.axestuple module
- hist.basehist module
BaseHist
BaseHist.T
BaseHist.density()
BaseHist.fill()
BaseHist.fill_flattened()
BaseHist.from_columns()
BaseHist.integrate()
BaseHist.plot()
BaseHist.plot1d()
BaseHist.plot2d()
BaseHist.plot2d_full()
BaseHist.plot_pie()
BaseHist.plot_pull()
BaseHist.plot_ratio()
BaseHist.profile()
BaseHist.project()
BaseHist.show()
BaseHist.sort()
BaseHist.stack()
BaseHist.sum()
SupportsLessThan
process_mistaken_quick_construct()
- hist.classichist module
- hist.hist module
- hist.intervals module
- hist.namedhist module
- hist.numpy module
- hist.plot module
- hist.quick_construct module
ConstructProxy
MetaConstructor
QuickConstruct
QuickConstruct.Bool()
QuickConstruct.Boolean()
QuickConstruct.Func()
QuickConstruct.Int()
QuickConstruct.IntCat()
QuickConstruct.IntCategory()
QuickConstruct.Integer()
QuickConstruct.Log()
QuickConstruct.Pow()
QuickConstruct.Reg()
QuickConstruct.Regular()
QuickConstruct.Sqrt()
QuickConstruct.StrCat()
QuickConstruct.StrCategory()
QuickConstruct.Var()
QuickConstruct.Variable()
QuickConstruct.axes
QuickConstruct.hist_class
- hist.stack module
- hist.storage module
- hist.svgplots module
- hist.svgutils module
- hist.tag module
- hist.version module