BinnedData#
- class zfit.data.BinnedData(*args, **kwds)[source]#
Bases:
zfit.core.interfaces.ZfitBinnedData
- classmethod from_tensor(space, values, variances=None)[source]#
Create a binned dataset defined in space where values are considered to be the counts.
- Parameters
space (ZfitSpace) – The space of the data. Variables need to match the values dimensions. The space has to be binned and carry the information about the edges.
values (znp.array) – Actual counts of the histogram.
variances (znp.array | None) – Uncertainties of the histogram values. If
True
, the uncertainties are taken to be poissonian distributed.
- Return type
- classmethod from_hist(hist)[source]#
Create a binned dataset from a
hist
histogram.- Parameters
hist (
NamedHist
) – A NamedHist. The axes will be used as the binning in zfit.- Return type
- with_obs(obs)[source]#
Return a subset of the data in the ordering of obs.
- Parameters
obs (
Union
[str
,Iterable
[str
],Space
]) – Which obs to return- Return type
- to_hist()[source]#
Convert the binned data to a
NamedHist
.While a binned data object can be used inside zfit (PDFs,…), it lacks many convenience features that the hist library offers, such as plots.
- Return type
- values()[source]#
Values of the histogram as an ndim array.
Compared to
hist
, zfit does not make a difference between a view and a copy; tensors are immutable. This distinction is made in the traced function by the compilation backend.- Return type
array
- Returns
Tensor of shape (nbins0, nbins1, …) with nbins the number of bins in each observable.
- variances()[source]#
Variances, if available, of the histogram as an ndim array.
Compared to
hist
, zfit does not make a difference between a view and a copy; tensors are immutable. This distinction is made in the traced function by the compilation backend.- Return type
None | znp.array
- Returns
Tensor of shape (nbins0, nbins1, …) with nbins the number of bins in each observable.
- counts()[source]#
Effective counts of the histogram as an ndim array.
Compared to
hist
, zfit does not make a difference between a view and a copy; tensors are immutable. This distinction is made in the traced function by the compilation backend.- Returns
Tensor of shape (nbins0, nbins1, …) with nbins the number of bins in each observable.