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

BinnedData

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: BinnedData

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: BinnedData

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: NamedHist

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.

Data

Param