Source code for zfit.models.histogram

#  Copyright (c) 2024 zfit
from __future__ import annotations

import numpy as np
from uhi.typing.plottable import PlottableHistogram

import zfit.z.numpy as znp

from ..core.binnedpdf import BaseBinnedPDFV1
from ..core.interfaces import ZfitBinnedData
from import supports
from ..util import ztyping
from ..util.exception import SpecificFunctionNotImplemented

[docs] class HistogramPDF(BaseBinnedPDFV1): def __init__( self, data: ztyping.BinnedDataInputType, extended: ztyping.ExtendedInputType | None = None, norm: ztyping.NormInputType | None = None, name: str = "HistogramPDF", label: str | None = None, ) -> None: """Binned PDF resembling a histogram. Simple histogram PDF that can be used to model a histogram as a PDF. Args: data: Histogram to be used as PDF. extended: |@doc:pdf.init.extended| The overall yield of the PDF. If this is parameter-like, it will be used as the yield, the expected number of events, and the PDF will be extended. An extended PDF has additional functionality, such as the ``ext_*`` methods and the ``counts`` (for binned PDFs). |@docend:pdf.init.extended| || If ``True``, the PDF will be extended automatically if the PDF is extended using the total number of events in the histogram. This is the default. || norm: |@doc:pdf.init.norm| Normalization of the PDF. By default, this is the same as the default space of the PDF. |@docend:pdf.init.norm| name: || Name of the PDF. Maybe has implications on the serialization and deserialization of the PDF. For a human-readable name, use the label. || label: |@doc:pdf.init.label| Human-readable name or label of the PDF for a better description, to be used with plots etc. Has no programmatical functional purpose as identification. |@docend:pdf.init.label| """ if extended is None: extended = True if not isinstance(data, ZfitBinnedData): if isinstance(data, PlottableHistogram): from zfit._data.binneddatav1 import BinnedData data = BinnedData.from_hist(data) else: msg = "data must be of type PlottableHistogram (UHI) or ZfitBinnedData" raise TypeError(msg) params = {} if extended is True: self._automatically_extended = True extended = znp.sum(data.values()) else: self._automatically_extended = False super().__init__(, extended=extended, norm=norm, params=params, name=name, label=label) self._data = data @supports(norm="space") def _ext_pdf(self, x, norm): if not self._automatically_extended: raise SpecificFunctionNotImplemented counts = self._counts(x, norm) areas =, axis=0) return counts / areas @supports(norm="space") def _pdf(self, x, norm): counts = self._rel_counts(x, norm) areas =, axis=0) return counts / areas @supports(norm="space") def _counts(self, x, norm=None): # noqa: ARG002 if not self._automatically_extended: raise SpecificFunctionNotImplemented return self._data.values() @supports(norm="space") def _rel_counts(self, x, norm=None): # noqa: ARG002 values = self._data.values() return values / znp.sum(values)