Basic shapes are fundamendal PDFs, with often well-known functional form. They are usually fully analytically implemented and often a thin wrapper around :py:class:`~tensorflow_probability.distribution.Distribution`. Any missing shape can be easily wrapped using :py:class:`~zfit.pdf.WrapDistribution`. .. autosummary:: :toctree: _generated/basic zfit.pdf.Gauss zfit.pdf.Exponential zfit.pdf.CrystalBall zfit.pdf.DoubleCB zfit.pdf.GeneralizedCB zfit.pdf.GaussExpTail zfit.pdf.GeneralizedGaussExpTail zfit.pdf.Uniform zfit.pdf.Cauchy zfit.pdf.Voigt zfit.pdf.TruncatedGauss zfit.pdf.BifurGauss zfit.pdf.Poisson zfit.pdf.LogNormal zfit.pdf.QGauss zfit.pdf.ChiSquared zfit.pdf.StudentT zfit.pdf.Gamma zfit.pdf.JohnsonSU zfit.pdf.GeneralizedGauss