v0.19

This release brings major improvements especially in two sectors: the treatment of numerical likelihoods and plotting functions for 1D and 2D likelihoods. Users of flavio.plots.band_plot should read on as there have been some interface changes.

Improved treatment of numerical likelihoods

• Measurements of one- or multi-dimensional experimental constraints can now be specified in numerical form directly in YAML files. An example are the correlated measurements of rare leptonic B decays by CMS and LHCb that are now included by default. See also the documentation.

Improvements to plot functions

• The function flavio.plots.band_plot, used for 2D likelihood plots given a log-likelihood function (e.g. from a FastFit instance) has been superseded by the new function flavio.plots.likelihood_contour. The old name still works but might be removed in the near future. flavio.plots.likelihood_contour actually calls two functions after one another: flavio.plots.likelihood_contour_data computes the numerical values to plot; flavio.plots.contour produces the actual plot.
  The advantage of this split is that these functions can also be called separately, e.g. to perform the time-consuming calculation only once and be able to make tweaks to the plot style without the need for recomputation.
• The function flavio.plots.density_contour, used for density plots e.g. for Bayesian MCMC analyses, has been rewritten from scratch:
  • Data production is also separated into flavio.plots.density_contour_data and the same function flavio.plots.contour as for the likelihood plots is used for presentation
  • For the kernel density estimate, a fast fourier transform is used now. For a large number of points, as is typical for MCMC analyses, this leads to an enormous speed-up. Density contours can now be plotted from samples with several million points in a matter of seconds!
• The function flavio.plots.smooth_histogram, the 1D analogue of density contour, has also been rewritten from scratch:
  • Instead of just interpolating a histogram, it now also uses a Gaussian KDE based on FFT
  • The 1 sigma region can now be displayed as a shaded vertical band
• A new function flavio.plots.pdf_plot plots 1D likelihoods, e.g. from FastFit instances, with the same style as smooth_histogram.

All the old and new plot functions are documented in detail in the API docs. Example notebooks will follow in due time.

Physics updates

Finally, there have also been some small physics improvements, in addition to the experimental measurements mentioned above.

• Some parameters updated to HFAG 2016 values
• Mass-eigenstate rate asymmetry in B_s→ll added (ADeltaGamma(Bs->mumu) etc.)
• Angular observable S₆^c in B→K*ll added (e.g. <S6c>(B0->K*mumu))