v0.2.1

Upgrades

• Better documentation on how to mock data without explicit observation
• fakeit_for_multiple_parameters has been optimized to explicitly prevent the replication of response matrix, easing folding for multiple parameters at once without blowing up memory
• prior_predictive_coverage should use multiple cores now
• Internal cleaning : we do not depend explicitly on the Heacit dataset but rather download what is needed on the fly

Bug Fixes

• Fix tbpcf and FDcut models that were not fully ported after the internal rework of jaxspec
• Fix Agauss, Zagauss, Zgauss which were in a similar situation

Full Changelog: v0.2.0...v0.2.1

v0.2.0

This new version brings a brand-new backend for the jaxspec model building tool. We are switching from haiku (which is now in maintenance mode) to nnx to handle the parameters in JAX. It brings some new breaking changes, but will help a lot for future maintenance.

Upgrades

• Background model scaling has been fixed, there was an issue because the scaling factor was applied after folding while it should be before.
• plot_ppc can now display multiple components in the model, see here
• Codebase and documentation were cleaned a bit

Breaking changes

• Model parameters are now all lower case and underscore use is forbidden for now. If you used components such as tbabs, be sure to change N_H to nh
• Custom model components should be built using nnx. It changes a bit when compared to haiku, and has been updated accordingly in the documentation

What's Changed

• Update pytest-cov requirement from >=4.1,<6.0 to >=4.1,<7.0 by @dependabot in #202
• Factor ARF from RSP by @lmauviard in #205
• switching to nnx by @renecotyfanboy in #203
• Update mendeleev requirement from >=0.15,<0.19 to >=0.15,<0.20 by @dependabot in #207
• Update mkdocstrings requirement from >=0.24,<0.27 to >=0.24,<0.28 by @dependabot in #206
• updating dependencies by @renecotyfanboy in #208
• Update numpyro requirement from ^0.15.3 to >=0.15.3,<0.17.0 by @dependabot in #211
• Update ruff requirement from >=0.2.1,<0.8.0 to >=0.2.1,<0.9.0 by @dependabot in #210
• update documentation by @renecotyfanboy in #209

New Contributors

• @lmauviard made their first contribution in #205

Full Changelog: v0.1.4...v0.2.0

v0.1.4

What's new ?

• Fixed a bug where subtracting background had no effect
• Add the possibility to use a spectral model as the background
• Luminosity can be computed using either distance or redshift
• Prior predicting coverage is clearer

Full Changelog: v0.1.3...v0.1.4

v0.1.3

Just fix a silent issue in the previous release

v0.1.2

• Prior predictive coverage using the BayesianFitter
• Internal fixings
• Pretty representation for SpectralModel

v0.1.1

This is our first release after the article acceptance.

• All the numpyro's MCMC are now gathered within our MCMCFitter class, where the user can switch using the sampler parameter
• Priors can now be passed as a flat dictionary instead of the nested dictionary from haiku. We want it to be the main way to pass prior in the future releases.
• Changes in the inner workings of the fitter for future features.

v0.1.0

That's it, we are now entering the beta release of jaxspec! You can expect bugs and changing APIs as always, but now, the project starts to be mature enough so that anyone can use it. You are welcome to give it a try!

Full Changelog: v0.0.8...v0.1.0

v0.0.8

New features

• The best-fit model photon flux, energy flux and luminosity can be computed using the FitResult new methods
• Introduction of NestedSamplingFitter which is still in beta status
• Large data tables and others are now downloaded at runtime using the pooch package

Breaking changes

• Prior distribution must now be passed when building the fitter object instead of using the .fit method
• BayesianFitter is renamed to NUTSFitter

Full Changelog: v0.0.7...v0.0.8

v0.0.7

New features

• Users can now compute the photon flux, energy flux and luminosity using the related methods from the FitResult class. These values can be registered so that comparison with the model parameters can be shown in the corner plots.
• A subset of parameters can be plotted in the FitResult.plot_corner by passing the columns parameter, which should be the list of parameters to display
• The cstat is accessible using FitResult.c_stat
• The plot_ppc has been slightly reworked, more upgrades to come in the future

v0.0.6

Major bugfixes related to the import of APEC tables. jaxspec should now automatically release for each new vX.X.X tag