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@renecotyfanboy renecotyfanboy released this 19 Apr 13:09
· 302 commits to main since this release
v0.0.5
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Learn about vigilant mode.

The 0.0.5 release of jaxspec is out ! Many code refactoring and internal cleaning is happening, but there are also new features, including a direct fit method for your spectral models.

New features

  • jaxspec.fit module now includes BayesianFitter and MinimizationFitter classes to perform either MCMC or direct minimization to find the best set of parameters. Note that MinimizationFitter is faster but more likely to fall in local minima.
  • Both BayesianFitter and MinimizationFitter can fit the same model using multiple ObsConfiguration at once to obtain stronger constraints. Either pass a list[ObsConfiguration] or a dict[str, ObsConfiguration] to achieve this.
  • Fit results are now plotable with any unit you want! FitResult.plot_ppc haw two new kwargs : x_unit and y_type. x_unit argument can be any unit of length, frequency, or energy and the plot will adapt. y_type can be any of "counts", "countrate", "photon_flux", "photon_flux_density" and will plot the equivalent curve.
  • fakeit and fakeit_for_multiple_parameters can specify sparsify_matrix = True for large RMF.
  • jaxspec.util.abundances now contains two tables. abundance_table contains the most used abundance tables in astrophysics, and element_table contains various data about elements, imported from the mendeleevpackage.
  • jaxspec is now tested against the HEACIT dataset to ensure that it is performant at reading the many types of instrument and observation files produced by the OGIP standard.

Breaking changes

  • ChainResult is renamed to FitResult
  • ChainResult.chain is renamed to FitResult.to_chain
  • ChainResult.sample has been split to FitResult.samples_haiku for a two level dictionary of posterior samples, e.g. samples['powerlaw_1']['alpha'], and to FitResult.samples_flat for a one level dictionary of posterior samples, e.g. samples['powerlaw_1_alpha'].
  • BayesianModel is renamed to BayesianFitter.
  • Instrument.from_ogip_file now takes arf_path as a kwarg since some instruments use a single .rmf file to carry both the redistribution matrix and effective area. Instrument.from_ogip_file("data/PN.rmf","data/PN.arf") should be changed to Instrument.from_ogip_file("data/PN.rmf", arf_path="data/PN.arf"). Even if the first syntax should work, be carefull to check that you did not intervert .arf and .rmf.
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