GitLab

Get back the modifications made to generate the wheels (and to remove
obsolete version numbers).

Slight update of the version number as CIGALE is now installable as non
editable.

The wheel is too big to fit in a Gitlab artefact.

Make sure that all the cores are occupied for the entire duration of the computation of the Bayesian and best-fit estimates. We do that with a chunksize of 1. This is not beneficial for the computation of the models as it would induce a large number of costly context switches and it would affect negatively the model cache as blocks would not be attributed consecutively to a process.

Slight update of the version number as CIGALE is now installable as non
editable.

The wheel is too big to fit in a Gitlab artefact.

Various optimisations have been made regarding shared arrays to make their access faster. The overall effect is a speedup of 3-4% for the computation of the models.

Implementation of the auto-detection of lines in the input flux file so they are automatically added to the list of bands in pcigale.ini

The time spent computing is now displayed in hours, minutes, and seconds rather than just seconds to improve legibility

Move read_table() and Counter() to a top-level utils directory as they are used both by pcigale and pcigale-plots.

Optimise the retrieval of a luminosity component as cigale has not supported having several modules of the same name in many years now.

The computation of all the cosmology-dependent quantities has been consolidated in pcigale/utils/cosmology.py and optimised. This leads to a slightly faster startup, in particular when there are many objects to fit, and it makes it easier to change the cosmology.

Create a pcigale/utils directory to store various utility functions in preparation for the inclusion of cosmology utility functions. Move pcigale/utils.py to pcigale/utils/io.py, which contains only read_table() and adapt the rest of the code accordingly.

Now that the minimum python version is 3.6, store integers as integers rather than as floats in SharedArray.

Speedup the computation of the weighted means and standard deviation by normalising the likelihhod, simplifying the computation

Maximise the CPU cache hit rate with computing the χ² by storing contiguously all the models at a given redshift.

When determining the fluxes to compute, make sure we only try to access the list of bands to analyse when that parameter is actually present in the analysis module.

Implement the possibility of specifying a list of bands for which to carry out a Bayesian flux estimate.