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Start the parallel processes with fork rather than spawn on Linux platforms, resulting in a faster startup.

Rename ParametersHandler to ParametersManager to be consistent with new managers that will come in the near future.

Pratical implementation of the validation of the parameters. The patch is quite long as it has a direct effect on the structure of the configuration dictionary. The validation has the advantage of automatically convert the parameters to the right type. Therefore rather than building a dictionary ourselves, we rather use the ready-made dictionary from ConfigObj. Because the names of the sections are not the same, quite a bit of code had to be adapted. Finally, note that the validation file containing the specification of each variable, pcigale.ini.spec, is created while building the pcigale.ini file. Also because it is needed to convert the data to the right type, one cannot run cigale without a correct validation file.

Abstract the call to the parameters handler to allow for the creation of different handlers depending on how the parameters are provided, for instance either a systematic grid by giving then in pcigale.ini or through a file with each line providing a the parameters for a different model. The change is transparent to the rest of pcigale so it does not matter which handler is actually used.

When the redshifts are not indicated in pcigale.ini, compute them from the input flux file when the configuration dictionary is returned rather than in the analysis module, which should not have to change the configuration.

Simplify the interface of the analysis modules as it is needlessly restrictive by forcing a precise list of parameters. Different modules do not necessarily need the same information and the need for different input parameters may emerge in the future. To make the interface future-proof, we simply pass the file containing the configuration file. Then each analysis module picks the data it needs from it.

Get rid of the parameters array. Rather we generate parameters on-on-fly. This is done using a new class ParameterHandlers, which handles the generation of parameters from a given 1D index. While at it, also do away with global variables. This allows to spawn processes rather than fork them. Even if it takes a little time to do the spawn, this allows to solves some deadlocks with libraries which do not support being used on both sides of a forked process. Overall these modifications makes startup faster (no need to compute the cache cleaning parameters beforehand) and the generation speed is also a few percent faster when the number of models is large enough to compensate for the relatively slow spaning time.

Make pdf_analysis parallel. This required important changes. Functions saving data have been moved to the utils.py file. Workers for the parallel processes have been put in workers.py. To make sure we eliminate models incompatible with the age of the universe now the latter is indicated in sed.info for easy access. Ditto for the redshift.

Move the igmattenuation module and its LSST dependencies inside the psum
analysis module.
Remove the redshift_module and redshift_configuration parts of the
configuration file.

Remove the author email addresses from the source files and add a AUTHORS.rst
file with the addresses and current affiliation to make it easier to update
the information.

Also, give copyright to the University of Cambridge and the University of
Crete for code developed by authors working there.

For the creation and analysis modules, move the contents of the
common.py files to the __init__.py.

Move the SED creation modules to pcigale.creation_modules to be more
consistent with the analysis module location.

We follow the astropy version number scheme VERSION-RELEASE.

The redshifting module must be separated from the main modules producing
the restframe SED, because the redshift parameter is taken directly from
the observation list.
Nevertheless, it is still a SED creation module because one may want to
use it for testing various redshifts.

Make the statistical analysis module behave the same way as the SED
creation module so that one can easily develop and use another one.

s/[Pp]arametre/[Pp]arameter/g
s/[Dd]ictionnary/[Dd]ictionary/g

- Make the list of the analysed variables configurable.
- Compute the weighted average and standard deviation for these
  variables.
- Write the variable analysis results to a file.

First implementation of the run script.