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Replace the SED.info OrderedDict() with a very light weight and speficically tailored reimplementation of an OrderedDict(). The reason is that an OrderedDict() takes an inordinate amount to time to copy. In the end this could amount to a very significant fraction of the total runtime. Do not use this new implementation anywhere or it will break your code. It makes very strong assumptions on how it is to be used.

To verify whether a variable is among the keys of a dictionary there is actually no need to call the keys() function. A dictionary has a __contains__() member which is called when the “in” keyword is used.

There is no need to build a list of keys to check whether a variable is among the keys of a dictionary.

Avoid retrieving the module parameters for the sed.info dictionary each time we process a SED as these parameters are set in stone. Rather add them as class members in the init. This should result in a slight speedup.

Repair the badly broken dustatt_powerlaw module. It did not handle the contribution names properly, which broke the code if the nebular module was called.

Remove leftover comments from debugging and add the stellar population back in the output parameters.

BURGARELLA Denis authored Jul 31, 2015 and Yannick Roehlly committed Jul 31, 2015

For now, CIGALE does not work with a parameterless module, so we use
a fake one.

BURGARELLA Denis authored Jul 31, 2015 and Yannick Roehlly committed Jul 31, 2015

- mbb: modified black body
- param: parameterless module to compute some parameters and add them to
  the information dictionary
- sfhcomb_constant and sfhcomb_delayed: two star formation histories

The pseudo filters used to compute (pseudo) line fluxes must not be
normalised to 1. Also, we set their effective wavelength to the mean
wavelength of the positive part.

The wavelengths must be in angstrom.

Addition of pseudo filters used to compute de fluxes in some lines.
They are composed of a positive part (normalised to 1) above the line
and two negative part (of the same total area) on each side used to
remove the continuum.

The PSEUDO_D4000 pseudo filter measures the difference (not the ratio)
of the 4000 Å break.

Addition of a new module performing a quench on the star formation
history.  We must change a little the SED object to allow the
modification of the SED.

Addition of a new module to compute a star formation history as
described in Buat et al. 2008.

For the cache to be efficient it needs to be shared between all instances of the class. As the computation is done in separate processes, we do not need to worry about race conditions, the cache will only ever be accessed by a single instance at any given time.

The wavelength sampling varies depending on the wavelength. This means that we need to cache different grids depending on the redshift.

Médéric Boquien authored Jun 19, 2015 and Yannick Roehlly committed Jul 15, 2015

Only copy the SFH if it exists. For instance when only modelling the dust we do not have any stellar population.

Using a list to keep the information keys that are proportional to the
mass leads to problems when forcing the update of a proportional
information: the key name appears then twice (or more) in the list and
the information is multiplied twice (or more) by the mass.

A division was replaced by a comma.

Rather than reinterpolating all the components when adding a new one, let's be smart about that and compute the interpolation only for new wavelengths. At the same time, make use of memoisation not to repeat the same computation all the time when marging different wavelength grids.

Optimise the copy of a SED object. First, use direct references to the time grid and SFH rather than copies as they will never change. Then, directly assign self._sfh, bypassing the slow setter.

Homogeneize the attenuation modules with the latest changes regarding the way we handle filters in compute_fnu(). Also make sure we do not request the key from the filter list as it is not a dictionary anymore.

Implement a cache for the computation of the optimal grid when merging two grids. As the best_grid() function takes numpy arrays as arguments, it makes caching difficult as they are not hashable. To solve the problem we define a helper function to do the memoisation based on the size, min, and max values of each of the input arrays.

Implement a cache for the filters to compute the fluxes. Rather than passing the transmission table as an argument to compute_fnu(), which makes caching difficult and/or slow to compute the hash, we rather pass the filter name. Then the SED object fetches the filter from the database and resamples it on the optimal wavelength grid. The result is stored in cache to avoid carrying out this operation repeatedly.

Implement the nebular lines over 9 points in wavelength rather than 19. It barely changes anything to the results and it speeds up the computation by 20%.

Plot only to λ=50 cm as the models do not extend much further and there is very rarely any observation beyond λ=21 cm.

As there should never be an sfh.age in sed.info when we add it, remove the option to force an update. Better to stop as it shows there is something wrong going on.

Display the model fluxes on top of the spectrum. Otherwise the dots can be partially masked by the spectrum.