Handle the case where we do not know the redshift to estimate the physical parameters by taking all models at all redshifts. This means that in effect pcigale can also act as a photo-z code now on.

Now that we leave the models with NaN fluxes, the scaling factors and χ² may be NaN too. Handle this case.

The galaxy_mass parameter confuses a lot of people. Change its name to sfh.integrated because it is actually the integral of the SFR.

Add an _init_code() to sfh2exp to avoid repeating twice the same operations. Even though that should not be a common occurrence, it is cleaner by separating the computation of the data and the actual processing of the SED object.

The SSPs in the database are always built on a time grid with 1 Myr time steps. No need to drag around a constant for this as it will stay that way for the forseeable future.

By construction the SFH in cigale is a comb. Every 1 Myr stars are formed. All at the same time. In effect star formation is not continuous. This means that we should not use trapz to integrate the SFR or use an analytic relation. Rather we just sum, which is correct for the discrete nature of the SFH.

Rename the SED info dictionary key for the AGN faction added by dale2014
module from agn.fracAGN to agn.fracAGN_dale2014 to avoid conflict with
fritz2006 module.

Avoid multiply the array by a scalar once rather than twice. It makes the computation quite a bit faster.

Using fancy indexing to select all the models as a given redshift is very suboptimal as it forces a copy for each of the index arrays. Now because the redshift is the last parameter, we can just use a proper slice. The first element is the index of the redshift in the list of redshift (paying attention that this list is in the same order as the computation order), and the step is the number of redshifts.

Because we are looping on the bands now and we can just test at each iteration whether it is a valid band, we do not need to create a new array without the invalid bands. This should save some memory bandwidth and time.

Rather than computing the scaling factor and the χ² in one block over the entire grid of models, let's compute them band by band. The main advantage is that we avoid the creation of temporary arrays that can be as large is the model fluxes array, which can be very large. Because we loop on the bands rather than on the models, the impact on the performance should remain very limited.

Now that we do not use magic numbers anymore but NaN values, we do not need to select the valid models. We can just compute on the entire grid. Invalid models will have a χ² of NaN and will therefore naturally and elegantly be eliminated from further analysis.

Magic values are a bit of a pain to handle and are not safe. This patch removes the use of magic values and rather replaces them with NaN whenever appropriate. The logic of the input file stays the same but the magic values are converted internally after reading it so that the rest of the code does not have to deal with that.

The creation of the mock catalogue is overly and needlessly long ang complicated. This patch implement a much short and simpler version.

Computing the parameters and their uncertainties through the histogram of the PDF makes the code more complex and can introduce biases in some cases. This patch moves the computation of the histograms to the function that saves them onto the disk. In parallel the estimated value of the parameters and the corresponding uncertainties are simply computed from the weighted mean and standard deviation of the models that are at least 0.1% as likely as the best model to reproduce the observations.

To compute the reduced χ², we need to divide by the number of bands-1 (and not the number of bands). We do that because we consider that the models depend on one meta-parameter.

In the Calzetti attenuation module, add a warning saying that is the
power law slope is different than 0, the E(B-V) will no longer be the
real one. Also add "B_B90" to the list of computed attenuation so that
users can calculate the E(B-V).

Shorten the left and right 0 parts of the pseudo D4000 filter so that
it can be applied on smaller spectra.

The flux is mass dependent.

Initialise the mock arrays to 0 in case some fluxes fall between the cracks and do not get initialised.

To clarify the structure of the analysis worker, the computation of the χ² is now done in a specific function

Simplify the handling of the mock analysis by removing the so-called phase variable. From the point of view of the analysis, it does not matter at all whether we are analysing real or mock observations. We only do not output the PDF/χ²/best fits when analysing mocks. So we just put these options to False.

For some reason a point in the GALEX FUV filter has a negative transmission. That should not happen. After comparison with the filter on the GALEX website I just changed that point to 0.

Add the possibility to compute some fluxes in the "param" module to add
them to the SED info dictionary.  This can be used for instance to
compute probability distribution of fluxes during an analysis.

When the error column for a flux was present in the observation table
but not in the used column list (when the user prefers to use a default
error instead of the real one), the error on the flux was set to 0.

Addition of a pseudo filter to compute the flux in the Lyman continuum.
This is a box function taking everything between 91 Å and 911 Å.

NOTE: This filter was made for the BC03 SSP which begin at 91 Å. It
      can't be used if the spectrum is redshifted as the filter
      wavelengths will then be outside of the SED ones.