Make sure we also provide the best fits for the bands for which we ask a Bayesian estimate.

CHANGELOG.md

@@ -9,6 +9,7 @@
 ### Fixed
 - Ensure that `pcigale-plots` correctly detects the `skirtor2016` AGN models. (Médéric Boquien, reported by Guang Yang)
 - Correct a typo in the `themis` module. (Médéric Boquien, reported by Alexandros Maragkoudakis)
+- Make sure that the best fit is also given for the bands for which `pdf\_analysis` provides a Bayesian estimate. (Médéric Boquien)
 ### Optimised
 - The estimation of the physical properties and the related uncertainties has been made up to 50% faster. The final gain in the analysis speed accounting for all the steps depends on the number of properties to be evaluated and the number of models but can be over 25% when estimating many properties over a large parameter space. (Médéric Boquien)
 

pcigale/managers/results.py

@@ -183,7 +183,9 @@ class BestResultsManager(object):
         # to the pool. Each worker will fill a part of the RawArrays. It is
         # important that there is no conflict and that two different workers do
         # not write on the same section.
-        self.flux = {band: SharedArray(nobs) for band in models.obs.bands}
+        fluxnames = list(dict.fromkeys(models.obs.bands +
+                                       models.conf['analysis_params']['bands']))
+        self.flux = {band: SharedArray(nobs) for band in fluxnames}
         allintpropnames = models.allintpropnames
         allextpropnames = models.allextpropnames
         self.intprop = {prop: SharedArray(nobs)
@@ -418,7 +420,7 @@ class ResultsManager(object):
                                     name="best."+prop,
                                     unit=Unit(self.unit[prop])))
 
-        for band in self.obs.bands:
+        for band in self.best.flux:
             if band.startswith('line.') or band.startswith('linefilter.'):
                 unit = 'W/m^2'
             else: