Take into account the effect of the differential redshifting between the...

Take into account the effect of the differential redshifting between the observed and grid redshifts.

CHANGELOG.md

@@ -2,6 +2,7 @@
 
 ## Unreleased
 ### Added
+- The (1+z1)/(1+z2) factor between observed and grid flux densities caused by the differential redshifting is now taken into account. With a default grid redshift rounding of two decimals this yields a difference of at most 0.5% in the estimated physical properties at z=0 and even less at higher z. (Médéric Boquien)
 ### Changed
 ### Fixed
 - Make sure we can plot the PDF of equivalent widths. (Médéric Boquien)

pcigale/analysis_modules/pdf_analysis/utils.py

@@ -30,26 +30,28 @@ def save_chi2(obs, variable, models, chi2, values):
 
 
 @lru_cache(maxsize=None)
-def compute_corr_dz(model_z, obs_dist):
+def compute_corr_dz(model_z, obs):
     """The mass-dependent physical properties are computed assuming the
     redshift of the model. However because we round the observed redshifts to
     two decimals, there can be a difference of 0.005 in redshift between the
-    models and the actual observation. At low redshift, this can cause a
+    models and the actual observation. This causes two issues. First there is a
+    difference in the luminosity distance. At low redshift, this can cause a
     discrepancy in the mass-dependent physical properties: ~0.35 dex at z=0.010
-    vs 0.015 for instance. Therefore we correct these physical quantities by
-    multiplying them by corr_dz.
+    vs 0.015 for instance. In addition, the 1+z dimming will be different.
+    We compute here the correction factor for these two effects.
 
     Parameters
     ----------
     model_z: float
         Redshift of the model.
-    obs_dist: float
-        Luminosity distance of the observed object.
+    obs: instance of the Observation class
+        Object containing the distance and redshift of an object
 
     """
     if model_z == 0.:
-        return (obs_dist / (10. * parsec)) ** 2.
-    return (obs_dist / cosmo.luminosity_distance(model_z).value) ** 2.
+        return (obs.distance / (10. * parsec)) ** 2. / (1. + obs.redshift)
+    return (obs.distance / cosmo.luminosity_distance(model_z).value) ** 2. * \
+           (1. + model_z) / (1. + obs.redshift)
 
 
 def dchi2_over_ds2(s, obsdata, obsdata_err, obslim, obslim_err, moddata,

pcigale/analysis_modules/pdf_analysis/workers.py

@@ -142,7 +142,7 @@ def analysis(idx, obs):
         z = np.array(
             gbl_models.conf['sed_modules_params']['redshifting']['redshift'])
         wz = slice(np.abs(obs.redshift-z).argmin(), None, z.size)
-        corr_dz = compute_corr_dz(z[wz.start], obs.distance)
+        corr_dz = compute_corr_dz(z[wz.start], obs)
     else:  # We do not know the redshift so we use the full grid
         wz = slice(0, None, 1)
         corr_dz = 1.
@@ -236,7 +236,7 @@ def bestfit(oidx, obs):
     params = deepcopy(gbl_params.from_index(best_index))
     if obs.redshift >= 0.:
         params[gbl_params.modules.index('redshifting')]['redshift'] = obs.redshift
-        corr_dz = compute_corr_dz(obs.redshift, obs.distance)
+        corr_dz = compute_corr_dz(obs.redshift, obs)
     else:  # The model redshift is always exact in redhisfting mode
         corr_dz = 1.
     sed = gbl_warehouse.get_sed(gbl_params.modules, params)