DM-38616: Add Sersic (+ point source) model fits to pipeline

pipelines/fit.yaml

@@ -71,6 +71,38 @@ tasks:
             prior_size_stddev=0.3,
           )
         }
+  fit_src_ser_multiprofit:
+    class: lsst.pipe.tasks.fit_coadd_multiband.CoaddMultibandFitTask
+    config:
+      connections.cat_output: deepCoadd_ser_multiprofit
+      python: |
+        from lsst.meas.extensions.multiprofit.fit_coadd_multiband import MultiProFitSourceTask
+        from lsst.multiprofit.componentconfig import SersicConfig, SersicIndexConfig
+        config.fit_coadd_multiband.retarget(MultiProFitSourceTask)
+        config.fit_coadd_multiband.n_pointsources = 0
+        config.fit_coadd_multiband.sersics = {
+          "ser": SersicConfig(
+            sersicindex=SersicIndexConfig(fixed=False, value_initial=1.0),
+            prior_axrat_stddev=0.8,
+            prior_size_stddev=0.3,
+          )
+        }
+  fit_src_psser_multiprofit:
+    class: lsst.pipe.tasks.fit_coadd_multiband.CoaddMultibandFitTask
+    config:
+      connections.cat_output: deepCoadd_psser_multiprofit
+      python: |
+        from lsst.meas.extensions.multiprofit.fit_coadd_multiband import MultiProFitSourceTask
+        from lsst.multiprofit.componentconfig import SersicConfig, SersicIndexConfig
+        config.fit_coadd_multiband.retarget(MultiProFitSourceTask)
+        config.fit_coadd_multiband.n_pointsources = 1
+        config.fit_coadd_multiband.sersics = {
+          "ser": SersicConfig(
+            sersicindex=SersicIndexConfig(fixed=False, value_initial=1.63),
+            prior_axrat_stddev=0.8,
+            prior_size_stddev=0.3,
+          )
+        }
   fit_src_psexpdev_multiprofit:
     class: lsst.pipe.tasks.fit_coadd_multiband.CoaddMultibandFitTask
     config:

pipelines/merge.yaml

@@ -29,18 +29,24 @@ tasks:
             is_multipatch=True,
             storageClass="DataFrame",
           ),
-          "deepCoadd_psexpdev_multiprofit": InputConfig(
-            doc="Point Source + Exponential + DeVaucouleurs source fit",
-            action=MergeMultibandFluxes(name_model="psexpdev"),
-            column_id="id",
-            is_multiband=True,
-          ),
           "deepCoadd_psgauss_multiprofit": InputConfig(
             doc="Point Source + Gaussian source fit",
             action=MergeMultibandFluxes(name_model="psgauss"),
             column_id="id",
             is_multiband=True,
           ),
+          "deepCoadd_psser_multiprofit": InputConfig(
+            doc="Point Source + Sersic source fit",
+            action=MergeMultibandFluxes(name_model="psser"),
+            column_id="id",
+            is_multiband=True,
+          ),
+          "deepCoadd_psexpdev_multiprofit": InputConfig(
+            doc="Point Source + Exponential + DeVaucouleurs source fit",
+            action=MergeMultibandFluxes(name_model="psexpdev"),
+            column_id="id",
+            is_multiband=True,
+          ),
         }
   match_multiprofit:
     class: lsst.pipe.tasks.match_tract_catalog.MatchTractCatalogTask
@@ -100,7 +106,7 @@ tasks:
         if parameters.size_include:
             for ax in ("x", "y"):
                 config.columns_target_copy.append(
-                    f"{parameters.model_prefix}_{parameters.size_include}_sigma_{ax}"
+                    f"{parameters.model_prefix}_{parameters.size_include}_reff_{ax}"
                 )
         config.columns_flux = columns_flux
         config.coord_format.column_target_coord1 = f"{parameters.model_prefix}_cen_ra"

python/lsst/meas/extensions/multiprofit/fit_coadd_multiband.py

@@ -115,7 +115,6 @@ class MultiProFitSourceConfig(CatalogSourceFitterConfig, fitMB.CoaddMultibandFit
         doc="list of bandpass filters to fit",
         listCheck=lambda x: len(set(x)) == len(x),
     )
-    fit_linear = pexConfig.Field[bool](default=True, doc="Fit linear parameters to initialize")
     mask_names_zero = pexConfig.ListField[str](
         default=["BAD", "EDGE", "SAT", "NO_DATA"], doc="Mask bits to mask out"
     )
@@ -272,7 +271,12 @@ def initialize_model(
 
         for comp in comps[:n_psfs]:
             self._init_component(comp, values_init=values_init_psf, limits_init=limits_init_psf)
-        for comp in comps[n_psfs:]:
+        for comp, config_comp in zip(comps[n_psfs:], self.config.sersics.values()):
+            if config_comp.sersicindex.fixed:
+                if g2f.SersicIndexParameterD in values_init:
+                    del values_init[g2f.SersicMixComponentIndexParameterD]
+            else:
+                values_init[g2f.SersicMixComponentIndexParameterD] = config_comp.sersicindex.value_initial
             self._init_component(comp, values_init=values_init, limits_init=limits_init)
         for prior in model.priors:
             if isinstance(prior, g2f.GaussianPrior):

python/lsst/meas/extensions/multiprofit/fit_coadd_psf.py

@@ -39,7 +39,6 @@ class CatalogExposure(fitCP.CatalogExposurePsf, CatalogExposurePsfABC):
 class MultiProFitPsfConfig(CatalogPsfFitterConfig, fitCP.CoaddPsfFitSubConfig):
     """Configuration for the MultiProFit Gaussian mixture PSF fitter."""
 
-    fit_linear = pexConfig.Field[bool](default=True, doc="Fit linear parameters to initialize")
     prefix_column = pexConfig.Field[str](default="mpf_psf_", doc="Column name prefix")
 
     def setDefaults(self):