SVM: Reconcile removal of bad segments from segmentation image with r…

…emoval of corresponding rows from the "total" or white light source catalog (#1771)

CHANGELOG.rst

@@ -19,19 +19,19 @@ number of the code change for that issue.  These PRs can be viewed at:
 
 
 
-3.7.1 (unreleased)
-=====================
+3.7.0rc2 (22-Mar-2024) Infrastructure Build
+===========================================
+
+- Force the identified bad rows to be removed from the total (aka white light)
+  source catalog before the corresponding bad segments are removed from the
+  segmentation image. [#1771]
 
 - Reverted PR #1222 allowing pixels to be filled with available data where WHT=0. [#1767]
 
 - Improved calculation of S_REGION using dialation and erosion. [#1762]
 
 - Skycell added to flt(c) and drz(c) science headers for the pipeline and svm products. [#1729]
 
-
-3.7.0rc1 (22-Feb-2024) Infrastructure Build
-===========================================
-
 - Update project.toml file to specify numpy>=1.18,  <2.0 [#1743]
 
 - Update project.toml file to specify python_requires>=3.10 [#1737]
@@ -61,6 +61,7 @@ number of the code change for that issue.  These PRs can be viewed at:
 - Initial setup for Architectural Design Records used to keep track of top-level
   thinking behind the code. [#1697]
 
+
 3.6.2 (27-Nov-2023)
 ===================
 

drizzlepac/haputils/catalog_utils.py

@@ -1,6 +1,5 @@
 """This script contains code to support creation of photometric sourcelists using two techniques:
 aperture photometry and segmentation-map based photometry."""
-
 import copy
 import math
 import sys
@@ -1874,20 +1873,13 @@ def identify_sources(self, **pars):
             # the segmentation image too
             good_rows = []
             good_segm_rows_by_label = []
-            bad_segm_rows_by_label = []
             updated_table = None
             for i, old_row in enumerate(total_measurements_table):
                 if np.isfinite(old_row["xcentroid"]):
                     good_rows.append(old_row)
                     good_segm_rows_by_label.append(total_measurements_table['label'][i])
-                else:
-                    bad_segm_rows_by_label.append(total_measurements_table['label'][i])
-            updated_table = Table(rows=good_rows, names=total_measurements_table.colnames)
-            if self.diagnostic_mode and bad_segm_rows_by_label:
-                log.info("Bad segments removed from segmentation image for Total detection image {}.".format(self.imgname))
 
-            # Remove the bad segments from the image
-            self.segm_img.remove_labels(bad_segm_rows_by_label, relabel=True)
+            updated_table = Table(rows=good_rows, names=total_measurements_table.colnames)
 
             # Need to keep an updated copy of the total image SourceCatalog object for use when
             # making measurements in the filtered images
@@ -1901,7 +1893,11 @@ def identify_sources(self, **pars):
             # (create_catalog_products()).  This is the way the independent catalogs of total and filter products
             # process the same segmentation image.
             # BEWARE: self.sources for "segmentation" is a SegmentationImage, but for "point" it is an Astropy table
-            self.sources = copy.deepcopy(self.segm_img)
+            # Keep only the good segments from the image
+            self.segm_img.keep_labels(good_segm_rows_by_label, relabel=True)
+
+            # Make a deep copy of the total "white light" segmentation image
+            self.sources = self.segm_img.copy()
 
             log.info("Done identifying sources in total detection image for the segmentation catalog.")
             log.info("")