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spacetelescope · Mar 21, 2023 · 569355a · 569355a
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diff --git a/docs/roman/source_detection/arguments.rst b/docs/roman/source_detection/arguments.rst
@@ -4,26 +4,28 @@ The source detection fitting step has several arguments. These can be specified
 by the user by passing them to the step in a Python session, or setting them
 in a parameter file.
 
-* ``--coverage_mask``: True/False to mask pixels with DO_NOT_USE flags in their
-                       dq array. Default is True.
 * ``--kernel_fwhm``: A parameter for DAOStarFinder: size of Gaussian kernel in
                      pixels. Default is 2.0.
 * ``--sharplo``: A parameter for DAOStarFinder: lower bound for sharpness.
                  Default is 0.0.
 * ``--sharphi``: A parameter for DAOStarFinder: upper bound for sharpness.
                  Default is 1.0.
 * ``--roundlo``: A parameter for DAOStarFinder: lower bound for roundness.
-                 Default is -1.0.
+                 Default is -1.0. A circular source will have a zero roundness.
+                 A source extended in x or y will have a negative or positive
+                 roundness, respectively.
 * ``--roundhi``: A parameter for DAOStarFinder: upper bound for roundness.
-                 Default is 1.0.
+                 Default is 1.0. A circular source will have a zero roundness.
+                 A source extended in x or y will have a negative or positive
+                 roundness, respectively.
 * ``--peakmax``: A parameter for DAOStarFinder: upper limit on brightest pixel
                  in sources. Default is 1000.0.
 * ``--max_sources``: The maximum number of sources in the output catalog,
                      choosing brightest. Default is None, which will return all
                      detected sources.
-* ``--scalar_threshold``: If specified, a single scalar threshold to be used
-                          for source detection with DAOStarFinder across the
-                          entire image. One of `scalar_threshold`,
+* ``--scalar_threshold``: If specified, the absolute detection threshold to be
+                          used for the entire image. Units are assumed to be the
+                          same as input data. One of `scalar_threshold`,
                           `calc_scalar_threshold` must be chosen. Default is
                           None.
 * ``--calc_scalar_threshold``: If specified, a single scalar threshold will be

diff --git a/docs/roman/source_detection/description.rst b/docs/roman/source_detection/description.rst
@@ -46,13 +46,6 @@ threshold value for the entire image based on the sigma-clipped average
 Other Options
 =============
 
-Masking DO_NOT_USE pixels
--------------------------
-
-By default, sources that fall on pixels with DO_NOT_USE in their DQ array
-will be excluded from the final output catalog. This can be controlled with
-the `coverage_mask` parameter.
-
 Limiting maximum number of sources
 ----------------------------------
 

diff --git a/romancal/source_detection/source_detection_step.py b/romancal/source_detection/source_detection_step.py
@@ -34,12 +34,13 @@ class SourceDetectionStep(RomanStep):
     """
 
     spec = """
-        coverage_mask = boolean(default=True) # Mask DO_NOT_USE pixels in image?
         kernel_fwhm = float(default=2.)  # DAOStarFinder:Size of Gaussian kernel,
         # in pixels.
         sharplo = float(default=0.)  # DAOStarFinder: Lower bound for sharpness.
         sharphi = float(default=1.0)  # DAOStarFinder: Upper bound for sharpness.
         roundlo = float(default=-1.0)  # DAOStarFinder: Lower bound for roundness.
+        # A circular source will have a zero roundness. A source extended in x or
+        # y will have a negative or positive roundness, respectively.
         roundhi = float(default=1.0)  # DAOStarFinder: Upper bound for roundness.
         peakmax = float(default=1000.0)  # Upper limit on brightest pixel in sources.
         max_sources = float(default=None)  # Max number of sources, choosing brightest.
@@ -75,13 +76,12 @@ def process(self, input):
             else:
                 self.data = input_model.data
 
-            # mask DO_NOT_USE pixels?
-            if self.coverage_mask:
-                self.coverage_mask = (
-                    (dqflags.pixel["DO_NOT_USE"]) & input_model.dq
-                ).astype(bool)
-            else:
-                self.coverage_mask = None
+            # mask DO_NOT_USE pixels
+
+            self.coverage_mask = (
+                (dqflags.pixel["DO_NOT_USE"]) & input_model.dq
+            ).astype(bool)
+
 
             # if a pre-determined threshold value for detection for the whole
             # image is provided, use this
@@ -118,7 +118,8 @@ def process(self, input):
 
             elif self.calc_threshold is not None:
                 # subtrack background from data if calculating abs. threshold
-                sources = daofind(self.data - bkg.background, mask=self.coverage_mask)
+                sources = daofind(self.data - bkg.background,
+                                  mask=self.coverage_mask)
 
             # reduce table to minimal number of columns, just source ID,
             # positions, and fluxes