move test from RT to unit

jwst/background/background_sub.py

@@ -272,6 +272,20 @@ def average_background(input_model, bkg_list, sigma, maxiters):
     return avg_bkg
 
 
+def sufficient_background_pixels(dq_array, bkg_mask, min_pixels=100):
+    """Count number of good pixels for background use.
+
+    Check DQ flags of pixels selected for bkg use - XOR the DQ values with
+    the DO_NOT_USE flag to flip the DO_NOT_USE bit. Then count the number
+    of pixels that AND with the DO_NOT_USE flag, i.e. initially did not have
+    the DO_NOT_USE bit set.
+    """
+    return np.count_nonzero((dq_array[bkg_mask]
+                            ^ pixel['DO_NOT_USE'])
+                            & pixel['DO_NOT_USE']
+                            ) > min_pixels
+
+
 def subtract_wfss_bkg(input_model, bkg_filename, wl_range_name, mmag_extract=None):
     """Scale and subtract a background reference image from WFSS/GRISM data.
 
@@ -310,14 +324,7 @@ def subtract_wfss_bkg(input_model, bkg_filename, wl_range_name, mmag_extract=Non
     # i.e. in regions we can use as background.
     if got_catalog:
         bkg_mask = mask_from_source_cat(input_model, wl_range_name, mmag_extract)
-        # Check DQ flags of pixels selected for bkg use - XOR the DQ values with
-        # the DO_NOT_USE flag to flip the DO_NOT_USE bit. Then count the number
-        # of pixels that AND with the DO_NOT_USE flag, i.e. initially did not have
-        # the DO_NOT_USE bit set.
-        if np.count_nonzero((input_model.dq[bkg_mask]
-                            ^ pixel['DO_NOT_USE'])
-                            & pixel['DO_NOT_USE']
-                            ) < 100:
+        if not sufficient_background_pixels(input_model.dq, bkg_mask):
             log.warning("Not enough background pixels to work with.")
             log.warning("Step will be SKIPPED.")
             return None

jwst/background/tests/test_background.py

@@ -9,11 +9,13 @@
 from numpy.testing import assert_allclose
 
 from stdatamodels.jwst import datamodels
+from stdatamodels.jwst.datamodels.dqflags import pixel
 
 from jwst.assign_wcs import AssignWcsStep
 from jwst.background import BackgroundStep
 from jwst.stpipe import Step
-from jwst.background.background_sub import robust_mean, mask_from_source_cat, no_NaN
+from jwst.background.background_sub import (robust_mean, mask_from_source_cat,
+                                            no_NaN, sufficient_background_pixels)
 
 
 @pytest.fixture(scope="module")
@@ -403,3 +405,23 @@ def test_no_nan():
 
     # Make sure arrays are equal.
     assert np.array_equal(model.data, result.data)
+
+
+def test_sufficient_background_pixels():
+    model = datamodels.ImageModel(data=np.zeros((2048, 2048)),
+                                  dq=np.zeros((2048, 2048)))
+    refpix_flags = pixel['DO_NOT_USE'] | pixel['REFERENCE_PIXEL']
+    model.dq[:4, :] = refpix_flags
+    model.dq[-4:, :] = refpix_flags
+    model.dq[:, :4] = refpix_flags
+    model.dq[:, -4:] = refpix_flags
+
+    bkg_mask = np.ones((2048, 2048), dtype=bool)
+    # With full array minux refpix available for bkg, should be sufficient
+    assert sufficient_background_pixels(model.dq, bkg_mask)
+
+    bkg_mask[4: -4, :] = 0
+    bkg_mask[:, 4: -4] = 0
+    # Now mask out entire array, mocking full source coverage of detector -
+    # no pixels should be available for bkg
+    assert not sufficient_background_pixels(model.dq, bkg_mask)

jwst/regtest/test_nircam_wfss_spec2.py

@@ -32,26 +32,6 @@ def run_pipeline(rtdata_module):
     return rtdata
 
 
-@pytest.fixture(scope="module")
-def run_pipeline_skip_bkg(rtdata_module):
-    """Run the calwebb_spec2 pipeline on a single NIRSpec WFSS exposure."""
-
-    rtdata = rtdata_module
-
-    # Get the input data; load individual data files first, load ASN file last
-    rtdata.get_data("nircam/wfss/jw01076-o101_t002_nircam_clear-f356w_spoof_cat.ecsv")
-    rtdata.get_data("nircam/wfss/jw01076101001_02101_00003_nrcalong_rate.fits")
-    rtdata.get_data("nircam/wfss/jw01076-o101_20220403t120233_spec2_002_spoof_asn.json")
-
-    # Run the calwebb_spec2 pipeline; save results from intermediate steps
-    args = ["calwebb_spec2", rtdata.input,
-            "--output_file='skip_bkgsub'",
-            "--steps.bkg_subtract.skip=False"]
-    Step.from_cmdline(args)
-
-    return rtdata
-
-
 @pytest.mark.bigdata
 @pytest.mark.parametrize("suffix", [
     "assign_wcs", "bsub", "extract_2d", "flat_field", "srctype",
@@ -71,29 +51,3 @@ def test_nircam_wfss_spec2(run_pipeline, fitsdiff_default_kwargs, suffix):
     # Compare the results
     diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
     assert diff.identical, diff.report()
-
-
-@pytest.mark.bigdata
-@pytest.mark.parametrize("suffix", [
-    "cal", "x1d"])
-def test_nircam_wfss_spec2_nobkg(run_pipeline_skip_bkg,
-                                 fitsdiff_default_kwargs, suffix):
-    """Test of calwebb_spec2 on NIRCam WFSS with skipped
-    background subtraction.
-
-    In WFSS background subtraction, pixels in source cutouts are masked
-    out of the background calculation. Test the case where no pixels are
-    available for background calculation.
-    """
-
-    # Run the pipeline and retrieve outputs
-    rtdata = run_pipeline_skip_bkg
-    output = f"skip_bkgsub_{suffix}.fits"
-    rtdata.output = output
-
-    # Get the truth files
-    rtdata.get_truth("truth/test_nircam_wfss_spec2/" + output)
-
-    # Compare the results
-    diff = FITSDiff(rtdata.output, rtdata.truth, **fitsdiff_default_kwargs)
-    assert diff.identical, diff.report()