JP-3613: Update error arrays to match NaN in data (#8463)

CHANGES.rst

@@ -59,6 +59,9 @@ flat_field
 - Update the flatfield code for NIRSpec IFU data to ensure that SCI=ERR=NaN and
   DQ has the DO_NOT_USE flag set outside the footprint of the IFU slices [#8385]
 
+- Update NIRSpec flatfield code for all modes to ensure SCI=ERR=NaN wherever the
+  DO_NOT_USE flag is set in the DQ array. [#8463]
+
 general
 -------
 

jwst/flatfield/flat_field.py

@@ -442,7 +442,12 @@ def nirspec_fs_msa(output_model, f_flat_model, s_flat_model, d_flat_model, dispa
 
         # Make sure all DO_NOT_USE pixels are set to NaN,
         # including those flagged by this step
-        slit.data[np.where(slit.dq & dqflags.pixel['DO_NOT_USE'])] = np.nan
+        dnu = np.where(slit.dq & dqflags.pixel['DO_NOT_USE'])
+        slit.data[dnu] = np.nan
+        slit.err[dnu] = np.nan
+        slit.var_poisson[dnu] = np.nan
+        slit.var_rnoise[dnu] = np.nan
+        slit.var_flat[dnu] = np.nan
 
         any_updated = True
 
@@ -521,7 +526,12 @@ def nirspec_brightobj(output_model, f_flat_model, s_flat_model, d_flat_model, di
 
     # Make sure all DO_NOT_USE pixels are set to NaN,
     # including those flagged by this step
-    output_model.data[np.where(output_model.dq & dqflags.pixel['DO_NOT_USE'])] = np.nan
+    dnu = np.where(output_model.dq & dqflags.pixel['DO_NOT_USE'])
+    output_model.data[dnu] = np.nan
+    output_model.err[dnu] = np.nan
+    output_model.var_poisson[dnu] = np.nan
+    output_model.var_rnoise[dnu] = np.nan
+    output_model.var_flat[dnu] = np.nan
 
     output_model.meta.cal_step.flat_field = 'COMPLETE'
 
@@ -591,7 +601,12 @@ def nirspec_ifu(output_model, f_flat_model, s_flat_model, d_flat_model, dispaxis
 
         # Make sure all DO_NOT_USE pixels are set to NaN,
         # including those flagged by this step
-        output_model.data[np.where(output_model.dq & dqflags.pixel['DO_NOT_USE'])] = np.nan
+        dnu = np.where(output_model.dq & dqflags.pixel['DO_NOT_USE'])
+        output_model.data[dnu] = np.nan
+        output_model.err[dnu] = np.nan
+        output_model.var_poisson[dnu] = np.nan
+        output_model.var_rnoise[dnu] = np.nan
+        output_model.var_flat[dnu] = np.nan
 
         output_model.meta.cal_step.flat_field = 'COMPLETE'
 

jwst/regtest/test_nirspec_steps_spec2.py

@@ -60,6 +60,13 @@ def test_ff_inv(rtdata, fitsdiff_default_kwargs):
     # make sure NaNs are only at do_not_use pixels
     assert np.all(unflatted.dq[is_nan] & dm.dqflags.pixel['DO_NOT_USE'])
 
+    # make sure NaNs at science pixels are also NaN in error and var arrays
+    assert np.all(np.isnan(unflatted.err[is_nan]))
+    assert np.all(np.isnan(unflatted.var_poisson[is_nan]))
+    assert np.all(np.isnan(unflatted.var_rnoise[is_nan]))
+    assert np.all(np.isnan(unflatted.var_flat[is_nan]))
+
+
 @pytest.mark.slow
 @pytest.mark.bigdata
 def test_pathloss_corrpars(rtdata):