populate new dq bit, erase all knowledge of unreliable_reset

Author: tapastro

docs/jwst/references_general/references_general.rst

@@ -602,7 +602,7 @@ Bit  Value         Name              Description
 4    16            OUTLIER           Flagged by outlier detection
 5    32            PERSISTENCE       High persistence
 6    64            AD_FLOOR          Below A/D floor
-7    128           RESERVED
+7    128           UNDERSAMP         Undersampling correction
 8    256           UNRELIABLE_ERROR  Uncertainty exceeds quoted error
 9    512           NON_SCIENCE       Pixel not on science portion of detector
 10   1024          DEAD              Dead pixel
@@ -623,7 +623,7 @@ Bit  Value         Name              Description
 25   33554432      UNRELIABLE_FLAT   Flat variance large
 26   67108864      OPEN              Open pixel (counts move to adjacent pixels)
 27   134217728     ADJ_OPEN          Adjacent to open pixel
-28   268435456     UNRELIABLE_RESET  Sensitive to reset anomaly
+28   268435456     FLUX_ESTIMATED    Pixel flux estimated due to missing/bad data
 29   536870912     MSA_FAILED_OPEN   Pixel sees light from failed-open shutter
 30   1073741824    OTHER_BAD_PIXEL   A catch-all flag
 31   2147483648    REFERENCE_PIXEL   Pixel is a reference pixel

jwst/pixel_replace/pixel_replace.py

@@ -21,7 +21,7 @@ class PixelReplacement:
 
     # Shortcuts for DQ Flags
     DO_NOT_USE = datamodels.dqflags.pixel['DO_NOT_USE']
-    REPLACED = datamodels.dqflags.pixel['LOW_QE']
+    FLUX_ESTIMATED = datamodels.dqflags.pixel['FLUX_ESTIMATED']
     NON_SCIENCE = datamodels.dqflags.pixel['NON_SCIENCE']
 
     # Shortcuts for dispersion direction for ease of reading
@@ -71,7 +71,7 @@ def replace(self):
         # ImageModel inputs (MIR_LRS-FIXEDSLIT)
         if isinstance(self.input, datamodels.ImageModel):
             self.output = self.algorithm(self.input)
-            n_replaced = np.count_nonzero(self.output.dq & self.REPLACED)
+            n_replaced = np.count_nonzero(self.output.dq & self.FLUX_ESTIMATED)
             log.info(f"Input model had {n_replaced} pixels replaced.")
         elif isinstance(self.input, datamodels.IFUImageModel):
                 # Attempt to run pixel replacement on each throw of the IFU slicer
@@ -107,12 +107,12 @@ def replace(self):
                             self.output.dq
                         )
 
-                        n_replaced = np.count_nonzero(trace_model.dq & self.REPLACED)
+                        n_replaced = np.count_nonzero(trace_model.dq & self.FLUX_ESTIMATED)
                         log.info(f"Input MRS frame had {n_replaced} pixels replaced in IFU slice {i+1}.")
 
                         trace_model.close()
 
-                    n_replaced = np.count_nonzero(self.output.dq & self.REPLACED)
+                    n_replaced = np.count_nonzero(self.output.dq & self.FLUX_ESTIMATED)
                     log.info(f"Input MRS frame had {n_replaced} total pixels replaced.")
                 else:
                     # NRS_IFU method - Fixed number of IFU slices to iterate over
@@ -145,12 +145,12 @@ def replace(self):
                             self.output.dq
                         )
 
-                        n_replaced = np.count_nonzero(trace_model.dq & self.REPLACED)
+                        n_replaced = np.count_nonzero(trace_model.dq & self.FLUX_ESTIMATED)
                         log.info(f"Input NRS_IFU frame had {n_replaced} pixels replaced in IFU slice {i + 1}.")
 
                         trace_model.close()
 
-                    n_replaced = np.count_nonzero(self.output.dq & self.REPLACED)
+                    n_replaced = np.count_nonzero(self.output.dq & self.FLUX_ESTIMATED)
                     log.info(f"Input NRS_IFU frame had {n_replaced} total pixels replaced.")
 
         # MultiSlitModel inputs (WFSS, NRS_FIXEDSLIT, ?)
@@ -160,7 +160,7 @@ def replace(self):
                 slit_model = datamodels.SlitModel(self.input.slits[i].instance)
                 slit_replaced = self.algorithm(slit_model)
 
-                n_replaced = np.count_nonzero(slit_replaced.dq & self.REPLACED)
+                n_replaced = np.count_nonzero(slit_replaced.dq & self.FLUX_ESTIMATED)
                 log.info(f"Slit {i} had {n_replaced} pixels replaced.")
 
                 self.output.slits[i] = slit_replaced
@@ -177,7 +177,7 @@ def replace(self):
                 dummy_model = datamodels.ImageModel(data=self.input.data[i], dq=self.input.dq[i])
                 dummy_model.update(self.input)
                 dummy_replaced = self.algorithm(dummy_model)
-                n_replaced = np.count_nonzero(dummy_replaced.dq & self.REPLACED)
+                n_replaced = np.count_nonzero(dummy_replaced.dq & self.FLUX_ESTIMATED)
                 log.info(f"Input TSO integration {i} had {n_replaced} pixels replaced.")
 
                 self.output.data[i] = dummy_replaced.data
@@ -322,7 +322,7 @@ def fit_profile(self, model):
             replaced_dq = np.where(
                 (current_dq & self.DO_NOT_USE ^ current_dq & self.NON_SCIENCE == 1) &
                 ~(np.isnan(replaced_current)),
-                current_dq ^ self.DO_NOT_USE ^ self.REPLACED,
+                current_dq ^ self.DO_NOT_USE ^ self.FLUX_ESTIMATED,
                 current_dq
             )
 

jwst/reset/tests/test_reset_sub.py

@@ -110,20 +110,20 @@ def test_dq_combine(make_rampmodel, make_resetmodel):
     jump_det = dqflags.pixel['JUMP_DET']
     saturated = dqflags.pixel['SATURATED']
     do_not_use = dqflags.pixel['DO_NOT_USE']
-    unreliable_reset = dqflags.pixel['UNRELIABLE_RESET']
+    nonlinear = dqflags.pixel['NONLINEAR']
 
     # populate dq flags of sci pixeldq and reference dq
     dm_ramp.pixeldq[50, 50] = jump_det
     dm_ramp.pixeldq[50, 51] = saturated
 
-    reset.dq[50, 50] = np.bitwise_or(do_not_use, unreliable_reset)
-    reset.dq[50, 51] = unreliable_reset
+    reset.dq[50, 50] = np.bitwise_or(do_not_use, nonlinear)
+    reset.dq[50, 51] = nonlinear
 
     # run correction step
     outfile = resetcorr(dm_ramp, reset)
 
-    t50_50 = jump_det | do_not_use | unreliable_reset
-    t50_51 = saturated | unreliable_reset
+    t50_50 = jump_det | do_not_use | nonlinear
+    t50_51 = saturated | nonlinear
     # check that dq flags were correctly added
     assert outfile.pixeldq[50, 50] == t50_50
     assert outfile.pixeldq[50, 51] == t50_51