Refactoring of parse_subarray_map_step and test

liger_iris_pipeline/datamodels/schemas/liger_iris_core.schema.yaml

@@ -677,4 +677,22 @@ properties:
             title: Number of pixels in detector y-axis direction
             type: integer
             fits_keyword: DETYSIZ
-            blend_table: True
+            blend_table: True
+      subarray_map:
+        title: Subarray map
+        type: array
+        items:
+          type: object
+          properties:
+            xstart:
+              title: Starting pixel in axis 1 direction
+              type: integer
+            ystart:
+              title: Starting pixel in axis 2 direction
+              type: integer
+            xsize:
+              title: Number of pixels in axis 1 direction
+              type: integer
+            ysize:
+              title: Number of pixels in axis 2 direction
+              type: integer

liger_iris_pipeline/parse_subarray_map/parse_subarray_map_step.py

@@ -1,13 +1,14 @@
 import numpy as np
 
 from jwst.stpipe import Step
-from jwst import datamodels
+from .. import datamodels
+import stdatamodels
 
 __all__ = ["ParseSubarrayMapStep"]
 
 SUBARRAY_DQ_BIT = 4
 
-
+# NOTE: xstart/ystart use 1-based indexing
 def parse_subarray_map(subarray_map):
     subarray_metadata = []
     for subarray_id in range(1, 10 + 1):
@@ -34,18 +35,28 @@ class ParseSubarrayMapStep(Step):
 
     def process(self, input):
 
-        with datamodels.open(input) as input_model:
-
-            if "subarr_map" in input_model:
-                self.log.info("Parsing the SUBARR_MAP extension")
-                result = input_model.copy()
-                for each in parse_subarray_map(result["subarr_map"]):
-                    result.meta.subarray_map.append(each)
-                result.dq[result["subarr_map"] != 0] = np.bitwise_or(
-                    result.dq[result["subarr_map"] != 0], 2 ** SUBARRAY_DQ_BIT
-                )
-            else:
-                self.log.info("No SUBARR_MAP extension found")
-                result = input_model
+        if isinstance(input, str):
+            input_model = datamodels.open(input)
+        else:
+            input_model = input
+
+        if "subarr_map" in input_model:
+
+            self.log.info("Parsing the SUBARR_MAP extension")
+
+            result = input_model.copy()
+
+            # Create metadata from image ID map
+            for each in parse_subarray_map(result["subarr_map"]):
+                result.meta.subarray_map.append(each)
+
+            # Indicate subarrays in dq flags
+            result.dq[result["subarr_map"] != 0] = np.bitwise_or(
+                result.dq[result["subarr_map"] != 0],
+                2 ** SUBARRAY_DQ_BIT
+            )
+        else:
+            self.log.info("No SUBARR_MAP extension found")
+            result = input_model
 
         return result