JP-3248: Add ref file data model and step keywords for new MIRI EMI c…

…orrection (#200)

.gitignore

@@ -2,6 +2,7 @@
 __pycache__/
 *.py[cod]
 *$py.class
+*.DS_Store
 
 # C extensions
 *.so

CHANGES.rst

@@ -18,6 +18,10 @@ Other
 - Updated JWST core datamodel schema to include the new step status keyword
   "S_NSCLEN" for the new "nsclean" calibration step. [#237]
 
+- Adding emicorr datamodel and schema, as well as
+  corresponding completion and reference file keywords [#200]
+
+
 
 1.8.4 (2023-12-04)
 ==================

src/stdatamodels/jwst/datamodels/__init__.py

@@ -17,6 +17,7 @@
 from .darkMIRI import DarkMIRIModel
 from .drizpars import DrizParsModel
 from .drizproduct import DrizProductModel
+from .emi import EmiModel
 from .extract1dimage import Extract1dImageModel
 from .extract1d_spec import Extract1dIFUModel
 from .flat import FlatModel
@@ -107,6 +108,7 @@
     'DisperserModel', 'DistortionModel', 'DistortionMRSModel',
     'DrizParsModel',
     'DrizProductModel',
+    'EmiModel',
     'Extract1dImageModel',
     'Extract1dIFUModel',
     'FilteroffsetModel',

src/stdatamodels/jwst/datamodels/emi.py

@@ -0,0 +1,35 @@
+from .reference import ReferenceFileModel
+
+
+__all__ = ['EmiModel']
+
+
+class EmiModel(ReferenceFileModel):
+    """
+    A data model to correct MIRI images for EMI contamination.
+
+    Parameters
+    __________
+    data : numpy table
+        The reference waves to correct for MIRI EMI.
+        A table-like object containing phase amplitude values
+        corresponding to the appropriate frequency
+        - Hz390: float32 1D array
+        - Hz218a: float32 1D array
+        - Hz218b: float32 1D array
+        - Hz218c: float32 1D array
+        - Hz164: float32 1D array
+        - Hz10: float32 1D array
+    """
+    schema_url = "http://stsci.edu/schemas/jwst_datamodel/emi.schema"
+    reftype = "emicorr"
+
+    def __init__(self, init=None, **kwargs):
+        super(EmiModel, self).__init__(init=init, **kwargs)
+
+    def on_save(self, path=None):
+        self.meta.reftype = self.reftype
+        self.meta.instrument.name = "MIRI"
+
+    def validate(self):
+        super(EmiModel, self).validate()

src/stdatamodels/jwst/datamodels/schemas/core.schema.yaml

@@ -1824,6 +1824,15 @@ properties:
                 type: string
                 fits_keyword: R_DRZPAR
                 blend_table: True
+          emicorr:
+            title: MIRI EMI reference file information
+            type: object
+            properties:
+              name:
+                title: MIRI EMI correction reference file name
+                type: string
+                fits_keyword: R_MIREMI
+                blend_table: True
           extract1d:
             title: 1-D extraction parameters reference file information
             type: object
@@ -2325,6 +2334,11 @@ properties:
             type: string
             fits_keyword: S_DQINIT
             blend_table: True
+          emicorr:
+            title: MIRI EMI Correction
+            type: string
+            fits_keyword: S_MIREMI
+            blend_table: True
           emission:
             title: Telescope Emission Correction
             type: string

src/stdatamodels/jwst/datamodels/schemas/emi.schema.yaml

@@ -0,0 +1,22 @@
+%YAML 1.1
+---
+$schema: "http://stsci.edu/schemas/asdf/asdf-schema-1.0.0"
+id: "http://stsci.edu/schemas/jwst_datamodel/emi.schema"
+allOf:
+- $ref: referencefile.schema
+- type: object
+  properties:
+    data:
+      title: MIRI Reference Waves Table for EMI correction
+      type: object
+      properties:
+        meta:
+            type: object
+        frequencies:
+            type: object
+            description: |
+               Frequency names, values, and phase amplitude values
+        subarray_cases:
+            type: object
+            description: |
+               Frequencies to correct for according to subarray