Rename mrs_time_correction parameter; apply option to all modes

Author: melanieclarke

jwst/photom/photom.py

@@ -100,7 +100,7 @@ def __init__(
         model,
         inverse=False,
         source_type=None,
-        mrs_time_correction=False,
+        apply_time_correction=True,
         correction_pars=None,
     ):
         """
@@ -114,8 +114,8 @@ def __init__(
             Invert the math operations used to apply the corrections.
         source_type : str or None
             Force processing using the specified source type.
-        mrs_time_correction : bool
-            Switch to apply/not apply the MRS time correction.
+        apply_time_correction : bool
+            Switch to apply/not apply a time correction, if available.
         correction_pars : dict
             Correction meta-data from a previous run.
         """
@@ -158,7 +158,7 @@ def __init__(
         self.integ_row = -1
         self.inverse = inverse
         self.source_type = None
-        self.mrs_time_correction = mrs_time_correction
+        self.apply_time_correction = apply_time_correction
 
         # For MultiSlitModels, only set a generic source_type value for the
         # entire datamodel if the user has set the source_type parameter.
@@ -545,9 +545,9 @@ def calc_miri(self, ftab):
                     "Skipping MRS MIRI time correction.  "
                     "Extensions not found in the reference file."
                 )
-                self.mrs_time_correction = False
+                self.apply_time_correction = False
 
-            if self.mrs_time_correction:
+            if self.apply_time_correction:
                 log.info("Applying MRS IFU time dependent correction.")
                 mid_time = self.input.meta.exposure.mid_time
                 correction = time_dependence.miri_mrs_time_correction(
@@ -743,7 +743,8 @@ def photom_io(self, tabdata, order=None, time_correction=None):
             Multiplicative correction for time dependence, defined as the
             fractional amount of light recorded now divided by the light
             recorded on the zero-day MJD (t0).  The scalar conversion factor
-            will be divided by the correction value if provided.
+            will be divided by the correction value if provided, and if
+            ``self.apply_time_correction`` is True.
         """
         # First get the scalar conversion factor.
         # For most modes, the scalar conversion factor in the photom reference
@@ -796,7 +797,7 @@ def photom_io(self, tabdata, order=None, time_correction=None):
                     unit_is_surface_brightness = False
 
         # Apply the time-dependence correction
-        if time_correction is not None and time_correction != 1.0:
+        if self.apply_time_correction and time_correction is not None and time_correction != 1.0:
             log.info(f"Multiplicative time dependence correction is {time_correction:.6g}")
             conversion /= time_correction
 

jwst/photom/photom_step.py

@@ -14,8 +14,8 @@ class PhotomStep(Step):
 
     spec = """
         inverse = boolean(default=False)    # Invert the operation
-        source_type = string(default=None)  # Process as specified source type.
-        mrs_time_correction = boolean(default=True) # Apply the MIRI MRS time dependent correction
+        source_type = string(default=None)  # Process as specified source type
+        time_correction = boolean(default=True) # Apply time dependent corrections if available
     """  # noqa: E501
 
     reference_file_types = ["photom", "area"]
@@ -89,7 +89,7 @@ def process(self, input_data):
                 input_model,
                 self.inverse,
                 self.source_type,
-                self.mrs_time_correction,
+                self.time_correction,
                 correction_pars,
             )
             result = phot.apply_photom(phot_filename, area_filename)

jwst/photom/tests/test_photom.py

@@ -1649,7 +1649,7 @@ def test_miri_mrs_time_cor():
     input_model.meta.wcs.bounding_box = ((-0.5, shape[-1] - 0.5), (-0.5, shape[-2] - 0.5))
 
     save_input = input_model.copy()
-    ds = photom.DataSet(input_model, mrs_time_correction=True)
+    ds = photom.DataSet(input_model, apply_time_correction=True)
     value = 1.436
     pixel_area = 0.0436
     photmjsr = 17.3
@@ -1732,6 +1732,33 @@ def test_miri_image():
     assert_allclose(ratio, compare, rtol=1.0e-7)
 
 
+def test_miri_image_no_time_corr():
+    """Test the calc_miri method of the DataSet class, image data."""
+    input_model = create_input("MIRI", "MIRIMAGE", "MIR_IMAGE", filter_used="F1800W")
+    save_input = input_model.copy()
+    ds = photom.DataSet(input_model, apply_time_correction=False)
+    ftab = create_photom_miri_image()
+    ds.calc_miri(ftab)
+
+    input_data = save_input.data
+    output = ds.input.data  # ds.input is the output
+    rownum = find_row_in_ftab(save_input, ftab, ["filter"], slitname=None, order=None)
+    photmjsr = ftab.phot_table["photmjsr"][rownum]
+
+    shape = input_data.shape
+    ix = shape[1] // 2
+    iy = shape[0] // 2
+
+    # Time correction is not applied, so comparison value is just
+    # the conversion factor, even though timecoeff extensions
+    # are present.
+    compare = photmjsr
+
+    # Compare the values at the center pixel.
+    ratio = output[iy, ix] / input_data[iy, ix]
+    assert_allclose(ratio, compare, rtol=1.0e-7)
+
+
 def test_nircam_image():
     """Test the calc_nircam method of the DataSet class, image data."""
     input_model = create_input("NIRCAM", "NRCA3", "NRC_IMAGE", filter_used="F150W", pupil="CLEAR")