Fix NIRSPEC IFU slices problem in JP-932

CHANGES.rst

@@ -47,6 +47,12 @@ master_background
 
 - Fix open files bug [#4995]
 
+pathloss
+--------
+- fix bug in NIRSpec IFU data that causes valid pixel dq flags to set to 
+  NON-SCIENCE in the region of an overlapping bounding box slice [#5047]
+
+
 pipeline
 --------
 
@@ -58,6 +64,11 @@ pipeline
 - Fix open files bug in ``get_config_from_reference`` class method, and in
   ``Spec2Pipeline``, ``Spec3Pipeline`` and ``tso3``. [#4995]
 
+photom
+------
+- fix bug in NIRSpec IFU data that causes valid pixel dq flags to set to 
+  NON-SCIENCE in the region of an overlapping bounding box slice [#5047]
+
 ramp_fitting
 ------------
 

jwst/pathloss/pathloss.py

@@ -333,12 +333,11 @@ def do_correction(input_model, pathloss_model):
         for slice in NIRSPEC_IFU_SLICES:
             slice_wcs = nirspec.nrs_wcs_set_input(input_model, slice)
             x, y = wcstools.grid_from_bounding_box(slice_wcs.bounding_box)
-            xmin = int(x.min())
-            xmax = int(x.max())
-            ymin = int(y.min())
-            ymax = int(y.max())
             ra, dec, wavelength = slice_wcs(x, y)
-            wavelength_array[ymin:ymax+1, xmin:xmax+1] = wavelength
+            valid = ~np.isnan(wavelength)
+            x = x[valid]
+            y = y[valid]
+            wavelength_array[y.astype(int), x.astype(int)] = wavelength[valid]
 
         # Compute the pathloss 2D correction
         if is_pointsource(input_model.meta.target.source_type):

jwst/photom/photom.py

@@ -195,7 +195,6 @@ def calc_nirspec(self, ftab, area_fname):
 
                 # Get the conversion factor from the PHOTMJ column
                 conv_factor = tabdata['photmj']
-
                 # Populate the photometry keywords
                 self.input.meta.photometry.conversion_megajanskys = \
                     conv_factor
@@ -234,13 +233,10 @@ def calc_nirspec(self, ftab, area_fname):
                 # Compute relative sensitivity for each pixel based
                 # on its wavelength
                 sens2d = np.interp(wave2d, waves, relresps)
-
                 # Include the scalar conversion factor
                 sens2d *= conv_factor
-
                 # Divide by pixel area
                 sens2d /= area2d
-
                 # Reset NON_SCIENCE pixels to 1 in sens2d array and flag
                 # them in the science data DQ array
                 where_dq = \
@@ -541,31 +537,28 @@ def calc_nrs_ifu_sens2d(self, area_data):
 
             # Get the world coords for all pixels in this slice
             coords = ifu_wcs(x, y)
-
-            # Pull out the wavelengths only
+            dq = dqmap[y.astype(int),x.astype(int)]
             wl = coords[2]
-            nan_flag = np.isnan(wl)
-            good_flag = np.logical_not(nan_flag)
-            if wl[good_flag].max() < microns_100:
+            # pull out the valid wavelengths and reset other array to not include
+            # nan values
+            valid = ~np.isnan(wl)
+            wl = wl[valid]
+            dq = dq[valid]
+            x = x[valid]
+            y = y[valid]
+            dq[:] = 0
+
+            if wl.max() < microns_100:
                 log.info("Wavelengths in WCS table appear to be in meters")
 
-            # Set NaNs to a harmless value, but don't modify nan_flag.
-            wl[nan_flag] = 0.
-
-            # Mark pixels with no wavelength as non-science
-            dq = np.zeros_like(wl)
-            dq[nan_flag] = dqflags.pixel['NON_SCIENCE']
             dqmap[y.astype(int), x.astype(int)] = dq
-
             # Insert the wavelength values for this slice into the
             # whole image array
             wave2d[y.astype(int), x.astype(int)] = wl
-
             # Insert the pixel area value for this slice into the
             # whole image array
             ar = np.ones_like(wl)
-            ar[:, :] = area_data[np.where(area_data['slice_id'] == k)]['pixarea'][0]
-            ar[nan_flag] = 1.
+            ar[:] = area_data[np.where(area_data['slice_id'] == k)]['pixarea'][0]
             area2d[y.astype(int), x.astype(int)] = ar
 
         return wave2d, area2d, dqmap