JP-3848 Update S_REGION for MIRI LRS fixed slit data #9104
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## main #9104 +/- ##
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- Coverage 73.80% 33.81% -40.00%
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Files 372 372
Lines 37274 37348 +74
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- Hits 27510 12629 -14881
- Misses 9764 24719 +14955 ☔ View full report in Codecov by Sentry. |
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The code as written does not allow using the old file. Is this desirable to make the transition easier?
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Line 317 was added to account for the fact that the Tabular model defines its own range for inputs. If the bounding_box is larger then s_region will be filled with NaNs because this is the fill_value for the Tabular model. It's unlikely the slit corners are outside the range of the Tabular model so those lines should probably be removed.
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Also this needs some kind of test. It may be an addition to an existing test to check the
s_regionhas a reasonable value.
jwst/assign_wcs/util.py
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| @@ -807,6 +807,37 @@ def update_s_region_imaging(model): | |||
| model.meta.wcsinfo.s_region = s_region | |||
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| def update_s_region_lrs(model, reference_files): | |||
| """ | |||
| Update the ``S_REGION`` keyword using V2,V3 of the slit corners from reference file`. | |||
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| Update the ``S_REGION`` keyword using V2,V3 of the slit corners from reference file`. | |
| Update the ``S_REGION`` keyword using V2,V3 of the slit corners from reference file. |
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@nden I need a clarification on not needing dxmodel (line 317 any more)
Does that mean that we no longer need to determine bb_sub in line 311. So lines 301 to 311 can me cut:
These lines:
Fit for X shift as a function of Y
# Spline fit with enforced smoothness
spl = UnivariateSpline(ycen_subarray[::-1], xcen_subarray[::-1] - zero_point[0], s=0.002)
# Evaluate the fit at the y reference points
xshiftref = spl(ycen_subarray)
# This function will give slit dX as a function of Y subarray pixel value
dxmodel = models.Tabular1D(lookup_table=xshiftref, points=ycen_subarray, name='xshiftref',
bounds_error=False, fill_value=np.nan)
if input_model.meta.exposure.type.lower() == 'mir_lrs-fixedslit':
bb_sub = (bb_sub[0], (dxmodel.points[0].min(), dxmodel.points[0].max()))
jwst/assign_wcs/util.py
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| v2 = [v2vert1, v2vert2, v2vert3, v2vert4] | ||
| v3 = [v3vert1, v3vert2, v3vert3, v3vert4] | ||
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| lam = None # wavelength does not matter for s region |
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Transforms usually require numerical inputs. Although it might not crash in this specific case it makes sense to set it to a number.
jwst/assign_wcs/miri.py
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| zero_point = ref[0].header['imxsltl'] - 1, ref[0].header['imysltl'] - 1 | ||
| # Transform to slitless subarray from full array | ||
| zero_point = subarray2full.inverse(zero_point[0], zero_point[1]) | ||
| refmodel = MIRILrsModel(reference_files['specwcs']) |
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refmodel will need to be closed at the end
jwst/assign_wcs/miri.py
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| zero_point = ref[0].header['imxsltl'] - 1, ref[0].header['imysltl'] - 1 | ||
| # Transform to slitless subarray from full array | ||
| zero_point = subarray2full.inverse(zero_point[0], zero_point[1]) | ||
| refmodel = MIRILrsModel(reference_files['specwcs']) |
jwst/assign_wcs/util.py
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| Update the ``S_REGION`` keyword using V2,V3 of the slit corners from reference file`. | ||
| """ | ||
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| refmodel = MIRILrsModel(reference_files['specwcs']) |
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@nden If I remove following in miri.py dxmodel = models.Tabular1D(lookup_table=xshiftref, points=ycen_subarray, name='xshiftref',Then later on in the code dxmodel is used. How should xmodel be defined: What is the effective slit X as a function of subarray x,y? |
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@nden So the s_region is not updated and it is just what set telescope pointing set which I think is more desirable that the what the |
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@nden |
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@jemorrison regarding setting up the WCS of a LRS cal file - could you create in memory ImageModel with the appropriate configuration and call AssignWcs on it. Alternativelly add a check for s_region in one of the existing regression tests. May be this one will work. I agree with the decision about the old file. Also, I suggest you remove the lines below, not dxmodel. These reset the bounding_box and will have an effect on computing s_region. |
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@nden What I have written in resample_utils.py combine_s_regions_lrs is not correct. |
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@drlaw1558 @melanieclarke @hayescr |
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@jemorrison I'm having trouble running this PR myself (I pointed to your MIRI_LRS or MIRI_LRS_SpecWCS branches of stdatamodels, but I'm still getting odd-looking results). The plot above looks good though. Can we not construct the S_REGION of the output result from the S_REGION of all of the individual input files? Or do we not have access to that information any longer at the stage that we're trying to compute S_REGION for the resampled data? Alternatively, perhaps we could use one of the input S_REGIONs to compute the slit width dynamically (compute distance on sky from corner 1 to corners 2/3/4 and pick the minimum distance), and then use that width with the central line that you're getting from the bounding box approach above after resampling? That way we'd avoid hardcoding a value for the slit width. |
Resolves JP-3848
This PR needs a new datamodel that defines MIRI LRS specwcs reference files. The stdatamodels for this change is
spacetelescope/stdatamodels#383. The datamodel PR must be merged before this PR can be
merged.
THIS PR IS NOT READY TO BE MERGED. We still need to make changes to the resample code when it updates the S_REGION for MIRI LRS data.
This PR is not correct for updating the s-region for spec 3 MIRI LRS data. Still testing code.
Closes #
This PR correctly updates the s_region set by assign_wcs for MIRI LRS fixed slit data. The change requires using the slit corners in V2,V3 space which were added to the MIRI LRS specwcs reference file.
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changes/<PR#>.assign_wcs.rstchanges/<PR#>.badpix_selfcal.rstchanges/<PR#>.msaflagopen.rstchanges/<PR#>.nsclean.rstchanges/<PR#>.imprint.rstchanges/<PR#>.background.rstchanges/<PR#>.extract_2d.rstchanges/<PR#>.master_background.rstchanges/<PR#>.wavecorr.rstchanges/<PR#>.srctype.rstchanges/<PR#>.straylight.rstchanges/<PR#>.wfss_contam.rstchanges/<PR#>.flatfield.rstchanges/<PR#>.fringe.rstchanges/<PR#>.pathloss.rstchanges/<PR#>.barshadow.rstchanges/<PR#>.photom.rstchanges/<PR#>.pixel_replace.rstchanges/<PR#>.resample_spec.rstchanges/<PR#>.residual_fringe.rstchanges/<PR#>.cube_build.rstchanges/<PR#>.extract_1d.rstchanges/<PR#>.resample.rststage 3
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