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non-standard pixel sizes for distortion #669

Merged
merged 8 commits into from
Jul 27, 2023
Merged

non-standard pixel sizes for distortion #669

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75ff307
non-standard pixel sizes for distortion
JarronL May 12, 2023
64348ab
xidl_cen and yidl_cen need to be defined earlier
JarronL May 12, 2023
005a60f
fix test_apply_distortion_pixel_scale() failure
JarronL May 12, 2023
31926e7
revert to aper.convert
JarronL May 16, 2023
e511073
add test to verify fix of distortion with nonstandard pixelscale
mperrin May 17, 2023
454f1c4
updated test_apply_distortion_pixel_scale
JarronL Jul 26, 2023
b4fdee2
use per axis pixel sampling during distortion
JarronL Jul 26, 2023
5685897
Merge branch 'develop' into distortion_update
BradleySappington Jul 27, 2023
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25 changes: 14 additions & 11 deletions webbpsf/distortion.py
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Original file line number Diff line number Diff line change
Expand Up @@ -63,7 +63,7 @@
Value used to fill in any blank space by the skewed PSF. Default = 0.
If set to None, values outside the domain are extrapolated.
to_frame : str
Type of input coordinates.
Requested type of output coordinate frame.

* 'tel': arcsecs V2,V3
* 'sci': pixels, in conventional DMS axes orientation
Expand Down Expand Up @@ -116,29 +116,25 @@
# Pixel scale information
ny, nx = hdu_list[ext].shape
pixelscale = hdu_list[ext].header["PIXELSCL"] # the pixel scale carries the over-sample value
oversamp = hdu_list[ext].header["DET_SAMP"] # PSF oversampling relative to detector

# Get 'sci' reference location where PSF is observed
xsci_cen = hdu_list[ext].header["DET_X"] # center x location in pixels ('sci')
ysci_cen = hdu_list[ext].header["DET_Y"] # center y location in pixels ('sci')

# Convert the PSF center point from pixels to arcseconds using pysiaf
xidl_cen, yidl_cen = aper.sci_to_idl(xsci_cen, ysci_cen)

# ###############################################
# Create an array of indices (in pixels) for where the PSF is located on the detector
nx_half, ny_half = ( (nx-1)/2., (ny-1)/2. )
xlin = np.linspace(-1*nx_half, nx_half, nx)
ylin = np.linspace(-1*ny_half, ny_half, ny)
xarr, yarr = np.meshgrid(xlin, ylin)

# Convert the PSF center point from pixels to arcseconds using pysiaf
xidl_cen, yidl_cen = aper.sci_to_idl(xsci_cen, ysci_cen)

# Get 'idl' coords
xidl = xarr * pixelscale + xidl_cen
yidl = yarr * pixelscale + yidl_cen

# ###############################################
# Create an array of indices (in pixels) that the final data will be interpolated onto
xnew_cen, ynew_cen = aper.convert(xsci_cen, ysci_cen, 'sci', to_frame)

# If new x and y values are specified, create a meshgrid
if (xnew_coords is not None) and (ynew_coords is not None):
if len(xnew_coords.shape)==1 and len(ynew_coords.shape)==1:
Expand All @@ -147,9 +143,16 @@
assert xnew_coords.shape==ynew_coords.shape, "If new x and y inputs are a grid, must be same shapes"
xnew, ynew = xnew_coords, ynew_coords
elif to_frame=='sci':
xnew = xarr / oversamp + xnew_cen
ynew = yarr / oversamp + ynew_cen
osamp_x = aper.XSciScale / pixelscale
osamp_y = aper.YSciScale / pixelscale
osamp = (osamp_x + osamp_y) / 2
xnew = xarr / osamp + xnew_cen
ynew = yarr / osamp + ynew_cen
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Can you explain the logic here for averaging osamp? This computes first a distinct oversampling factor in each of X and Y, but then computes xnew and ynew using the average oversampling factor. Wouldn't it be more precise to calculate using the distinct oversampling factors per axis, like xnew = xarr / osamp_x + xnew_cen?

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I originally tried doing it per-axis, but test_apply_distortion_pixel_scale() would fail. I did not have time to look into why the test was failing, as I didn't quite understand the logic behind the test. Reverting to a single oversampling applied across both axes fixed the issue. Need to investigate further.

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Huh, yeah, now that I look at that test... I do not understand the logic either. 🤣

else:
# Get 'idl' coords
xidl = xarr * pixelscale + xidl_cen
yidl = yarr * pixelscale + yidl_cen

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xv, yv = aper.convert(xidl, yidl, 'idl', to_frame)
xmin, xmax = (xv.min(), xv.max())
ymin, ymax = (yv.min(), yv.max())
Expand Down