On the edge of HSC images background subtraction with BACK_SIZE = 64 ends up with only NaNs even though and then detects nothing even though everything works well with 32 or 128…
Do you have an idea what causes the problem?
Best
$ sex /Volumes/LaCie/LAM_BABCKUP/calexp/ImagesOnly/calexp-HSC-R-8283-6-8.fits -PARAMETERS_NAME sex.param -BACK_SIZE 64
----- SExtractor 2.19.5 started on 2020-05-22 at 12:57:19 with 1 thread
> Setting catalog parameters
> WARNING: Not enough apertures provided in config.:
some APER photometric values will remain blank
> Reading Neural Network Weights
> WARNING: Not enough apertures provided in config.:
some APER photometric values will remain blank
----- Measuring from: calexp-HSC-R-8283-6-8.fits
"Unnamed" / no ext. header / 4200x4100 / 32 bits (floats)
(M+D) Background: 0.00500251 RMS: 0.0560535 / Threshold: 0.0840803
Objects: detected 0 / sextracted 0
> All done (in 0.8 s: 5295.8 lines/s , 0.0 detection/s)
$ sex /Volumes/LaCie/LAM_BABCKUP/calexp/ImagesOnly/calexp-HSC-R-8283-6-8.fits -PARAMETERS_NAME sex.param -BACK_SIZE 32
----- SExtractor 2.19.5 started on 2020-05-22 at 12:57:24 with 1 thread
> Setting catalog parameters
> WARNING: Not enough apertures provided in config.:
some APER photometric values will remain blank
> Reading Neural Network Weights
> WARNING: Not enough apertures provided in config.:
some APER photometric values will remain blank
----- Measuring from: calexp-HSC-R-8283-6-8.fits
"Unnamed" / no ext. header / 4200x4100 / 32 bits (floats)
(M+D) Background: 0.00504417 RMS: 0.0558841 / Threshold: 0.0838262
Objects: detected 16799 / sextracted 13263
> All done (in 2.2 s: 1836.1 lines/s , 5939.4 detections/s)
The NaNs you are seeing on the background-subtracted check-image? I have tried to reproduce your issue with a 4200×4100 synthetic image but I am not seeing any NaN.
Same on the image you provided. You might want to check out a more recent version of the software, see this page for getting the most recent version of the code.
On the edge of HSC images background subtraction with BACK_SIZE = 64 ends up with only NaNs even though and then detects nothing even though everything works well with 32 or 128… Do you have an idea what causes the problem?
Best