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I am trying to generate authentic dark current files to help simulate background noise properties and use those to mitigate future TSO observational simulations. This would go slightly above nghxrg by having 'real' dark current.
My solution was to generate an image of a star that is too faint for NRC to detect (M_ab ~ 50); but I would be very happy to see "get_dark_current", "get_bias", "get_noise_signals" functions.
Been a couple years, but check out the latest develop branch of pynrc: https://github.com/JarronL/pynrc/tree/develop (to be pushed to the main branch soon). Specifically the simulate_detector_ramp in pynrc.simul.ngNRC.py.
Input requires a NIRCam cal object using the nircam_cal class in pynrc.reduce.calib.py.
Description
I am trying to generate authentic dark current files to help simulate background noise properties and use those to mitigate future TSO observational simulations. This would go slightly above
nghxrg
by having 'real' dark current.My solution was to generate an image of a star that is too faint for NRC to detect (M_ab ~ 50); but I would be very happy to see "get_dark_current", "get_bias", "get_noise_signals" functions.
What I Did
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