NIRLIN should be used to linearize all science data. This version uses three coefficients to correct for non-linearity in the NIRI detector: an exposure time correction, a counts squared term and a counts cubed term. These coefficents are dependent on the read mode and detector ROI. We have currently derived coefficients for the following configurations:
|Read Mode||ROI||Well Depth||dt||c2||c3|
Note: We have not yet quantified the effect of linearizing flat fields.
NAME nirlin.py - NIR linearization SYNOPSIS nirlin.py [options] infile DESCRIPTION Run on raw or nprepared Gemini NIRI data, this script calculates and applies a per-pixel linearity correction based on the counts in the pixel, the exposure time, the read mode, the bias level and the ROI. Pixels over the maximum correctable value are set to BADVAL unless given the force flag. Note that you may use glob expansion in infile, however, any pattern matching characters (*,?) must be either quoted or escaped with a backslash. OPTIONS -b
: value to assign to uncorrectable pixels  -f : force correction on all pixels -o <file> : write output to <file> [l<inputfile>] If no .fits is included this is assumed to be a directory -v : verbose debugging output VERSION 2013 Jun 24