# Default APO20 opECalib.par file mjd 51752 # MJD day number when this file was created. # This should be unique over the collection # of all configuration files for a given # camera. nsteps 13 # The linearity arrays are hardwired to be of # length 13 (we must adopt a size so that two # files with arrays of differing length aren't # read in together, which would lead to a # possibly undetectable bug). This parameter # records the number of array elements which # actually contain data. # i.e., if "nsteps" = 7, then only the first # 7 elements of the linearity arrays contain # real data. The remaining elements should # be ignored. typedef struct { char program[40]; # program name 'stare_0123' int camRow; # camRow mt=0 int camCol; # camCol mt=0 float readNoiseDN0; # in DN = ADU float fullWellDN0; # in DN = ADU float gain0; # in electrons/DN = electrons/ADU float biasLevel0; # in DN = ADU float DN0[13]; # array of DN's where linearity corrections # factors apply (after bias subtraction) float linearity0[13];# array of linearity correction factors # True_DN = Instrumental_DN * # linearity(Instrumental_DN) # (after bias subtraction) float readNoiseDN1; # in DN = ADU float fullWellDN1; # in DN = ADU float gain1; # in electrons/DN = electrons/ADU float biasLevel1; # in DN = ADU float DN1[13]; # array of DN's where linearity corrections # factors apply (after bias subtraction) float linearity1[13];# array of linearity correction factors # True_DN = Instrumental_DN * # linearity(Instrumental_DN) # (after bias subtraction) float readNoiseDN2; # in DN = ADU float fullWellDN2; # in DN = ADU float gain2; # in electrons/DN = electrons/ADU float biasLevel2; # in DN = ADU float DN2[13]; # array of DN's where linearity corrections # factors apply (after bias subtraction) float linearity2[13];# array of linearity correction factors # True_DN = Instrumental_DN * # linearity(Instrumental_DN) # (after bias subtraction) float readNoiseDN3; # in DN = ADU float fullWellDN3; # in DN = ADU float gain3; # in electrons/DN = electrons/ADU float biasLevel3; # in DN = ADU float DN3[13]; # array of DN's where linearity corrections # factors apply (after bias subtraction) float linearity3[13];# array of linearity correction factors # True_DN = Instrumental_DN * # linearity(Instrumental_DN) # (after bias subtraction) } ECALIB; # Note: this camera uses only 2 amplifiers. Data for amps 2 and 3 are nonsense ECALIB pt_stare 0 0 \ 1.52 62444 4.89 1360 \ { 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 60000 65000} \ {1.000 1.000 0.998 0.997 0.995 0.994 0.993 0.992 0.991 0.991 0.991 0.990 0.990} \ 1.77 64149 4.44 1288 \ { 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 60000 65000} \ {1.000 1.000 0.998 0.996 0.994 0.994 0.992 0.991 0.991 0.990 0.990 0.990 0.990} \ 0.0 0.0 0.0 0.0 \ {10000 0 0 0 0 0 0 0 0 0 0 0 0} \ {1.0 0 0 0 0 0 0 0 0 0 0 0 0} \ 0.0 0.0 0.0 0.0 \ {10000 0 0 0 0 0 0 0 0 0 0 0 0} \ {1.0 0 0 0 0 0 0 0 0 0 0 0 0} ECALIB pt_64 0 0 \ 1.52 62444 4.89 1360 \ { 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 60000 65000} \ {1.000 1.000 0.998 0.997 0.995 0.994 0.993 0.992 0.991 0.991 0.991 0.990 0.990} \ 1.77 64149 4.44 1288 \ { 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 60000 65000} \ {1.000 1.000 0.998 0.996 0.994 0.994 0.992 0.991 0.991 0.990 0.990 0.990 0.990} \ 0.0 0.0 0.0 0.0 \ {10000 0 0 0 0 0 0 0 0 0 0 0 0} \ {1.0 0 0 0 0 0 0 0 0 0 0 0 0} \ 0.0 0.0 0.0 0.0 \ {10000 0 0 0 0 0 0 0 0 0 0 0 0} \ {1.0 0 0 0 0 0 0 0 0 0 0 0 0} ECALIB pt_128 0 0 \ 1.52 62444 4.89 1360 \ { 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 60000 65000} \ {1.000 1.000 0.998 0.997 0.995 0.994 0.993 0.992 0.991 0.991 0.991 0.990 0.990} \ 1.77 64149 4.44 1288 \ { 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 60000 65000} \ {1.000 1.000 0.998 0.996 0.994 0.994 0.992 0.991 0.991 0.990 0.990 0.990 0.990} \ 0.0 0.0 0.0 0.0 \ {10000 0 0 0 0 0 0 0 0 0 0 0 0} \ {1.0 0 0 0 0 0 0 0 0 0 0 0 0} \ 0.0 0.0 0.0 0.0 \ {10000 0 0 0 0 0 0 0 0 0 0 0 0} \ {1.0 0 0 0 0 0 0 0 0 0 0 0 0} ECALIB pt_256 0 0 \ 1.52 62444 4.89 1360 \ { 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 60000 65000} \ {1.000 1.000 0.998 0.997 0.995 0.994 0.993 0.992 0.991 0.991 0.991 0.990 0.990} \ 1.77 64149 4.44 1288 \ { 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 60000 65000} \ {1.000 1.000 0.998 0.996 0.994 0.994 0.992 0.991 0.991 0.990 0.990 0.990 0.990} \ 0.0 0.0 0.0 0.0 \ {10000 0 0 0 0 0 0 0 0 0 0 0 0} \ {1.0 0 0 0 0 0 0 0 0 0 0 0 0} \ 0.0 0.0 0.0 0.0 \ {10000 0 0 0 0 0 0 0 0 0 0 0 0} \ {1.0 0 0 0 0 0 0 0 0 0 0 0 0} ECALIB pt_512 0 0 \ 1.52 62444 4.89 1360 \ { 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 60000 65000} \ {1.000 1.000 0.998 0.997 0.995 0.994 0.993 0.992 0.991 0.991 0.991 0.990 0.990} \ 1.77 64149 4.44 1288 \ { 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 60000 65000} \ {1.000 1.000 0.998 0.996 0.994 0.994 0.992 0.991 0.991 0.990 0.990 0.990 0.990} \ 0.0 0.0 0.0 0.0 \ {10000 0 0 0 0 0 0 0 0 0 0 0 0} \ {1.0 0 0 0 0 0 0 0 0 0 0 0 0} \ 0.0 0.0 0.0 0.0 \ {10000 0 0 0 0 0 0 0 0 0 0 0 0} \ {1.0 0 0 0 0 0 0 0 0 0 0 0 0} ECALIB pt_1024 0 0 \ 1.52 62444 4.89 1360 \ { 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 60000 65000} \ {1.000 1.000 0.998 0.997 0.995 0.994 0.993 0.992 0.991 0.991 0.991 0.990 0.990} \ 1.77 64149 4.44 1288 \ { 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 60000 65000} \ {1.000 1.000 0.998 0.996 0.994 0.994 0.992 0.991 0.991 0.990 0.990 0.990 0.990} \ 0.0 0.0 0.0 0.0 \ {10000 0 0 0 0 0 0 0 0 0 0 0 0} \ {1.0 0 0 0 0 0 0 0 0 0 0 0 0} \ 0.0 0.0 0.0 0.0 \ {10000 0 0 0 0 0 0 0 0 0 0 0 0} \ {1.0 0 0 0 0 0 0 0 0 0 0 0 0}