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include <mach.h>
include "../lib/center.h"
include "../lib/noise.h"
# AP_CSNRATIO -- Procedure to estimate the signal to noise ratio for centering.
real procedure ap_csnratio (ap, array, nx, ny, threshold)
pointer ap # apphot structure
real array[nx,ny] # data array
int nx, ny # subraster dimensions
real threshold # threshold value for snr computation
int apstati()
real apstatr(), ap_cratio(), ap_pratio()
begin
switch (apstati (ap, NOISEFUNCTION)) {
case AP_NCONSTANT:
return (ap_cratio (array, nx, ny, threshold, apstatr (ap,
SKYSIGMA)))
case AP_NPOISSON:
return (ap_pratio (array, nx, ny, threshold, apstatr (ap,
SKYSIGMA), apstatr (ap, EPADU)))
default:
return (MAX_REAL)
}
end
# AP_CRATIO -- Procedure to estimate the signal to noise ratio in the
# centering aperture assuming that the noise is due to a constant sky
# sigma. These computations are approximate only.
real procedure ap_cratio (array, nx, ny, sky, noise)
real array[nx,ny] # centering buffer
int nx, ny # dimensions of the centering buffer
real sky # mean sky value of the data in ADU
real noise # estimate of sky noise in ADU
int npts
real signal, tnoise
real asumr()
begin
npts = nx * ny
signal = asumr (array, npts) - npts * sky
if (IS_INDEFR(noise))
tnoise = 0.0
else
tnoise = sqrt (npts * noise ** 2)
if (signal <= 0.0)
return (0.0)
else if (tnoise <= 0.0)
return (MAX_REAL)
else
return (signal / tnoise)
end
# AP_PRATIO -- Procedure to estimate the signal to noise ratio in the
# centering aperture assuming the noise is due to a constant sky sigma
# and poisson statistics in the image. These computations are
# approximate only.
real procedure ap_pratio (array, nx, ny, sky, noise, padu)
real array[nx,ny] # centering buffer
int nx, ny # dimensions of the centering buffer
real sky # mean sky value of the data in ADU
real noise # estimate of sky noise in ADU
real padu # photons per adu
int npts
real signal, tnoise
real asumr()
begin
npts = nx * ny
signal = asumr (array, npts) - npts * sky
if (IS_INDEFR(noise))
tnoise = sqrt (abs (signal / padu))
else
tnoise = sqrt (abs (signal / padu) + npts * noise ** 2)
if (signal <= 0.0)
return (0.0)
else if (tnoise <= 0.0)
return (MAX_REAL)
else
return (signal / tnoise)
end
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