function ssastat

Returns statistics for ssa.

Arguments
like ssa. The resulting array will be [xshift, yshift, min, max, flux, fwhm, flag].

Syntax
result = ssastat(X, XCENTER, YCENTER, SKY, FLAT, DPL, MASK [, METHOD])

Arguments

X:   A FITS datacube

XCENTER:   The pixel where to shift in the first dimension

YCENTER:   The pixel where to shift in the second dimension

SKY:   A sky to be subtracted

FLAT:   A flatfield to be multiplied

DPL:   A dead pixel list to be applied

MASK:   The peak pixel will be searched for in an image multiplied by this mask

METHOD:   Optional, controls how the SSA will be done:

METHOD = 0:   Shift the brightest pixel to XCENTER, YCENTER (default)

METHOD = 1:   Integer shift the centroid to XCENTER, YCENTER

METHOD = 2:   Subpixel shift the centroid to XCENTER, YCENTER

METHOD < 0:   the same is done as if METHOD were set to 0, but the brightest pixel is searched in a smoothed version of the image. The smoothing is done by convolving with a gaussian of fwhm the negative of method.

See also
function ssa
function sssa

X:	A FITS datacube
XCENTER:	The pixel where to shift in the first dimension
YCENTER:	The pixel where to shift in the second dimension
SKY:	A sky to be subtracted
FLAT:	A flatfield to be multiplied
DPL:	A dead pixel list to be applied
MASK:	The peak pixel will be searched for in an image multiplied by this mask
METHOD:	Optional, controls how the SSA will be done:
METHOD = 0:	Shift the brightest pixel to XCENTER, YCENTER (default)
METHOD = 1:	Integer shift the centroid to XCENTER, YCENTER
METHOD = 2:	Subpixel shift the centroid to XCENTER, YCENTER
METHOD < 0:	the same is done as if METHOD were set to 0, but the brightest pixel is searched in a smoothed version of the image. The smoothing is done by convolving with a gaussian of fwhm the negative of method.