sdimprocess – Task for single-dish image processing – single dish task

Description

Task sdimprocess is used to remove a scanning noise that appears as a striped noise pattern along the scan direction in a raster scan data.

By default, the scanning noise is removed by using the FFT-based ‘Basket-Weaving’ method (Emerson & Grave 1988) that requires multiple images that observed exactly the same area with different scanning direction. If only one image is available, the ‘Pressed-out’ method (Sofue & Reich 1979) can be used to remove the scanning effect.

Parameters

Title
Parameter	Default	Description
infiles	`numpy.array( [ ] )`
mode	`''`	image processing mode ['press', 'basket']
numpoly	`int(2)`
beamsize	`float(0.0)`
smoothsize	`float(2.0)`
direction	`numpy.array( [ ] )`
maskwidth	`float(1.0)`
tmax	`float(0.0)`
tmin	`float(0.0)`
outfile	`''`
overwrite	`False`	overwrite the output file if already exists [True, False]

Parameter Explanations

infiles

numpy.array( [ ] )

list of name of input SD images (FITS or CASA image)

mode

''

image processing mode

numpoly

int(2)

order of polynomial fit for Pressed-out method

beamsize

float(0.0)

beam size for Pressed-out method

smoothsize

float(2.0)

size of smoothing beam for Pressed-out method

direction

numpy.array( [ ] )

scan direction (p.a.) counterclockwise from the horizontal axis in unit of degree

maskwidth

float(1.0)

mask width for Basket-Weaving (on percentage)

tmax

float(0.0)

maximum threshold value for processing

tmin

float(0.0)

minimum threshold value for processing

outfile

''

name of output file

overwrite

False

overwrite the output file if already exists