sdplot – ASAP SD plotting task – single dish task

Description

Task sdplot displays single-dish spectra, total power, or pointing direction of input data. It assumes that the spectra have been calibrated. It does allow selection of scans, spectral windows, polarizations, and some time and channel averaging/smoothing options also, but does not write out this data.

This task adds an additional toolbar to Matplotlib plotter. See the cookbook for details of its capability.

Parameters

Title

Parameter	Default	Description
infile	''
antenna	int(0)
fluxunit	''
telescopeparam	''
specunit	''	units for spectral axis ['','channel','km/s','GHz','MHz','kHz', or 'Hz']
restfreq	''
frame	''
doppler	''
field	''
spw	''
scan	''
pol	''
beam	''
rastermode	'row'
raster	''
timeaverage	False
tweight	'tintsys'	weighting for time averaging ['tintsys', 'tsys', 'tint', 'var', or 'median']
scanaverage	False
polaverage	False
pweight	'tsys'	weighting for polarization averaging ['tsys' or 'var']
kernel	''	type of spectral smoothing ['hanning','gaussian', or 'boxcar'] (''=no smoothing)
kwidth	int(5)
plottype	'spectra'	type of plot ['spectra','totalpower','azel','pointing', or 'grid']
stack	'p'	setting of plot overlay ['b'(beam), 'i'(spw), 'p'(pol), 'r'(row), 's'(scan), 't'(time or src type)]
panel	'i'	multple panel setting ['b'(beam), 'i'(spw), 'p'(pol), 'r'(row), 's'(scan), 't'(time)]
flrange	numpy.array( [  ] )
sprange	numpy.array( [  ] )
linecat	'none'
linedop	float(0.0)
subplot	int(-1)
colormap	'none'
linestyles	'none'
linewidth	[ ]
histogram	False
center	''
cell	numpy.array( [  ] )
scanpattern	False
header	True
headsize	int(9)
plotstyle	False
margin	numpy.array( [  ] )
legendloc	int(1)
outfile	''
overwrite	False

Parameter Explanations

infile

''

name of input SD dataset

antenna

int(0)

select an antenna name or ID, e.g. 'PM03' (only effective for MS input)

fluxunit

''

units of the flux (''=current)

telescopeparam

''

parameters of telescope for flux conversion (see examples in help)

specunit

''

units for spectral axis

restfreq

''

rest frequency (default unit: Hz)

frame

''

frequency reference frame (''=current)

doppler

''

doppler convention (''=current). Effective only when spw selection is in velocity unit

field

''

select data by field IDs and names, e.g. '3C2*' (''=all)

spw

''

select data by IF IDs (spectral windows), e.g. '3,5,7' (''=all)

scan

''

select data by scan numbers, e.g. '21~23' (''=all)

pol

''

select data by polarization IDs, e.g. '0,1' (''=all)

beam

''

select data by beam IDs, e.g. '0,1' (''=all)

rastermode

'row'

mode of raster selection ['row', 'raster']

raster

''

select data by raster scan row or map iteration e.g. '0~2' (''=all)

timeaverage

False

average spectra over time [True, False] (see examples in help)

tweight

'tintsys'

weighting for time averaging

scanaverage

False

average spectra within a scan number [True, False] (see examples in help)

polaverage

False

average spectra over polarizations [True, False]

pweight

'tsys'

weighting for polarization averaging

kernel

''

type of spectral smoothing

kwidth

int(5)

width of spectral kernel in channels

plottype

'spectra'

type of plot

stack

'p'

code for stacking on single plot for spectral plotting

panel

'i'

code for splitting into multiple panels for spectral plotting

flrange

numpy.array( [  ] )

range for flux axis of plot for spectral plotting

sprange

numpy.array( [  ] )

range for spectral axis of plot

linecat

'none'

control for line catalog plotting for spectral plotting

linedop

float(0.0)

doppler offset for line catalog plotting (spectral plotting)

subplot

int(-1)

number of subplots (row and column)

colormap

'none'

the colours to be used for plot lines

linestyles

'none'

the linestyles to be used for plot lines

linewidth

[ ]

width of plotted lines

histogram

False

plot histogram

center

''

the central direction of gridding. (default: map center)

cell

numpy.array( [  ] )

x and y cell size, e.g., [“1arcmin”,”1arcmin”]. (default map extent/subplot number)

scanpattern

False

plot scan patterns.

header

True

print header information on the plot

headsize

int(9)

header fontsize

plotstyle

False

customize plot settings

margin

numpy.array( [  ] )

subplot margins in figure coordinate

legendloc

int(1)

legend location

outfile

''

file name for hardcopy output

overwrite

False

overwrite the output file if already exists