sdimaging
- sdimaging(infiles, outfile='', overwrite=False, field='', spw='', antenna='', scan='', intent='OBSERVE_TARGET#ON_SOURCE', mode='channel', nchan=-1, start='0', width='1', veltype='radio', outframe='', gridfunction='BOX', convsupport=-1, truncate='-1', gwidth='-1', jwidth='-1', imsize='', cell='', phasecenter='', projection='SIN', ephemsrcname='', pointingcolumn='direction', restfreq='', stokes='', minweight=0.1, brightnessunit='', clipminmax=False, enablecache=True, convertfirst='never', interpolation='linear')[source]
SD task: imaging for total power and spectral data
[Description] [Examples] [Development] [Details]
- Parameters
infiles (pathVec) - a list of names of input SD Measurementsets (only MS is allowed for this task)
outfile (string=’’) - name of output image
overwrite (bool=False) - overwrite the output file if already exists [True, False]
field ({string, stringVec}=’’) - select data by field IDs and names, e.g. “3C2*” (“”=all)
spw ({string, stringVec}=’’) - select data by IF IDs (spectral windows), e.g. “3,5,7” (“”=all)
antenna ({string, stringVec}=’’) - select data by antenna names or IDs, e.g, “PM03” (”” = all antennas)
scan ({string, stringVec}=’’) - select data by scan numbers, e.g. “21~23” (“”=all)
intent ({string, stringVec}=’OBSERVE_TARGET#ON_SOURCE’) - select data by observational intent, e.g. “ON_SOURCE” (“”=all)
mode (string=’channel’) - spectral gridding type [“channel”, “frequency”, “velocity”]
mode = channel
mode = frequency
mode = velocity
nchan (int=-1) - number of channels (planes) in output image (-1=all)
start ({string, int}=’0’) - start of output spectral dimension, e.g. “0”, “110GHz”, “-20km/s”
width ({string, int}=’1’) - width of output spectral channels
veltype (string=’radio’) - velocity definition [“radio”, “optical”, “true” or “relativistic”]
outframe (string=’’) - velocity frame of output image [“lsrk”, “lsrd”, “bary”, “geo”, “topo”, “galacto”, “lgroup”, “cmb”] (“”=current frame or LSRK for multiple-MS inputs)
gridfunction (string=’BOX’) - gridding function for imaging [“BOX”, “SF”, “PB”, “GAUSS” or “GJINC”] (see description in help)
gridfunction = SF
convsupport (int=-1) - convolution support for gridding
gridfunction = sf
convsupport (int=-1) - convolution support for gridding
gridfunction = GAUSS
gridfunction = gauss
gridfunction = GJINC
imsize ({intVec, doubleVec}=’’) - x and y image size in pixels, e.g., [64,64]. Single value: same for both spatial axes ([] = number of pixels to cover whole pointings in MSes)
cell ({string, stringVec, doubleVec}=’’) - x and y cell size, (e.g., [“8arcsec”,”8arcsec”]. default unit arcmin. (”” = 1/3 of FWHM of primary beam)
phasecenter (variant=’’) - image center direction: position or field index, e.g., “J2000 17:30:15.0 -25.30.00.0”. (”” = the center of pointing directions in MSes)
projection (string=’SIN’) - map projection type
ephemsrcname (string=’’) - ephemeris source name, e.g. “MARS”
pointingcolumn (string=’direction’) - pointing data column to use [“direction”, “target”, “pointing_offset”, “source_offset” or “encoder”]
restfreq ({string, double}=’’) - rest frequency to assign to image, e.g., “114.5GHz”
stokes (string=’’) - stokes parameters or polarization types to image, e.g. “I”, “XX”
minweight (double=0.1) - Minimum weight ratio to use
brightnessunit (string=’’) - Overwrite the brightness unit in image ('' = respect the unit in MS) ['K' or 'Jy/beam']
clipminmax (bool=False) - Clip minimum and maximum value from each pixel
enablecache (bool=True) - Cache spectra pixels coordinates computed while creating the normal image, and re-use them when creating the weight image.
convertfirst (string=’never’) - pointing column: direction conversion-interpolation processing scheme to use [“never”, “auto”, “always”]
interpolation (string=’linear’) - Spectral interpolation [“nearest”, “linear”, “cubic”]
Description
Warning
There are Known Issues for sdimaging.
This task grids/images total power and spectral data according to a specified gridding kernel. The input data should be calibrated and bandpass corrected (where necessary), and the output is a CASA image format dataset, either 2-d, 3-d, or 4-d depending on the input parameters. Specifying multiple MSes is supported. The details of conformance checks that are performed on the list of MSes are summarized in the CASA Docs page on Combining Datasets.
The output image contains up to four axes: two spatial axes, frequency, and polarization. By default, the spatial coordinates are determined such that the imaged area is covered with a cell size equal to 1/3 of the FWHM of the primary beam of antennas in the first MS. It is also possible to define the spatial axes of the image by specifying the image center direction (phasecenter), the number of image pixels (imsize), and the pixel size (cell).
The frequency coordinate of the image is defined by three parameters: the number of channels (nchan), the channel number/frequency/velocity of the first channel (start), and the channel width (width). The start and width parameters can be in units of ‘channel’ (use channel number), ‘frequency’ (e.g., ‘GHz’), or ‘velocity’ (e.g., ‘km/s’). By default, nchan, start, and width are set so that all selected spectral windows are covered with a channel width equal to the separation of the first two channels selected. Finally, the polarization axis of the image is determined by the stokes parameter. For example, stokes =’XXYY’ produces an image cube with each plane containing the image of one of the polarizations, while stokes=’I’ produces a “total intensity”, or Stokes I image.
The parameter gridfunction sets the gridding function (convolution kernel) for imaging. Currently, the task supports ‘BOX’ (boxcar), ‘SF’ (Prolate Spheroidal Wave Function), ‘GAUSS’ (Gaussian), ‘GJINC’ (Gaussian*Jinc), where Jinc(x) = \(J_1(π*x/c)/(π*x/c)\) with a first order Bessel function J_1, and ‘PB’ (Primary Beam).
There are four subparameters for gridfunction: convsupport, truncate, gwidth, and jwidth. The convsupport parameter is an integer specifying the cutoff radius for ‘SF’ in units of pixels. By default (convsupport =-1), the cutoff radius is 3 pixels. The truncate parameter is a cutoff radius for ‘GAUSS’ or ‘GJINC’. It accepts integer, float, and string values, where the string would be a number plus unit. Allowed units include ‘deg’, ‘arcmin’, ‘arcsec’, and ‘pixel’. The default is ‘pixel’. The default value for truncate, which is used when a negative radius is set, is 3*HWHM for ‘GAUSS’, and the radius at the first null for ‘GJINC’. The gwidth is the HWHM of the Gaussian for ‘GAUSS’ and ‘GJINC’. The default value is sqrt(log(2)) pixels for ‘GAUSS’ and 2.52*sqrt(log(2)) pixels for ‘GJINC’. The jwidth specifies the width of the jinc function (parameter ‘c’ in the definition above). The default is 1.55 pixels. Both gwidth and jwidth allow integer, float, or string values, where the string would be a number plus unit. The default values for gwidth and jwidth are taken from Mangum, et al. 2007 [1] . The formula for ‘GAUSS’ and ‘GJINC’ are taken from Table 1 in the paper, and are written as follows using gwidth and jwidth:
GAUSS: \(\exp[-\log(2)*(|r|/gwidth)^2]\)
GJINC: \(J_1(π*|r|/jwidth)/(π*|r|/jwidth)* \exp[-\log(2)*(|r|/gwidth)^2]\)
The imagename should be unique. Clean will stop with an Exception error (e.g. Exception: Unable to open lattice) if imagename is the same as the vis name.
The ephemsrcname parameter can be set to specifiy an ephemeris for a moving source (solar sytem objects). If the source name in the data matches one of the solar system objects known by CASA, the imaging realigns the data by shifting the source, so that the source appears to be fixed in the image. The clipminmax function can clip minimum and maximum value from each pixel. This function makes the computed output slightly more robust to noise and spurious data. Note the benefit of clipping is lost when the number of integrations contributing to each gridded pixel is small, or where the incidence of spurious data points is approximately equal to or greater than the number of beams (in area) encompassed by the expected image.
The minweight parameter defines a threshold of weight values to mask. The pixels in outfile whose weight is smaller than minweight *median (weight) are masked out. The task also creates a weight image with the name outfile.weight.
The projection parameter allows to specify what kind of map projection is applied. The default is SIN (slant orthographic) projection. Besides that, the task supports CAR (plate carrée), TAN (gnomonic), and SFL (Sanson-Flamsteed).
Bibliography
- Examples
To generate a spectral line cube with 500 channels selected from channel 200 to 700:
spw='0' pol='XX' src='Moon' sdimaging(infiles='mydata.ms', spw=spw, nchan=500, start='200', width='1', cell=['30.0arcsec','30.0arcsec'], outfile='mydata.ms.im', imsize=[80,80], gridfunction='GAUSS', gwidth='4arcsec', stokes=pol, ephemsrcname=src)
The start parameter can be specified in different units:
start=100 # mode='channel' start='22.3GHz' # mode='frequency' start='5.0km/s' # mode='velocity'
The parameter ephemsrcname can be set to a solar system object:
ephemsrcname ='MERCURY'
- Development
No additional development details
- Parameter Details
Detailed descriptions of each function parameter
infiles (pathVec)
- a list of names of input SD Measurementsets (only MS is allowed for this task)outfile (string='')
- name of output imageoverwrite (bool=False)
- overwrite the output file if already exists [True, False]field ({string, stringVec}='')
- select data by field IDs and names, e.g. “3C2*” (“”=all)spw ({string, stringVec}='')
- select data by IF IDs (spectral windows), e.g. “3,5,7” (“”=all)antenna ({string, stringVec}='')
- select data by antenna names or IDs, e.g, “PM03” (”” = all antennas)scan ({string, stringVec}='')
- select data by scan numbers, e.g. “21~23” (“”=all)intent ({string, stringVec}='OBSERVE_TARGET#ON_SOURCE')
- select data by observational intent, e.g. “ON_SOURCE” (“”=all)mode (string='channel')
- spectral gridding typenchan (int=-1)
- number of channels (planes) in output image (-1=all)start ({string, int}='0')
- start of output spectral dimension, e.g. “0”, “110GHz”, “-20km/s”width ({string, int}='1')
- width of output spectral channelsveltype (string='radio')
- velocity definitionoutframe (string='')
- velocity frame of output image (“”=current frame or LSRK for multiple-MS inputs)gridfunction (string='BOX')
- gridding function for imaging (see description in help)convsupport (int=-1)
- convolution support for griddingtruncate ({string, int, double}='-1')
- truncation radius for griddinggwidth ({string, int, double}='-1')
- HWHM for gaussianjwidth ({string, int, double}='-1')
- c-parameter for jinc functionimsize ({intVec, doubleVec}='')
- x and y image size in pixels, e.g., [64,64]. Single value: same for both spatial axes ([] = number of pixels to cover whole pointings in MSes)cell ({string, stringVec, doubleVec}='')
- x and y cell size, (e.g., [“8arcsec”,”8arcsec”]. default unit arcmin. (”” = 1/3 of FWHM of primary beam)phasecenter (variant='')
- image center direction: position or field index, e.g., “J2000 17:30:15.0 -25.30.00.0”. (”” = the center of pointing directions in MSes)projection (string='SIN')
- map projection typeephemsrcname (string='')
- ephemeris source name, e.g. “MARS”pointingcolumn (string='direction')
- pointing data column to userestfreq ({string, double}='')
- rest frequency to assign to image, e.g., “114.5GHz”stokes (string='')
- stokes parameters or polarization types to image, e.g. “I”, “XX”minweight (double=0.1)
- Minimum weight ratio to the median of weight used in weight correction and weight beased maskingbrightnessunit (string='')
- Overwrite the brightness unit in image ('' = respect the unit in MS) ['K' or 'Jy/beam']clipminmax (bool=False)
- Clip minimum and maximum value from each pixel. Note the benefit of clipping is lost when the number of integrations contributing to each gridded pixel is small, or where the incidence of spurious datapoints is approximately or greater than the number of beams (in area) encompassed by expected image.enablecache (bool=True)
- Cache spectra pixels coordinates computed while creating the normal image, and re-use them when creating the weight image.convertfirst (string='never')
- Specify whether the direction of the specified pointing column must be converted to image”s reference frame prior to being interpolated at data-taking time, and when. “never”: interpolate against the pointing column, then convert. “always”: interpolate against the beforehand converted pointing column. “auto”: if there are less pointings than selected data rows convert first, else interpolate firstinterpolation (string='linear')
- Spectral interpolation [“nearest”, “linear”, “cubic”]Interpolation rules to use when binning data channels onto image channels and evaluating visibility values at the centers of image channels.Note :- “linear” and “cubic” interpolation requires data points on both sides of each image frequency. Errors are therefore possible at edge channels, or near flagged data channels. When image channel width is much larger than the data channel width there is nothing much to be gained using linear or cubic thus not worth the extra computation involved.- If there are significant differences in the observation dates of the input MSes, “nearest” interpolation may cause some problems with frequency channel matching.