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Deconvolve an image with selected algorithm This is the main clean deconvolution task. It contains many functions 1) Make 'dirty' image and 'dirty' beam (psf) 2) Multi-frequency-continuum images or spectral channel imaging 3) Full Stokes imaging 4) Mosaicking of several pointings 5) Multi-scale cleaning 6) Interactive clean boxing 7) Use starting model (eg from single dish) vis -- Name of input visibility file default: none; example: vis='ngc5921.ms' imagename -- Pre-name of output images: default: none; example: imagename='m2' output images are: m2.image; cleaned and restored image With or without primary beam correction m2.psf; point-spread function (dirty beam) m2.flux; relative sky sensitivity over field m2.flux.pbcoverage; relative pb coverage over field (gets created only for ft='mosaic') m2.model; image of clean components m2.residual; image of residuals m2.interactive.mask; image containing clean regions To include outlier fields: imagename=['n5921','outlier1','outlier2'] outlierfile --- Text file name which contains image names, sizes, field centers field -- Select fields in mosaic. Use field id(s) or field name(s). ['go listobs' to obtain the list id's or names] default: ''= all fields If field string is a non-negative integer, it is assumed to be a field index otherwise, it is assumed to be a field name field='0~2'; field ids 0,1,2 field='0,4,5~7'; field ids 0,4,5,6,7 field='3C286,3C295'; field named 3C286 and 3C295 field = '3,4C*'; field id 3, all names starting with 4C spw -- Select spectral window/channels NOTE: This selects the data passed as the INPUT to mode default: ''=all spectral windows and channels spw='0~2,4'; spectral windows 0,1,2,4 (all channels) spw='0:5~61'; spw 0, channels 5 to 61 spw='<2'; spectral windows less than 2 (i.e. 0,1) spw='0,10,3:3~45'; spw 0,10 all channels, spw 3, channels 3 to 45. spw='0~2:2~6'; spw 0,1,2 with channels 2 through 6 in each. spw='0:0~10;15~60'; spectral window 0 with channels 0-10,15-60 spw='0:0~10,1:20~30,2:1;2;3'; spw 0, channels 0-10, spw 1, channels 20-30, and spw 2, channels, 1,2 and 3 selectdata -- Other data selection parameters default: True >>> selectdata=True expandable parameters See help par.selectdata for more on these timerange -- Select data based on time range: default: '' (all); examples, timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss' Note: if YYYY/MM/DD is missing date defaults to first day in data set timerange='09:14:0~09:54:0' picks 40 min on first day timerange='25:00:00~27:30:00' picks 1 hr to 3 hr 30min on NEXT day timerange='09:44:00' pick data within one integration of time timerange='>10:24:00' data after this time uvrange -- Select data within uvrange (default units meters) default: '' (all); example: uvrange='0~1000klambda'; uvrange from 0-1000 kilo-lambda uvrange='>4klambda';uvranges greater than 4 kilo lambda antenna -- Select data based on antenna/baseline default: '' (all) If antenna string is a non-negative integer, it is assumed to be an antenna index, otherwise, it is considered an antenna name. antenna='5&6'; baseline between antenna index 5 and index 6. antenna='VA05&VA06'; baseline between VLA antenna 5 and 6. antenna='5&6;7&8'; baselines 5-6 and 7-8 antenna='5'; all baselines with antenna index 5 antenna='05'; all baselines with antenna number 05 (VLA old name) antenna='5,6,9'; all baselines with antennas 5,6,9 index numbers scan -- Scan number range. default: '' (all) example: scan='1~5' Check 'go listobs' to insure the scan numbers are in order. mode -- Frequency Specification: NOTE: See examples below: default: 'mfs' mode = 'mfs' means produce one image from all specified data. mode = 'channel'; Use with nchan, start, width to specify output image cube. See examples below mode = 'velocity', means channels are specified in velocity. mode = 'frequency', means channels are specified in frequency. >>> mode='mfs' expandable parameters Make a continuum image from the selected frequency channels/range using Multi-frequency synthesis algorithm for wide-band narrow field imaging. nterms is the number of Taylor terms to be used to model the frequency dependence of the sky emission. nterms=1 is equivalent to assuming no frequency dependence. nterms=2 is equivalent to the Sault-Wieringa algorithm (AandAS, 1994) reffreq is the reference frequency about which the Taylor expansion is done. >>> mode expandable parameters (for modes other than 'mfs') Start, width are given in units of channels, frequency or velocity as indicated by mode (note: only nearest neighbour interpolation is available at this time). nchan -- Number of channels (planes) in output image default: 1; example: nchan=3 start -- Start input channel (relative-0) default=0; example: start=5 width -- Output channel width in units of the input channel width (>1 indicates channel averaging) default=1; example: width=4 interpolation -- Interpolation type of spectral data when gridded on the uv-plane default = 'nearest' HOWEVER, 'linear' is recommended outframe -- velocity reference frame of output image (for mode='velocity' or 'frequency') Options: '','LSRK','LSRD','BARY','GEO','TOPO','GALACTO','LGROUP','CMB' default: ''; same as input data; example: frame='bary' for Barycentric frame veltype -- (for mode='velocity') velocity definition Options: 'radio','optical','true' (='relativistic') veltype='true' (or equivalently 'relativistic') for velocity defined without approximations using the relativistic expression default: 'radio' examples: spw = '0,1'; mode = 'mfs' will produce one image made from all channels in spw 0 and 1 spw='0:5~28^2'; mode = 'mfs' will produce one image made with channels (5,7,9,...,25,27) spw = '0'; mode = 'channel': nchan=3; start=5; width=4 will produce an image with 3 output planes plane 1 contains data from channels (5+6+7+8) plane 2 contains data from channels (9+10+11+12) plane 3 contains data from channels (13+14+15+16) spw = '0:0~63^3'; mode='channel'; nchan=21; start = 0; width = 1 will produce an image with 20 output planes Plane 1 contains data from channel 0 Plane 2 contains date from channel 2 Plane 21 contains data from channel 61 spw = '0:0~40^2'; mode = 'channel'; nchan = 3; start = 5; width = 4 will produce an image with three output planes plane 1 contains channels (5,7) plane 2 contains channels (13,15) plane 3 contains channels (21,23) psfmode -- method of PSF calculation to use during minor cycles: default: 'clark': Options: 'clark','clarkstokes', 'hogbom' 'clark' use smaller beam (faster, usually good enough); for stokes images clean components peaks are searched in the I^2+Q^2+U^2+V^2 domain 'clarkstokes' locate clean components independently in each stokes image 'hogbom' full-width of image (slower, better for poor uv-coverage) Note: psfmode will be used to clean is imagermode = '' imagermode -- Advanced imaging e.g mosaic or Cotton-Schwab clean default: imagermode='': Options: '', 'csclean', 'mosaic' default '' => psfmode cleaning algorithm used >>> gridmode='' expandable parameters The default value of '' has no effect. >>> gridmode='widefield' expandable parameters Apply corrections for non-coplanar effects during imaging using the W-Projection algorithm (Cornwell et al. IEEE JSTSP (2008)) or faceting or a combination of the two. wprojplanes is the number of pre-computed w-planes used for the W-Projection algorithm. wprojplanes=1 disables correction for non-coplanar effects. facets is the number of facets used. W-Projection is done for each facet. >>> gridmode='aprojection' expandable parameters Correct for the (E)VLA polarization squint using the A-Projection algorithm (Bhatnagar et al., AandA (2008)). cfcache is the name of the directory to be used to cache the convolution functions. These functions can be reused again if the image parameters are unchanged. If the image parameters change, a new cache must be created (or the existing one removed). painc (in degrees) is the Parallactic Angle increment used to compute the convolution functions. >>> imagermode='mosaic' expandable parameter(s): Image as a mosaic of the different pointings (uses csclean style too) mosweight -- Individually weight the fields of the mosaic default: False; example: mosweight=True This can be useful if some of your fields are more sensitive than others (i.e. due to time spent on-source); this parameter will give more weight to higher sensitivity fields in the overlap regions. ftmachine -- Gridding method for the image; Options: ft (standard interferometric gridding), sd (standard single dish) both (ft and sd as appropriate), mosaic (gridding use PB as convolution function) default: 'mosaic'; example: ftmachine='ft' if imagermode mosaic is chosen and ftmachine is mosaic, heterogenous arrays like Carma or Alma are recognized and the right Primary Beam (depending on the size of the dish) is used for each baseline. scaletype -- Controls scaling of pixels in the image plane. (Not fully implemented...for now only controls what is seen if interactive=True...but in the future will control the image on which clean components are searched) default='SAULT'; example: scaletype='PBCOR' Options: 'PBCOR','SAULT' 'SAULT' when interactive=True shows the residual with constant noise across the mosaic. If pbcor=False, the final output image is NOT corrected for the PB pattern, and therefore is not "flux correct". Division of SAULT <imagename>.image by the <imagename>.flux image will produce a "flux correct image", can also be acheived by setting pbcor=True. 'PBCOR' uses the SAULT scaling scheme for deconvolution, but if interactive=True shows the primary beam corrected image; the final PBCOR image is "flux correct" if pbcor=True. >>> imagermode='csclean' expandable parameter(s): Image using the Cotton-Schwab algorithm in between major cycles cyclefactor -- Change the threshold at which the deconvolution cycle will stop, degrid and subtract from the visibilities. For poor PSFs, reconcile often (cyclefactor=4 or 5); For good PSFs, use cyclefactor 1.5 to 2.0. Note: threshold = cyclefactor * max sidelobe * max residual. default: 1.5; example: cyclefactor=4 cyclespeedup -- Cycle threshold doubles in this number of iterations default: -1; example: cyclespeedup=3 try cyclespeedup = 50 to speed up cleaning multiscale -- set of scales to use in deconvolution. If set, cleans with several resolutions using hobgom clean. The scale sizes are in units of cellsize. So if cell='2arcsec', a multiscale scale=10 = 20arcsec. First scale should always be 0 (point), we suggest second on the order of synthesized beam, third 3-5 times synthesized beam, etc. For example if synthesized beam is 10" and cell=2", try multscale = [0,5,15]. Note, multiscale is currently a bit slow. default: multiscale= (standard CLEAN using psfmode algorithm, no multi-scale). Example: multiscale = [0,5,15] >>> multiscale expandable parameter(s): negcomponent -- Stop component search when the largest scale has found this number of negative components; -1 means continue component search even if the largest component is negative. default: -1; example: negcomponent=50 smallscalebias -- A bias toward smaller scales. The peak flux found at each scale is weighted by a factor = 1 - smallscalebias*scale/max_scale, so that Fw = F*factor. Typically the values range from 0.2 to 1.0. default: 0.6 imsize -- Image pixel size (x,y). DOES NOT HAVE TO BE A POWER OF 2 default = [256,256]; example: imsize=[350,350] imsize = 500 is equivalent to [500,500] If include outlier fields, e.g., [[400,400],[100,100]] or use outlierfile. Avoid odd-numbered imsize. cell -- Cell size (x,y) default= '1.0arcsec'; example: cell=['0.5arcsec,'0.5arcsec'] or cell=['1arcmin', '1arcmin'] cell = '1arcsec' is equivalent to ['1arcsec','1arcsec'] NOTE:cell = 2.0 => ['2arcsec', '2arcsec'] phasecenter -- direction measure or fieldid for the mosaic center default: '' => first field selected ; example: phasecenter=6 or phasecenter='J2000 19h30m00 -40d00m00' If include outlier fields, e.g. ['J2000 19h30m00 -40d00m00',J2000 19h25m00 -38d40m00'] or use outlierfile. restfreq -- Specify rest frequency to use for output image default='' Occasionally it is necessary to set this (for example some VLA spectral line data). For example for NH_3 (1,1) put restfreq='23.694496GHz' stokes -- Stokes parameters to image default='I'; example: stokes='IQUV'; Options: 'I','IV''QU','IQUV','RR','LL','XX','YY','RRLL','XXYY' niter -- Maximum number iterations, if niter=0, then no CLEANing is done ("invert" only) default: 500; example: niter=5000 gain -- Loop gain for CLEANing default: 0.1; example: gain=0.5 threshold -- Flux level at which to stop CLEANing default: '0.0mJy'; example: threshold='2.3mJy' (always include units) threshold = '0.0023Jy' threshold = '0.0023Jy/beam' (okay also) interactive -- use interactive clean (with GUI viewer) default: interactive=False example: interactive=True interactive clean allows the user to build the cleaning mask interactively using the viewer. The viewer will appear every npercycle interation, but modify as needed The final interactive mask is saved in the file imagename_interactive.mask. The initial masks use the union of mask and cleanbox (see below). >>> interactive=True expandable parameters npercycle -- this is the number of iterations between each clean to update mask interactively. It is important to modify this number interactively during the cleaning, starting wiht a low number like 20, but then increasing as more extended emission is encountered. chaniter -- specify how interactive CLEAN is performed, either by stepping through channels or do jointly for all channel default: chaniter='joint'; example: chaniter='channel'; step through channels mask -- Specification of cleanbox(es), mask image(s), and/or region(s) to be used for CLEANing. As long as the image has the same shape (size), mask images from a previous interactive session can be used for a new execution. NOTE: the initial clean mask actually used is the union of what is specified in mask and <imagename>.mask default:  (no masking); Possible specification types: (a) Explicit cleanbox pixel ranges example: mask=[110,110,150,145] clean region with blc=110,100; trc=150,145 (pixel values) (b) Filename with cleanbox pixel values with ascii format: example: mask='mycleanbox.txt' <fieldid blc-x blc-y trc-x trc-y> on each line 1 45 66 123 124 2 23 100 300 340 (c) Filename for image mask example: mask='myimage.mask' (d) Filename for region specification (e.g. from viewer) example: mask='myregion.rgn' (e) Combinations of any of the above example: mask=[[110,110,150,145],'mycleanbox.txt', 'myimage.mask','myregion.rgn'] If include outlier fields, then mask need to be specified in nested lists: e.g. mask=[[[110,110,150,145],'myimage.mask'],,[20,20,40,40]] (A clean box with [110,110,150,145] and a image mask for main field, no mask for 1st outlier field, 1 clean box for second outlier field.) uvtaper -- Apply additional uv tapering of the visibilities. default: uvtaper=False; example: uvtaper=True >>> uvtaper=True expandable parameters outertaper -- uv-taper on outer baselines in uv-plane [bmaj, bmin, bpa] taper Gaussian scale in uv or angular units. NOTE: uv taper in (klambda) is roughly on-sky FWHM(arcsec/200) default: outertaper=; no outer taper applied example: outertaper=['5klambda'] circular taper FWHM=5 kilo-lambda outertaper=['5klambda','3klambda','45.0deg'] outertaper=['10arcsec'] on-sky FWHM 10" outertaper=['300.0'] default units are meters in aperture plane innertaper -- uv-taper in center of uv-plane [bmaj,bmin,bpa] Gaussian scale at which taper falls to zero at uv=0 default: innertaper=; no inner taper applied NOT YET IMPLEMENTED modelimage -- Name of model image(s) to initialize cleaning. If multiple images, then these will be added together to form initial staring model NOTE: these are in addition to any initial model in the <imagename>.model image file default: '' (none); example: modelimage='orion.model' modelimage=['orion.model','sdorion.image'] Note: if the units in the image are Jy/beam as in a single-dish image, then it will be converted to Jy/pixel as in a model image, using the restoring beam in the image header weighting -- Weighting to apply to visibilities: default='natural'; example: weighting='uniform'; Options: 'natural','uniform','briggs', 'superuniform','briggsabs','radial' >>> Weighting expandable parameters For weighting='briggs' and 'briggsabs' robust -- Brigg's robustness parameter default=0.0; example: robust=0.5; Options: -2.0 to 2.0; -2 (uniform)/+2 (natural) For weighting='briggsabs' noise -- noise parameter to use for Briggs "abs" weighting example noise='1.0mJy' npixels -- uv-cell area used for weight calculation example npixels=1 Default = 0 superuniform: 0 Means 3x3 cells for weighting the cell weight is proportional to the weight of the 3x3 cells centered on it. superuniform = F means 1x1 cell for averaging weights. briggs/briggsabs: 0 is similar to 1x1 cell weight. 1 may? be similar to 3X3 cells. Only npixels 0 or 1 recommended restoringbeam -- Output Gaussian restoring beam for CLEAN image [bmaj, bmin, bpa] elliptical Gaussian restoring beam default units are in arc-seconds for bmaj,bmin, degrees for bpa default: restoringbeam=; Use PSF calculated from dirty beam. example: restoringbeam=['10arcsec'] circular Gaussian FWHM 10" example: restoringbeam=['10.0','5.0','45.0deg'] 10"x5" at 45 degrees pbcor -- Output primary beam-corrected image default: pbcor=False; output un-corrected image example: pbcor=True; output pb-corrected image (masked outside minpb) Note: if you set pbcor=False, you can later recover the pbcor image by dividing by the .flux image (e.g. using immath) minpb -- Minimum PB level to use default=0.1; The flux image is used to determine this except for the case of mosaic with ft='mosaic' where the flux.pbcoverage image is used. example: minpb=0.01 Note: this minpb is always in effect (regardless of pbcor=True/False) calready -- if True will create scratch columns if they are not there. And after clean completes the predicted model visibility is from the clean components are written to the ms. async -- Run asynchronously default = False; do not run asychronously ====================================================================== HINTS ON CLEAN WITH FLANKING FIELDS 1. Decide if the images will be specified directly in the inputs or with an outlier file. For more than a few fields, an outlier file more convenient. Direct Method: cell = ['1.0arcsec', '1.0arcsec'] imagename = ['M1_0','M1_1','M1_2] imsize = [[1024,1024],[128,128],[128,128]] phasecenter = ['J2000 13h27m20.98 43d26m28.0', 'J2000 13h30m52.159 43d23m08.02', 'J2000 13h24m08.16 43d09m48.0'] Text file method (in outlier.txt) imagename = 'M1' outlierfile = 'outlier.txt' [phasecenter, imsize ignored] Contents of outlier.txt C 0 1024 1024 13 27 20.98 43 26 28.0 C 1 128 128 13 30 52.158 43 23 08.00 C 2 128 128 13 24 08.163 43 09 48.00 In both cases the following images will be made: M1_0.image, M1_1.image, M1_2.image cleaned images M1.0.model, M1_1.model, M1_2.model model images M1.0.residual, M1_1.residual, M1_2.residual residual images an outlier file more convenient. Direct Method: cell = ['1.0arcsec', '1.0arcsec'] imagename = ['M1_0','M1_1','M1_2] imsize = [[1024,1024],[128,128],[128,128]] phasecenter = ['J2000 13h27m20.98 43d26m28.0', 'J2000 13h30m52.159 43d23m08.02', 'J2000 13h24m08.16 43d09m48.0'] Text file method (in outlier.txt) imagename = 'M1' outlierfile = 'outlier.txt' [phasecenter, imsize ignored] Contents of outlier.txt C 0 1024 1024 13 27 20.98 43 26 28.0 C 1 128 128 13 30 52.158 43 23 08.00 C 2 128 128 13 24 08.163 43 09 48.00 In both cases the following images will be made: M1_0.image, M1_1.image, M1_2.image cleaned images M1.0.model, M1_1.model, M1_2.model model images M1.0.residual, M1_1.residual, M1_2.residual residual images 2. Masks for flanking fields are specified in same way as in the single output field case, but need extra '[ ]' to distinguish each field. mask=[['myregion.rg',[100,100,150,150]],['myimage1.mask'],] would apply masks: for the first field (main field), myregion.rg and a box defined by [100,100,150,150] in pixels for the seconf field (first outlier), myimage1.mask for the third field (second outlier), no mask (produce a mask for whole field) However, if boxfiles are given, ids in the first column of the files are used to match with fields (using order given imagename or outlierfile. So, if the content of a boxfile looks like this, 0 45 66 123 124 1 23 100 300 340 2 20 20 40 40 then [45 66 123 124] is assigned to first field (imagename, or first line of outlierfile).