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1##################### generated by xml-casa (v2) from sdintimaging.xml ##############
2##################### ca888a2f22e7dfabc903d68b3be18731 ##############################
3from __future__ import absolute_import
4import numpy
5from casatools.typecheck import CasaValidator as _val_ctor
6_pc = _val_ctor( )
7from casatools.coercetype import coerce as _coerce
8from casatools.errors import create_error_string
9from .private.task_sdintimaging import sdintimaging as _sdintimaging_t
10from casatasks.private.task_logging import start_log as _start_log
11from casatasks.private.task_logging import end_log as _end_log
12from casatasks.private.task_logging import except_log as _except_log
14class _sdintimaging:
15 """
16 sdintimaging ----
18 Form images from interferometric visibilities and single dish image
19 to reconstruct a sky model by joint deconvolution.
22 --------- parameter descriptions ---------------------------------------------
24 usedata Output image type: 'int' - use interferometric data only;
25 'sd' - use single dish data only;
26 'sdint' - use both single dish and interferometric data (only Stokes I)
27 sdimage Input single dish image
28 This single dish Image cube must contain images per frequency channel (blanked for empty
29 or flagged channels).
31 If the associated sdpsf parameter is set to an empty string to signal an automatic
32 calculation of the SD PSF cube, this SD image cube must contain per-plane
33 restoringbeams that represent the effect SDbeam per frequency.
34 sdpsf Input single dish PSF image.
36 This single dish PSF cube must contain the effective SD beam in the center of the image,
37 for each frequency channel, normalized to peak 1. The coordinate system should ideally
38 be the same as the SD image cube and contain per-plane restoringbeams that represent the
39 effect SD beam per frequency.
41 If the sdpsf is set to a blank string (sdpsf="") an approximate PSF cube will be automatically
42 calculated internally by using per-plane restoring-beam information from the regridded sdimage
43 to evaluate 2D Gaussians.
45 In the future, we will provide an option to auto-generate Airy disk beams derived from
46 the specified dish diameter.
47 sdgain A factor or gain to adjust single dish flux scale (to use in feather stage)
48 dishdia Effective dish diameter of the SD telescope (meters)
49 vis Name(s) of input visibility file(s)
50 default: none;
51 example: vis='ngc5921.ms'
52 vis=['ngc5921a.ms','ngc5921b.ms']; multiple MSes
53 selectdata Enable data selection parameters.
54 field to image or mosaic. Use field id(s) or name(s).
55 ['go listobs' to obtain the list id's or names]
56 default: ''= all fields
57 If field string is a non-negative integer, it is assumed to
58 be a field index otherwise, it is assumed to be a
59 field name
60 field='0~2'; field ids 0,1,2
61 field='0,4,5~7'; field ids 0,4,5,6,7
62 field='3C286,3C295'; field named 3C286 and 3C295
63 field = '3,4C\*'; field id 3, all names starting with 4C
64 For multiple MS input, a list of field strings can be used:
65 field = ['0~2','0~4']; field ids 0-2 for the first MS and 0-4
66 for the second
67 field = '0~2'; field ids 0-2 for all input MSes
68 spw l window/channels
69 NOTE: channels de-selected here will contain all zeros if
70 selected by the parameter mode subparameters.
71 default: ''=all spectral windows and channels
72 spw='0~2,4'; spectral windows 0,1,2,4 (all channels)
73 spw='0:5~61'; spw 0, channels 5 to 61
74 spw='<2'; spectral windows less than 2 (i.e. 0,1)
75 spw='0,10,3:3~45'; spw 0,10 all channels, spw 3,
76 channels 3 to 45.
77 spw='0~2:2~6'; spw 0,1,2 with channels 2 through 6 in each.
78 For multiple MS input, a list of spw strings can be used:
79 spw=['0','0~3']; spw ids 0 for the first MS and 0-3 for the second
80 spw='0~3' spw ids 0-3 for all input MS
81 spw='3:10~20;50~60' for multiple channel ranges within spw id 3
82 spw='3:10~20;50~60,4:0~30' for different channel ranges for spw ids 3 and 4
83 spw='0:0~10,1:20~30,2:1;2;3'; spw 0, channels 0-10,
84 spw 1, channels 20-30, and spw 2, channels, 1,2 and 3
85 spw='1~4;6:15~48' for channels 15 through 48 for spw ids 1,2,3,4 and 6
86 timerange Range of time to select from data
88 default: '' (all); examples,
89 timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
90 Note: if YYYY/MM/DD is missing date defaults to first
91 day in data set
92 timerange='09:14:0~09:54:0' picks 40 min on first day
93 timerange='25:00:00~27:30:00' picks 1 hr to 3 hr
94 30min on NEXT day
95 timerange='09:44:00' pick data within one integration
96 of time
97 timerange='> 10:24:00' data after this time
98 For multiple MS input, a list of timerange strings can be
99 used:
100 timerange=['09:14:0~09:54:0','> 10:24:00']
101 timerange='09:14:0~09:54:0''; apply the same timerange for
102 all input MSes
103 uvrange Select data within uvrange (default unit is meters)
104 default: '' (all); example:
105 uvrange='0~1000klambda'; uvrange from 0-1000 kilo-lambda
106 uvrange='> 4klambda';uvranges greater than 4 kilo lambda
107 For multiple MS input, a list of uvrange strings can be
108 used:
109 uvrange=['0~1000klambda','100~1000klamda']
110 uvrange='0~1000klambda'; apply 0-1000 kilo-lambda for all
111 input MSes
112 antenna Select data based on antenna/baseline
114 default: '' (all)
115 If antenna string is a non-negative integer, it is
116 assumed to be an antenna index, otherwise, it is
117 considered an antenna name.
118 antenna='5\&6'; baseline between antenna index 5 and
119 index 6.
120 antenna='VA05\&VA06'; baseline between VLA antenna 5
121 and 6.
122 antenna='5\&6;7\&8'; baselines 5-6 and 7-8
123 antenna='5'; all baselines with antenna index 5
124 antenna='05'; all baselines with antenna number 05
125 (VLA old name)
126 antenna='5,6,9'; all baselines with antennas 5,6,9
127 index number
128 For multiple MS input, a list of antenna strings can be
129 used:
130 antenna=['5','5\&6'];
131 antenna='5'; antenna index 5 for all input MSes
132 antenna='!DV14'; use all antennas except DV14
133 scan Scan number range
135 default: '' (all)
136 example: scan='1~5'
137 For multiple MS input, a list of scan strings can be used:
138 scan=['0~100','10~200']
139 scan='0~100; scan ids 0-100 for all input MSes
140 observation Observation ID range
141 default: '' (all)
142 example: observation='1~5'
143 intent Scan Intent(s)
145 default: '' (all)
146 example: intent='TARGET_SOURCE'
147 example: intent='TARGET_SOURCE1,TARGET_SOURCE2'
148 example: intent='TARGET_POINTING\*'
149 datacolumn Data column to image (data or observed, corrected)
150 default:'corrected'
151 ( If 'corrected' does not exist, it will use 'data' instead )
152 imagename Pre-name of output images
154 example : imagename='try'
156 Output images will be (a subset of) :
158 try.psf - Point spread function
159 try.residual - Residual image
160 try.image - Restored image
161 try.model - Model image (contains only flux components)
162 try.sumwt - Single pixel image containing sum-of-weights.
163 (for natural weighting, sensitivity=1/sqrt(sumwt))
164 try.pb - Primary beam model (values depend on the gridder used)
166 Widefield projection algorithms (gridder=mosaic,awproject) will
167 compute the following images too.
168 try.weight - FT of gridded weights or the
169 un-normalized sum of PB-square (for all pointings)
170 Here, PB = sqrt(weight) normalized to a maximum of 1.0
172 For multi-term wideband imaging, all relevant images above will
173 have additional .tt0,.tt1, etc suffixes to indicate Taylor terms,
174 plus the following extra output images.
175 try.alpha - spectral index
176 try.alpha.error - estimate of error on spectral index
177 try.beta - spectral curvature (if nterms \> 2)
179 Tip : Include a directory name in 'imagename' for all
180 output images to be sent there instead of the
181 current working directory : imagename='mydir/try'
183 Tip : Restarting an imaging run without changing 'imagename'
184 implies continuation from the existing model image on disk.
185 - If 'startmodel' was initially specified it needs to be set to ""
186 for the restart run (or sdintimaging will exit with an error message).
187 - By default, the residual image and psf will be recomputed
188 but if no changes were made to relevant parameters between
189 the runs, set calcres=False, calcpsf=False to resume directly from
190 the minor cycle without the (unnecessary) first major cycle.
191 To automatically change 'imagename' with a numerical
192 increment, set restart=False (see sdintimaging docs for 'restart').
194 Note : All imaging runs will by default produce restored images.
195 For a niter=0 run, this will be redundant and can optionally
196 be turned off via the 'restoration=T/F' parameter.
197 imsize Number of pixels
198 example:
200 imsize = [350,250]
201 imsize = 500 is equivalent to [500,500]
203 To take proper advantage of internal optimized FFT routines, the
204 number of pixels must be even and factorizable by 2,3,5 only.
205 To find the nearest optimal imsize to that desired by the user, please use the following tool method:
207 from casatools import synthesisutils
208 su = synthesisutils()
209 su.getOptimumSize(345)
210 Output : 360
211 cell Cell size
212 example: cell=['0.5arcsec,'0.5arcsec'] or
213 cell=['1arcmin', '1arcmin']
214 cell = '1arcsec' is equivalent to ['1arcsec','1arcsec']
215 phasecenter Phase center of the image (string or field id); if the phasecenter is the name known major solar system object ('MERCURY', 'VENUS', 'MARS', 'JUPITER', 'SATURN', 'URANUS', 'NEPTUNE', 'PLUTO', 'SUN', 'MOON') or is an ephemerides table then that source is tracked and the background sources get smeared. There is a special case, when phasecenter='TRACKFIELD', which will use the ephemerides or polynomial phasecenter in the FIELD table of the MS's as the source center to track.
216 example: phasecenter=6
217 phasecenter='J2000 19h30m00 -40d00m00'
218 phasecenter='J2000 292.5deg -40.0deg'
219 phasecenter='J2000 5.105rad -0.698rad'
220 phasecenter='ICRS 13:05:27.2780 -049.28.04.458'
221 phasecenter='myComet_ephem.tab'
222 phasecenter='MOON'
223 phasecenter='TRACKFIELD'
224 stokes Stokes Planes to make
225 default='I'; example: stokes='IQUV';
226 Options: 'I','Q','U','V','IV','QU','IQ','UV','IQUV','RR','LL','XX','YY','RRLL','XXYY','pseudoI'
228 Note: for parameter usedata='sdint', presently only stokes='I' is supported.
230 Note : Due to current internal code constraints, if any correlation pair
231 is flagged, by default, no data for that row in the MS will be used.
232 So, in an MS with XX,YY, if only YY is flagged, neither a
233 Stokes I image nor an XX image can be made from those data points.
234 In such a situation, please split out only the unflagged correlation into
235 a separate MS.
237 Note : The 'pseudoI' option is a partial solution, allowing Stokes I imaging
238 when either of the parallel-hand correlations are unflagged.
240 The remaining constraints shall be removed (where logical) in a future release.
241 projection Coordinate projection
242 Examples : SIN, NCP
243 A list of supported (but untested) projections can be found here :
244 http://casa.nrao.edu/active/docs/doxygen/html/classcasa_1_1Projection.html#a3d5f9ec787e4eabdce57ab5edaf7c0cd
245 startmodel Name of starting model image
247 The contents of the supplied starting model image will be
248 copied to the imagename.model before the run begins.
250 example : startmodel = 'singledish.im'
252 For deconvolver='mtmfs', one image per Taylor term must be provided.
253 example : startmodel = ['try.model.tt0', 'try.model.tt1']
254 startmodel = ['try.model.tt0'] will use a starting model only
255 for the zeroth order term.
256 startmodel = ['','try.model.tt1'] will use a starting model only
257 for the first order term.
259 This starting model can be of a different image shape and size from
260 what is currently being imaged. If so, an image regrid is first triggered
261 to resample the input image onto the target coordinate system.
263 A common usage is to set this parameter equal to a single dish image
265 Negative components in the model image will be included as is.
267 [ Note : If an error occurs during image resampling/regridding,
268 please try using task imregrid to resample the starting model
269 image onto a CASA image with the target shape and
270 coordinate system before supplying it via startmodel ]
271 specmode Spectral definition mode (mfs,cube,cubedata, cubesource)
273 mode='mfs' : Continuum imaging with only one output image channel.
274 (mode='cont' can also be used here)
276 mode='cube' : Spectral line imaging with one or more channels
277 Parameters start, width,and nchan define the spectral
278 coordinate system and can be specified either in terms
279 of channel numbers, frequency or velocity in whatever
280 spectral frame is specified in 'outframe'.
281 All internal and output images are made with outframe as the
282 base spectral frame. However imaging code internally uses the fixed
283 spectral frame, LSRK for automatic internal software
284 Doppler tracking so that a spectral line observed over an
285 extended time range will line up appropriately.
286 Therefore the output images have additional spectral frame conversion
287 layer in LSRK on the top the base frame.
290 (Note : Even if the input parameters are specified in a frame
291 other than LSRK, the viewer still displays spectral
292 axis in LSRK by default because of the conversion frame
293 layer mentioned above. The viewer can be used to relabel
294 the spectral axis in any desired frame - via the spectral
295 reference option under axis label properties in the
296 data display options window.)
301 mode='cubedata' : Spectral line imaging with one or more channels
302 There is no internal software Doppler tracking so
303 a spectral line observed over an extended time range
304 may be smeared out in frequency. There is strictly
305 no valid spectral frame with which to label the output
306 images, but they will list the frame defined in the MS.
308 mode='cubesource': Spectral line imaging while
309 tracking moving source (near field or solar system
310 objects). The velocity of the source is accounted
311 and the frequency reported is in the source frame.
312 As there is not SOURCE frame defined,
313 the frame reported will be REST (as it may not be
314 in the rest frame emission region may be
315 moving w.r.t the systemic velocity frame)
316 reffreq Reference frequency of the output image coordinate system
318 Example : reffreq='1.5GHz' as a string with units.
320 By default, it is calculated as the middle of the selected frequency range.
322 For deconvolver='mtmfs' the Taylor expansion is also done about
323 this specified reference frequency.
324 nchan Number of channels in the output image
325 For default (=-1), the number of channels will be automatically determined
326 based on data selected by 'spw' with 'start' and 'width'.
327 It is often easiest to leave nchan at the default value.
328 example: nchan=100
329 start First channel (e.g. start=3,start=\'1.1GHz\',start=\'15343km/s\')
330 of output cube images specified by data channel number (integer),
331 velocity (string with a unit), or frequency (string with a unit).
332 Default:''; The first channel is automatically determined based on
333 the 'spw' channel selection and 'width'.
334 When the channel number is used along with the channel selection
335 in 'spw' (e.g. spw='0:6~100'),
336 'start' channel number is RELATIVE (zero-based) to the selected
337 channels in 'spw'. So for the above example,
338 start=1 means that the first image channel is the second selected
339 data channel, which is channel 7.
340 For specmode='cube', when velocity or frequency is used it is
341 interpreted with the frame defined in outframe. [The parameters of
342 the desired output cube can be estimated by using the 'transform'
343 functionality of 'plotms']
344 examples: start='5.0km/s'; 1st channel, 5.0km/s in outframe
345 start='22.3GHz'; 1st channel, 22.3GHz in outframe
346 width Channel width (e.g. width=2,width=\'0.1MHz\',width=\'10km/s\') of output cube images
347 specified by data channel number (integer), velocity (string with a unit), or
348 or frequency (string with a unit).
349 Default:''; data channel width
350 The sign of width defines the direction of the channels to be incremented.
351 For width specified in velocity or frequency with '-' in front gives image channels in
352 decreasing velocity or frequency, respectively.
353 For specmode='cube', when velocity or frequency is used it is interpreted with
354 the reference frame defined in outframe.
355 examples: width='2.0km/s'; results in channels with increasing velocity
356 width='-2.0km/s'; results in channels with decreasing velocity
357 width='40kHz'; results in channels with increasing frequency
358 width=-2; results in channels averaged of 2 data channels incremented from
359 high to low channel numbers
360 outframe Spectral reference frame in which to interpret \'start\' and \'width\'
361 Options: '','LSRK','LSRD','BARY','GEO','TOPO','GALACTO','LGROUP','CMB'
362 example: outframe='bary' for Barycentric frame
364 REST -- Rest frequency
365 LSRD -- Local Standard of Rest (J2000)
366 -- as the dynamical definition (IAU, [9,12,7] km/s in galactic coordinates)
367 LSRK -- LSR as a kinematical (radio) definition
368 -- 20.0 km/s in direction ra,dec = [270,+30] deg (B1900.0)
369 BARY -- Barycentric (J2000)
370 GEO --- Geocentric
371 TOPO -- Topocentric
372 GALACTO -- Galacto centric (with rotation of 220 km/s in direction l,b = [90,0] deg.
373 LGROUP -- Local group velocity -- 308km/s towards l,b = [105,-7] deg (F. Ghigo)
374 CMB -- CMB velocity -- 369.5km/s towards l,b = [264.4, 48.4] deg (F. Ghigo)
375 DEFAULT = LSRK
376 veltype Velocity type (radio, z, ratio, beta, gamma, optical)
377 For start and/or width specified in velocity, specifies the velocity definition
378 Options: 'radio','optical','z','beta','gamma','optical'
379 NOTE: the viewer always defaults to displaying the 'radio' frame,
380 but that can be changed in the position tracking pull down.
382 The different types (with F = f/f0, the frequency ratio), are:
384 Z = (-1 + 1/F)
385 RATIO = (F) \*
386 RADIO = (1 - F)
387 OPTICAL == Z
388 BETA = ((1 - F2)/(1 + F2))
389 GAMMA = ((1 + F2)/2F) \*
390 RELATIVISTIC == BETA (== v/c)
391 DEFAULT == RADIO
392 Note that the ones with an '\*' have no real interpretation
393 (although the calculation will proceed) if given as a velocity.
394 restfreq List of rest frequencies or a rest frequency in a string.
395 Specify rest frequency to use for output image.
396 Currently it uses the first rest frequency in the list for translation of
397 velocities. The list will be stored in the output images.
398 Default: []; look for the rest frequency stored in the MS, if not available,
399 use center frequency of the selected channels
400 examples: restfreq=['1.42GHz']
401 restfreq='1.42GHz'
402 interpolation Spectral interpolation (nearest,linear,cubic)
404 Interpolation rules to use when binning data channels onto image channels
405 and evaluating visibility values at the centers of image channels.
407 Note : 'linear' and 'cubic' interpolation requires data points on both sides of
408 each image frequency. Errors are therefore possible at edge channels, or near
409 flagged data channels. When image channel width is much larger than the data
410 channel width there is nothing much to be gained using linear or cubic thus
411 not worth the extra computation involved.
412 perchanweightdensity When calculating weight density for Briggs
413 style weighting in a cube, this parameter
414 determines whether to calculate the weight
415 density for each channel independently
416 (the default, True)
417 or a common weight density for all of the selected
418 data. This parameter has no
419 meaning for continuum (specmode='mfs')
420 imaging but for cube imaging
421 perchanweightdensity=True is a recommended
422 option that provides more uniform
423 sensitivity per channel for cubes, but with
424 generally larger psfs than the
425 perchanweightdensity=False (prior behavior)
426 option. When using Briggs style weight with
427 perchanweightdensity=True, the imaging weight
428 density calculations use only the weights of
429 data that contribute specifically to that
430 channel. On the other hand, when
431 perchanweightdensity=False, the imaging
432 weight density calculations sum all of the
433 weights from all of the data channels
434 selected whose (u,v) falls in a given uv cell
435 on the weight density grid. Since the
436 aggregated weights, in any given uv cell,
437 will change depending on the number of
438 channels included when imaging, the psf
439 calculated for a given frequency channel will
440 also necessarily change, resulting in
441 variability in the psf for a given frequency
442 channel when perchanweightdensity=False. In
443 general, perchanweightdensity=False results
444 in smaller psfs for the same value of
445 robustness compared to
446 perchanweightdensity=True, but the rms noise
447 as a function of channel varies and increases
448 toward the edge channels;
449 perchanweightdensity=True provides more
450 uniform sensitivity per channel for
451 cubes. This may make it harder to find
452 estimates of continuum when
453 perchanweightdensity=False. If you intend to
454 image a large cube in many smaller subcubes
455 and subsequently concatenate, it is advisable
456 to use perchanweightdensity=True to avoid
457 surprisingly varying sensitivity and psfs
458 across the concatenated cube.
459 gridder Gridding options (standard, wproject, widefield, mosaic, awproject)
461 The following options choose different gridding convolution
462 functions for the process of convolutional resampling of the measured
463 visibilities onto a regular uv-grid prior to an inverse FFT.
464 Model prediction (degridding) also uses these same functions.
465 Several wide-field effects can be accounted for via careful choices of
466 convolution functions. Gridding (degridding) runtime will rise in
467 proportion to the support size of these convolution functions (in uv-pixels).
469 standard : Prolate Spheroid with 3x3 uv pixel support size
471 [ This mode can also be invoked using 'ft' or 'gridft' ]
473 wproject : W-Projection algorithm to correct for the widefield
474 non-coplanar baseline effect. [Cornwell et.al 2008]
476 wprojplanes is the number of distinct w-values at
477 which to compute and use different gridding convolution
478 functions (see help for wprojplanes).
479 Convolution function support size can range
480 from 5x5 to few 100 x few 100.
482 [ This mode can also be invoked using 'wprojectft' ]
484 widefield : Facetted imaging with or without W-Projection per facet.
486 A set of facets x facets subregions of the specified image
487 are gridded separately using their respective phase centers
488 (to minimize max W). Deconvolution is done on the joint
489 full size image, using a PSF from the first subregion.
491 wprojplanes=1 : standard prolate spheroid gridder per facet.
492 wprojplanes > 1 : W-Projection gridder per facet.
493 nfacets=1, wprojplanes > 1 : Pure W-Projection and no facetting
494 nfacets=1, wprojplanes=1 : Same as standard,ft,gridft
496 A combination of facetting and W-Projection is relevant only for
497 very large fields of view.
499 mosaic : A-Projection with azimuthally symmetric beams without
500 sidelobes, beam rotation or squint correction.
501 Gridding convolution functions per visibility are computed
502 from FTs of PB models per antenna.
503 This gridder can be run on single fields as well as mosaics.
505 VLA : PB polynomial fit model (Napier and Rots, 1982)
506 EVLA : PB polynomial fit model (Perley, 2015)
507 ALMA : Airy disks for a 10.7m dish (for 12m dishes) and
508 6.25m dish (for 7m dishes) each with 0.75m
509 blockages (Hunter/Brogan 2011). Joint mosaic
510 imaging supports heterogeneous arrays for ALMA.
512 Typical gridding convolution function support sizes are
513 between 7 and 50 depending on the desired
514 accuracy (given by the uv cell size or image field of view).
516 [ This mode can also be invoked using 'mosaicft' or 'ftmosaic' ]
518 awproject : A-Projection with azimuthally asymmetric beams and
519 including beam rotation, squint correction,
520 conjugate frequency beams and W-projection.
521 [Bhatnagar et.al, 2008]
523 Gridding convolution functions are computed from
524 aperture illumination models per antenna and optionally
525 combined with W-Projection kernels and a prolate spheroid.
526 This gridder can be run on single fields as well as mosaics.
528 The awproject gridder is current not supported in the sdintimaging task.
529 This feature will be added in the near future.
531 VLA : Uses ray traced model (VLA and EVLA) including feed
532 leg and subreflector shadows, off-axis feed location
533 (for beam squint and other polarization effects), and
534 a Gaussian fit for the feed beams (Ref: Brisken 2009)
535 ALMA : Similar ray-traced model as above (but the correctness
536 of its polarization properties remains un-verified).
538 Typical gridding convolution function support sizes are
539 between 7 and 50 depending on the desired
540 accuracy (given by the uv cell size or image field of view).
541 When combined with W-Projection they can be significantly larger.
543 [ This mode can also be invoked using 'awprojectft' ]
545 imagemosaic : (untested implementation)
546 Grid and iFT each pointing separately and combine the
547 images as a linear mosaic (weighted by a PB model) in
548 the image domain before a joint minor cycle.
550 VLA/ALMA PB models are same as for gridder='mosaicft'
552 ------ Notes on PB models :
554 (1) Several different sources of PB models are used in the modes
555 listed above. This is partly for reasons of algorithmic flexibility
556 and partly due to the current lack of a common beam model
557 repository or consensus on what beam models are most appropriate.
559 (2) For ALMA and gridder='mosaic', ray-traced (TICRA) beams
560 are also available via the vpmanager tool.
561 For example, call the following before the sdintimaging run.
562 vp.setpbimage(telescope="ALMA",
563 compleximage='/home/casa/data/trunk/alma/responses/ALMA_0_DV__0_0_360_0_45_90_348.5_373_373_GHz_ticra2007_VP.im',
564 antnames=['DV'+'%02d'%k for k in range(25)])
565 vp.saveastable('mypb.tab')
566 Then, supply vptable='mypb.tab' to sdintimaging.
569 ------ Note on PB masks :
571 In sdintimaging, A-Projection gridders (mosaic and awproject) produce a
572 .pb image and use the 'pblimit' subparameter to decide normalization
573 cutoffs and construct an internal T/F mask in the .pb and .image images.
574 However, this T/F mask cannot directly be used during deconvolution
575 (which needs a 1/0 mask). There are two options for making a pb based
576 deconvolution mask.
577 -- Run sdintimaging with niter=0 to produce the .pb, construct a 1/0 image
578 with the desired threshold (using ia.open('newmask.im');
579 ia.calc('iif("xxx.pb">0.3,1.0,0.0)');ia.close() for example),
580 and supply it via the 'mask' parameter in a subsequent run
581 (with calcres=F and calcpsf=F to restart directly from the minor cycle).
582 -- Run sdintimaging with usemask='pb' for it to automatically construct
583 a 1/0 mask from the internal T/F mask from .pb at a fixed 0.2 threshold.
585 ----- Making PBs for gridders other than mosaic,awproject
587 After the PSF generation, a PB is constructed using the same
588 models used in gridder='mosaic' but just evaluated in the image
589 domain without consideration to weights.
590 facets Number of facets on a side
592 A set of (facets x facets) subregions of the specified image
593 are gridded separately using their respective phase centers
594 (to minimize max W). Deconvolution is done on the joint
595 full size image, using a PSF from the first subregion/facet.
596 psfphasecenter For mosaic use psf centered on this
597 optional direction. You may need to use
598 this if for example the mosaic does not
599 have any pointing in the center of the
600 image. Another reason; as the psf is
601 approximate for a mosaic, this may help
602 to deconvolve a non central bright source
603 well and quickly.
605 example:
607 psfphasecenter=6 #center psf on field 6
608 psfphasecenter='J2000 19h30m00 -40d00m00'
609 psfphasecenter='J2000 292.5deg -40.0deg'
610 psfphasecenter='J2000 5.105rad -0.698rad'
611 psfphasecenter='ICRS 13:05:27.2780 -049.28.04.458'
612 wprojplanes Number of distinct w-values at which to compute and use different
613 gridding convolution functions for W-Projection
615 An appropriate value of wprojplanes depends on the presence/absence
616 of a bright source far from the phase center, the desired dynamic
617 range of an image in the presence of a bright far out source,
618 the maximum w-value in the measurements, and the desired trade off
619 between accuracy and computing cost.
621 As a (rough) guide, VLA L-Band D-config may require a
622 value of 128 for a source 30arcmin away from the phase
623 center. A-config may require 1024 or more. To converge to an
624 appropriate value, try starting with 128 and then increasing
625 it if artifacts persist. W-term artifacts (for the VLA) typically look
626 like arc-shaped smears in a synthesis image or a shift in source
627 position between images made at different times. These artifacts
628 are more pronounced the further the source is from the phase center.
630 There is no harm in simply always choosing a large value (say, 1024)
631 but there will be a significant performance cost to doing so, especially
632 for gridder='awproject' where it is combined with A-Projection.
634 wprojplanes=-1 is an option for gridder='widefield' or 'wproject'
635 in which the number of planes is automatically computed.
636 vptable vpmanager
638 vptable="" : Choose default beams for different telescopes
639 ALMA : Airy disks
640 EVLA : old VLA models.
642 Other primary beam models can be chosen via the vpmanager tool.
644 Step 1 : Set up the vpmanager tool and save its state in a table
646 vp.setpbpoly(telescope='EVLA', coeff=[1.0, -1.529e-3, 8.69e-7, -1.88e-10])
647 vp.saveastable('myvp.tab')
649 Step 2 : Supply the name of that table in sdintimaging.
651 sdintimaging(....., vptable='myvp.tab',....)
653 Please see the documentation for the vpmanager for more details on how to
654 choose different beam models. Work is in progress to update the defaults
655 for EVLA and ALMA.
657 Note : AWProjection currently does not use this mechanism to choose
658 beam models. It instead uses ray-traced beams computed from
659 parameterized aperture illumination functions, which are not
660 available via the vpmanager. So, gridder='awproject' does not allow
661 the user to set this parameter.
662 mosweight When doing Brigg's style weighting (including uniform) to perform the weight density calculation for each field indepedently if True. If False the weight density is calculated from the average uv distribution of all the fields.
663 aterm Use aperture illumination functions during gridding
665 This parameter turns on the A-term of the AW-Projection gridder.
666 Gridding convolution functions are constructed from aperture illumination
667 function models of each antenna.
668 psterm Include the Prolate Spheroidal (PS) funtion as the anti-aliasing
669 operator in the gridding convolution functions used for gridding.
671 Setting this parameter to true is necessary when aterm is set to
672 false. It can be set to false when aterm is set to true, though
673 with this setting effects of aliasing may be there in the image,
674 particularly near the edges.
676 When set to true, the .pb images will contain the fourier transform
677 of the of the PS funtion. The table below enumarates the functional
678 effects of the psterm, aterm and wprojplanes settings. PB referes to
679 the Primary Beam and FT() refers to the Fourier transform operation.
681 Operation aterm psterm wprojplanes Contents of the .pb image
682 ----------------------------------------------------------------------
683 AW-Projection True True >1 FT(PS) x PB
684 False PB
686 A-Projection True True 1 FT(PS) x PB
687 False PB
689 W-Projection False True >1 FT(PS)
691 Standard False True 1 FT(PS)
692 wbawp Use frequency dependent A-terms
693 Scale aperture illumination functions appropriately with frequency
694 when gridding and combining data from multiple channels.
695 cfcache Convolution function cache directory name
697 Name of a directory in which to store gridding convolution functions.
698 This cache is filled at the beginning of an imaging run. This step can be time
699 consuming but the cache can be reused across multiple imaging runs that
700 use the same image parameters (cell size, image size , spectral data
701 selections, wprojplanes, wbawp, psterm, aterm). The effect of the wbawp,
702 psterm and aterm settings is frozen-in in the cfcache. Using an existing cfcache
703 made with a different setting of these parameters will not reflect the current
704 settings.
706 In a parallel execution, the construction of the cfcache is also parallelized
707 and the time to compute scales close to linearly with the number of compute
708 cores used. With the re-computation of Convolution Functions (CF) due to PA
709 rotation turned-off (the computepastep parameter), the total number of in the
710 cfcache can be computed as [No. of wprojplanes x No. of selected spectral windows x 4]
712 By default, cfcache = imagename + '.cf'
713 usepointing The usepointing flag informs the gridder that it should utilize the pointing table
714 to use the correct direction in which the antenna is pointing with respect to the pointing phasecenter.
715 computepastep Parallactic angle interval after the AIFs are recomputed (deg)
717 This parameter controls the accuracy of the aperture illumination function
718 used with AProjection for alt-az mount dishes where the AIF rotates on the
719 sky as the synthesis image is built up. Once the PA in the data changes by
720 the given interval, AIFs are re-computed at the new PA.
722 A value of 360.0 deg (the default) implies no re-computation due to PA rotation.
723 AIFs are computed for the PA value of the first valid data received and used for
724 all of the data.
725 rotatepastep Parallactic angle interval after which the nearest AIF is rotated (deg)
727 Instead of recomputing the AIF for every timestep's parallactic angle,
728 the nearest existing AIF is used and rotated
729 after the PA changed by rotatepastep value.
731 A value of 360.0 deg (the default) disables rotation of the AIF.
733 For example, computepastep=360.0 and rotatepastep=5.0 will compute
734 the AIFs at only the starting parallactic angle and all other timesteps will
735 use a rotated version of that AIF at the nearest 5.0 degree point.
736 pointingoffsetsigdev Corrections for heterogenous and time-dependent pointing
737 offsets via AWProjection are controlled by this parameter.
738 It is a vector of 2 ints or doubles each of which is interpreted
739 in units of arcsec. Based on the first threshold, a clustering
740 algorithm is applied to entries from the POINTING subtable
741 of the MS to determine how distinct antenna groups for which
742 the pointing offset must be computed separately. The second
743 number controls how much a pointing change across time can
744 be ignored and after which an antenna rebinning is required.
747 Note : The default value of this parameter is [], due a programmatic constraint.
748 If run with this value, it will internally pick [600,600] and exercise the
749 option of using large tolerances (10arcmin) on both axes. Please choose
750 a setting explicitly for runs that need to use this parameter.
752 Note : This option is available only for gridder='awproject' and usepointing=True and
753 and has been validated primarily with VLASS on-the-fly mosaic data
754 where POINTING subtables have been modified after the data are recorded.
757 Examples of parameter usage :
759 [100.0,100.0] : Pointing offsets of 100 arcsec or less are considered
760 small enough to be ignored. Using large values for both
761 indicates a homogeneous array.
764 [10.0, 100.0] : Based on entries in the POINTING subtable, antennas
765 are grouped into clusters based on a 10arcsec bin size.
766 All antennas in a bin are given a pointing offset calculated
767 as the average of the offsets of all antennas in the bin.
768 On the time axis, offset changes upto 100 arcsec will be ignored.
770 [10.0,10.0] : Calculate separate pointing offsets for each antenna group
771 (with a 10 arcsec bin size). As a function of time, recalculate
772 the antenna binning if the POINTING table entries change by
773 more than 10 arcsec w.r.to the previously computed binning.
775 [1.0, 1.0] : Tight tolerances will imply a fully heterogenous situation where
776 each antenna gets its own pointing offset. Also, time-dependent
777 offset changes greater than 1 arcsec will trigger recomputes of
778 the phase gradients. This is the most general situation and is also
779 the most expensive option as it constructs and uses separate
780 phase gradients for all baselines and timesteps.
782 For VLASS 1.1 data with two kinds of pointing offsets, the recommended
783 setting is [ 30.0, 30.0 ].
785 For VLASS 1.2 data with only the time-dependent pointing offsets, the
786 recommended setting is [ 300.0, 30.0 ] to turn off the antenna grouping
787 but to retain the time dependent corrections required from one timestep
788 to the next.
789 pblimit PB gain level at which to cut off normalizations
791 Divisions by .pb during normalizations have a cut off at a .pb gain
792 level given by pblimit. Outside this limit, image values are set to zero.
793 Additionally, by default, an internal T/F mask is applied to the .pb, .image and
794 .residual images to mask out (T) all invalid pixels outside the pblimit area.
796 Note : This internal T/F mask cannot be used as a deconvolution mask.
797 To do so, please follow the steps listed above in the Notes for the
798 'gridder' parameter.
800 Note : To prevent the internal T/F mask from appearing in anything other
801 than the .pb and .image.pbcor images, 'pblimit' can be set to a
802 negative number. The absolute value will still be used as a valid 'pblimit'.
803 A sdintimaging restart using existing output images on disk that already
804 have this T/F mask in the .residual and .image but only pblimit set
805 to a negative value, will remove this mask after the next major cycle.
806 deconvolver Name of minor cycle algorithm (hogbom,clark,multiscale,mtmfs,mem,clarkstokes,asp)
808 Each of the following algorithms operate on residual images and psfs
809 from the gridder and produce output model and restored images.
810 Minor cycles stop and a major cycle is triggered when cyclethreshold
811 or cycleniter are reached. For all methods, components are picked from
812 the entire extent of the image or (if specified) within a mask.
814 hogbom : An adapted version of Hogbom Clean [Hogbom, 1974]
815 - Find the location of the peak residual
816 - Add this delta function component to the model image
817 - Subtract a scaled and shifted PSF of the same size as the image
818 from regions of the residual image where the two overlap.
819 - Repeat
821 clark : An adapted version of Clark Clean [Clark, 1980]
822 - Find the location of max(I^2+Q^2+U^2+V^2)
823 - Add delta functions to each stokes plane of the model image
824 - Subtract a scaled and shifted PSF within a small patch size
825 from regions of the residual image where the two overlap.
826 - After several iterations trigger a Clark major cycle to subtract
827 components from the visibility domain, but without de-gridding.
828 - Repeat
830 ( Note : 'clark' maps to imagermode='' in the old clean task.
831 'clark_exp' is another implementation that maps to
832 imagermode='mosaic' or 'csclean' in the old clean task
833 but the behavior is not identical. For now, please
834 use deconvolver='hogbom' if you encounter problems. )
836 clarkstokes : Clark Clean operating separately per Stokes plane
838 (Note : 'clarkstokes_exp' is an alternate version. See above.)
840 multiscale : MultiScale Clean [Cornwell, 2008]
841 - Smooth the residual image to multiple scale sizes
842 - Find the location and scale at which the peak occurs
843 - Add this multiscale component to the model image
844 - Subtract a scaled,smoothed,shifted PSF (within a small
845 patch size per scale) from all residual images
846 - Repeat from step 2
848 mtmfs : Multi-term (Multi Scale) Multi-Frequency Synthesis [Rau and Cornwell, 2011]
849 - Smooth each Taylor residual image to multiple scale sizes
850 - Solve a NTxNT system of equations per scale size to compute
851 Taylor coefficients for components at all locations
852 - Compute gradient chi-square and pick the Taylor coefficients
853 and scale size at the location with maximum reduction in
854 chi-square
855 - Add multi-scale components to each Taylor-coefficient
856 model image
857 - Subtract scaled,smoothed,shifted PSF (within a small patch size
858 per scale) from all smoothed Taylor residual images
859 - Repeat from step 2
862 mem : Maximum Entropy Method [Cornwell and Evans, 1985]
863 - Iteratively solve for values at all individual pixels via the
864 MEM method. It minimizes an objective function of
865 chi-square plus entropy (here, a measure of difference
866 between the current model and a flat prior model).
868 (Note : This MEM implementation is not very robust.
869 Improvements will be made in the future.)
871 asp : ASP Clean [Bhatnagar and Cornwell, 2004]
872 scales List of scale sizes (in pixels) for multi-scale and mtmfs algorithms.
873 --> scales=[0,6,20]
874 This set of scale sizes should represent the sizes
875 (diameters in units of number of pixels)
876 of dominant features in the image being reconstructed.
878 The smallest scale size is recommended to be 0 (point source),
879 the second the size of the synthesized beam and the third 3-5
880 times the synthesized beam, etc. For example, if the synthesized
881 beam is 10" FWHM and cell=2",try scales = [0,5,15].
883 For numerical stability, the largest scale must be
884 smaller than the image (or mask) size and smaller than or
885 comparable to the scale corresponding to the lowest measured
886 spatial frequency (as a scale size much larger than what the
887 instrument is sensitive to is unconstrained by the data making
888 it harder to recovery from errors during the minor cycle).
889 nterms Number of Taylor coefficients in the spectral model
891 - nterms=1 : Assume flat spectrum source
892 - nterms=2 : Spectrum is a straight line with a slope
893 - nterms=N : A polynomial of order N-1
895 From a Taylor expansion of the expression of a power law, the
896 spectral index is derived as alpha = taylorcoeff_1 / taylorcoeff_0
898 Spectral curvature is similarly derived when possible.
900 The optimal number of Taylor terms depends on the available
901 signal to noise ratio, bandwidth ratio, and spectral shape of the
902 source as seen by the telescope (sky spectrum x PB spectrum).
904 nterms=2 is a good starting point for wideband EVLA imaging
905 and the lower frequency bands of ALMA (when fractional bandwidth
906 is greater than 10%) and if there is at least one bright source for
907 which a dynamic range of greater than few 100 is desired.
909 Spectral artifacts for the VLA often look like spokes radiating out from
910 a bright source (i.e. in the image made with standard mfs imaging).
911 If increasing the number of terms does not eliminate these artifacts,
912 check the data for inadequate bandpass calibration. If the source is away
913 from the pointing center, consider including wide-field corrections too.
915 (Note : In addition to output Taylor coefficient images .tt0,.tt1,etc
916 images of spectral index (.alpha), an estimate of error on
917 spectral index (.alpha.error) and spectral curvature (.beta,
918 if nterms is greater than 2) are produced.
919 - These alpha, alpha.error and beta images contain
920 internal T/F masks based on a threshold computed
921 as peakresidual/10. Additional masking based on
922 .alpha/.alpha.error may be desirable.
923 - .alpha.error is a purely empirical estimate derived
924 from the propagation of error during the division of
925 two noisy numbers (alpha = xx.tt1/xx.tt0) where the
926 'error' on tt1 and tt0 are simply the values picked from
927 the corresponding residual images. The absolute value
928 of the error is not always accurate and it is best to interpret
929 the errors across the image only in a relative sense.)
930 smallscalebias A numerical control to bias the scales when using multi-scale or mtmfs algorithms.
931 The peak from each scale's smoothed residual is
932 multiplied by ( 1 - smallscalebias \* scale/maxscale )
933 to increase or decrease the amplitude relative to other scales,
934 before the scale with the largest peak is chosen.
935 Smallscalebias can be varied between -1.0 and 1.0.
936 A score of 0.0 gives all scales equal weight (default).
937 A score larger than 0.0 will bias the solution towards smaller scales.
938 A score smaller than 0.0 will bias the solution towards larger scales.
939 The effect of smallscalebias is more pronounced when using multi-scale relative to mtmfs.
940 restoration e.
942 Construct a restored image : imagename.image by convolving the model
943 image with a clean beam and adding the residual image to the result.
944 If a restoringbeam is specified, the residual image is also
945 smoothed to that target resolution before adding it in.
947 If a .model does not exist, it will make an empty one and create
948 the restored image from the residuals ( with additional smoothing if needed ).
949 With algorithm='mtmfs', this will construct Taylor coefficient maps from
950 the residuals and compute .alpha and .alpha.error.
951 restoringbeam ize to use.
953 - restoringbeam='' or ['']
954 A Gaussian fitted to the PSF main lobe (separately per image plane).
956 - restoringbeam='10.0arcsec'
957 Use a circular Gaussian of this width for all planes
959 - restoringbeam=['8.0arcsec','10.0arcsec','45deg']
960 Use this elliptical Gaussian for all planes
962 - restoringbeam='common'
963 Automatically estimate a common beam shape/size appropriate for
964 all planes.
966 Note : For any restoring beam different from the native resolution
967 the model image is convolved with the beam and added to
968 residuals that have been convolved to the same target resolution.
969 pbcor the output restored image
971 A new image with extension .image.pbcor will be created from
972 the evaluation of .image / .pb for all pixels above the specified pblimit.
974 Note : Stand-alone PB-correction can be triggered by re-running
975 sdintimaging with the appropriate imagename and with
976 niter=0, calcpsf=False, calcres=False, pbcor=True, vptable='vp.tab'
977 ( where vp.tab is the name of the vpmanager file.
978 See the inline help for the 'vptable' parameter )
980 Note : Multi-term PB correction that includes a correction for the
981 spectral index of the PB has not been enabled for the 4.7 release.
982 Please use the widebandpbcor task instead.
983 ( Wideband PB corrections are required when the amplitude of the
984 brightest source is known accurately enough to be sensitive
985 to the difference in the PB gain between the upper and lower
986 end of the band at its location. As a guideline, the artificial spectral
987 index due to the PB is -1.4 at the 0.5 gain level and less than -0.2
988 at the 0.9 gain level at the middle frequency )
989 weighting Weighting scheme (natural,uniform,briggs,superuniform,radial, briggsabs)
991 During gridding of the dirty or residual image, each visibility value is
992 multiplied by a weight before it is accumulated on the uv-grid.
993 The PSF's uv-grid is generated by gridding only the weights (weightgrid).
995 weighting='natural' : Gridding weights are identical to the data weights
996 from the MS. For visibilities with similar data weights,
997 the weightgrid will follow the sample density
998 pattern on the uv-plane. This weighting scheme
999 provides the maximum imaging sensitivity at the
1000 expense of a possibly fat PSF with high sidelobes.
1001 It is most appropriate for detection experiments
1002 where sensitivity is most important.
1004 weighting='uniform' : Gridding weights per visibility data point are the
1005 original data weights divided by the total weight of
1006 all data points that map to the same uv grid cell :
1007 ' data_weight / total_wt_per_cell '.
1009 The weightgrid is as close to flat as possible resulting
1010 in a PSF with a narrow main lobe and suppressed
1011 sidelobes. However, since heavily sampled areas of
1012 the uv-plane get down-weighted, the imaging
1013 sensitivity is not as high as with natural weighting.
1014 It is most appropriate for imaging experiments where
1015 a well behaved PSF can help the reconstruction.
1017 weighting='briggs' : Gridding weights per visibility data point are given by
1018 'data_weight / ( A \* total_wt_per_cell + B ) ' where
1019 A and B vary according to the 'robust' parameter.
1021 robust = -2.0 maps to A=1,B=0 or uniform weighting.
1022 robust = +2.0 maps to natural weighting.
1023 (robust=0.5 is equivalent to robust=0.0 in AIPS IMAGR.)
1025 Robust/Briggs weighting generates a PSF that can
1026 vary smoothly between 'natural' and 'uniform' and
1027 allow customized trade-offs between PSF shape and
1028 imaging sensitivity.
1029 weighting='briggsabs' : Experimental option.
1030 Same as Briggs except the formula is different A=
1031 robust\*robust and B is dependent on the
1032 noise per visibility estimated. Giving noise='0Jy'
1033 is a not a reasonable option.
1034 In this mode (or formula) robust values
1035 from -2.0 to 0.0 only make sense (2.0 and
1036 -2.0 will get the same weighting)
1038 weighting='superuniform' : This is similar to uniform weighting except that
1039 the total_wt_per_cell is replaced by the
1040 total_wt_within_NxN_cells around the uv cell of
1041 interest. ( N = subparameter 'npixels' )
1043 This method tends to give a PSF with inner
1044 sidelobes that are suppressed as in uniform
1045 weighting but with far-out sidelobes closer to
1046 natural weighting. The peak sensitivity is also
1047 closer to natural weighting.
1049 weighting='radial' : Gridding weights are given by ' data_weight \* uvdistance '
1051 This method approximately minimizes rms sidelobes
1052 for an east-west synthesis array.
1054 weighting='briggsbwtaper' : A modified version of Briggs weighting for cubes where an inverse uv taper,
1055 which is proportional to the fractional bandwidth of the entire cube,
1056 is applied per channel. The objective is to modify cube (perchanweightdensity = True)
1057 imaging weights to have a similar density to that of the continuum imaging weights.
1058 This is currently an experimental weighting scheme being developed for ALMA.
1061 For more details on weighting please see Chapter3
1062 of Dan Briggs' thesis (http://www.aoc.nrao.edu/dissertations/dbriggs)
1063 robust Robustness parameter for Briggs weighting.
1065 robust = -2.0 maps to uniform weighting.
1066 robust = +2.0 maps to natural weighting.
1067 (robust=0.5 is equivalent to robust=0.0 in AIPS IMAGR.)
1068 noise noise parameter for briggs abs mode weighting
1069 npixels Number of pixels to determine uv-cell size for super-uniform weighting
1070 (0 defaults to -/+ 3 pixels)
1072 npixels -- uv-box used for weight calculation
1073 a box going from -npixel/2 to +npixel/2 on each side
1074 around a point is used to calculate weight density.
1076 npixels=2 goes from -1 to +1 and covers 3 pixels on a side.
1078 npixels=0 implies a single pixel, which does not make sense for
1079 superuniform weighting. Therefore, if npixels=0 it will
1080 be forced to 6 (or a box of -3pixels to +3pixels) to cover
1081 7 pixels on a side.
1082 uvtaper uv-taper on outer baselines in uv-plane
1084 Apply a Gaussian taper in addition to the weighting scheme specified
1085 via the 'weighting' parameter. Higher spatial frequencies are weighted
1086 down relative to lower spatial frequencies to suppress artifacts
1087 arising from poorly sampled areas of the uv-plane. It is equivalent to
1088 smoothing the PSF obtained by other weighting schemes and can be
1089 specified either as a Gaussian in uv-space (eg. units of lambda)
1090 or as a Gaussian in the image domain (eg. angular units like arcsec).
1092 uvtaper = [bmaj, bmin, bpa]
1094 NOTE: the on-sky FWHM in arcsec is roughly the uv taper/200 (klambda).
1095 default: uvtaper=[]; no Gaussian taper applied
1096 example: uvtaper=['5klambda'] circular taper
1097 FWHM=5 kilo-lambda
1098 uvtaper=['5klambda','3klambda','45.0deg']
1099 uvtaper=['10arcsec'] on-sky FWHM 10 arcseconds
1100 uvtaper=['300.0'] default units are lambda
1101 in aperture plane
1102 niter Maximum number of iterations
1104 A stopping criterion based on total iteration count.
1105 Currently the parameter type is defined as an integer therefore the integer value
1106 larger than 2147483647 will not be set properly as it causes an overflow.
1108 Iterations are typically defined as the selecting one flux component
1109 and partially subtracting it out from the residual image.
1111 niter=0 : Do only the initial major cycle (make dirty image, psf, pb, etc)
1113 niter larger than zero : Run major and minor cycles.
1115 Note : Global stopping criteria vs major-cycle triggers
1117 In addition to global stopping criteria, the following rules are
1118 used to determine when to terminate a set of minor cycle iterations
1119 and trigger major cycles [derived from Cotton-Schwab Clean, 1984]
1121 'cycleniter' : controls the maximum number of iterations per image
1122 plane before triggering a major cycle.
1123 'cyclethreshold' : Automatically computed threshold related to the
1124 max sidelobe level of the PSF and peak residual.
1125 Divergence, detected as an increase of 10% in peak residual from the
1126 minimum so far (during minor cycle iterations)
1128 The first criterion to be satisfied takes precedence.
1130 Note : Iteration counts for cubes or multi-field images :
1131 For images with multiple planes (or image fields) on which the
1132 deconvolver operates in sequence, iterations are counted across
1133 all planes (or image fields). The iteration count is compared with
1134 'niter' only after all channels/planes/fields have completed their
1135 minor cycles and exited either due to 'cycleniter' or 'cyclethreshold'.
1136 Therefore, the actual number of iterations reported in the logger
1137 can sometimes be larger than the user specified value in 'niter'.
1138 For example, with niter=100, cycleniter=20,nchan=10,threshold=0,
1139 a total of 200 iterations will be done in the first set of minor cycles
1140 before the total is compared with niter=100 and it exits.
1142 Note : Additional global stopping criteria include
1143 - no change in peak residual across two major cycles
1144 - a 50% or more increase in peak residual across one major cycle
1145 gain Loop gain
1147 Fraction of the source flux to subtract out of the residual image
1148 for the CLEAN algorithm and its variants.
1150 A low value (0.2 or less) is recommended when the sky brightness
1151 distribution is not well represented by the basis functions used by
1152 the chosen deconvolution algorithm. A higher value can be tried when
1153 there is a good match between the true sky brightness structure and
1154 the basis function shapes. For example, for extended emission,
1155 multiscale clean with an appropriate set of scale sizes will tolerate
1156 a higher loop gain than Clark clean (for example).
1157 threshold Stopping threshold (number in units of Jy, or string)
1159 A global stopping threshold that the peak residual (within clean mask)
1160 across all image planes is compared to.
1162 threshold = 0.005 : 5mJy
1163 threshold = '5.0mJy'
1165 Note : A 'cyclethreshold' is internally computed and used as a major cycle
1166 trigger. It is related what fraction of the PSF can be reliably
1167 used during minor cycle updates of the residual image. By default
1168 the minor cycle iterations terminate once the peak residual reaches
1169 the first sidelobe level of the brightest source.
1171 'cyclethreshold' is computed as follows using the settings in
1172 parameters 'cyclefactor','minpsffraction','maxpsffraction','threshold' :
1174 psf_fraction = max_psf_sidelobe_level \* 'cyclefactor'
1175 psf_fraction = max(psf_fraction, 'minpsffraction');
1176 psf_fraction = min(psf_fraction, 'maxpsffraction');
1177 cyclethreshold = peak_residual \* psf_fraction
1178 cyclethreshold = max( cyclethreshold, 'threshold' )
1180 If nsigma is set (>0.0), the N-sigma threshold is calculated (see
1181 the description under nsigma), then cyclethreshold is further modified as,
1183 cyclethreshold = max( cyclethreshold, nsgima_threshold )
1186 'cyclethreshold' is made visible and editable only in the
1187 interactive GUI when sdintimaging is run with interactive=True.
1188 nsigma Multiplicative factor for rms-based threshold stopping
1190 N-sigma threshold is calculated as nsigma \* rms value per image plane determined
1191 from a robust statistics. For nsigma > 0.0, in a minor cycle, a maximum of the two values,
1192 the N-sigma threshold and cyclethreshold, is used to trigger a major cycle
1193 (see also the descreption under 'threshold').
1194 Set nsigma=0.0 to preserve the previous sdintimaging behavior without this feature.
1195 The top level parameter, fastnoise is relevant for the rms noise calculation which is used
1196 to determine the threshold.
1197 cycleniter Maximum number of minor-cycle iterations (per plane) before triggering
1198 a major cycle
1200 For example, for a single plane image, if niter=100 and cycleniter=20,
1201 there will be 5 major cycles after the initial one (assuming there is no
1202 threshold based stopping criterion). At each major cycle boundary, if
1203 the number of iterations left over (to reach niter) is less than cycleniter,
1204 it is set to the difference.
1206 Note : cycleniter applies per image plane, even if cycleniter x nplanes
1207 gives a total number of iterations greater than 'niter'. This is to
1208 preserve consistency across image planes within one set of minor
1209 cycle iterations.
1210 cyclefactor Scaling on PSF sidelobe level to compute the minor-cycle stopping threshold.
1212 Please refer to the Note under the documentation for 'threshold' that
1213 discussed the calculation of 'cyclethreshold'
1215 cyclefactor=1.0 results in a cyclethreshold at the first sidelobe level of
1216 the brightest source in the residual image before the minor cycle starts.
1218 cyclefactor=0.5 allows the minor cycle to go deeper.
1219 cyclefactor=2.0 triggers a major cycle sooner.
1220 minpsffraction PSF fraction that marks the max depth of cleaning in the minor cycle
1222 Please refer to the Note under the documentation for 'threshold' that
1223 discussed the calculation of 'cyclethreshold'
1225 For example, minpsffraction=0.5 will stop cleaning at half the height of
1226 the peak residual and trigger a major cycle earlier.
1227 maxpsffraction PSF fraction that marks the minimum depth of cleaning in the minor cycle
1229 Please refer to the Note under the documentation for 'threshold' that
1230 discussed the calculation of 'cyclethreshold'
1232 For example, maxpsffraction=0.8 will ensure that at least the top 20
1233 percent of the source will be subtracted out in the minor cycle even if
1234 the first PSF sidelobe is at the 0.9 level (an extreme example), or if the
1235 cyclefactor is set too high for anything to get cleaned.
1236 interactive Modify masks and parameters at runtime
1238 interactive=True will trigger an interactive GUI at every major cycle
1239 boundary (after the major cycle and before the minor cycle).
1241 Options for runtime parameter modification are :
1243 Interactive clean mask : Draw a 1/0 mask (appears as a contour) by hand.
1244 If a mask is supplied at the task interface or if
1245 automasking is invoked, the current mask is
1246 displayed in the GUI and is available for manual
1247 editing.
1249 Note : If a mask contour is not visible, please
1250 check the cursor display at the bottom of
1251 GUI to see which parts of the mask image
1252 have ones and zeros. If the entire mask=1
1253 no contours will be visible.
1256 Operation buttons : -- Stop execution now (restore current model and exit)
1257 -- Continue on until global stopping criteria are reached
1258 without stopping for any more interaction
1259 -- Continue with minor cycles and return for interaction
1260 after the next major cycle.
1262 Iteration control : -- max cycleniter : Trigger for the next major cycle
1264 The display begins with
1265 [ min( cycleniter, niter - itercount ) ]
1266 and can be edited by hand.
1268 -- iterations left : The display begins with [niter-itercount ]
1269 and can be edited to increase or
1270 decrease the total allowed niter.
1272 -- threshold : Edit global stopping threshold
1274 -- cyclethreshold : The display begins with the
1275 automatically computed value
1276 (see Note in help for 'threshold'),
1277 and can be edited by hand.
1279 All edits will be reflected in the log messages that appear
1280 once minor cycles begin.
1281 fullsummary Return dictionary with complete convergence history
1283 fullsummary=True: A full version of the summary dictionary is returned.
1284 Keys include 'iterDone','peakRes','modelFlux','cycleThresh' that record the
1285 convergence state at the end of each set of minor cycle iterations
1286 separately for each image plane (i.e. channel/stokes) being
1287 deconvolved. Additional keys report the convergence state at the
1288 start of minor cycle iterations, stopping criteria that triggered major
1289 cycles, and a processor ID per channel, for parallel cube runs.
1291 fullsummary=False (default): A shorten version of the summary dictionary is returned
1292 with only 'iterDone','peakRes','modelFlux', and 'cycleThresh'.
1294 Detailed information about the return dictionary fields may be found
1295 at CASA Docs > Synthesis Imaging > Iteration Control > Returned Dictionary.
1296 nmajor The nmajor parameter limits the number of minor and major cycle sets
1297 that sdintimaging executes. It is defined as the number of major cycles after the
1298 initial set of minor cycle iterations. The count of nmajor does
1299 not include the initial residual calculation that occurs when calcres=True.
1301 A setting of nmajor=-1 implies no limit (default -1).
1302 A setting of nmajor=0 implies nothing other than the initial residual calculation
1303 A setting of nmajor>0 imples that nmajor sets of minor and major cycles will
1304 be done in addition to the initial residual calculation.
1306 If the major cycle limit is reached, stopcode 9 will be returned. Other stopping
1307 criteria (such as threshold) could cause sdintimaging to stop in fewer than this
1308 number of major cycles. If sdintimaging reaches another stopping criteria, first
1309 or at the same time as nmajor, then that stopcode will be returned instead.
1311 Note however that major cycle ids in the log messages as well as in the return
1312 dictionary do begin with 1 for the initial residual calculation, when it exists.
1314 Example 1 : A run with 'nmajor=5' and 'calcres=True' will iterate for
1315 5 major cycles (not counting the initial residual calculation). But, the return
1316 dictionary will show 'nmajordone:6'. If 'calcres=False', then the return
1317 dictionary will show 'nmajordone:5'.
1319 Example 2 : For both the following cases, there will be a printout in the logs
1320 "Running Major Cycle 1" and the return value will include "nmajordone: 1",
1321 however there is a difference in the purpose of the major cycle and the
1322 number of minor cycles executed:
1323 Case 1; nmajor=0, calcres=True: The major cycle done is for the creation
1324 of the residual, and no minor cycles are executed.
1325 Case 2; nmajor=1, calcres=False: The major cycle is done as part of the
1326 major/minor cycle loop, and 1 minor cycle will be executed.
1328 Note : For sdintimaging, the 'nmajor' parameter is not implemented for
1329 usedata='sdonly'. Other stopping criteria still apply as usual.
1330 usemask Type of mask(s) to be used for deconvolution
1332 user: (default) mask image(s) or user specified region file(s) or string CRTF expression(s)
1333 subparameters: mask, pbmask
1334 pb: primary beam mask
1335 subparameter: pbmask
1337 Example: usemask="pb", pbmask=0.2
1338 Construct a mask at the 0.2 pb gain level.
1339 (Currently, this option will work only with
1340 gridders that produce .pb (i.e. mosaic and awproject)
1341 or if an externally produced .pb image exists on disk)
1343 auto-multithresh : auto-masking by multiple thresholds for deconvolution
1344 subparameters : sidelobethreshold, noisethreshold, lownoisethreshold, negativethrehsold, smoothfactor,
1345 minbeamfrac, cutthreshold, pbmask, growiterations, dogrowprune, minpercentchange, verbose
1346 Additional top level parameter relevant to auto-multithresh: fastnoise
1348 if pbmask is >0.0, the region outside the specified pb gain level is excluded from
1349 image statistics in determination of the threshold.
1354 Note: By default the intermediate mask generated by automask at each deconvolution cycle
1355 is over-written in the next cycle but one can save them by setting
1356 the environment variable, SAVE_ALL_AUTOMASKS="true".
1357 (e.g. in the CASA prompt, os.environ['SAVE_ALL_AUTOMASKS']="true" )
1358 The saved CASA mask image name will be imagename.mask.autothresh#, where
1359 # is the iteration cycle number.
1360 mask Mask (a list of image name(s) or region file(s) or region string(s)
1363 The name of a CASA image or region file or region string that specifies
1364 a 1/0 mask to be used for deconvolution. Only locations with value 1 will
1365 be considered for the centers of flux components in the minor cycle.
1366 If regions specified fall completely outside of the image, sdintimaging will throw an error.
1368 Manual mask options/examples :
1370 mask='xxx.mask' : Use this CASA image named xxx.mask and containing
1371 ones and zeros as the mask.
1372 If the mask is only different in spatial coordinates from what is being made
1373 it will be resampled to the target coordinate system before being used.
1374 The mask has to have the same shape in velocity and Stokes planes
1375 as the output image. Exceptions are single velocity and/or single
1376 Stokes plane masks. They will be expanded to cover all velocity and/or
1377 Stokes planes of the output cube.
1379 [ Note : If an error occurs during image resampling or
1380 if the expected mask does not appear, please try
1381 using tasks 'imregrid' or 'makemask' to resample
1382 the mask image onto a CASA image with the target
1383 shape and coordinates and supply it via the 'mask'
1384 parameter. ]
1387 mask='xxx.crtf' : A text file with region strings and the following on the first line
1388 ( #CRTFv0 CASA Region Text Format version 0 )
1389 This is the format of a file created via the viewer's region
1390 tool when saved in CASA region file format.
1392 mask='circle[[40pix,40pix],10pix]' : A CASA region string.
1394 mask=['xxx.mask','xxx.crtf', 'circle[[40pix,40pix],10pix]'] : a list of masks
1400 Note : Mask images for deconvolution must contain 1 or 0 in each pixel.
1401 Such a mask is different from an internal T/F mask that can be
1402 held within each CASA image. These two types of masks are not
1403 automatically interchangeable, so please use the makemask task
1404 to copy between them if you need to construct a 1/0 based mask
1405 from a T/F one.
1407 Note : Work is in progress to generate more flexible masking options and
1408 enable more controls.
1409 pbmask Sub-parameter for usemask: primary beam mask
1411 Examples : pbmask=0.0 (default, no pb mask)
1412 pbmask=0.2 (construct a mask at the 0.2 pb gain level)
1413 sidelobethreshold Sub-parameter for "auto-multithresh": mask threshold based on sidelobe levels: sidelobethreshold \* max_sidelobe_level \* peak residual
1414 noisethreshold Sub-parameter for "auto-multithresh": mask threshold based on the noise level: noisethreshold \* rms + location (=median)
1416 The rms is calculated from MAD with rms = 1.4826\*MAD.
1417 lownoisethreshold Sub-parameter for "auto-multithresh": mask threshold to grow previously masked regions via binary dilation: lownoisethreshold \* rms in residual image + location (=median)
1419 The rms is calculated from MAD with rms = 1.4826\*MAD.
1420 negativethreshold Sub-parameter for "auto-multithresh": mask threshold for negative features: -1.0* negativethreshold \* rms + location(=median)
1422 The rms is calculated from MAD with rms = 1.4826\*MAD.
1423 smoothfactor Sub-parameter for "auto-multithresh": smoothing factor in a unit of the beam
1424 minbeamfrac Sub-parameter for "auto-multithresh": minimum beam fraction in size to prune masks smaller than mimbeamfrac \* beam
1425 <=0.0 : No pruning
1426 cutthreshold Sub-parameter for "auto-multithresh": threshold to cut the smoothed mask to create a final mask: cutthreshold \* peak of the smoothed mask
1427 growiterations Sub-parameter for "auto-multithresh": Maximum number of iterations to perform using binary dilation for growing the mask
1428 dogrowprune Experimental sub-parameter for "auto-multithresh": Do pruning on the grow mask
1429 minpercentchange If the change in the mask size in a particular channel is less than minpercentchange, stop masking that channel in subsequent cycles. This check is only applied when noise based threshold is used and when the previous clean major cycle had a cyclethreshold value equal to the clean threshold. Values equal to -1.0 (or any value less than 0.0) will turn off this check (the default). Automask will still stop masking if the current channel mask is an empty mask and the noise threshold was used to determine the mask.
1430 verbose he summary of automasking at the end of each automasking process
1431 is printed in the logger. Following information per channel will be listed in the summary.
1433 chan: channel number
1434 masking?: F - stop updating automask for the subsequent iteration cycles
1435 RMS: robust rms noise
1436 peak: peak in residual image
1437 thresh_type: type of threshold used (noise or sidelobe)
1438 thresh_value: the value of threshold used
1439 N_reg: number of the automask regions
1440 N_pruned: number of the automask regions removed by pruning
1441 N_grow: number of the grow mask regions
1442 N_grow_pruned: number of the grow mask regions removed by pruning
1443 N_neg_pix: number of pixels for negative mask regions
1445 Note that for a large cube, extra logging may slow down the process.
1446 fastnoise Only relevant when automask (user='multi-autothresh') and/or n-sigma stopping threshold (nsigma>0.0) are/is used. If it is set to True, a simpler but faster noise calucation is used.
1447 In this case, the threshold values are determined based on classic statistics (using all
1448 unmasked pixels for the calculations).
1450 If it is set to False, the new noise calculation
1451 method is used based on pre-existing mask.
1453 Case 1: no exiting mask
1454 Calculate image statistics using Chauvenet algorithm
1456 Case 2: there is an existing mask
1457 Calculate image statistics by classical method on the region
1458 outside the mask and inside the primary beam mask.
1460 In all cases above RMS noise is calculated from MAD.
1461 restart images (and start from an existing model image)
1462 or automatically increment the image name and make a new image set.
1464 True : Re-use existing images. If imagename.model exists the subsequent
1465 run will start from this model (i.e. predicting it using current gridder
1466 settings and starting from the residual image). Care must be taken
1467 when combining this option with startmodel. Currently, only one or
1468 the other can be used.
1470 startmodel='', imagename.model exists :
1471 - Start from imagename.model
1472 startmodel='xxx', imagename.model does not exist :
1473 - Start from startmodel
1474 startmodel='xxx', imagename.model exists :
1475 - Exit with an error message requesting the user to pick
1476 only one model. This situation can arise when doing one
1477 run with startmodel='xxx' to produce an output
1478 imagename.model that includes the content of startmodel,
1479 and wanting to restart a second run to continue deconvolution.
1480 Startmodel should be set to '' before continuing.
1482 If any change in the shape or coordinate system of the image is
1483 desired during the restart, please change the image name and
1484 use the startmodel (and mask) parameter(s) so that the old model
1485 (and mask) can be regridded to the new coordinate system before starting.
1487 False : A convenience feature to increment imagename with '_1', '_2',
1488 etc as suffixes so that all runs of sdintimaging are fresh starts (without
1489 having to change the imagename parameter or delete images).
1491 This mode will search the current directory for all existing
1492 imagename extensions, pick the maximum, and adds 1.
1493 For imagename='try' it will make try.psf, try_2.psf, try_3.psf, etc.
1495 This also works if you specify a directory name in the path :
1496 imagename='outdir/try'. If './outdir' does not exist, it will create it.
1497 Then it will search for existing filenames inside that directory.
1499 If outlier fields are specified, the incrementing happens for each
1500 of them (since each has its own 'imagename'). The counters are
1501 synchronized across imagefields, to make it easier to match up sets
1502 of output images. It adds 1 to the 'max id' from all outlier names
1503 on disk. So, if you do two runs with only the main field
1504 (imagename='try'), and in the third run you add an outlier with
1505 imagename='outtry', you will get the following image names
1506 for the third run : 'try_3' and 'outtry_3' even though
1507 'outry' and 'outtry_2' have not been used.
1508 calcres Calculate initial residual image
1510 This parameter controls what the first major cycle does.
1512 calcres=False with niter greater than 0 will assume that
1513 a .residual image already exists and that the minor cycle can
1514 begin without recomputing it.
1516 calcres=False with niter=0 implies that only the PSF will be made
1517 and no data will be gridded.
1519 calcres=True requires that calcpsf=True or that the .psf and .sumwt
1520 images already exist on disk (for normalization purposes).
1522 Usage example : For large runs (or a pipeline scripts) it may be
1523 useful to first run sdintimaging with niter=0 to create
1524 an initial .residual to look at and perhaps make
1525 a custom mask for. Imaging can be resumed
1526 without recomputing it.
1527 calcpsf Calculate PSF
1529 This parameter controls what the first major cycle does.
1531 calcpsf=False will assume that a .psf image already exists
1532 and that the minor cycle can begin without recomputing it.
1533 [1;42mRETURNS[1;m void
1535 --------- examples -----------------------------------------------------------
1539 Please refer to the CASAdocs pages for the task sdintimaging for examples.
1544 """
1546 _info_group_ = """imaging"""
1547 _info_desc_ = """"""
1549 def __call__( self, usedata='sdint', sdimage='', sdpsf='', sdgain=float(1.0), dishdia=float(0), vis='', selectdata=True, field='', spw='', timerange='', uvrange='', antenna='', scan='', observation='', intent='', datacolumn='corrected', imagename='', imsize=[ ], cell=[ ], phasecenter='', stokes='I', projection='SIN', startmodel='', specmode='mfs', reffreq='', nchan=int(-1), start='', width='', outframe='LSRK', veltype='radio', restfreq=[ ], interpolation='linear', perchanweightdensity=True, gridder='standard', facets=int(1), psfphasecenter='', wprojplanes=int(1), vptable='', mosweight=True, aterm=True, psterm=False, wbawp=True, cfcache='', usepointing=False, computepastep=float(360.0), rotatepastep=float(360.0), pointingoffsetsigdev=[ ], pblimit=float(0.2), deconvolver='hogbom', scales=[ ], nterms=int(2), smallscalebias=float(0.0), restoration=True, restoringbeam=[ ], pbcor=False, weighting='natural', robust=float(0.5), noise='1.0Jy', npixels=int(0), uvtaper=[ '' ], niter=int(0), gain=float(0.1), threshold=float(0.0), nsigma=float(0.0), cycleniter=int(-1), cyclefactor=float(1.0), minpsffraction=float(0.05), maxpsffraction=float(0.8), interactive=False, fullsummary=False, nmajor=int(-1), usemask='user', mask='', pbmask=float(0.0), sidelobethreshold=float(3.0), noisethreshold=float(5.0), lownoisethreshold=float(1.5), negativethreshold=float(0.0), smoothfactor=float(1.0), minbeamfrac=float(0.3), cutthreshold=float(0.01), growiterations=int(75), dogrowprune=True, minpercentchange=float(-1.0), verbose=False, fastnoise=True, restart=True, calcres=True, calcpsf=True ):
1550 schema = {'usedata': {'type': 'cStr', 'coerce': _coerce.to_str}, 'sdimage': {'type': 'cStr', 'coerce': _coerce.to_str}, 'sdpsf': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cFloat', 'coerce': _coerce.to_float}]}, 'sdgain': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'dishdia': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'vis': {'anyof': [{'type': 'cReqPath', 'coerce': _coerce.expand_path}, {'type': 'cReqPathVec', 'coerce': [_coerce.to_list,_coerce.expand_pathvec]}]}, 'selectdata': {'type': 'cBool'}, 'field': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'spw': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'timerange': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'uvrange': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'antenna': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'scan': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'observation': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cInt'}]}, 'intent': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'datacolumn': {'type': 'cStr', 'coerce': _coerce.to_str}, 'imagename': {'anyof': [{'type': 'cInt'}, {'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'imsize': {'anyof': [{'type': 'cInt'}, {'type': 'cIntVec', 'coerce': [_coerce.to_list,_coerce.to_intvec]}]}, 'cell': {'anyof': [{'type': 'cIntVec', 'coerce': [_coerce.to_list,_coerce.to_intvec]}, {'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cFloat', 'coerce': _coerce.to_float}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}, {'type': 'cInt'}, {'type': 'cFloatVec', 'coerce': [_coerce.to_list,_coerce.to_floatvec]}]}, 'phasecenter': {'anyof': [{'type': 'cInt'}, {'type': 'cStr', 'coerce': _coerce.to_str}]}, 'stokes': {'type': 'cStr', 'coerce': _coerce.to_str, 'allowed': [ 'I', 'IQUV', 'UV', 'RRLL', 'IQ', 'V', 'pseudoI', 'QU', 'YY', 'RR', 'Q', 'U', 'IV', 'XX', 'XXYY', 'LL' ]}, 'projection': {'type': 'cStr', 'coerce': _coerce.to_str}, 'startmodel': {'type': 'cVariant', 'coerce': [_coerce.to_variant]}, 'specmode': {'type': 'cVariant', 'coerce': [_coerce.to_variant] # <allowed> IS NOT ALLOWED FOR A PARAMETER OF TYPE any
1551}, 'reffreq': {'type': 'cVariant', 'coerce': [_coerce.to_variant]}, 'nchan': {'type': 'cInt'}, 'start': {'type': 'cVariant', 'coerce': [_coerce.to_variant]}, 'width': {'type': 'cVariant', 'coerce': [_coerce.to_variant]}, 'outframe': {'type': 'cStr', 'coerce': _coerce.to_str}, 'veltype': {'type': 'cStr', 'coerce': _coerce.to_str}, 'restfreq': {'type': 'cVariant', 'coerce': [_coerce.to_variant]}, 'interpolation': {'type': 'cStr', 'coerce': _coerce.to_str, 'allowed': [ 'nearest', 'linear', 'cubic' ]}, 'perchanweightdensity': {'type': 'cBool'}, 'gridder': {'type': 'cStr', 'coerce': _coerce.to_str, 'allowed': [ 'widefield', 'wproject', 'imagemosaic', 'standard', 'awproject', 'wprojectft', 'mosaicft', 'ft', 'ftmosaic', 'mosaic', 'awprojectft', 'gridft' ]}, 'facets': {'type': 'cInt'}, 'psfphasecenter': {'anyof': [{'type': 'cInt'}, {'type': 'cStr', 'coerce': _coerce.to_str}]}, 'wprojplanes': {'type': 'cInt'}, 'vptable': {'type': 'cStr', 'coerce': _coerce.to_str}, 'mosweight': {'type': 'cBool'}, 'aterm': {'type': 'cBool'}, 'psterm': {'type': 'cBool'}, 'wbawp': {'type': 'cBool'}, 'cfcache': {'type': 'cStr', 'coerce': _coerce.to_str}, 'usepointing': {'type': 'cBool'}, 'computepastep': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'rotatepastep': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'pointingoffsetsigdev': {'anyof': [{'type': 'cIntVec', 'coerce': [_coerce.to_list,_coerce.to_intvec]}, {'type': 'cFloatVec', 'coerce': [_coerce.to_list,_coerce.to_floatvec]}]}, 'pblimit': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'deconvolver': {'type': 'cStr', 'coerce': _coerce.to_str, 'allowed': [ 'clarkstokes_exp', 'mtmfs', 'mem', 'clarkstokes', 'hogbom', 'clark_exp', 'clark', 'asp', 'multiscale' ]}, 'scales': {'anyof': [{'type': 'cIntVec', 'coerce': [_coerce.to_list,_coerce.to_intvec]}, {'type': 'cFloatVec', 'coerce': [_coerce.to_list,_coerce.to_floatvec]}]}, 'nterms': {'type': 'cInt'}, 'smallscalebias': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'restoration': {'type': 'cBool'}, 'restoringbeam': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'pbcor': {'type': 'cBool'}, 'weighting': {'type': 'cStr', 'coerce': _coerce.to_str, 'allowed': [ 'briggsabs', 'briggs', 'briggsbwtaper', 'natural', 'radial', 'superuniform', 'uniform' ]}, 'robust': {'type': 'cFloat', 'coerce': _coerce.to_float, 'min': -2.0, 'max': 2.0}, 'noise': {'type': 'cVariant', 'coerce': [_coerce.to_variant]}, 'npixels': {'type': 'cInt'}, 'uvtaper': {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}, 'niter': {'type': 'cInt'}, 'gain': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'threshold': {'type': 'cVariant', 'coerce': [_coerce.to_variant]}, 'nsigma': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'cycleniter': {'type': 'cInt'}, 'cyclefactor': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'minpsffraction': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'maxpsffraction': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'interactive': {'type': 'cBool'}, 'fullsummary': {'type': 'cBool'}, 'nmajor': {'type': 'cInt'}, 'usemask': {'type': 'cStr', 'coerce': _coerce.to_str, 'allowed': [ 'user', 'pb', 'auto-multithresh' ]}, 'mask': {'anyof': [{'type': 'cStr', 'coerce': _coerce.to_str}, {'type': 'cStrVec', 'coerce': [_coerce.to_list,_coerce.to_strvec]}]}, 'pbmask': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'sidelobethreshold': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'noisethreshold': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'lownoisethreshold': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'negativethreshold': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'smoothfactor': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'minbeamfrac': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'cutthreshold': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'growiterations': {'type': 'cInt'}, 'dogrowprune': {'type': 'cBool'}, 'minpercentchange': {'type': 'cFloat', 'coerce': _coerce.to_float}, 'verbose': {'type': 'cBool'}, 'fastnoise': {'type': 'cBool'}, 'restart': {'type': 'cBool'}, 'calcres': {'type': 'cBool'}, 'calcpsf': {'type': 'cBool'}}
1552 doc = {'usedata': usedata, 'sdimage': sdimage, 'sdpsf': sdpsf, 'sdgain': sdgain, 'dishdia': dishdia, 'vis': vis, 'selectdata': selectdata, 'field': field, 'spw': spw, 'timerange': timerange, 'uvrange': uvrange, 'antenna': antenna, 'scan': scan, 'observation': observation, 'intent': intent, 'datacolumn': datacolumn, 'imagename': imagename, 'imsize': imsize, 'cell': cell, 'phasecenter': phasecenter, 'stokes': stokes, 'projection': projection, 'startmodel': startmodel, 'specmode': specmode, 'reffreq': reffreq, 'nchan': nchan, 'start': start, 'width': width, 'outframe': outframe, 'veltype': veltype, 'restfreq': restfreq, 'interpolation': interpolation, 'perchanweightdensity': perchanweightdensity, 'gridder': gridder, 'facets': facets, 'psfphasecenter': psfphasecenter, 'wprojplanes': wprojplanes, 'vptable': vptable, 'mosweight': mosweight, 'aterm': aterm, 'psterm': psterm, 'wbawp': wbawp, 'cfcache': cfcache, 'usepointing': usepointing, 'computepastep': computepastep, 'rotatepastep': rotatepastep, 'pointingoffsetsigdev': pointingoffsetsigdev, 'pblimit': pblimit, 'deconvolver': deconvolver, 'scales': scales, 'nterms': nterms, 'smallscalebias': smallscalebias, 'restoration': restoration, 'restoringbeam': restoringbeam, 'pbcor': pbcor, 'weighting': weighting, 'robust': robust, 'noise': noise, 'npixels': npixels, 'uvtaper': uvtaper, 'niter': niter, 'gain': gain, 'threshold': threshold, 'nsigma': nsigma, 'cycleniter': cycleniter, 'cyclefactor': cyclefactor, 'minpsffraction': minpsffraction, 'maxpsffraction': maxpsffraction, 'interactive': interactive, 'fullsummary': fullsummary, 'nmajor': nmajor, 'usemask': usemask, 'mask': mask, 'pbmask': pbmask, 'sidelobethreshold': sidelobethreshold, 'noisethreshold': noisethreshold, 'lownoisethreshold': lownoisethreshold, 'negativethreshold': negativethreshold, 'smoothfactor': smoothfactor, 'minbeamfrac': minbeamfrac, 'cutthreshold': cutthreshold, 'growiterations': growiterations, 'dogrowprune': dogrowprune, 'minpercentchange': minpercentchange, 'verbose': verbose, 'fastnoise': fastnoise, 'restart': restart, 'calcres': calcres, 'calcpsf': calcpsf}
1553 assert _pc.validate(doc,schema), create_error_string(_pc.errors)
1554 _logging_state_ = _start_log( 'sdintimaging', [ 'usedata=' + repr(_pc.document['usedata']), 'sdimage=' + repr(_pc.document['sdimage']), 'sdpsf=' + repr(_pc.document['sdpsf']), 'sdgain=' + repr(_pc.document['sdgain']), 'dishdia=' + repr(_pc.document['dishdia']), 'vis=' + repr(_pc.document['vis']), 'selectdata=' + repr(_pc.document['selectdata']), 'field=' + repr(_pc.document['field']), 'spw=' + repr(_pc.document['spw']), 'timerange=' + repr(_pc.document['timerange']), 'uvrange=' + repr(_pc.document['uvrange']), 'antenna=' + repr(_pc.document['antenna']), 'scan=' + repr(_pc.document['scan']), 'observation=' + repr(_pc.document['observation']), 'intent=' + repr(_pc.document['intent']), 'datacolumn=' + repr(_pc.document['datacolumn']), 'imagename=' + repr(_pc.document['imagename']), 'imsize=' + repr(_pc.document['imsize']), 'cell=' + repr(_pc.document['cell']), 'phasecenter=' + repr(_pc.document['phasecenter']), 'stokes=' + repr(_pc.document['stokes']), 'projection=' + repr(_pc.document['projection']), 'startmodel=' + repr(_pc.document['startmodel']), 'specmode=' + repr(_pc.document['specmode']), 'reffreq=' + repr(_pc.document['reffreq']), 'nchan=' + repr(_pc.document['nchan']), 'start=' + repr(_pc.document['start']), 'width=' + repr(_pc.document['width']), 'outframe=' + repr(_pc.document['outframe']), 'veltype=' + repr(_pc.document['veltype']), 'restfreq=' + repr(_pc.document['restfreq']), 'interpolation=' + repr(_pc.document['interpolation']), 'perchanweightdensity=' + repr(_pc.document['perchanweightdensity']), 'gridder=' + repr(_pc.document['gridder']), 'facets=' + repr(_pc.document['facets']), 'psfphasecenter=' + repr(_pc.document['psfphasecenter']), 'wprojplanes=' + repr(_pc.document['wprojplanes']), 'vptable=' + repr(_pc.document['vptable']), 'mosweight=' + repr(_pc.document['mosweight']), 'aterm=' + repr(_pc.document['aterm']), 'psterm=' + repr(_pc.document['psterm']), 'wbawp=' + repr(_pc.document['wbawp']), 'cfcache=' + repr(_pc.document['cfcache']), 'usepointing=' + repr(_pc.document['usepointing']), 'computepastep=' + repr(_pc.document['computepastep']), 'rotatepastep=' + repr(_pc.document['rotatepastep']), 'pointingoffsetsigdev=' + repr(_pc.document['pointingoffsetsigdev']), 'pblimit=' + repr(_pc.document['pblimit']), 'deconvolver=' + repr(_pc.document['deconvolver']), 'scales=' + repr(_pc.document['scales']), 'nterms=' + repr(_pc.document['nterms']), 'smallscalebias=' + repr(_pc.document['smallscalebias']), 'restoration=' + repr(_pc.document['restoration']), 'restoringbeam=' + repr(_pc.document['restoringbeam']), 'pbcor=' + repr(_pc.document['pbcor']), 'weighting=' + repr(_pc.document['weighting']), 'robust=' + repr(_pc.document['robust']), 'noise=' + repr(_pc.document['noise']), 'npixels=' + repr(_pc.document['npixels']), 'uvtaper=' + repr(_pc.document['uvtaper']), 'niter=' + repr(_pc.document['niter']), 'gain=' + repr(_pc.document['gain']), 'threshold=' + repr(_pc.document['threshold']), 'nsigma=' + repr(_pc.document['nsigma']), 'cycleniter=' + repr(_pc.document['cycleniter']), 'cyclefactor=' + repr(_pc.document['cyclefactor']), 'minpsffraction=' + repr(_pc.document['minpsffraction']), 'maxpsffraction=' + repr(_pc.document['maxpsffraction']), 'interactive=' + repr(_pc.document['interactive']), 'fullsummary=' + repr(_pc.document['fullsummary']), 'nmajor=' + repr(_pc.document['nmajor']), 'usemask=' + repr(_pc.document['usemask']), 'mask=' + repr(_pc.document['mask']), 'pbmask=' + repr(_pc.document['pbmask']), 'sidelobethreshold=' + repr(_pc.document['sidelobethreshold']), 'noisethreshold=' + repr(_pc.document['noisethreshold']), 'lownoisethreshold=' + repr(_pc.document['lownoisethreshold']), 'negativethreshold=' + repr(_pc.document['negativethreshold']), 'smoothfactor=' + repr(_pc.document['smoothfactor']), 'minbeamfrac=' + repr(_pc.document['minbeamfrac']), 'cutthreshold=' + repr(_pc.document['cutthreshold']), 'growiterations=' + repr(_pc.document['growiterations']), 'dogrowprune=' + repr(_pc.document['dogrowprune']), 'minpercentchange=' + repr(_pc.document['minpercentchange']), 'verbose=' + repr(_pc.document['verbose']), 'fastnoise=' + repr(_pc.document['fastnoise']), 'restart=' + repr(_pc.document['restart']), 'calcres=' + repr(_pc.document['calcres']), 'calcpsf=' + repr(_pc.document['calcpsf']) ] )
1555 task_result = None
1556 try:
1557 task_result = _sdintimaging_t( _pc.document['usedata'], _pc.document['sdimage'], _pc.document['sdpsf'], _pc.document['sdgain'], _pc.document['dishdia'], _pc.document['vis'], _pc.document['selectdata'], _pc.document['field'], _pc.document['spw'], _pc.document['timerange'], _pc.document['uvrange'], _pc.document['antenna'], _pc.document['scan'], _pc.document['observation'], _pc.document['intent'], _pc.document['datacolumn'], _pc.document['imagename'], _pc.document['imsize'], _pc.document['cell'], _pc.document['phasecenter'], _pc.document['stokes'], _pc.document['projection'], _pc.document['startmodel'], _pc.document['specmode'], _pc.document['reffreq'], _pc.document['nchan'], _pc.document['start'], _pc.document['width'], _pc.document['outframe'], _pc.document['veltype'], _pc.document['restfreq'], _pc.document['interpolation'], _pc.document['perchanweightdensity'], _pc.document['gridder'], _pc.document['facets'], _pc.document['psfphasecenter'], _pc.document['wprojplanes'], _pc.document['vptable'], _pc.document['mosweight'], _pc.document['aterm'], _pc.document['psterm'], _pc.document['wbawp'], _pc.document['cfcache'], _pc.document['usepointing'], _pc.document['computepastep'], _pc.document['rotatepastep'], _pc.document['pointingoffsetsigdev'], _pc.document['pblimit'], _pc.document['deconvolver'], _pc.document['scales'], _pc.document['nterms'], _pc.document['smallscalebias'], _pc.document['restoration'], _pc.document['restoringbeam'], _pc.document['pbcor'], _pc.document['weighting'], _pc.document['robust'], _pc.document['noise'], _pc.document['npixels'], _pc.document['uvtaper'], _pc.document['niter'], _pc.document['gain'], _pc.document['threshold'], _pc.document['nsigma'], _pc.document['cycleniter'], _pc.document['cyclefactor'], _pc.document['minpsffraction'], _pc.document['maxpsffraction'], _pc.document['interactive'], _pc.document['fullsummary'], _pc.document['nmajor'], _pc.document['usemask'], _pc.document['mask'], _pc.document['pbmask'], _pc.document['sidelobethreshold'], _pc.document['noisethreshold'], _pc.document['lownoisethreshold'], _pc.document['negativethreshold'], _pc.document['smoothfactor'], _pc.document['minbeamfrac'], _pc.document['cutthreshold'], _pc.document['growiterations'], _pc.document['dogrowprune'], _pc.document['minpercentchange'], _pc.document['verbose'], _pc.document['fastnoise'], _pc.document['restart'], _pc.document['calcres'], _pc.document['calcpsf'] )
1558 except Exception as exc:
1559 _except_log('sdintimaging', exc)
1560 raise
1561 finally:
1562 task_result = _end_log( _logging_state_, 'sdintimaging', task_result )
1563 return task_result
1565sdintimaging = _sdintimaging( )