Coverage for /wheeldirectory/casa-6.7.0-12-py3.10.el8/lib/py/lib/python3.10/site-packages/casatasks/sdintimaging.py: 56%
27 statements
« prev ^ index » next coverage.py v7.6.4, created at 2024-10-31 18:48 +0000
1##################### generated by xml-casa (v2) from sdintimaging.xml ##############
2##################### 92e5faa737b23ea6b51a6815d68ef04f ##############################
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 interferic data
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 : Due to current internal code constraints, if any correlation pair
229 is flagged, by default, no data for that row in the MS will be used.
230 So, in an MS with XX,YY, if only YY is flagged, neither a
231 Stokes I image nor an XX image can be made from those data points.
232 In such a situation, please split out only the unflagged correlation into
233 a separate MS.
235 Note : The 'pseudoI' option is a partial solution, allowing Stokes I imaging
236 when either of the parallel-hand correlations are unflagged.
238 The remaining constraints shall be removed (where logical) in a future release.
239 projection Coordinate projection
240 Examples : SIN, NCP
241 A list of supported (but untested) projections can be found here :
242 http://casa.nrao.edu/active/docs/doxygen/html/classcasa_1_1Projection.html#a3d5f9ec787e4eabdce57ab5edaf7c0cd
243 startmodel Name of starting model image
245 The contents of the supplied starting model image will be
246 copied to the imagename.model before the run begins.
248 example : startmodel = 'singledish.im'
250 For deconvolver='mtmfs', one image per Taylor term must be provided.
251 example : startmodel = ['try.model.tt0', 'try.model.tt1']
252 startmodel = ['try.model.tt0'] will use a starting model only
253 for the zeroth order term.
254 startmodel = ['','try.model.tt1'] will use a starting model only
255 for the first order term.
257 This starting model can be of a different image shape and size from
258 what is currently being imaged. If so, an image regrid is first triggered
259 to resample the input image onto the target coordinate system.
261 A common usage is to set this parameter equal to a single dish image
263 Negative components in the model image will be included as is.
265 [ Note : If an error occurs during image resampling/regridding,
266 please try using task imregrid to resample the starting model
267 image onto a CASA image with the target shape and
268 coordinate system before supplying it via startmodel ]
269 specmode Spectral definition mode (mfs,cube,cubedata, cubesource)
271 mode='mfs' : Continuum imaging with only one output image channel.
272 (mode='cont' can also be used here)
274 mode='cube' : Spectral line imaging with one or more channels
275 Parameters start, width,and nchan define the spectral
276 coordinate system and can be specified either in terms
277 of channel numbers, frequency or velocity in whatever
278 spectral frame is specified in 'outframe'.
279 All internal and output images are made with outframe as the
280 base spectral frame. However imaging code internally uses the fixed
281 spectral frame, LSRK for automatic internal software
282 Doppler tracking so that a spectral line observed over an
283 extended time range will line up appropriately.
284 Therefore the output images have additional spectral frame conversion
285 layer in LSRK on the top the base frame.
288 (Note : Even if the input parameters are specified in a frame
289 other than LSRK, the viewer still displays spectral
290 axis in LSRK by default because of the conversion frame
291 layer mentioned above. The viewer can be used to relabel
292 the spectral axis in any desired frame - via the spectral
293 reference option under axis label properties in the
294 data display options window.)
299 mode='cubedata' : Spectral line imaging with one or more channels
300 There is no internal software Doppler tracking so
301 a spectral line observed over an extended time range
302 may be smeared out in frequency. There is strictly
303 no valid spectral frame with which to label the output
304 images, but they will list the frame defined in the MS.
306 mode='cubesource': Spectral line imaging while
307 tracking moving source (near field or solar system
308 objects). The velocity of the source is accounted
309 and the frequency reported is in the source frame.
310 As there is not SOURCE frame defined,
311 the frame reported will be REST (as it may not be
312 in the rest frame emission region may be
313 moving w.r.t the systemic velocity frame)
314 reffreq Reference frequency of the output image coordinate system
316 Example : reffreq='1.5GHz' as a string with units.
318 By default, it is calculated as the middle of the selected frequency range.
320 For deconvolver='mtmfs' the Taylor expansion is also done about
321 this specified reference frequency.
322 nchan Number of channels in the output image
323 For default (=-1), the number of channels will be automatically determined
324 based on data selected by 'spw' with 'start' and 'width'.
325 It is often easiest to leave nchan at the default value.
326 example: nchan=100
327 start First channel (e.g. start=3,start=\'1.1GHz\',start=\'15343km/s\')
328 of output cube images specified by data channel number (integer),
329 velocity (string with a unit), or frequency (string with a unit).
330 Default:''; The first channel is automatically determined based on
331 the 'spw' channel selection and 'width'.
332 When the channel number is used along with the channel selection
333 in 'spw' (e.g. spw='0:6~100'),
334 'start' channel number is RELATIVE (zero-based) to the selected
335 channels in 'spw'. So for the above example,
336 start=1 means that the first image channel is the second selected
337 data channel, which is channel 7.
338 For specmode='cube', when velocity or frequency is used it is
339 interpreted with the frame defined in outframe. [The parameters of
340 the desired output cube can be estimated by using the 'transform'
341 functionality of 'plotms']
342 examples: start='5.0km/s'; 1st channel, 5.0km/s in outframe
343 start='22.3GHz'; 1st channel, 22.3GHz in outframe
344 width Channel width (e.g. width=2,width=\'0.1MHz\',width=\'10km/s\') of output cube images
345 specified by data channel number (integer), velocity (string with a unit), or
346 or frequency (string with a unit).
347 Default:''; data channel width
348 The sign of width defines the direction of the channels to be incremented.
349 For width specified in velocity or frequency with '-' in front gives image channels in
350 decreasing velocity or frequency, respectively.
351 For specmode='cube', when velocity or frequency is used it is interpreted with
352 the reference frame defined in outframe.
353 examples: width='2.0km/s'; results in channels with increasing velocity
354 width='-2.0km/s'; results in channels with decreasing velocity
355 width='40kHz'; results in channels with increasing frequency
356 width=-2; results in channels averaged of 2 data channels incremented from
357 high to low channel numbers
358 outframe Spectral reference frame in which to interpret \'start\' and \'width\'
359 Options: '','LSRK','LSRD','BARY','GEO','TOPO','GALACTO','LGROUP','CMB'
360 example: outframe='bary' for Barycentric frame
362 REST -- Rest frequency
363 LSRD -- Local Standard of Rest (J2000)
364 -- as the dynamical definition (IAU, [9,12,7] km/s in galactic coordinates)
365 LSRK -- LSR as a kinematical (radio) definition
366 -- 20.0 km/s in direction ra,dec = [270,+30] deg (B1900.0)
367 BARY -- Barycentric (J2000)
368 GEO --- Geocentric
369 TOPO -- Topocentric
370 GALACTO -- Galacto centric (with rotation of 220 km/s in direction l,b = [90,0] deg.
371 LGROUP -- Local group velocity -- 308km/s towards l,b = [105,-7] deg (F. Ghigo)
372 CMB -- CMB velocity -- 369.5km/s towards l,b = [264.4, 48.4] deg (F. Ghigo)
373 DEFAULT = LSRK
374 veltype Velocity type (radio, z, ratio, beta, gamma, optical)
375 For start and/or width specified in velocity, specifies the velocity definition
376 Options: 'radio','optical','z','beta','gamma','optical'
377 NOTE: the viewer always defaults to displaying the 'radio' frame,
378 but that can be changed in the position tracking pull down.
380 The different types (with F = f/f0, the frequency ratio), are:
382 Z = (-1 + 1/F)
383 RATIO = (F) \*
384 RADIO = (1 - F)
385 OPTICAL == Z
386 BETA = ((1 - F2)/(1 + F2))
387 GAMMA = ((1 + F2)/2F) \*
388 RELATIVISTIC == BETA (== v/c)
389 DEFAULT == RADIO
390 Note that the ones with an '\*' have no real interpretation
391 (although the calculation will proceed) if given as a velocity.
392 restfreq List of rest frequencies or a rest frequency in a string.
393 Specify rest frequency to use for output image.
394 Currently it uses the first rest frequency in the list for translation of
395 velocities. The list will be stored in the output images.
396 Default: []; look for the rest frequency stored in the MS, if not available,
397 use center frequency of the selected channels
398 examples: restfreq=['1.42GHz']
399 restfreq='1.42GHz'
400 interpolation Spectral interpolation (nearest,linear,cubic)
402 Interpolation rules to use when binning data channels onto image channels
403 and evaluating visibility values at the centers of image channels.
405 Note : 'linear' and 'cubic' interpolation requires data points on both sides of
406 each image frequency. Errors are therefore possible at edge channels, or near
407 flagged data channels. When image channel width is much larger than the data
408 channel width there is nothing much to be gained using linear or cubic thus
409 not worth the extra computation involved.
410 perchanweightdensity When calculating weight density for Briggs
411 style weighting in a cube, this parameter
412 determines whether to calculate the weight
413 density for each channel independently
414 (the default, True)
415 or a common weight density for all of the selected
416 data. This parameter has no
417 meaning for continuum (specmode='mfs')
418 imaging but for cube imaging
419 perchanweightdensity=True is a recommended
420 option that provides more uniform
421 sensitivity per channel for cubes, but with
422 generally larger psfs than the
423 perchanweightdensity=False (prior behavior)
424 option. When using Briggs style weight with
425 perchanweightdensity=True, the imaging weight
426 density calculations use only the weights of
427 data that contribute specifically to that
428 channel. On the other hand, when
429 perchanweightdensity=False, the imaging
430 weight density calculations sum all of the
431 weights from all of the data channels
432 selected whose (u,v) falls in a given uv cell
433 on the weight density grid. Since the
434 aggregated weights, in any given uv cell,
435 will change depending on the number of
436 channels included when imaging, the psf
437 calculated for a given frequency channel will
438 also necessarily change, resulting in
439 variability in the psf for a given frequency
440 channel when perchanweightdensity=False. In
441 general, perchanweightdensity=False results
442 in smaller psfs for the same value of
443 robustness compared to
444 perchanweightdensity=True, but the rms noise
445 as a function of channel varies and increases
446 toward the edge channels;
447 perchanweightdensity=True provides more
448 uniform sensitivity per channel for
449 cubes. This may make it harder to find
450 estimates of continuum when
451 perchanweightdensity=False. If you intend to
452 image a large cube in many smaller subcubes
453 and subsequently concatenate, it is advisable
454 to use perchanweightdensity=True to avoid
455 surprisingly varying sensitivity and psfs
456 across the concatenated cube.
457 gridder Gridding options (standard, wproject, widefield, mosaic, awproject)
459 The following options choose different gridding convolution
460 functions for the process of convolutional resampling of the measured
461 visibilities onto a regular uv-grid prior to an inverse FFT.
462 Model prediction (degridding) also uses these same functions.
463 Several wide-field effects can be accounted for via careful choices of
464 convolution functions. Gridding (degridding) runtime will rise in
465 proportion to the support size of these convolution functions (in uv-pixels).
467 standard : Prolate Spheroid with 3x3 uv pixel support size
469 [ This mode can also be invoked using 'ft' or 'gridft' ]
471 wproject : W-Projection algorithm to correct for the widefield
472 non-coplanar baseline effect. [Cornwell et.al 2008]
474 wprojplanes is the number of distinct w-values at
475 which to compute and use different gridding convolution
476 functions (see help for wprojplanes).
477 Convolution function support size can range
478 from 5x5 to few 100 x few 100.
480 [ This mode can also be invoked using 'wprojectft' ]
482 widefield : Facetted imaging with or without W-Projection per facet.
484 A set of facets x facets subregions of the specified image
485 are gridded separately using their respective phase centers
486 (to minimize max W). Deconvolution is done on the joint
487 full size image, using a PSF from the first subregion.
489 wprojplanes=1 : standard prolate spheroid gridder per facet.
490 wprojplanes > 1 : W-Projection gridder per facet.
491 nfacets=1, wprojplanes > 1 : Pure W-Projection and no facetting
492 nfacets=1, wprojplanes=1 : Same as standard,ft,gridft
494 A combination of facetting and W-Projection is relevant only for
495 very large fields of view.
497 mosaic : A-Projection with azimuthally symmetric beams without
498 sidelobes, beam rotation or squint correction.
499 Gridding convolution functions per visibility are computed
500 from FTs of PB models per antenna.
501 This gridder can be run on single fields as well as mosaics.
503 VLA : PB polynomial fit model (Napier and Rots, 1982)
504 EVLA : PB polynomial fit model (Perley, 2015)
505 ALMA : Airy disks for a 10.7m dish (for 12m dishes) and
506 6.25m dish (for 7m dishes) each with 0.75m
507 blockages (Hunter/Brogan 2011). Joint mosaic
508 imaging supports heterogeneous arrays for ALMA.
510 Typical gridding convolution function support sizes are
511 between 7 and 50 depending on the desired
512 accuracy (given by the uv cell size or image field of view).
514 [ This mode can also be invoked using 'mosaicft' or 'ftmosaic' ]
516 awproject : A-Projection with azimuthally asymmetric beams and
517 including beam rotation, squint correction,
518 conjugate frequency beams and W-projection.
519 [Bhatnagar et.al, 2008]
521 Gridding convolution functions are computed from
522 aperture illumination models per antenna and optionally
523 combined with W-Projection kernels and a prolate spheroid.
524 This gridder can be run on single fields as well as mosaics.
526 The awproject gridder is current not supported in the sdintimaging task.
527 This feature will be added in the near future.
529 VLA : Uses ray traced model (VLA and EVLA) including feed
530 leg and subreflector shadows, off-axis feed location
531 (for beam squint and other polarization effects), and
532 a Gaussian fit for the feed beams (Ref: Brisken 2009)
533 ALMA : Similar ray-traced model as above (but the correctness
534 of its polarization properties remains un-verified).
536 Typical gridding convolution function support sizes are
537 between 7 and 50 depending on the desired
538 accuracy (given by the uv cell size or image field of view).
539 When combined with W-Projection they can be significantly larger.
541 [ This mode can also be invoked using 'awprojectft' ]
543 imagemosaic : (untested implementation)
544 Grid and iFT each pointing separately and combine the
545 images as a linear mosaic (weighted by a PB model) in
546 the image domain before a joint minor cycle.
548 VLA/ALMA PB models are same as for gridder='mosaicft'
550 ------ Notes on PB models :
552 (1) Several different sources of PB models are used in the modes
553 listed above. This is partly for reasons of algorithmic flexibility
554 and partly due to the current lack of a common beam model
555 repository or consensus on what beam models are most appropriate.
557 (2) For ALMA and gridder='mosaic', ray-traced (TICRA) beams
558 are also available via the vpmanager tool.
559 For example, call the following before the sdintimaging run.
560 vp.setpbimage(telescope="ALMA",
561 compleximage='/home/casa/data/trunk/alma/responses/ALMA_0_DV__0_0_360_0_45_90_348.5_373_373_GHz_ticra2007_VP.im',
562 antnames=['DV'+'%02d'%k for k in range(25)])
563 vp.saveastable('mypb.tab')
564 Then, supply vptable='mypb.tab' to sdintimaging.
567 ------ Note on PB masks :
569 In sdintimaging, A-Projection gridders (mosaic and awproject) produce a
570 .pb image and use the 'pblimit' subparameter to decide normalization
571 cutoffs and construct an internal T/F mask in the .pb and .image images.
572 However, this T/F mask cannot directly be used during deconvolution
573 (which needs a 1/0 mask). There are two options for making a pb based
574 deconvolution mask.
575 -- Run sdintimaging with niter=0 to produce the .pb, construct a 1/0 image
576 with the desired threshold (using ia.open('newmask.im');
577 ia.calc('iif("xxx.pb">0.3,1.0,0.0)');ia.close() for example),
578 and supply it via the 'mask' parameter in a subsequent run
579 (with calcres=F and calcpsf=F to restart directly from the minor cycle).
580 -- Run sdintimaging with usemask='pb' for it to automatically construct
581 a 1/0 mask from the internal T/F mask from .pb at a fixed 0.2 threshold.
583 ----- Making PBs for gridders other than mosaic,awproject
585 After the PSF generation, a PB is constructed using the same
586 models used in gridder='mosaic' but just evaluated in the image
587 domain without consideration to weights.
588 facets Number of facets on a side
590 A set of (facets x facets) subregions of the specified image
591 are gridded separately using their respective phase centers
592 (to minimize max W). Deconvolution is done on the joint
593 full size image, using a PSF from the first subregion/facet.
594 psfphasecenter For mosaic use psf centered on this
595 optional direction. You may need to use
596 this if for example the mosaic does not
597 have any pointing in the center of the
598 image. Another reason; as the psf is
599 approximate for a mosaic, this may help
600 to deconvolve a non central bright source
601 well and quickly.
603 example:
605 psfphasecenter=6 #center psf on field 6
606 psfphasecenter='J2000 19h30m00 -40d00m00'
607 psfphasecenter='J2000 292.5deg -40.0deg'
608 psfphasecenter='J2000 5.105rad -0.698rad'
609 psfphasecenter='ICRS 13:05:27.2780 -049.28.04.458'
610 wprojplanes Number of distinct w-values at which to compute and use different
611 gridding convolution functions for W-Projection
613 An appropriate value of wprojplanes depends on the presence/absence
614 of a bright source far from the phase center, the desired dynamic
615 range of an image in the presence of a bright far out source,
616 the maximum w-value in the measurements, and the desired trade off
617 between accuracy and computing cost.
619 As a (rough) guide, VLA L-Band D-config may require a
620 value of 128 for a source 30arcmin away from the phase
621 center. A-config may require 1024 or more. To converge to an
622 appropriate value, try starting with 128 and then increasing
623 it if artifacts persist. W-term artifacts (for the VLA) typically look
624 like arc-shaped smears in a synthesis image or a shift in source
625 position between images made at different times. These artifacts
626 are more pronounced the further the source is from the phase center.
628 There is no harm in simply always choosing a large value (say, 1024)
629 but there will be a significant performance cost to doing so, especially
630 for gridder='awproject' where it is combined with A-Projection.
632 wprojplanes=-1 is an option for gridder='widefield' or 'wproject'
633 in which the number of planes is automatically computed.
634 vptable vpmanager
636 vptable="" : Choose default beams for different telescopes
637 ALMA : Airy disks
638 EVLA : old VLA models.
640 Other primary beam models can be chosen via the vpmanager tool.
642 Step 1 : Set up the vpmanager tool and save its state in a table
644 vp.setpbpoly(telescope='EVLA', coeff=[1.0, -1.529e-3, 8.69e-7, -1.88e-10])
645 vp.saveastable('myvp.tab')
647 Step 2 : Supply the name of that table in sdintimaging.
649 sdintimaging(....., vptable='myvp.tab',....)
651 Please see the documentation for the vpmanager for more details on how to
652 choose different beam models. Work is in progress to update the defaults
653 for EVLA and ALMA.
655 Note : AWProjection currently does not use this mechanism to choose
656 beam models. It instead uses ray-traced beams computed from
657 parameterized aperture illumination functions, which are not
658 available via the vpmanager. So, gridder='awproject' does not allow
659 the user to set this parameter.
660 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.
661 aterm Use aperture illumination functions during gridding
663 This parameter turns on the A-term of the AW-Projection gridder.
664 Gridding convolution functions are constructed from aperture illumination
665 function models of each antenna.
666 psterm Include the Prolate Spheroidal (PS) funtion as the anti-aliasing
667 operator in the gridding convolution functions used for gridding.
669 Setting this parameter to true is necessary when aterm is set to
670 false. It can be set to false when aterm is set to true, though
671 with this setting effects of aliasing may be there in the image,
672 particularly near the edges.
674 When set to true, the .pb images will contain the fourier transform
675 of the of the PS funtion. The table below enumarates the functional
676 effects of the psterm, aterm and wprojplanes settings. PB referes to
677 the Primary Beam and FT() refers to the Fourier transform operation.
679 Operation aterm psterm wprojplanes Contents of the .pb image
680 ----------------------------------------------------------------------
681 AW-Projection True True >1 FT(PS) x PB
682 False PB
684 A-Projection True True 1 FT(PS) x PB
685 False PB
687 W-Projection False True >1 FT(PS)
689 Standard False True 1 FT(PS)
690 wbawp Use frequency dependent A-terms
691 Scale aperture illumination functions appropriately with frequency
692 when gridding and combining data from multiple channels.
693 cfcache Convolution function cache directory name
695 Name of a directory in which to store gridding convolution functions.
696 This cache is filled at the beginning of an imaging run. This step can be time
697 consuming but the cache can be reused across multiple imaging runs that
698 use the same image parameters (cell size, image size , spectral data
699 selections, wprojplanes, wbawp, psterm, aterm). The effect of the wbawp,
700 psterm and aterm settings is frozen-in in the cfcache. Using an existing cfcache
701 made with a different setting of these parameters will not reflect the current
702 settings.
704 In a parallel execution, the construction of the cfcache is also parallelized
705 and the time to compute scales close to linearly with the number of compute
706 cores used. With the re-computation of Convolution Functions (CF) due to PA
707 rotation turned-off (the computepastep parameter), the total number of in the
708 cfcache can be computed as [No. of wprojplanes x No. of selected spectral windows x 4]
710 By default, cfcache = imagename + '.cf'
711 usepointing The usepointing flag informs the gridder that it should utilize the pointing table
712 to use the correct direction in which the antenna is pointing with respect to the pointing phasecenter.
713 computepastep Parallactic angle interval after the AIFs are recomputed (deg)
715 This parameter controls the accuracy of the aperture illumination function
716 used with AProjection for alt-az mount dishes where the AIF rotates on the
717 sky as the synthesis image is built up. Once the PA in the data changes by
718 the given interval, AIFs are re-computed at the new PA.
720 A value of 360.0 deg (the default) implies no re-computation due to PA rotation.
721 AIFs are computed for the PA value of the first valid data received and used for
722 all of the data.
723 rotatepastep Parallactic angle interval after which the nearest AIF is rotated (deg)
725 Instead of recomputing the AIF for every timestep's parallactic angle,
726 the nearest existing AIF is used and rotated
727 after the PA changed by rotatepastep value.
729 A value of 360.0 deg (the default) disables rotation of the AIF.
731 For example, computepastep=360.0 and rotatepastep=5.0 will compute
732 the AIFs at only the starting parallactic angle and all other timesteps will
733 use a rotated version of that AIF at the nearest 5.0 degree point.
734 pointingoffsetsigdev Corrections for heterogenous and time-dependent pointing
735 offsets via AWProjection are controlled by this parameter.
736 It is a vector of 2 ints or doubles each of which is interpreted
737 in units of arcsec. Based on the first threshold, a clustering
738 algorithm is applied to entries from the POINTING subtable
739 of the MS to determine how distinct antenna groups for which
740 the pointing offset must be computed separately. The second
741 number controls how much a pointing change across time can
742 be ignored and after which an antenna rebinning is required.
745 Note : The default value of this parameter is [], due a programmatic constraint.
746 If run with this value, it will internally pick [600,600] and exercise the
747 option of using large tolerances (10arcmin) on both axes. Please choose
748 a setting explicitly for runs that need to use this parameter.
750 Note : This option is available only for gridder='awproject' and usepointing=True and
751 and has been validated primarily with VLASS on-the-fly mosaic data
752 where POINTING subtables have been modified after the data are recorded.
755 Examples of parameter usage :
757 [100.0,100.0] : Pointing offsets of 100 arcsec or less are considered
758 small enough to be ignored. Using large values for both
759 indicates a homogeneous array.
762 [10.0, 100.0] : Based on entries in the POINTING subtable, antennas
763 are grouped into clusters based on a 10arcsec bin size.
764 All antennas in a bin are given a pointing offset calculated
765 as the average of the offsets of all antennas in the bin.
766 On the time axis, offset changes upto 100 arcsec will be ignored.
768 [10.0,10.0] : Calculate separate pointing offsets for each antenna group
769 (with a 10 arcsec bin size). As a function of time, recalculate
770 the antenna binning if the POINTING table entries change by
771 more than 10 arcsec w.r.to the previously computed binning.
773 [1.0, 1.0] : Tight tolerances will imply a fully heterogenous situation where
774 each antenna gets its own pointing offset. Also, time-dependent
775 offset changes greater than 1 arcsec will trigger recomputes of
776 the phase gradients. This is the most general situation and is also
777 the most expensive option as it constructs and uses separate
778 phase gradients for all baselines and timesteps.
780 For VLASS 1.1 data with two kinds of pointing offsets, the recommended
781 setting is [ 30.0, 30.0 ].
783 For VLASS 1.2 data with only the time-dependent pointing offsets, the
784 recommended setting is [ 300.0, 30.0 ] to turn off the antenna grouping
785 but to retain the time dependent corrections required from one timestep
786 to the next.
787 pblimit PB gain level at which to cut off normalizations
789 Divisions by .pb during normalizations have a cut off at a .pb gain
790 level given by pblimit. Outside this limit, image values are set to zero.
791 Additionally, by default, an internal T/F mask is applied to the .pb, .image and
792 .residual images to mask out (T) all invalid pixels outside the pblimit area.
794 Note : This internal T/F mask cannot be used as a deconvolution mask.
795 To do so, please follow the steps listed above in the Notes for the
796 'gridder' parameter.
798 Note : To prevent the internal T/F mask from appearing in anything other
799 than the .pb and .image.pbcor images, 'pblimit' can be set to a
800 negative number. The absolute value will still be used as a valid 'pblimit'.
801 A sdintimaging restart using existing output images on disk that already
802 have this T/F mask in the .residual and .image but only pblimit set
803 to a negative value, will remove this mask after the next major cycle.
804 deconvolver Name of minor cycle algorithm (hogbom,clark,multiscale,mtmfs,mem,clarkstokes,asp)
806 Each of the following algorithms operate on residual images and psfs
807 from the gridder and produce output model and restored images.
808 Minor cycles stop and a major cycle is triggered when cyclethreshold
809 or cycleniter are reached. For all methods, components are picked from
810 the entire extent of the image or (if specified) within a mask.
812 hogbom : An adapted version of Hogbom Clean [Hogbom, 1974]
813 - Find the location of the peak residual
814 - Add this delta function component to the model image
815 - Subtract a scaled and shifted PSF of the same size as the image
816 from regions of the residual image where the two overlap.
817 - Repeat
819 clark : An adapted version of Clark Clean [Clark, 1980]
820 - Find the location of max(I^2+Q^2+U^2+V^2)
821 - Add delta functions to each stokes plane of the model image
822 - Subtract a scaled and shifted PSF within a small patch size
823 from regions of the residual image where the two overlap.
824 - After several iterations trigger a Clark major cycle to subtract
825 components from the visibility domain, but without de-gridding.
826 - Repeat
828 ( Note : 'clark' maps to imagermode='' in the old clean task.
829 'clark_exp' is another implementation that maps to
830 imagermode='mosaic' or 'csclean' in the old clean task
831 but the behavior is not identical. For now, please
832 use deconvolver='hogbom' if you encounter problems. )
834 clarkstokes : Clark Clean operating separately per Stokes plane
836 (Note : 'clarkstokes_exp' is an alternate version. See above.)
838 multiscale : MultiScale Clean [Cornwell, 2008]
839 - Smooth the residual image to multiple scale sizes
840 - Find the location and scale at which the peak occurs
841 - Add this multiscale component to the model image
842 - Subtract a scaled,smoothed,shifted PSF (within a small
843 patch size per scale) from all residual images
844 - Repeat from step 2
846 mtmfs : Multi-term (Multi Scale) Multi-Frequency Synthesis [Rau and Cornwell, 2011]
847 - Smooth each Taylor residual image to multiple scale sizes
848 - Solve a NTxNT system of equations per scale size to compute
849 Taylor coefficients for components at all locations
850 - Compute gradient chi-square and pick the Taylor coefficients
851 and scale size at the location with maximum reduction in
852 chi-square
853 - Add multi-scale components to each Taylor-coefficient
854 model image
855 - Subtract scaled,smoothed,shifted PSF (within a small patch size
856 per scale) from all smoothed Taylor residual images
857 - Repeat from step 2
860 mem : Maximum Entropy Method [Cornwell and Evans, 1985]
861 - Iteratively solve for values at all individual pixels via the
862 MEM method. It minimizes an objective function of
863 chi-square plus entropy (here, a measure of difference
864 between the current model and a flat prior model).
866 (Note : This MEM implementation is not very robust.
867 Improvements will be made in the future.)
869 asp : ASP Clean [Bhatnagar and Cornwell, 2004]
870 scales List of scale sizes (in pixels) for multi-scale and mtmfs algorithms.
871 --> scales=[0,6,20]
872 This set of scale sizes should represent the sizes
873 (diameters in units of number of pixels)
874 of dominant features in the image being reconstructed.
876 The smallest scale size is recommended to be 0 (point source),
877 the second the size of the synthesized beam and the third 3-5
878 times the synthesized beam, etc. For example, if the synthesized
879 beam is 10" FWHM and cell=2",try scales = [0,5,15].
881 For numerical stability, the largest scale must be
882 smaller than the image (or mask) size and smaller than or
883 comparable to the scale corresponding to the lowest measured
884 spatial frequency (as a scale size much larger than what the
885 instrument is sensitive to is unconstrained by the data making
886 it harder to recovery from errors during the minor cycle).
887 nterms Number of Taylor coefficients in the spectral model
889 - nterms=1 : Assume flat spectrum source
890 - nterms=2 : Spectrum is a straight line with a slope
891 - nterms=N : A polynomial of order N-1
893 From a Taylor expansion of the expression of a power law, the
894 spectral index is derived as alpha = taylorcoeff_1 / taylorcoeff_0
896 Spectral curvature is similarly derived when possible.
898 The optimal number of Taylor terms depends on the available
899 signal to noise ratio, bandwidth ratio, and spectral shape of the
900 source as seen by the telescope (sky spectrum x PB spectrum).
902 nterms=2 is a good starting point for wideband EVLA imaging
903 and the lower frequency bands of ALMA (when fractional bandwidth
904 is greater than 10%) and if there is at least one bright source for
905 which a dynamic range of greater than few 100 is desired.
907 Spectral artifacts for the VLA often look like spokes radiating out from
908 a bright source (i.e. in the image made with standard mfs imaging).
909 If increasing the number of terms does not eliminate these artifacts,
910 check the data for inadequate bandpass calibration. If the source is away
911 from the pointing center, consider including wide-field corrections too.
913 (Note : In addition to output Taylor coefficient images .tt0,.tt1,etc
914 images of spectral index (.alpha), an estimate of error on
915 spectral index (.alpha.error) and spectral curvature (.beta,
916 if nterms is greater than 2) are produced.
917 - These alpha, alpha.error and beta images contain
918 internal T/F masks based on a threshold computed
919 as peakresidual/10. Additional masking based on
920 .alpha/.alpha.error may be desirable.
921 - .alpha.error is a purely empirical estimate derived
922 from the propagation of error during the division of
923 two noisy numbers (alpha = xx.tt1/xx.tt0) where the
924 'error' on tt1 and tt0 are simply the values picked from
925 the corresponding residual images. The absolute value
926 of the error is not always accurate and it is best to interpret
927 the errors across the image only in a relative sense.)
928 smallscalebias A numerical control to bias the scales when using multi-scale or mtmfs algorithms.
929 The peak from each scale's smoothed residual is
930 multiplied by ( 1 - smallscalebias \* scale/maxscale )
931 to increase or decrease the amplitude relative to other scales,
932 before the scale with the largest peak is chosen.
933 Smallscalebias can be varied between -1.0 and 1.0.
934 A score of 0.0 gives all scales equal weight (default).
935 A score larger than 0.0 will bias the solution towards smaller scales.
936 A score smaller than 0.0 will bias the solution towards larger scales.
937 The effect of smallscalebias is more pronounced when using multi-scale relative to mtmfs.
938 restoration e.
940 Construct a restored image : imagename.image by convolving the model
941 image with a clean beam and adding the residual image to the result.
942 If a restoringbeam is specified, the residual image is also
943 smoothed to that target resolution before adding it in.
945 If a .model does not exist, it will make an empty one and create
946 the restored image from the residuals ( with additional smoothing if needed ).
947 With algorithm='mtmfs', this will construct Taylor coefficient maps from
948 the residuals and compute .alpha and .alpha.error.
949 restoringbeam ize to use.
951 - restoringbeam='' or ['']
952 A Gaussian fitted to the PSF main lobe (separately per image plane).
954 - restoringbeam='10.0arcsec'
955 Use a circular Gaussian of this width for all planes
957 - restoringbeam=['8.0arcsec','10.0arcsec','45deg']
958 Use this elliptical Gaussian for all planes
960 - restoringbeam='common'
961 Automatically estimate a common beam shape/size appropriate for
962 all planes.
964 Note : For any restoring beam different from the native resolution
965 the model image is convolved with the beam and added to
966 residuals that have been convolved to the same target resolution.
967 pbcor the output restored image
969 A new image with extension .image.pbcor will be created from
970 the evaluation of .image / .pb for all pixels above the specified pblimit.
972 Note : Stand-alone PB-correction can be triggered by re-running
973 sdintimaging with the appropriate imagename and with
974 niter=0, calcpsf=False, calcres=False, pbcor=True, vptable='vp.tab'
975 ( where vp.tab is the name of the vpmanager file.
976 See the inline help for the 'vptable' parameter )
978 Note : Multi-term PB correction that includes a correction for the
979 spectral index of the PB has not been enabled for the 4.7 release.
980 Please use the widebandpbcor task instead.
981 ( Wideband PB corrections are required when the amplitude of the
982 brightest source is known accurately enough to be sensitive
983 to the difference in the PB gain between the upper and lower
984 end of the band at its location. As a guideline, the artificial spectral
985 index due to the PB is -1.4 at the 0.5 gain level and less than -0.2
986 at the 0.9 gain level at the middle frequency )
987 weighting Weighting scheme (natural,uniform,briggs,superuniform,radial, briggsabs)
989 During gridding of the dirty or residual image, each visibility value is
990 multiplied by a weight before it is accumulated on the uv-grid.
991 The PSF's uv-grid is generated by gridding only the weights (weightgrid).
993 weighting='natural' : Gridding weights are identical to the data weights
994 from the MS. For visibilities with similar data weights,
995 the weightgrid will follow the sample density
996 pattern on the uv-plane. This weighting scheme
997 provides the maximum imaging sensitivity at the
998 expense of a possibly fat PSF with high sidelobes.
999 It is most appropriate for detection experiments
1000 where sensitivity is most important.
1002 weighting='uniform' : Gridding weights per visibility data point are the
1003 original data weights divided by the total weight of
1004 all data points that map to the same uv grid cell :
1005 ' data_weight / total_wt_per_cell '.
1007 The weightgrid is as close to flat as possible resulting
1008 in a PSF with a narrow main lobe and suppressed
1009 sidelobes. However, since heavily sampled areas of
1010 the uv-plane get down-weighted, the imaging
1011 sensitivity is not as high as with natural weighting.
1012 It is most appropriate for imaging experiments where
1013 a well behaved PSF can help the reconstruction.
1015 weighting='briggs' : Gridding weights per visibility data point are given by
1016 'data_weight / ( A \* total_wt_per_cell + B ) ' where
1017 A and B vary according to the 'robust' parameter.
1019 robust = -2.0 maps to A=1,B=0 or uniform weighting.
1020 robust = +2.0 maps to natural weighting.
1021 (robust=0.5 is equivalent to robust=0.0 in AIPS IMAGR.)
1023 Robust/Briggs weighting generates a PSF that can
1024 vary smoothly between 'natural' and 'uniform' and
1025 allow customized trade-offs between PSF shape and
1026 imaging sensitivity.
1027 weighting='briggsabs' : Experimental option.
1028 Same as Briggs except the formula is different A=
1029 robust\*robust and B is dependent on the
1030 noise per visibility estimated. Giving noise='0Jy'
1031 is a not a reasonable option.
1032 In this mode (or formula) robust values
1033 from -2.0 to 0.0 only make sense (2.0 and
1034 -2.0 will get the same weighting)
1036 weighting='superuniform' : This is similar to uniform weighting except that
1037 the total_wt_per_cell is replaced by the
1038 total_wt_within_NxN_cells around the uv cell of
1039 interest. ( N = subparameter 'npixels' )
1041 This method tends to give a PSF with inner
1042 sidelobes that are suppressed as in uniform
1043 weighting but with far-out sidelobes closer to
1044 natural weighting. The peak sensitivity is also
1045 closer to natural weighting.
1047 weighting='radial' : Gridding weights are given by ' data_weight \* uvdistance '
1049 This method approximately minimizes rms sidelobes
1050 for an east-west synthesis array.
1052 weighting='briggsbwtaper' : A modified version of Briggs weighting for cubes where an inverse uv taper,
1053 which is proportional to the fractional bandwidth of the entire cube,
1054 is applied per channel. The objective is to modify cube (perchanweightdensity = True)
1055 imaging weights to have a similar density to that of the continuum imaging weights.
1056 This is currently an experimental weighting scheme being developed for ALMA.
1059 For more details on weighting please see Chapter3
1060 of Dan Briggs' thesis (http://www.aoc.nrao.edu/dissertations/dbriggs)
1061 robust Robustness parameter for Briggs weighting.
1063 robust = -2.0 maps to uniform weighting.
1064 robust = +2.0 maps to natural weighting.
1065 (robust=0.5 is equivalent to robust=0.0 in AIPS IMAGR.)
1066 noise noise parameter for briggs abs mode weighting
1067 npixels Number of pixels to determine uv-cell size for super-uniform weighting
1068 (0 defaults to -/+ 3 pixels)
1070 npixels -- uv-box used for weight calculation
1071 a box going from -npixel/2 to +npixel/2 on each side
1072 around a point is used to calculate weight density.
1074 npixels=2 goes from -1 to +1 and covers 3 pixels on a side.
1076 npixels=0 implies a single pixel, which does not make sense for
1077 superuniform weighting. Therefore, if npixels=0 it will
1078 be forced to 6 (or a box of -3pixels to +3pixels) to cover
1079 7 pixels on a side.
1080 uvtaper uv-taper on outer baselines in uv-plane
1082 Apply a Gaussian taper in addition to the weighting scheme specified
1083 via the 'weighting' parameter. Higher spatial frequencies are weighted
1084 down relative to lower spatial frequencies to suppress artifacts
1085 arising from poorly sampled areas of the uv-plane. It is equivalent to
1086 smoothing the PSF obtained by other weighting schemes and can be
1087 specified either as a Gaussian in uv-space (eg. units of lambda)
1088 or as a Gaussian in the image domain (eg. angular units like arcsec).
1090 uvtaper = [bmaj, bmin, bpa]
1092 NOTE: the on-sky FWHM in arcsec is roughly the uv taper/200 (klambda).
1093 default: uvtaper=[]; no Gaussian taper applied
1094 example: uvtaper=['5klambda'] circular taper
1095 FWHM=5 kilo-lambda
1096 uvtaper=['5klambda','3klambda','45.0deg']
1097 uvtaper=['10arcsec'] on-sky FWHM 10 arcseconds
1098 uvtaper=['300.0'] default units are lambda
1099 in aperture plane
1100 niter Maximum number of iterations
1102 A stopping criterion based on total iteration count.
1103 Currently the parameter type is defined as an integer therefore the integer value
1104 larger than 2147483647 will not be set properly as it causes an overflow.
1106 Iterations are typically defined as the selecting one flux component
1107 and partially subtracting it out from the residual image.
1109 niter=0 : Do only the initial major cycle (make dirty image, psf, pb, etc)
1111 niter larger than zero : Run major and minor cycles.
1113 Note : Global stopping criteria vs major-cycle triggers
1115 In addition to global stopping criteria, the following rules are
1116 used to determine when to terminate a set of minor cycle iterations
1117 and trigger major cycles [derived from Cotton-Schwab Clean, 1984]
1119 'cycleniter' : controls the maximum number of iterations per image
1120 plane before triggering a major cycle.
1121 'cyclethreshold' : Automatically computed threshold related to the
1122 max sidelobe level of the PSF and peak residual.
1123 Divergence, detected as an increase of 10% in peak residual from the
1124 minimum so far (during minor cycle iterations)
1126 The first criterion to be satisfied takes precedence.
1128 Note : Iteration counts for cubes or multi-field images :
1129 For images with multiple planes (or image fields) on which the
1130 deconvolver operates in sequence, iterations are counted across
1131 all planes (or image fields). The iteration count is compared with
1132 'niter' only after all channels/planes/fields have completed their
1133 minor cycles and exited either due to 'cycleniter' or 'cyclethreshold'.
1134 Therefore, the actual number of iterations reported in the logger
1135 can sometimes be larger than the user specified value in 'niter'.
1136 For example, with niter=100, cycleniter=20,nchan=10,threshold=0,
1137 a total of 200 iterations will be done in the first set of minor cycles
1138 before the total is compared with niter=100 and it exits.
1140 Note : Additional global stopping criteria include
1141 - no change in peak residual across two major cycles
1142 - a 50% or more increase in peak residual across one major cycle
1143 gain Loop gain
1145 Fraction of the source flux to subtract out of the residual image
1146 for the CLEAN algorithm and its variants.
1148 A low value (0.2 or less) is recommended when the sky brightness
1149 distribution is not well represented by the basis functions used by
1150 the chosen deconvolution algorithm. A higher value can be tried when
1151 there is a good match between the true sky brightness structure and
1152 the basis function shapes. For example, for extended emission,
1153 multiscale clean with an appropriate set of scale sizes will tolerate
1154 a higher loop gain than Clark clean (for example).
1155 threshold Stopping threshold (number in units of Jy, or string)
1157 A global stopping threshold that the peak residual (within clean mask)
1158 across all image planes is compared to.
1160 threshold = 0.005 : 5mJy
1161 threshold = '5.0mJy'
1163 Note : A 'cyclethreshold' is internally computed and used as a major cycle
1164 trigger. It is related what fraction of the PSF can be reliably
1165 used during minor cycle updates of the residual image. By default
1166 the minor cycle iterations terminate once the peak residual reaches
1167 the first sidelobe level of the brightest source.
1169 'cyclethreshold' is computed as follows using the settings in
1170 parameters 'cyclefactor','minpsffraction','maxpsffraction','threshold' :
1172 psf_fraction = max_psf_sidelobe_level \* 'cyclefactor'
1173 psf_fraction = max(psf_fraction, 'minpsffraction');
1174 psf_fraction = min(psf_fraction, 'maxpsffraction');
1175 cyclethreshold = peak_residual \* psf_fraction
1176 cyclethreshold = max( cyclethreshold, 'threshold' )
1178 If nsigma is set (>0.0), the N-sigma threshold is calculated (see
1179 the description under nsigma), then cyclethreshold is further modified as,
1181 cyclethreshold = max( cyclethreshold, nsgima_threshold )
1184 'cyclethreshold' is made visible and editable only in the
1185 interactive GUI when sdintimaging is run with interactive=True.
1186 nsigma Multiplicative factor for rms-based threshold stopping
1188 N-sigma threshold is calculated as nsigma \* rms value per image plane determined
1189 from a robust statistics. For nsigma > 0.0, in a minor cycle, a maximum of the two values,
1190 the N-sigma threshold and cyclethreshold, is used to trigger a major cycle
1191 (see also the descreption under 'threshold').
1192 Set nsigma=0.0 to preserve the previous sdintimaging behavior without this feature.
1193 The top level parameter, fastnoise is relevant for the rms noise calculation which is used
1194 to determine the threshold.
1195 cycleniter Maximum number of minor-cycle iterations (per plane) before triggering
1196 a major cycle
1198 For example, for a single plane image, if niter=100 and cycleniter=20,
1199 there will be 5 major cycles after the initial one (assuming there is no
1200 threshold based stopping criterion). At each major cycle boundary, if
1201 the number of iterations left over (to reach niter) is less than cycleniter,
1202 it is set to the difference.
1204 Note : cycleniter applies per image plane, even if cycleniter x nplanes
1205 gives a total number of iterations greater than 'niter'. This is to
1206 preserve consistency across image planes within one set of minor
1207 cycle iterations.
1208 cyclefactor Scaling on PSF sidelobe level to compute the minor-cycle stopping threshold.
1210 Please refer to the Note under the documentation for 'threshold' that
1211 discussed the calculation of 'cyclethreshold'
1213 cyclefactor=1.0 results in a cyclethreshold at the first sidelobe level of
1214 the brightest source in the residual image before the minor cycle starts.
1216 cyclefactor=0.5 allows the minor cycle to go deeper.
1217 cyclefactor=2.0 triggers a major cycle sooner.
1218 minpsffraction PSF fraction that marks the max depth of cleaning in the minor cycle
1220 Please refer to the Note under the documentation for 'threshold' that
1221 discussed the calculation of 'cyclethreshold'
1223 For example, minpsffraction=0.5 will stop cleaning at half the height of
1224 the peak residual and trigger a major cycle earlier.
1225 maxpsffraction PSF fraction that marks the minimum depth of cleaning in the minor cycle
1227 Please refer to the Note under the documentation for 'threshold' that
1228 discussed the calculation of 'cyclethreshold'
1230 For example, maxpsffraction=0.8 will ensure that at least the top 20
1231 percent of the source will be subtracted out in the minor cycle even if
1232 the first PSF sidelobe is at the 0.9 level (an extreme example), or if the
1233 cyclefactor is set too high for anything to get cleaned.
1234 interactive Modify masks and parameters at runtime
1236 interactive=True will trigger an interactive GUI at every major cycle
1237 boundary (after the major cycle and before the minor cycle).
1239 Options for runtime parameter modification are :
1241 Interactive clean mask : Draw a 1/0 mask (appears as a contour) by hand.
1242 If a mask is supplied at the task interface or if
1243 automasking is invoked, the current mask is
1244 displayed in the GUI and is available for manual
1245 editing.
1247 Note : If a mask contour is not visible, please
1248 check the cursor display at the bottom of
1249 GUI to see which parts of the mask image
1250 have ones and zeros. If the entire mask=1
1251 no contours will be visible.
1254 Operation buttons : -- Stop execution now (restore current model and exit)
1255 -- Continue on until global stopping criteria are reached
1256 without stopping for any more interaction
1257 -- Continue with minor cycles and return for interaction
1258 after the next major cycle.
1260 Iteration control : -- max cycleniter : Trigger for the next major cycle
1262 The display begins with
1263 [ min( cycleniter, niter - itercount ) ]
1264 and can be edited by hand.
1266 -- iterations left : The display begins with [niter-itercount ]
1267 and can be edited to increase or
1268 decrease the total allowed niter.
1270 -- threshold : Edit global stopping threshold
1272 -- cyclethreshold : The display begins with the
1273 automatically computed value
1274 (see Note in help for 'threshold'),
1275 and can be edited by hand.
1277 All edits will be reflected in the log messages that appear
1278 once minor cycles begin.
1279 fullsummary Return dictionary with complete convergence history
1281 fullsummary=True: A full version of the summary dictionary is returned.
1282 Keys include 'iterDone','peakRes','modelFlux','cycleThresh' that record the
1283 convergence state at the end of each set of minor cycle iterations
1284 separately for each image plane (i.e. channel/stokes) being
1285 deconvolved. Additional keys report the convergence state at the
1286 start of minor cycle iterations, stopping criteria that triggered major
1287 cycles, and a processor ID per channel, for parallel cube runs.
1289 fullsummary=False (default): A shorten version of the summary dictionary is returned
1290 with only 'iterDone','peakRes','modelFlux', and 'cycleThresh'.
1292 Detailed information about the return dictionary fields may be found
1293 at CASA Docs > Synthesis Imaging > Iteration Control > Returned Dictionary.
1294 nmajor The nmajor parameter limits the number of minor and major cycle sets
1295 that sdintimaging executes. It is defined as the number of major cycles after the
1296 initial set of minor cycle iterations. The count of nmajor does
1297 not include the initial residual calculation that occurs when calcres=True.
1299 A setting of nmajor=-1 implies no limit (default -1).
1300 A setting of nmajor=0 implies nothing other than the initial residual calculation
1301 A setting of nmajor>0 imples that nmajor sets of minor and major cycles will
1302 be done in addition to the initial residual calculation.
1304 If the major cycle limit is reached, stopcode 9 will be returned. Other stopping
1305 criteria (such as threshold) could cause sdintimaging to stop in fewer than this
1306 number of major cycles. If sdintimaging reaches another stopping criteria, first
1307 or at the same time as nmajor, then that stopcode will be returned instead.
1309 Note however that major cycle ids in the log messages as well as in the return
1310 dictionary do begin with 1 for the initial residual calculation, when it exists.
1312 Example 1 : A run with 'nmajor=5' and 'calcres=True' will iterate for
1313 5 major cycles (not counting the initial residual calculation). But, the return
1314 dictionary will show 'nmajordone:6'. If 'calcres=False', then the return
1315 dictionary will show 'nmajordone:5'.
1317 Example 2 : For both the following cases, there will be a printout in the logs
1318 "Running Major Cycle 1" and the return value will include "nmajordone: 1",
1319 however there is a difference in the purpose of the major cycle and the
1320 number of minor cycles executed:
1321 Case 1; nmajor=0, calcres=True: The major cycle done is for the creation
1322 of the residual, and no minor cycles are executed.
1323 Case 2; nmajor=1, calcres=False: The major cycle is done as part of the
1324 major/minor cycle loop, and 1 minor cycle will be executed.
1326 Note : For sdintimaging, the 'nmajor' parameter is not implemented for
1327 usedata='sdonly'. Other stopping criteria still apply as usual.
1328 usemask Type of mask(s) to be used for deconvolution
1330 user: (default) mask image(s) or user specified region file(s) or string CRTF expression(s)
1331 subparameters: mask, pbmask
1332 pb: primary beam mask
1333 subparameter: pbmask
1335 Example: usemask="pb", pbmask=0.2
1336 Construct a mask at the 0.2 pb gain level.
1337 (Currently, this option will work only with
1338 gridders that produce .pb (i.e. mosaic and awproject)
1339 or if an externally produced .pb image exists on disk)
1341 auto-multithresh : auto-masking by multiple thresholds for deconvolution
1342 subparameters : sidelobethreshold, noisethreshold, lownoisethreshold, negativethrehsold, smoothfactor,
1343 minbeamfrac, cutthreshold, pbmask, growiterations, dogrowprune, minpercentchange, verbose
1344 Additional top level parameter relevant to auto-multithresh: fastnoise
1346 if pbmask is >0.0, the region outside the specified pb gain level is excluded from
1347 image statistics in determination of the threshold.
1352 Note: By default the intermediate mask generated by automask at each deconvolution cycle
1353 is over-written in the next cycle but one can save them by setting
1354 the environment variable, SAVE_ALL_AUTOMASKS="true".
1355 (e.g. in the CASA prompt, os.environ['SAVE_ALL_AUTOMASKS']="true" )
1356 The saved CASA mask image name will be imagename.mask.autothresh#, where
1357 # is the iteration cycle number.
1358 mask Mask (a list of image name(s) or region file(s) or region string(s)
1361 The name of a CASA image or region file or region string that specifies
1362 a 1/0 mask to be used for deconvolution. Only locations with value 1 will
1363 be considered for the centers of flux components in the minor cycle.
1364 If regions specified fall completely outside of the image, sdintimaging will throw an error.
1366 Manual mask options/examples :
1368 mask='xxx.mask' : Use this CASA image named xxx.mask and containing
1369 ones and zeros as the mask.
1370 If the mask is only different in spatial coordinates from what is being made
1371 it will be resampled to the target coordinate system before being used.
1372 The mask has to have the same shape in velocity and Stokes planes
1373 as the output image. Exceptions are single velocity and/or single
1374 Stokes plane masks. They will be expanded to cover all velocity and/or
1375 Stokes planes of the output cube.
1377 [ Note : If an error occurs during image resampling or
1378 if the expected mask does not appear, please try
1379 using tasks 'imregrid' or 'makemask' to resample
1380 the mask image onto a CASA image with the target
1381 shape and coordinates and supply it via the 'mask'
1382 parameter. ]
1385 mask='xxx.crtf' : A text file with region strings and the following on the first line
1386 ( #CRTFv0 CASA Region Text Format version 0 )
1387 This is the format of a file created via the viewer's region
1388 tool when saved in CASA region file format.
1390 mask='circle[[40pix,40pix],10pix]' : A CASA region string.
1392 mask=['xxx.mask','xxx.crtf', 'circle[[40pix,40pix],10pix]'] : a list of masks
1398 Note : Mask images for deconvolution must contain 1 or 0 in each pixel.
1399 Such a mask is different from an internal T/F mask that can be
1400 held within each CASA image. These two types of masks are not
1401 automatically interchangeable, so please use the makemask task
1402 to copy between them if you need to construct a 1/0 based mask
1403 from a T/F one.
1405 Note : Work is in progress to generate more flexible masking options and
1406 enable more controls.
1407 pbmask Sub-parameter for usemask: primary beam mask
1409 Examples : pbmask=0.0 (default, no pb mask)
1410 pbmask=0.2 (construct a mask at the 0.2 pb gain level)
1411 sidelobethreshold Sub-parameter for "auto-multithresh": mask threshold based on sidelobe levels: sidelobethreshold \* max_sidelobe_level \* peak residual
1412 noisethreshold Sub-parameter for "auto-multithresh": mask threshold based on the noise level: noisethreshold \* rms + location (=median)
1414 The rms is calculated from MAD with rms = 1.4826\*MAD.
1415 lownoisethreshold Sub-parameter for "auto-multithresh": mask threshold to grow previously masked regions via binary dilation: lownoisethreshold \* rms in residual image + location (=median)
1417 The rms is calculated from MAD with rms = 1.4826\*MAD.
1418 negativethreshold Sub-parameter for "auto-multithresh": mask threshold for negative features: -1.0* negativethreshold \* rms + location(=median)
1420 The rms is calculated from MAD with rms = 1.4826\*MAD.
1421 smoothfactor Sub-parameter for "auto-multithresh": smoothing factor in a unit of the beam
1422 minbeamfrac Sub-parameter for "auto-multithresh": minimum beam fraction in size to prune masks smaller than mimbeamfrac \* beam
1423 <=0.0 : No pruning
1424 cutthreshold Sub-parameter for "auto-multithresh": threshold to cut the smoothed mask to create a final mask: cutthreshold \* peak of the smoothed mask
1425 growiterations Sub-parameter for "auto-multithresh": Maximum number of iterations to perform using binary dilation for growing the mask
1426 dogrowprune Experimental sub-parameter for "auto-multithresh": Do pruning on the grow mask
1427 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.
1428 verbose he summary of automasking at the end of each automasking process
1429 is printed in the logger. Following information per channel will be listed in the summary.
1431 chan: channel number
1432 masking?: F - stop updating automask for the subsequent iteration cycles
1433 RMS: robust rms noise
1434 peak: peak in residual image
1435 thresh_type: type of threshold used (noise or sidelobe)
1436 thresh_value: the value of threshold used
1437 N_reg: number of the automask regions
1438 N_pruned: number of the automask regions removed by pruning
1439 N_grow: number of the grow mask regions
1440 N_grow_pruned: number of the grow mask regions removed by pruning
1441 N_neg_pix: number of pixels for negative mask regions
1443 Note that for a large cube, extra logging may slow down the process.
1444 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.
1445 In this case, the threshold values are determined based on classic statistics (using all
1446 unmasked pixels for the calculations).
1448 If it is set to False, the new noise calculation
1449 method is used based on pre-existing mask.
1451 Case 1: no exiting mask
1452 Calculate image statistics using Chauvenet algorithm
1454 Case 2: there is an existing mask
1455 Calculate image statistics by classical method on the region
1456 outside the mask and inside the primary beam mask.
1458 In all cases above RMS noise is calculated from MAD.
1459 restart images (and start from an existing model image)
1460 or automatically increment the image name and make a new image set.
1462 True : Re-use existing images. If imagename.model exists the subsequent
1463 run will start from this model (i.e. predicting it using current gridder
1464 settings and starting from the residual image). Care must be taken
1465 when combining this option with startmodel. Currently, only one or
1466 the other can be used.
1468 startmodel='', imagename.model exists :
1469 - Start from imagename.model
1470 startmodel='xxx', imagename.model does not exist :
1471 - Start from startmodel
1472 startmodel='xxx', imagename.model exists :
1473 - Exit with an error message requesting the user to pick
1474 only one model. This situation can arise when doing one
1475 run with startmodel='xxx' to produce an output
1476 imagename.model that includes the content of startmodel,
1477 and wanting to restart a second run to continue deconvolution.
1478 Startmodel should be set to '' before continuing.
1480 If any change in the shape or coordinate system of the image is
1481 desired during the restart, please change the image name and
1482 use the startmodel (and mask) parameter(s) so that the old model
1483 (and mask) can be regridded to the new coordinate system before starting.
1485 False : A convenience feature to increment imagename with '_1', '_2',
1486 etc as suffixes so that all runs of sdintimaging are fresh starts (without
1487 having to change the imagename parameter or delete images).
1489 This mode will search the current directory for all existing
1490 imagename extensions, pick the maximum, and adds 1.
1491 For imagename='try' it will make try.psf, try_2.psf, try_3.psf, etc.
1493 This also works if you specify a directory name in the path :
1494 imagename='outdir/try'. If './outdir' does not exist, it will create it.
1495 Then it will search for existing filenames inside that directory.
1497 If outlier fields are specified, the incrementing happens for each
1498 of them (since each has its own 'imagename'). The counters are
1499 synchronized across imagefields, to make it easier to match up sets
1500 of output images. It adds 1 to the 'max id' from all outlier names
1501 on disk. So, if you do two runs with only the main field
1502 (imagename='try'), and in the third run you add an outlier with
1503 imagename='outtry', you will get the following image names
1504 for the third run : 'try_3' and 'outtry_3' even though
1505 'outry' and 'outtry_2' have not been used.
1506 calcres Calculate initial residual image
1508 This parameter controls what the first major cycle does.
1510 calcres=False with niter greater than 0 will assume that
1511 a .residual image already exists and that the minor cycle can
1512 begin without recomputing it.
1514 calcres=False with niter=0 implies that only the PSF will be made
1515 and no data will be gridded.
1517 calcres=True requires that calcpsf=True or that the .psf and .sumwt
1518 images already exist on disk (for normalization purposes).
1520 Usage example : For large runs (or a pipeline scripts) it may be
1521 useful to first run sdintimaging with niter=0 to create
1522 an initial .residual to look at and perhaps make
1523 a custom mask for. Imaging can be resumed
1524 without recomputing it.
1525 calcpsf Calculate PSF
1527 This parameter controls what the first major cycle does.
1529 calcpsf=False will assume that a .psf image already exists
1530 and that the minor cycle can begin without recomputing it.
1531 [1;42mRETURNS[1;m void
1533 --------- examples -----------------------------------------------------------
1537 Please refer to the CASAdocs pages for the task sdintimaging for examples.
1542 """
1544 _info_group_ = """imaging"""
1545 _info_desc_ = """"""
1547 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 ):
1548 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
1549}, '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'}}
1550 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}
1551 assert _pc.validate(doc,schema), create_error_string(_pc.errors)
1552 _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']) ] )
1553 task_result = None
1554 try:
1555 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'] )
1556 except Exception as exc:
1557 _except_log('sdintimaging', exc)
1558 raise
1559 finally:
1560 task_result = _end_log( _logging_state_, 'sdintimaging', task_result )
1561 return task_result
1563sdintimaging = _sdintimaging( )