self_cal¶
Perform Self calibration on the data
enable¶
bool
Execute this segment
label¶
str, optional, default = corr
Label of the .MS files to process
undo_subtractmodelcol¶
bool, optional, default = False
replace the corrected column with the sum of corrected and model columns to undo continuum subtraction that may have been done by the image HI worker.
primary_beam¶
bool, optional, default = False
Use primary beam
calibrate_with¶
{“meqtrees”, “cubical”}, optional, default = cubical
Tool to use for calibration
spwid¶
int, optional, default = 0
Provide spectral window id
ncpu¶
int, optional, default = 5
number of cpu’s to use
minuvw_m¶
int, optional, default = 0
Exclude baselines shorter than this value (given in metres) from the imaging and selfcalibration loop.
img_npix¶
int, optional, default = 1800
Number of pixels in output image
img_padding¶
float, optional, default = 1.3
Padding in WSclean
img_mgain¶
float, optional, default = 0.99
Image CLEANing gain
img_cell¶
float, optional, default = 2.
Image pixel size (arcsec)
img_weight¶
{“briggs”, “uniform”, “natural”}, optional, default = briggs
Image weighting type. If Briggs, set the img robust parameter
img_robust¶
float, optional, default = 0.
Briggs robust value
img_uvtaper¶
str, optional, default = 0
Taper for imaging (arcsec)
img_niter¶
int, optional, default = 1000000
Number of cleaning iterations
img_nmiter¶
int, optional, default = 0
Number of major cycles
img_cleanborder¶
float, optional, default = 1.3
Clean border
img_nchans¶
int, optional, default = 3
Number of channesls in output image
img_joinchannels¶
bool, optional, default = True
Join channels to create MFS image
img_fit_spectral_pol¶
int, optional, default = 2
Number of spectral polynomial terms to fit to each clean component. This is equal to the order of the polynomial plus 1.
img_pol¶
str, optional, default = I
Stokes image to create
cal_gain_amplitude_clip_low¶
float, optional, default = 0.5
Lower gain amplitude clipping
cal_gain_amplitude_clip_high¶
float, optional, default = 2.
Higher gain amplitude clipping
cal_niter¶
int, optional, default = 2
Number of self-calibration iterations to perform
start_at_iter¶
int, optional, default = 1
Start self-cal iteration loop at this start value, 1-based.
cal_time_chunk¶
int, optional, default = 1
Chunk data up by this number of timeslots. This limits the amount of data processed at once. Smaller chunks allow for a smaller RAM footprint and greater parallelism but sets an upper limit on the time solution intervals that may be employed. 0 means use full time axis but does not cross scan boundaries.
cal_freq_chunk¶
int, optional, default = 0
Chunk data up by this number of channels. This limits the amount of data processed at once. Smaller chunks allow for a smaller RAM footprint and greater parallelism but sets an upper limit on the frequency solution intervals that may be employed. 0 means use full frequency axis but does not cross SPW boundaries.
aimfast¶
Quality assessment parameter
enable
bool, optional, default = False
Execute this segment
tolerance
float, optional, default = 0.02
Relative change in weighted mean of several indicators from aimfast.
convergence_criteria
list of str, optional, default = DR
The residual statistic to check convergence against. Every criterium listed will be combined into a weighted mean. Options [“DR”,”SKEW”,”KURT”,”STDDev”,”MEAN”]. Note that when calibrate model_mode = ‘vis_only’ DR is not an option.
area_factor
int, optional, default = 6
Peak flux source area multiplying factor i.e tot_area = psf-size*af
normality_model
{“normaltest”, “shapiro”}, optional, default = normaltest
normality test model to use. Note that normaltest is the D’Agostino
plot
bool, optional, default = True
Generate html plots for comparing catalogs and residuals
image¶
Imaging parameter
enable
bool, optional, default = True
Execute this segment
auto_mask
list of float, optional, default = 30, 10, 7
Auto masking threshold
auto_threshold
list of float, optional, default = 0.5
Auto clean threshold
column
list of str, optional, default = DATA, CORRECTED_DATA
Column to image
mask_from_sky
bool, optional, default = False
switch on cleaning within mask from fits file
fits_mask
list of str, optional, default = catalog_mask.fits
filename of fits mask (in output/masking folder)
multi_scale
bool, optional, default = False
switch on multiscale cleaning
multi_scale_scales
list of int, optional, default = 10, 20, 30
scales of multiscale [0,10,20,etc, etc] in pixels
local_rms
bool, optional, default = False
switch on local rms measurement for cleaning
sofia_mask¶
Run SoFiA source finder to produce a source mask and a Moment-0 map
enable
bool, optional, default = False
Execute segment sofia (yes/no)?
threshold
float, optional, default = 4.0
SoFiA source finding threshold.
flag
bool, optional, default = False
Use flag regions (yes/no)?
flagregion
list of str, optional, default = ‘ ‘
Pixel/channel range(s) to be flagged prior to source finding. Format is [[x1, x2, y1, y2, z1, z2], …].
inputmask
str, optional, default = ‘ ‘
input mask over which add Sofia’s
fornax_special
bool, optional, default = False
Activates masking of Fornax A using Sofia
fornax_thresh
list of float, optional, default = 4.0
SoFiA source finding threshold. Default is 4.0.
use_sofia
bool, optional, default = False
use sofia for mask of Fornax A instead of Fomalont mask
scale_noise_window
int, optional, default = 31
window size where to measure local rms in pixels
positivity
bool, optional, default = False
merges only positive pixesl of sources in mask
extract_sources¶
Source finding parameters
enable
bool, optional, default = False
Execute this segment
sourcefinder
str, optional, default = pybdsm
choose your favorite sourcefinder pybdsm, (pybdsf), sofia
local_rms
bool, optional, default = False
Execute this segment
spi
bool, optional, default = False
Extract source spectral index
thresh_pix
list of int, optional, default = 5
Source finder pixel threshold
thresh_isl
list of int, optional, default = 3
Source finder island threshold
calibrate¶
Calibration parameters
enable
bool, optional, default = True
Execute this segment
model
list of str, optional, default = 1,2
Model number to use [or combination e.g. ‘1+2’ to use first and second models]
output_data
list of str, optional, default = CORR_DATA
Data to output after calibration
gain_matrix_type
list of str, optional, default = GainDiagPhase
Gain matrix type
model_mode
str, optional, default = vis_only
pybdsm_vis, pybdsm_only, vis_only are the possible options
shared_memory
str, optional, default = 100Gb
Set the amount of shared memory for cubical. Default ‘100Gb’
two_step
bool, optional, default = False
Trigger a two step calibration process where the phase only calibration is applied before continuing with amplitude + phase cal. When cubical is used this happens simultaneous and gain parameters can be used with DDsols parameters. Set DDsol_time to -1 one to avoid amplitude calibration in an itereation. The parameter DDjones should be set to false.
add_vis_model
bool, optional, default = True
Add/Use clean components from latest imaging step to/as sky model for calibation
Gsols_time
list of float, optional, default = 1
G-Jones time solution interval. The parameter cal_time_chunk above should a multiple of Gsols_time. 0 means a single solution for the full time chunk.
Gsols_channel
list of float, optional, default = 0
G-Jones frequency solution interval. The parameter cal_frq_chunk above should a multiple of Gsols_channel. 0 means a single solution for the full frequency chunk.
Bjones
bool, optional, default = False
Enable Bjones
Bsols_time
list of int, optional, default = 0
Gsols for individual calibration steps, if not given will default to cal_Gsols
Bsols_channel
list of float, optional, default = 2
Gsols for individual calibration steps, if not given will default to cal_Gsols
DDjones
bool, optional, default = False
Enable direction dependent calibration, currently experimental.
DDsols_time
list of float, optional, default = 0
Calibration solution intervals
DDsols_channel
list of float, optional, default = 0
Calibration solution intervals
weight_column
str, optional, default = WEIGHT
Column with weights
madmax_flagging
bool, optional, default = True
Flags based on maximum of mad
madmax_flag_thresh
list of int, optional, default = 0, 10
Threshold for madmax flagging
sol_term_iters
str, optional, default = auto
Number of iterations per Jones term. If set to ‘auto’, uses hardcoded iteration numbers depending on the jones chain.
dist_max_chunks
int, optional, default = 4
Maximum number of time/freq data-chunks to load into memory simultaneously. If 0, then as many as possible will be loaded.
ragavi_plot
Plotting dignostics plots for delay correction calibration.
enable
bool, optional, default = False
Enables plotting dignostics
gaintype
list of str, optional, default = G
List of gain solution types
field
list of int, optional, default = 0
Fields to plot. Specify by field id, index.
restore_model¶
Restore modelled to final calibrated residual image
enable
bool, optional, default = False
Execute this segment
model
str, optional, default = 1+2
Model number to use [or combination e.g. ‘1+2’ to use first and second models]
clean_model
str, optional, default = 3
Clean model number to use [or combination e.g. ‘1+2’ to use first and second models]
flagging_summary¶
Output the flagging summary
enable
bool, optional, default = False
Execute this segment
transfer_apply_gains¶
Interpolate gains over the high frequency resolution data
enable
bool, optional, default = False
Execute this segment
transfer_to_label
str, optional, default = corr
label of cross-calibrated .ms file to which to transfer and apply the selfcal gains
interpolate
To interpolate the gains or not to interpolate the gains. That is indeed the question.
enable
bool, optional, default = True
Enable gain interpolation.
time_int
int, optional, default = 1
Solution interval in time (units of timeslots/intergration time) to transfer gains.
freq_int
int, optional, default = 0
Solution interval in frequency (units of channels) to transfer gains.
time_chunk
int, optional, default = 128
Time chunk in units of timeslots for transferring gains with Cubical.
freq_chunk
int, optional, default = 0
Frequency chunk in units of channels for transferring gains with Cubical. ‘0’ means the whole spw.
transfer_model¶
Transfer model from last WSclean imaging run to the MODEL_DATA column of another .MS
enable
bool, optional, default = True
Execute this segment (default False)
transfer_to_label
str, optional, default = corr
label of .ms file to which to transfer the model
model
str, optional, default = auto
Name of the sky model file (currently the only supported format is that of WSclean component lists). When ‘auto’, the pipeline builds the file name from the input parameters of the selfcal loop. The file is assumed to be in the ‘output’ directory.
spectra
bool, optional, default = True
Model sources as non-flat spectra. The spectral coefficients and reference frequency must be present in the sky model.
row_chunks
int, optional, default = 0
Number of rows of input .MS that are processed in a single chunk.
model_chunks
int, optional, default = 0
Number of sky model components that are processed in a single chunk.
exp-sign-convention
str, optional, default = casa
Sign convention to use for the complex exponential. ‘casa’ specifies the e^(2.pi.I) convention while ‘thompson’ specifies the e^(-2.pi.I) convention in the white book and Fourier analysis literature. Defaults to ‘casa’.
within
str, optional, default = ‘ ‘
Give JS9 region file. Only sources within those regions will be included.
points_only
bool, optional, default = False
Select only point-only sources. Default is False.
num_sources
int, optional, default = 0
Select only N brightest sources. Default is 0
num_workers
int, optional, default = 0
Explicitly set the number of worker threads. Default is 0, meaning it uses all threads.
memory_fraction
float, optional, default = 0.5
Fraction of system RAM that can be used. Used when setting automatically the chunk size.