arrakis.utils.msutils

MeasurementSet utilities

Functions

beam_from_ms(→ int)	Work out which beam is in this MS
field_idx_from_ms(→ int)	Get the field from MS metadata
field_name_from_ms(→ str)	Get the field name from MS metadata
get_pol_axis(→ astropy.units.Quantity)	Get the polarization axis from the ASKAP MS. Checks are performed
wsclean(→ str)	Construct a wsclean command.

Module Contents

arrakis.utils.msutils.beam_from_ms(ms: str) → int

Work out which beam is in this MS

arrakis.utils.msutils.field_idx_from_ms(ms: str) → int

Get the field from MS metadata

arrakis.utils.msutils.field_name_from_ms(ms: str) → str

Get the field name from MS metadata

arrakis.utils.msutils.get_pol_axis(ms: pathlib.Path, feed_idx: int | None = None, col: str = 'RECEPTOR_ANGLE') → astropy.units.Quantity

Get the polarization axis from the ASKAP MS. Checks are performed to ensure this polarisation axis angle is constant throughout the observation.

Parameters:

• ms (Path) – The path to the measurement set that will be inspected

• feed_idx (Optional[int], optional) – Specify the entery in the FEED

• table of `ms` to return. This might be required when a subset of a

• measurement set has been extracted from an observation with a varying

• orientation.

• col (str, optional) – The column to extract the polarization angle from.

Returns:

The rotation of the PAF throughout the observing.

Return type:

astropy.units.Quantity

arrakis.utils.msutils.wsclean(mslist: list, use_mpi: bool, version: bool = False, j: int | None = None, parallel_gridding: int | None = None, parallel_reordering: int | None = None, no_work_on_master: bool = False, mem: float | None = None, abs_mem: float | None = None, verbose: bool = False, log_time: bool = False, quiet: bool = False, reorder: bool = False, no_reorder: bool = False, temp_dir: str | None = None, update_model_required: bool = False, no_update_model_required: bool = False, no_dirty: bool = False, save_first_residual: bool = False, save_weights: bool = False, save_uv: bool = False, reuse_psf: str | None = None, reuse_dirty: str | None = None, apply_primary_beam: bool = False, reuse_primary_beam: bool = False, use_differential_lofar_beam: bool = False, primary_beam_limit: float | None = None, mwa_path: str | None = None, save_psf_pb: bool = False, pb_grid_size: int | None = None, beam_model: str | None = None, beam_mode: str | None = None, beam_normalisation_mode: str | None = None, dry_run: bool = False, weight: str | None = None, super_weight: float | None = None, mf_weighting: bool = False, no_mf_weighting: bool = False, weighting_rank_filter: float | None = None, weighting_rank_filter_size: float | None = None, taper_gaussian: str | None = None, taper_tukey: float | None = None, taper_inner_tukey: float | None = None, taper_edge: float | None = None, taper_edge_tukey: float | None = None, use_weights_as_taper: bool = False, store_imaging_weights: bool = False, name: str | None = None, size: str | None = None, padding: float | None = None, scale: str | None = None, predict: bool = False, ws_continue: bool = False, subtract_model: bool = False, gridder: str | None = None, channels_out: int | None = None, shift: str | None = None, gap_channel_division: bool = False, channel_division_frequencies: str | None = None, nwlayers: int | None = None, nwlayers_factor: float | None = None, nwlayers_for_size: str | None = None, no_small_inversion: bool = False, small_inversion: bool = False, grid_mode: str | None = None, kernel_size: int | None = None, oversampling: int | None = None, make_psf: bool = False, make_psf_only: bool = False, visibility_weighting_mode: str | None = None, no_normalize_for_weighting: bool = False, baseline_averaging: float | None = None, simulate_noise: float | None = None, simulate_baseline_noise: str | None = None, idg_mode: str | None = None, wgridder_accuracy: float | None = None, aterm_config: str | None = None, grid_with_beam: bool = False, beam_aterm_update: int | None = False, aterm_kernel_size: float | None = None, apply_facet_solutions: str | None = None, apply_facet_beam: bool = False, facet_beam_update: int | None = False, save_aterms: bool = False, pol: str | None = None, interval: str | None = None, intervals_out: int | None = None, even_timesteps: bool = False, odd_timesteps: bool = False, channel_range: str | None = None, field: int | None = None, spws: str | None = None, data_column: str | None = None, maxuvw_m: float | None = None, minuvw_m: float | None = None, maxuv_l: float | None = None, minuv_l: float | None = None, maxw: float | None = None, niter: int | None = None, nmiter: int | None = None, threshold: float | None = None, auto_threshold: float | None = None, auto_mask: float | None = None, force_mask_rounds: int | None = None, local_rms: bool = False, local_rms_window: float | None = False, local_rms_method: str | None = None, gain: float | None = None, mgain: float | None = None, join_polarizations: bool = False, link_polarizations: str | None = None, facet_regions: str | None = None, join_channels: bool = False, spectral_correction: str | None = None, no_fast_subminor: bool = False, multiscale: bool = False, multiscale_scale_bias: float | None = None, multiscale_max_scales: int | None = None, multiscale_scales: str | None = None, multiscale_shape: str | None = None, multiscale_gain: float | None = None, multiscale_convolution_padding: float | None = None, no_multiscale_fast_subminor: bool = False, python_deconvolution: str | None = None, iuwt: bool = False, iuwt_snr_test: bool = False, no_iuwt_snr_test: bool = False, moresane_ext: str | None = None, moresane_arg: str | None = None, moresane_sl: str | None = None, save_source_list: bool = False, clean_border: float | None = None, fits_mask: str | None = None, casa_mask: str | None = None, horizon_mask: str | None = None, no_negative: bool = False, negative: bool = False, stop_negative: bool = False, fit_spectral_pol: int | None = None, fit_spectral_log_pol: int | None = None, force_spectrum: str | None = None, deconvolution_channels: int | None = None, squared_channel_joining: bool = False, parallel_deconvolution: int | None = None, deconvolution_threads: int | None = None, restore: str | None = None, restore_list: str | None = None, beam_size: float | None = None, beam_shape: str | None = None, fit_beam: bool = False, no_fit_beam: bool = False, beam_fitting_size: float | None = None, theoretic_beam: bool = False, circular_beam: bool = False, elliptical_beam: bool = False) → str

Construct a wsclean command. If False or None is passed as a parameter, the parameter is not included in the command (i.e. wsclean will assume a default value). :Parameters: * mslist (list) – List of MSs to be processed.

• use_mpi (bool) – Use wsclean-mp for parallel processing.

• version (bool, optional) – Print WSClean’s version and exit. Defaults to False.

• j (int, optional) – Specify number of computing threads to use, i.e., number of cpu cores that will be used. Default: use all cpu cores. to None.

• parallel_gridding (int, optional) – Will execute multiple gridders simultaneously. This can make things faster in certain cases, but will increase memory usage. Defaults to None.

• parallel_reordering (int, optional) – Process the reordering with multipliple threads. Defaults to None.

• no_work_on_master (bool, optional) – In MPI runs, do not use the master for gridding. This may be useful if the resources such as memory of the master are limited. Defaults to False.

• mem (float, optional) – Limit memory usage to the given fraction of the total system memory. This is an approximate value. Default: 100. Defaults to None.

• abs_mem (float, optional) – Like -mem, but this specifies a fixed amount of memory in gigabytes. Defaults to None.

• verbose (bool, optional) – Increase verbosity of output. Defaults to False.

• log_time (bool, optional) – Add date and time to each line in the output. Defaults to False.

• quiet (bool, optional) – Do not output anything but errors. Defaults to False.

• reorder (bool, optional) – Force reordering of Measurement Set. This can be faster when the measurement set needs to be iterated several times, such as with many major iterations or in channel imaging mode. Default: only reorder when in channel imaging mode. Defaults to False.

• no_reorder (bool, optional) – Disable reordering of Measurement Set. This can be faster when the measurement set needs to be iterated several times, such as with many major iterations or in channel imaging mode. Default: only reorder when in channel imaging mode. Defaults to False.

• temp_dir (str, optional) – Set the temporary directory used when reordering files. Default: same directory as input measurement set. Defaults to None.

• update_model_required (bool, optional) – Default. Defaults to False.

• no_update_model_required (bool, optional) – These two options specify whether the model data column is required to contain valid model data after imaging. It can save time to not update the model data column. Defaults to False.

• no_dirty (bool, optional) – Do not save the dirty image. Defaults to False.

• save_first_residual (bool, optional) – Save the residual after the first iteration. Defaults to False.

• save_weights (bool, optional) – Save the gridded weights in the a fits file named <image-prefix>-weights.fits. Defaults to False.

• save_uv (bool, optional) – Save the gridded uv plane, i.e., the FFT of the residual image. The UV plane is complex, hence two images will be output: <prefix>-uv-real.fits and <prefix>-uv-imag.fits. Defaults to False.

• reuse_psf (str, optional) – Load the psf(s) from the given prefix and skip the inversion for the psf image. Defaults to None.

• reuse_dirty (str, optional) – Load the dirty from the given prefix and skip the inversion for the dirty image. Defaults to None.

• apply_primary_beam (bool, optional) – Calculate and apply the primary beam and save images for the Jones components, with weighting identical to the weighting as used by the imager. Only available for instruments supported by EveryBeam. Defaults to False.

• reuse_primary_beam (bool, optional) – If a primary beam image exists on disk, reuse those images. Defaults to False.

• use_differential_lofar_beam (bool, optional) – Assume the visibilities have already been beam-corrected for the reference direction. By default, WSClean will use the information in the measurement set to determine if the differential beam should be applied for obtaining proper flux levels. Defaults to False.

• primary_beam_limit (float, optional) – Level at which to trim the beam when performing image-based beam correction,. Default: 0.005. Defaults to None.

• mwa_path (str, optional) – Set path where to find the MWA beam file(s). Defaults to None.

• save_psf_pb (bool, optional) – When applying beam correction, also save the primary-beam corrected PSF image. Defaults to False.

• pb_grid_size (int, optional) – Specify the grid size in number of pixels at which to evaluate the primary beam. Typically, the primary beam is calculated at a coarse resolution grid and interpolated, to reduce the time spent in evaluating the beam. This parameter controls the resolution of the grid at which to evaluate the primary beam. For rectangular images, pb-grid-size indicates the number of pixels along the shortest dimension. The total number of pixels in the primary beam grid thus amounts to:

  max(width, height) / min(width, height) * pb-grid-size**2.

  Default: 32. Defaults to None.

• beam_model (str, optional) – Specify the beam model, only relevant for SKA and LOFAR. Available models are Hamaker, Lobes, OskarDipole, OskarSphericalWave. Input is case insensitive. Default is Hamaker for LOFAR and OskarSphericalWave for SKA. Defaults to None.

• beam_mode (str, optional) – [DEBUGGING ONLY] Manually specify the beam mode. Only relevant for simulated SKA measurement sets. Available modes are array_factor, element and full. Input is case insensitive. Default is full. Defaults to None.

• beam_normalisation_mode (str, optional) – [DEBUGGING ONLY] Manually specify the normalisation of the beam. Only relevant for simulated SKA measurement sets. Available modes are none, preapplied, full, and amplitude. Default is preapplied. Defaults to None.

• dry_run (bool, optional) – Parses the command line and quits afterwards. No imaging is done. Defaults to False.

• weight (str, optional) – Weightmode can be: natural, uniform, briggs. Default: uniform. When using Briggs’ weighting, add the robustness parameter, like: “-weight briggs 0.5”. Defaults to None.

• super_weight (float, optional) – Increase the weight gridding box size, similar to Casa’s superuniform weighting scheme. Default: 1.0 The factor can be rational and can be less than one for subpixel weighting. Defaults to None.

• mf_weighting (bool, optional) – In spectral mode, calculate the weights as if the image was made using MF. This makes sure that the sum of channel images equals the MF weights. Otherwise, the channel image will become a bit more naturally weighted. This is only relevant for weighting modes that require gridding (i.e., Uniform, Briggs’). Default: off, unless -join-channels is specified. Defaults to False.

• no_mf_weighting (bool, optional) – Opposite of -ms-weighting; can be used to turn off MF weighting in -join-channels mode. Defaults to False.

• weighting_rank_filter (float, optional) – Filter the weights and set high weights to the local mean. The level parameter specifies the filter level; any value larger than level*localmean will be set to level*localmean. Defaults to None.

• weighting_rank_filter_size (float, optional) – Set size of weighting rank filter. Default: 16. Defaults to None.

• taper_gaussian (str, optional) – Taper the weights with a Gaussian function. This will reduce the contribution of long baselines. The beamsize is by default in asec, but a unit can be specified (“2amin”). Defaults to None.

• taper_tukey (float, optional) – Taper the outer weights with a Tukey transition. Lambda specifies the size of the transition; use in combination with -maxuv-l. Defaults to None.

• taper_inner_tukey (float, optional) – Taper the weights with a Tukey transition. Lambda specifies the size of the transition; use in combination with -minuv-l. Defaults to None.

• taper_edge (float, optional) – Taper the weights with a rectangle, to keep a space of lambda between the edge and gridded visibilities. Defaults to None.

• taper_edge_tukey (float, optional) – Taper the edge weights with a Tukey window. Lambda is the size of the Tukey transition. When -taper-edge is also specified, the Tukey transition starts inside the inner rectangle. Defaults to None.

• use_weights_as_taper (bool, optional) – Will not use visibility weights when determining the imaging weights. This has the effect that e.g. uniform weighting can be modified by increasing the visibility weight of certain baselines. Without this option, uniform imaging weights absorb the visibility weight to make the weighting truly uniform. Defaults to False.

• store_imaging_weights (bool, optional) – Will store the imaging weights in a column named ‘IMAGING_WEIGHT_SPECTRUM’. Defaults to False.

• name (str, optional) – Use image-prefix as prefix for output files. Default is ‘wsclean’. Defaults to None.

• size (str, optional) – Set the output image size in number of pixels (without padding). Defaults to None.

• padding (float, optional) – Pad images by the given factor during inversion to avoid aliasing. Default: 1.2 (=20%). Defaults to None.

• scale (str, optional) – Scale of a pixel. Default unit is degrees, but can be specificied, e.g. -scale 20asec. Default: 0.01deg. Defaults to None.

• predict (bool, optional) – Only perform a single prediction for an existing image. Doesn’t do any imaging or cleaning. The input images should have the same name as the model output images would have in normal imaging mode. Defaults to False.

• ws_continue (bool, optional) – Will continue an earlier WSClean run. Earlier model images will be read and model visibilities will be subtracted to create the first dirty residual. CS should have been used in the earlier run, and model datashould have been written to the measurement set for this to work. Default: off. Defaults to False.

• subtract_model (bool, optional) – Subtract the model from the data column in the first iteration. This can be used to reimage an already cleaned image, e.g. at a different resolution. Defaults to False.

• gridder (str) – Set gridder type: direct-ft, idg, wgridder, tuned-wgridder, or wstacking.

• channels_out (int, optional) – Splits the bandwidth and makes count nr. of images. Default: 1. Defaults to None.

• shift (str, optional) – Shift the phase centre to the given location. The shift is along the tangential plane. Defaults to None.

• gap_channel_division (bool, optional) – In case of irregular frequency spacing, this option can be used to not try and split channels to make the output channel bandwidth similar, but instead to split largest gaps first. Defaults to False.

• channel_division_frequencies (str, optional) – Split the bandwidth at the specified frequencies (in Hz) before the normal bandwidth division is performed. This can e.g. be useful for imaging multiple bands with irregular number of channels. Defaults to None.

• nwlayers (int, optional) – Number of w-layers to use. Default: minimum suggested #w-layers for first MS. Defaults to None.

• nwlayers_factor (float, optional) – Use automatic calculation of the number of w-layers, but multiple that number by the given factor. This can e.g. be useful for increasing w-accuracy. Defaults to None.

• nwlayers_for_size (str, optional) – Use the minimum suggested w-layers for an image of the given size. Can e.g. be used to increase accuracy when predicting small part of full image. Defaults to None.

• no_small_inversion (bool, optional) – Perform inversion at the Nyquist resolution and upscale the image to the requested image size afterwards. This speeds up inversion considerably, but makes aliasing slightly worse. This effect is in most cases <1%. Default: on. Defaults to False.

• small_inversion (bool, optional) – Perform inversion at the Nyquist resolution and upscale the image to the requested image size afterwards. This speeds up inversion considerably, but makes aliasing slightly worse. This effect is in most cases <1%. Default: on. Defaults to False.

• grid_mode (str, optional) – Kernel and mode used for gridding: kb = Kaiser-Bessel (default with 7 pixels), nn = nearest neighbour (no kernel), more options: rect, kb-no-sinc, gaus, bn. Default: kb. Defaults to None.

• kernel_size (int, optional) – Gridding antialiasing kernel size. Default: 7. Defaults to None.

• oversampling (int, optional) – Oversampling factor used during gridding. Default: 63. Defaults to None.

• make_psf (bool, optional) – Always make the psf, even when no cleaning is performed. Defaults to False.

• make_psf_only (bool, optional) – Only make the psf, no images are made. Defaults to False.

• visibility_weighting_mode (str, optional) – Specify visibility weighting modi. Affects how the weights (normally) stored in WEIGHT_SPECTRUM column are applied. Useful for estimating e.g. EoR power spectra errors. Normally one would use this in combination with -no-normalize-for-weighting. Defaults to None.

• no_normalize_for_weighting (bool, optional) – Disable the normalization for the weights, which makes the PSF’s peak one. See -visibility-weighting-mode. Only useful with natural weighting. Defaults to False.

• baseline_averaging (float, optional) – Enable baseline-dependent averaging. The specified size is in number of wavelengths (i.e., uvw-units). One way to calculate this is with

  <baseline in nr. of lambdas> * 2pi * <acceptable integration in s> / (24*60*60).

  Defaults to None.

• simulate_noise (float, optional) – Will replace every visibility by a Gaussian distributed value with given standard deviation before imaging. Defaults to None.

• simulate_baseline_noise (str, optional) – Like -simulate-noise, but the stddevs are provided per baseline, in a text file with antenna1 and antenna2 indices and the stddev per line, separated by spaces, e.g. “0 1 3.14”. Defaults to None.

• idg_mode (str, optional) – Sets the IDG mode. Default: cpu. Hybrid is recommended when a GPU is available. Defaults to None.

• wgridder_accuracy (float, optional) – Set the w-gridding accuracy. Default: 1e-4 Useful range: 1e-2 to 1e-. Defaults to None.

• aterm_config (str, optional) – Specify a parameter set describing how a-terms should be applied. Please refer to the documentation for details of the configuration file format. Applying a-terms is only possible when IDG is enabled. Defaults to None.

• grid_with_beam (bool, optional) – Apply a-terms to correct for the primary beam. This is only possible when IDG is enabled. Defaults to False.

• beam_aterm_update (int, optional) – Set the ATerm update time in seconds. The default is every 300 seconds. It also sets the interval over which to calculate the primary beam when using -apply-primary-beam when not gridding with the beam. Defaults to False.

• aterm_kernel_size (float, optional) – Kernel size reserved for aterms by IDG. Defaults to None.

• apply_facet_solutions (str, optional) – Apply solutions from the provided (h5) file per facet when gridding facet based images. Provided file is assumed to be in H5Parm format. Filename is followed by a comma separated list of strings specifying which sol tabs from the provided H5Parm file are used. Defaults to None.

• apply_facet_beam (bool, optional) – Apply beam gains to facet center when gridding facet based image. Defaults to False.

• facet_beam_update (int, optional) – Set the facet beam update time in seconds. The default is every 120 seconds. Defaults to False.

• save_aterms (bool, optional) – Output a fits file for every aterm update, containing the applied image for every station. Defaults to False.

• pol (str, optional) – Default: ‘I’. Possible values: XX, XY, YX, YY, I, Q, U, V, RR, RL, LR or LL (case insensitive). It is allowed but not necessary to separate with commas, e.g.: ‘xx,xy,yx,yy’.Two or four polarizations can be joinedly cleaned (see ‘-joinpolarizations’), but this is not the default. I, Q, U and V polarizations will be directly calculated from the visibilities, which might require correction to get to real IQUV values. The ‘xy’ polarization will output both a real and an imaginary image, which allows calculating true Stokes polarizations for those telescopes. Defaults to None.

• interval (str, optional) – Only image the given time interval. Indices specify the timesteps, end index is exclusive. Default: image all time steps. Defaults to None.

• intervals_out (int, optional) – Number of intervals to image inside the selected global interval. Default: . Defaults to None.

• even_timesteps (bool, optional) – Only select even timesteps. Can be used together with -odd-timesteps to determine noise values. Defaults to False.

• odd_timesteps (bool, optional) – Only select odd timesteps. Defaults to False.

• channel_range (str, optional) – Only image the given channel range. Indices specify channel indices, end index is exclusive. Default: image all channels. Defaults to None.

• field (str, optional) – Image the given field id(s). A comma-separated list of field ids can be provided. When multiple fields are given, all fields should have the same phase centre. Specifying ‘-field all’ will image all fields in the measurement set. Default: first field (id 0). Defaults to None.

• spws (str, optional) – Selects only the spws given in the list. list should be a comma-separated list of integers. Default: all spws. Defaults to None.

• data_column (str, optional) – Default: CORRECTED_DATA if it exists, otherwise DATA will be used. Defaults to None.

• maxuvw_m (float, optional) – Set the min max uv distance in lambda. Defaults to None.

• minuvw_m (float, optional) – Set the max baseline distance in meters. Defaults to None.

• maxuv_l (float, optional) – Set the min max uv distance in lambda. Defaults to None.

• minuv_l (float, optional) – Set the max uv distance in lambda. Defaults to None.

• maxw (float, optional) – Do not grid visibilities with a w-value higher than the given percentage of the max w, to save speed. Default: grid everythin. Defaults to None.

• niter (int, optional) – Maximum number of clean iterations to perform. Default: 0 (=no cleaning). Defaults to None.

• nmiter (int, optional) – Maximum number of major clean (inversion/prediction) iterations. Default: 20.A value of 0 means no limit. Defaults to None.

• threshold (float, optional) – Stopping clean thresholding in Jy. Default: 0.0. Defaults to None.

• auto_threshold (float, optional) – Estimate noise level using a robust estimator and stop at sigma x stddev. Defaults to None.

• auto_mask (float, optional) – Construct a mask from found components and when a threshold of sigma is reached, continue cleaning with the mask down to the normal threshold. Defaults to None.

• force_mask_rounds (int, optional) – Will force the derivation of the mask to be carried out across a set number of major cleaning rounds.

• local_rms (bool, optional) – Instead of using a single RMS for auto thresholding/masking, use a spatially varying RMS image. Defaults to False.

• local_rms_window (bool, optional) – Size of window for creating the RMS background map, in number of PSFs. Default: 25 psfs. Defaults to False.

• local_rms_method (bool, optional) – Either ‘rms’ (default, uses sliding window RMS) or ‘rms-with-min’ (use max(window rms, 0.3 x window min)). Defaults to False.

• gain (float, optional) – Cleaning gain: Ratio of peak that will be subtracted in each iteration. Default: 0.1. Defaults to None.

• mgain (float, optional) – Cleaning gain for major iterations: Ratio of peak that will be subtracted in each major iteration. To use major iterations, 0.85 is a good value. Default: 1.0. Defaults to None.

• join_polarizations (bool, optional) – Perform deconvolution by searching for peaks in the sum of squares of the polarizations, but subtract components from the individual images. Only possible when imaging two or four Stokes or linear parameters. Default: off. Defaults to False.

• link_polarizations (str, optional) – Links all polarizations to be cleaned from the given list: components are found in the given list, but cleaned from all polarizations. Defaults to None.

• facet_regions (str, optional) – Split the image into facets using the facet regions defined in the facets.reg file. Default: off. Defaults to None.

• join_channels (bool, optional) – Perform deconvolution by searching for peaks in the MF image, but subtract components from individual channels. This will turn on mf-weighting by default. Default: off. Defaults to False.

• spectral_correction (str, optional) – Enable correction of the given spectral function inside deconvolution. This can e.g. avoid downweighting higher frequencies because of reduced flux density. 1st term is total flux, 2nd is si, 3rd curvature, etc. Example: -spectral-correction 150e6 83.084,-0.699,-0.110 Defaults to None.

• no_fast_subminor (bool, optional) – Do not use the subminor loop optimization during (non-multiscale) cleaning. Default: use the optimization. Defaults to False.

• multiscale (bool, optional) – Clean on different scales. This is a new algorithm. Default: off. This parameter invokes the optimized multiscale algorithm published by Offringa & Smirnov (2017). Defaults to False.

• multiscale_scale_bias (bool, optional) – Parameter to prevent cleaning small scales in the large-scale iterations. A lower bias will give more focus to larger scales. Default: 0.6 Defaults to False.

• multiscale_max_scales (int, optional) – Set the maximum number of scales that WSClean should use in multiscale cleaning. Only relevant when -multiscale-scales is not set. Default: unlimited. Defaults to None.

• multiscale_scales (str, optional) – Sets a list of scales to use in multi-scale cleaning. If unset, WSClean will select the delta (zero) scale, scales starting at four times the synthesized PSF, and increase by a factor of two until the maximum scale is reached or the maximum number of scales is reached. Example: -multiscale-scales 0,5,12.5 Defaults to None.

• multiscale_shape (str, optional) – Sets the shape function used during multi-scale clean. Either ‘tapered-quadratic’ (default) or ‘gaussian’. Defaults to None.

• multiscale_gain (float, optional) – Size of step made in the subminor loop of multi-scale. Default currently 0.2, but shows sign of instability. A value of 0.1 might be more stable. Defaults to None.

• multiscale_convolution_padding (float, optional) – Size of zero-padding for convolutions during the multi-scale cleaning. Default: 1.1 Defaults to None.

• no_multiscale_fast_subminor (bool, optional) – Disable the ‘fast subminor loop’ optimization, that will only search a part of the image during the multi-scale subminor loop. The optimization is on by default. Defaults to False.

• python_deconvolution (str, optional) – Run a custom deconvolution algorithm written in Python. See manual for the interface. Defaults to None.

• iuwt (bool, optional) – Use the IUWT deconvolution algorithm. Defaults to False.

• iuwt_snr_test (bool, optional) – Stop IUWT when the SNR decreases. This might help limitting divergence, but can occasionally also stop the algorithm too early. Default: no SNR test. Defaults to False.

• no_iuwt_snr_test (bool, optional) – Do not stop IUWT when the SNR decreases. This might help limitting divergence, but can occasionally also stop the algorithm too early. Default: no SNR test. Defaults to False.

• moresane_ext (str, optional) – Use the MoreSane deconvolution algorithm, installed at the specified location. Defaults to None.

• moresane_arg (str, optional) – Pass the specified arguments to moresane. Note that multiple parameters have to be enclosed in quotes. Defaults to None.

• moresane_sl (str, optional) – MoreSane –sigmalevel setting for each major loop iteration. Useful to start at high levels and go down with subsequent loops, e.g. 20,10,5 Defaults to None.

• save_source_list (bool, optional) – Saves the found clean components as a BBS/DP3 text sky model. This parameter enables Gaussian shapes during multi-scale cleaning (-multiscale-shape gaussian). Defaults to False.

• clean_border (float, optional) – Set the border size in which no cleaning is performed, in percentage of the width/height of the image. With an image size of 1000 and clean border of 1%, each border is 10 pixels. Default: 0% Defaults to None.

• fits_mask (str, optional) – Use the specified fits-file as mask during cleaning. Defaults to None.

• casa_mask (str, optional) – Use the specified CASA mask as mask

• during cleaning. Defaults to None.

• horizon_mask (str, optional) – Use a mask that avoids cleaning emission beyond the horizon. Distance is an angle (e.g. “5deg”) that (when positive) decreases the size of the mask to stay further away from the horizon. Defaults to None.

• no_negative (bool, optional) – Do not allow negative components during cleaning. Not the default. Defaults to False.

• negative (bool, optional) – Default on: opposite of -nonegative. Defaults to False.

• stop_negative (bool, optional) – Stop on negative components. Not the default. Defaults to False.

• fit_spectral_pol (int, optional) – Fit a polynomial over frequency to each clean component. This has only effect when the channels are joined with -join-channels. Defaults to None.

• fit_spectral_log_pol (int, optional) – Like fit-spectral-pol, but fits a logarithmic polynomial over frequency instead. Defaults to None.

• force_spectrum (str, optional) – Uses the fits file to force spectral indices (or other/more terms)during the deconvolution. Defaults to None.

• deconvolution_channels (int, optional) – Decrease the number of channels as specified by -channels-out to the given number for deconvolution. Only possible in combination with one of the -fit-spectral options. Proper residuals/restored images will only be returned when mgain < 1. Defaults to None.

• squared_channel_joining (bool, optional) – Use with -join-channels to perform peak finding in the sum of squared values over channels, instead of the normal sum. This is useful for imaging QU polarizations with non-zero rotation measures, for which the normal

  sum is insensitive. Defaults to False.

• parallel_deconvolution (int, optional) – Deconvolve subimages in parallel. Subimages will be at most of the given size. Defaults to None.

• deconvolution_threads (int, optional) – Number of threads to use during deconvolution. On machines with a large nr of cores, this may be

  used to decrease the memory usage. Defaults to None.

• restore (str, optional) – Restore the model image onto the residual image and save it in output image. By default, the beam parameters

  are read from the residual image. If this parameter is given,

  wsclean will do the restoring and then exit:

  no cleaning is performed. Defaults to None.

• restore_list (str, optional) – Restore a source list onto the residual image and save it in output image. Except for the model input format, this parameter behaves equal to -restore. Defaults to None.

• beam_size (float, optional) – Set a circular beam size (FWHM) in arcsec for restoring the clean components. This is the same as -beam-shape <size> <size> 0. Defaults to None.

• beam_shape (str, optional) – Set the FWHM beam shape for restoring the clean components. Defaults units for maj and min are arcsec, and degrees for PA. Can be overriden, e.g. ‘-beam-shape 1amin 1amin 3deg’. Default: shape of PSF. Defaults to None.

• fit_beam (bool, optional) – Determine beam shape by fitting the PSF (default if PSF is made). Defaults to False.

• no_fit_beam (bool, optional) – Do not determine beam shape from the PSF. Defaults to False.

• beam_fitting_size (float, optional) – Use a fitting box the size of <factor> times the theoretical beam size for fitting a Gaussian to the PSF. Defaults to None.

• theoretic_beam (bool, optional) – Write the beam in output fits files as calculated from the longest projected baseline. This method results in slightly less accurate beam size/integrated fluxes, but provides

  a beam size without making the PSF for quick imaging. Default: off. Defaults to False.

• circular_beam (bool, optional) – Force the beam to be circular: bmin will be set to bmaj. Defaults to False.

• elliptical_beam (bool, optional) – Allow the beam to be elliptical. Default. Defaults to False.

Returns:

WSClean command

Return type:

str