Visibility

rascil.processing_components.visibility.base Module

Base simple visibility operations, placed here to avoid circular dependencies

`vis_summary`(vis)	Return string summarizing the Visibility
`copy_visibility`(vis[, zero])	Copy a visibility
`create_visibility_from_ms`(msname[, channum, ...])	Minimal MS to Visibility converter
`create_visibility_from_uvfits`(fitsname[, ...])	Minimal UVFIT to Visibility converter
`create_visibility`(config, times, frequency, ...)	Create a Visibility from Configuration, hour angles, and direction of source
`phaserotate_visibility`(vis, newphasecentre)	Phase rotate from the current phase centre to a new phase centre
`export_visibility_to_ms`(msname, vis_list[, ...])	Minimal Visibility to MS converter
`extend_visibility_to_ms`(msname, bvis)
`list_ms`(msname[, ack])	List sources and data descriptors in a MeasurementSet
`generate_baselines`(nant)	Generate mapping from antennas to baselines
`get_baseline`(ant1, ant2, baselines)	Given the antenna numbers work out the baseline number.

Visibility operations

`concatenate_visibility_frequency`(bvis_list)	Concatenate a list of Visibility's in frequency
`concatenate_visibility`(vis_list[, dim])	Concatenate a list of visibilities
`subtract_visibility`(vis, model_vis[, inplace])	Subtract model_vis from vis, returning new visibility
`qa_visibility`(vis[, context])	Assess the quality of Visibility
`remove_continuum_visibility`(vis[, degree, mask])	Fit and remove continuum visibility
`divide_visibility`(vis, modelvis)	Divide visibility by model forming visibility for equivalent point source
`integrate_visibility_by_channel`(vis)	Integrate visibility across all channels, returning new visibility
`average_visibility_by_channel`(vis[, ...])	Average visibility by groups of channels, returning list of new visibility
`convert_visibility_to_stokes`(vis)	Convert the polarisation frame data into Stokes parameters.
`convert_visibility_to_stokesI`(vis)	Convert the polarisation frame data into Stokes I dropping other polarisations, return new Visibility
`convert_visibility_stokesI_to_polframe`(vis)	Convert the Stokes I into full polarisation, return new Visibility

Visibility fitting

fit_visibility(vis, sc[, tol, niter, ...])

Fit a single component to a visibility

Functions for calculating geometry of a Visibility

`calculate_visibility_transit_time`(bvis[, ...])	Find the UTC time of the nearest transit
`calculate_visibility_hourangles`(bvis)	Return hour angles for location, utc_time, and direction
`calculate_visibility_parallactic_angles`(bvis)	Return parallactic angles for location, utc_time, and direction
`calculate_visibility_azel`(bvis)	Return az el for a location, utc_time, and direction

Visibility selection functions

Visibility selection can be done using xarray capabilities. For example, for flag all long baselines:

bvis["flags"] = xarray.where(
    bvis["uvdist_lambda"] > 20000.0, bvis["flags"], 1.0
)

To select by row number:

selected_bvis = bvis.isel({"time": slice(5, 7)})

To select by frequency channel:

selected_bvis = bvis.isel({"frequency": slice(1, 3)})

To select by frequency:

selected_bvis = bvis.sel({"frequency": slice(0.9e8, 1.2e8)})

To select by frequency and polarisation:

selected_bvis = bvis.sel(
    {"frequency": slice(0.9e8, 1.2e8), "polarisation": ["XX", "YY"]}
).dropna(dim="frequency", how="all")

In addition there are rascil functions which wrap up more complex selections. To flag all data in uvrange uvmin, uvmax (wavelengths):

bvis = visibility_flag_uvrange(bvis, uvmin, uvmax)

Note that this is not a selection operator but flags the unwanted data instead.

To select all data with dishes/stations with distance from the array centre in a range rmin, rmax (metres):

selected_bvis = visibility_select_r_range(bvis, rmin, rmax)

`visibility_select_uv_range`(bvis[, uvmin, uvmax])	Flag in-place all visibility data outside uvrange uvmin, uvmax (wavelengths)
`visibility_select_r_range`(bvis[, rmin, rmax])	Select a visibility with stations in a range of distance from the array centre