Functions

Create empty visibility data set for observation

• For Visibility: rascil.processing_components.visibility.base.create_visibility()

Read existing Measurement Set

Casacore must be installed for MS reading and writing:

• List contents of a MeasurementSet: rascil.processing_components.visibility.base.list_ms()

• Creates a list of BlockVisibilities, one per FIELD_ID and DATA_DESC_ID: rascil.processing_components.visibility.base.create_visibility_from_ms()

Visibility weighting and tapering

• Weighting: rascil.processing_components.imaging.weighting.weight_visibility()

• Gaussian tapering: rascil.processing_components.imaging.weighting.taper_visibility_gaussian()

• Tukey tapering: rascil.processing_components.imaging.weighting.taper_visibility_tukey()

Visibility predict and invert

• Predict by de-gridding visibilities with Nifty Gridder rascil.processing_components.imaging.ng.predict_ng()

• Invert by gridding visibilities with Nifty Gridder rascil.processing_components.imaging.ng.invert_ng()

• Predict by de-gridding visibilities with GPU-based WAGG rascil.processing_components.imaging.wg.predict_wg()

• Invert by gridding visibilities with GPU-based WAGG rascil.processing_components.imaging.wg.invert_wg()

• Predict Visibility for SkyComponent rascil.processing_components.imaging.dft.dft_skycomponent_visibility()

• Predict SkyComponent from Visibility rascil.processing_components.imaging.dft.idft_visibility_skycomponent()

Deconvolution

• Deconvolution rascil.processing_components.image.deconvolution.deconvolve_cube() wraps:

• Hogbom Clean: rascil.processing_components.arrays.cleaners.hogbom()

• Hogbom Complex Clean: rascil.processing_components.arrays.cleaners.hogbom_complex()

• Multi-scale Clean: rascil.processing_components.arrays.cleaners.msclean()

• Multi-scale multi-frequency Clean: rascil.processing_components.arrays.cleaners.msmfsclean()

• Restore: rascil.processing_components.image.deconvolution.restore_cube()

Calibration

• Create empty gain table: rascil.processing_components.calibration.operations.create_gaintable_from_visibility()

• Solve for complex gains: rascil.processing_components.calibration.solvers.solve_gaintable()

• Apply complex gains: rascil.processing_components.calibration.operations.apply_gaintable()

Coordinate transforms

• Phase rotation: rascil.processing_components.visibility.base.phaserotate_visibility()

• Station/baseline (XYZ <-> UVW): rascil.processing_components.util.coordinate_support

• Source (spherical -> tangent plane): rascil.processing_components.util.coordinate_support

Image

• Image operations: rascil.processing_components.image.operations()

• Import from FITS: rascil.processing_components.image.operations.import_image_from_fits()

• Export from FITS: rascil.processing_components.image.operations.export_image_to_fits()

• Re-project coordinate system: rascil.processing_components.image.operations.reproject_image()

• Smooth image: rascil.processing_components.image.operations.smooth_image()

• FFT: rascil.processing_components.image.operations.fft_image_to_griddata()

• Remove continuum: rascil.processing_components.image.operations.remove_continuum_image()

• Convert polarisation:

• From Stokes To Polarisation: rascil.processing_components.image.operations.convert_stokes_to_polimage()

• From Polarisation to Stokes: rascil.processing_components.image.operations.convert_polimage_to_stokes()

Visibility

• Append/sum/divide/QualityAssessment: rascil.processing_components.visibility.operations.divide_visibility()

• Remove continuum: rascil.processing_components.visibility.operations.remove_continuum_visibility()

• Integrate across channels: rascil.processing_components.visibility.operations.integrate_visibility_by_channel()